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Investment Management

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Table of Contents

1. Fundamental Analysis ............................................................................................... 5 Learning Outcomes................................................................................................................... 5 Overview .................................................................................................................................... 5 Economic Industry Company (EIC) Approach...................................................................... 7

Macroeconomic Analysis...................................................................................................................... 7 Global Economy.......................................................................................................................... 7

Domestic Economic Policy .............................................................................................................. 9 Fiscal Policy ................................................................................................................................ 9 Monetary Policy, Interest rates, Price level & Inflation ............................................................ 10 Regulatory Policy ...................................................................................................................... 11

Economic growth in the country .................................................................................................... 11 Other Macro Factors in the Domestic Economy ............................................................................ 12

Industry Analysis ................................................................................................................................ 13 Life cycles ................................................................................................................................. 13 Industry Analysis- Macro approach .......................................................................................... 14

Porter’s Five Force Model .................................................................................................................. 16 Company Analysis .............................................................................................................................. 17

Fundamental Valuation.......................................................................................................... 18 Valuation Model ................................................................................................................................. 18

Use of PBV-ROE Matrix........................................................................................................... 18 Valuation Ratios ................................................................................................................................. 19

Mini Case study on Stock-Picking using Fundamental Analysis........................................ 20 References ................................................................................................................................ 26 Questions.................................................................................................................................. 26

2. Technical Analysis ................................................................................................... 29 Learning Outcomes................................................................................................................. 29 Overview .................................................................................................................................. 29

Technical Analysis (TA) versus Fundamental Analysis (FA) ............................................................ 29 Dow Theory and Trend Analysis ........................................................................................... 30

Dow Theory ........................................................................................................................................ 30 Trend Line........................................................................................................................................... 31

Understanding Patterns.......................................................................................................... 31 Resistance and Support ....................................................................................................................... 31 Chart Patterns...................................................................................................................................... 32 Volume Confirmation ......................................................................................................................... 34

Moving Averages..................................................................................................................... 35 Interpretation of Moving Averages..................................................................................................... 36

Momentum Indicators ............................................................................................................ 37 Relative Strength Index (RSI)............................................................................................................. 38 Stochastic Oscillator ........................................................................................................................... 39

Fibonacci Ratio........................................................................................................................ 39 Candlesticks Charting ............................................................................................................ 41

The Doji .............................................................................................................................................. 42 Engulfing Patterns............................................................................................................................... 42

ilLearnFinance Investment Management ver 1.0

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Hammers............................................................................................................................................. 43 Harami Patterns................................................................................................................................... 43

Bullish Harami .......................................................................................................................... 43 Bearish Harami.......................................................................................................................... 44

Morning Star ....................................................................................................................................... 44 Evening star ........................................................................................................................................ 45 Shooting Star....................................................................................................................................... 45 Inverted Hammer ................................................................................................................................ 46

References ................................................................................................................................ 47 Questions.................................................................................................................................. 47

3. Portfolio Management ............................................................................................. 50 Learning Outcomes................................................................................................................. 50 Overview .................................................................................................................................. 50 Efficient Markets Hypothesis................................................................................................. 50

Efficient Market Hypothesis: Types ................................................................................................... 51 EMH: Weak Form..................................................................................................................... 51 EMH: Semi strong form ............................................................................................................ 52 EMH: Strong form..................................................................................................................... 52

Exceptions to Efficient Market Hypothesis ........................................................................................ 53 Size Effect ................................................................................................................................. 53 P/E effect ................................................................................................................................... 54 Monday Effect........................................................................................................................... 54

Risk & Return ......................................................................................................................... 54 Return ................................................................................................................................................. 54

Components of Return: ............................................................................................................. 55 Time Value Of Money ........................................................................................................................ 55 Use of Historical returns ..................................................................................................................... 56 Expected Return.................................................................................................................................. 56 Risk ..................................................................................................................................................... 57

Sources of risk ........................................................................................................................... 57 Types of risk.............................................................................................................................. 57 Calculating risk.......................................................................................................................... 58 Standard Deviation .................................................................................................................... 58 Normal Distribution .................................................................................................................. 59 Risk Aversion............................................................................................................................ 60 Risk Premium............................................................................................................................ 60

Modern Portfolio Theory ....................................................................................................... 61 Portfolio Return .................................................................................................................................. 61 Diversification .................................................................................................................................... 62 Portfolio Risk...................................................................................................................................... 62 Covariance .......................................................................................................................................... 66

Coefficient of Correlation.......................................................................................................... 66 Markowitz model ................................................................................................................................ 68 Efficient Frontier................................................................................................................................. 69 Capital Market Theory........................................................................................................................ 69 Capital Asset Pricing Model ............................................................................................................... 71

CAPM Assumptions.................................................................................................................. 72 Beta ..................................................................................................................................................... 73 Beta calculation................................................................................................................................... 73 Security Market Line .......................................................................................................................... 74

Estimating SML ........................................................................................................................ 75


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Managing portfolios and evaluating performance............................................................... 75 Portfolio Management ........................................................................................................................ 75

Portfolio Rebalancing................................................................................................................ 76 Portfolio rebalancing strategies ................................................................................................. 76 Portfolio Upgrading................................................................................................................... 77

Performance Evaluation...................................................................................................................... 77 Rate of Return – review............................................................................................................. 78 Risk Review .............................................................................................................................. 78

Portfolio Measurements ...................................................................................................................... 78 Sharpe ratio ............................................................................................................................... 79 Treynor ratio.............................................................................................................................. 81 Jensen’s alpha............................................................................................................................ 82

References ................................................................................................................................ 84 Questions.................................................................................................................................. 84


Fundamental Analysis 5


1. Fundamental Analysis

Learning Outcomes In this section, we will be discussing the technique of Fundamental Analysis, which is the most widely used method of investment analysis. First the qualitative aspects will be taken up. The Economy-Industry-Company (EIC) approach will be discussed in detail. Also the Porter model will be explained. Then the focus will shift to quantitative methods and certain valuation parameters popular with managers are set out. (You would need to brush up what you have learnt in Unit I for some of these) The section ends with a live case study of a listed Indian company where all the tools learnt will be used to make an investment decision. At the end of this section you should be able to

• Analyse the economic, industrial and company specific factors that are relevant for a company and make a judgement whether these are favourable or unfavourable for making an investment in that company

• Make a quantitative valuation of the company and decide whether it merits a Buy, Hold or Sell at that point in time.

Overview

• Looks at the company’s financial performance as the key yardstick to determine the valuation of its equity.

• Includes a study of global, economy wide, industry wide and company specific factors that have a significant bearing on the future performance of a particular company.

• Values a company based on DCF and market related ratios There are two approaches to investing. One is Fundamental analysis and the other is Technical analysis. Both are quite different in their philosophy and methodology. Both can be used profitably as long as you know for what purpose you are using them. Most famous investment icons like Warren Buffet and Peter Lynch use Fundamental analysis.

Even in Fundamental analysis there are two distinct parts the Qualitative part and the Quantitative part. We will discuss both.

In a nutshell Fundamental analysis looks at the broad economic trends, industrial activity and a company’s financial performance as key yardsticks to determine a fair value for the company’s share.

It is mainly used by long-term investors who have a time horizon of six months or more.

It is qualitative though when it comes to valuation we do use some mathematics.

The fundamental analyst makes a key assumption that a company is very much a part of an industry. So he spends time looking at the fortunes of that industry. He does not stop at this. He also realizes that industries work within the national economy and so he spends time analyzing quite deeply the problems and prospects of that nation’s economy also. His researches don’t end here! He knows that the world is globalised and fortunes of any national economy are inextricably linked to the vagaries of the global



economy. So the fundamental analyst studies the global trends and tries to gauge if they are conducive for equity investments. In short, you can see that he is studying global and national economies, specific industries and the financial well being of specific companies. This approach is commonly referred to as EIC approach (Economy Industry Company)

It is hard work and calls for the ability to understand and assimilate economic trends and convert them into stock picking. In all this, let us not lose sight of our basic purpose, to evaluate companies and make good investment decisions



Economic Industry Company (EIC) Approach

• The Economy Industry Company model - a top-down approach to investing that involves:

• Understanding the macro-economic environment • Analyzing the prospects of the industry • Assessing the projected performance of the company.

The EIC approach is a top down approach. For instance, if the economies of the world are not doing well and likely to have problems, the investor is not in a hurry to make stock investments. If the Indian economy is not doing well, just because the global cues are good, investor should not jump in. If economic tidings are favorable but the particular industry is not doing well, then investor is going to avoid that industry. Last but not the least, the industry may be doing well but if the company is not doing well, investor is going to avoid it.

Macroeconomic Analysis

Global Economy Factor to be considered • Global Growth Rate- Real and Nominal GDPs • Coupling of economies • Risk appetite among investors- Dollar and Volatility indices • Flow of liquidity in markets

Global growth rate

The first factor is the global growth rate. For markets to trend up global economies should register decent growth. When we say growth we mean the overall growth of the GDP (Gross Domestic Product). For those who are hearing of GDP for the first time, GDP is defined as the monetary value of all the finished goods and services produced within a country's borders in a specific time period. Though GDP is usually calculated on an annual basis, it is related to a base year and growth is often expressed as a percentage. It is also calculated as the sum of all of private and public consumption, government outlays, investments and exports less imports in a country. To put it as a simple formula

GDP = C + G + I + NX

where: "C" is equal to all private consumption, or consumer spending, in a nation's economy "G" is the sum of government spending "I" is the sum of all the country's businesses spending on capital "NX" is the nation's total net exports, calculated as total exports minus total imports. (NX = Exports - Imports)

Economists and analysts always talk about Real GDP. The actual GDP (called Nominal GDP) as deflated by the annual inflation is the Real GDP and that is invariably used in all analysis. For example, if the GDP has grown at 13% compared to the previous year at current prices, then we deflate it by the annual inflation rate to get at the real GDP growth. If the inflation is 6%, we say the GDP has grown by 7%. The sanctity and importance of GDP is it is one number which covers the entire economy. So, if GDP is growing at a



healthy pace, one could make the assumption that while bits and pieces of it may be struggling, the economy as a whole is growing.

Recently in December 2009 we again saw how GDP growth estimate influenced market behaviour. The stock market had got into a range with the Nifty between 4950 and 5180 for 10 weeks and was going nowhere. Suddenly the Finance Minister made a statement t that in his view the GDP for 2009-10 should grow at 7.5%. This was above the 6 to 6.5% that most analysts were predicting. Immediately the market shot up 4% in a single day! And then it continued to rise for a few more days.

While GDP as a number is itself very important, many analysts use it to predict which industries will shape up well when GDP grows. This is done by deriving a correlation between the growth in GDP and the growth in that particular industry. Steel cement, commercial vehicles are some industries which have a strong positive correlation with GDP growth. So these industries find favour with investors when the GDP picks up.

Components of GDP

GDP has Agriculture, manufacturing and Services as components and analysts look at the growth in each of these. One level lower analysts like to make sure that within that overall growth, demand for manufactured products is growing and employment is growing. When demand for products grows companies making them make better profits. When jobs get created, people have more money to spend and the purchasing power in the economies in the world goes up. This creates a bullish sentiment among investors.

Coupling of Global economies

In 2008, we saw how when an economic downturn happened due to the financial crisis, all stock markets crashed. This phenomenon of all global markets moving in tandem is called Coupling. The crisis did not hit India that much and our banks were hardly exposed. Our growth fell but not disastrously ; even then our market lost 60% in value. All global economies have become coupled due to smooth trade and liquidity flows. When India had not opened up through reforms we were not coupled at all. In the 70s and 80s one can see that our markets were often out of sync with the US or Europe but subject to trends in the national economy we will discuss shortly. After the Indian economy was opened up in 1991 trade and liquidity flows with other nations became free and we have become more globalised in terms of trade and investments and now India is quite coupled too.

Risk Appetite among investors

Another big global factor is what one may call the risk appetite. Globally risk appetite means how much risk investors are prepared to take on their books. At one end of the spectrum, we have risk free but low return investment option like Bank Deposits or Government bonds. When people are not feeling very comfortable about the future money, they move out to riskier assets like stocks and commodities. Till a few years ago people did not understand or care that much about risk aversion but the last two years have taught even the Pundits that if they just look at returns without giving equal importance to risk, they will lose.

2008 and 2009 have been textbook cases for studying impact or risks on market. In the second half of 2008 and early 2009, as global markets collapsed investors panicked. Here we are not talking about the housewife in Meerut or a student in Shillong. Even major investment groups like Fidelity, Morgan Stanley put all their money in the US Government Bonds rather than keeping them in key stocks. Now, we are finding the reverse happening. As economies recover we find that risk aversion has reduced a lot, big investors are moving their money banks from bonds to stocks.

Dollar Index

The Dollar index is a weighted geometric mean of the U.S. Dollar against six currencies Euro (58%), the Japanese yen (14%), Great Britain Pound (12%), Swedish Kroner (3%), Canadian Dollar (9%) and the Swiss Franc (4%). In the recent past the Dollar Index has become very popular. One can explain this by saying that when risk aversion is high in the market, investors move funds into U.S. Government bonds as a safe haven and this induces people to buy Dollars. So the Dollar index rises. Vice versa when people are not feeling risk averse, they sell U.S. Government bonds and buy riskier assets like Commodities and shares. So Dollar index falls.



Volatility Index

Another important indicator for Risk aversion and risk appetite is the Volatility Index. This measures this level of volatility in the market. If market has a difference of 5% intra day between the high of the day and the low of the day that means it is very volatile. If it has high-low difference of say 1% the volatility is low. Higher volatility means less risk appetite and vice versa. Investors often use this as a yard stock to understand the psychological element called Risk Aversion.

Flow of liquidity in markets

At the end of this chain of the global economy is liquidity. Liquidity is a generic term given by analysts to the flow of money. We have found that liquidity flows have a big influence on markets and prices. In a sense liquidity flows are the result of economic factors and risk aversion. One could call it the link between macro economic trends at one side and demand and supply of shares on other. Simply put, when there is higher liquidity chasing stocks share prices will go up. If liquidity is getting drained out share prices will fall. In India the impact of global liquidity has been profound indeed. Global liquidity makes its presence felt in India through the powerful voice of foreign institutional funds and hedge funds which bring in or take out huge money more than any other single factor. In a day’s trading they actually trade more than even the domestic mutual funds. There actions are often governed by global trends rather then developments specific to India. It is such a big presence that just a single figure that FIIs are buyers or sellers in the market has a big influence on share prices. From this analysis, we see that global economic activity, global risk aversion and global liquidity influence stocks.

The concept of liquidity should be understood carefully. There is always ample liquidity in the global financial system. It is just that investors move fund from one asset class to another depending on their perception of risk and reward at that point in time. So risk aversion and liquidity are closely linked.

Domestic Economic Policy • Fiscal Policy of Government • Union Budget, Fiscal Deficit and Deficit Financing, Government borrowing • Monetary Policy of Reserve Bank of India - Interest rates, inflation and prices. Liquidity management • Regulatory changes - Foreign investment, Structural reforms

So far we have seen that global macro factors like liquidity risk aversion can have a profound influence on stock market movements. The stock market of every country is influenced in a big way by what is happening in that country’s domestic economy. The economy has many parts to it but we will try to understand those aspects which directly affect the stock market.

Fiscal Policy Fiscal policy means the policy of the Government towards economic issues in general and its finances in particular. What the government says and does is very important especially in emerging economies like India. The Union Budget is a very useful tool of the government to formulate the fiscal policy. From the market point of view an analyst looks at the government spending. If government spends a lot on infrastructure and social services that is viewed favorably. This is because economy and companies will benefit from it .One should also look at the fiscal deficit which is the difference between what the government gets by way of taxes and inflows and what it spends. It is normally expressed as a percentage of the GDP. If the fiscal deficit is low analysts are happy. If it is high that will lead to either borrowing or printing of notes by the government which will again lead to inflation.

Long term investors look for two things when it comes to fiscal policy. Firstly they want the fiscal deficit to be as low as possible. When it is very low that means the government is not over spending or living beyond it means. Just for you and me, even for Governments spending more than it can earn is bad! True Government has a printing press where it can print money which we don’t! Another thing that large



investors look at is how the deficit is financed. If the government finances the deficit totally out of borrowings, that is not good. More the Government borrows and spends money, its annual interest payments go up and so do the repayments. When that happens, all the revenue it gets from taxes goes to meet interest and very little is available is for spending on infrastructure, education etc.

Fiscal Policy, Stock Prices and Crowding Out

The recent Union Budget for 2010-11 presented by Mr. Pranab Mukherjee is a perfect example of the impact of fiscal deficit on stock market. In 2009 because of global recession the government had cut taxes and increased its own spending. This was done to stimulate the economy. While that was very good the fiscal deficit got badly affected and went up 3.7% of GDP in 2008-09 to a high of 6.8% in 2009-10. Foreign investors were saying before the Budget that this deficit was too high and India would fall into a “Debt Trap” if India did not do something about it. So when FM announced that he was planning to cut the fiscal deficit sharply from 6.8% to 5.5%, the stock market just shot up. The foreign investors who were waiting on the side lines started buying in a big way.

When the government borrows more money we saw that its interest and repayment obligations will eat into all its income; that is not the only problem. When government borrows money all the insurance companies and banks lend the money. The more it borrows the more resources of insurers and banks are locked with government. In other words private sector companies have no money to get from the banks. This is called the Crowding Out effect. Due to this private sector investment will suffer and even if they finally get money from bank they will have to pay more interest. So large investors were also looking at the Government borrowing number. In the 2010 Budget another good thing was the Finance Minister capped the government borrowings at a reasonable level. He also said government will be selling more public sector shares and also using novel methods like sale of telecom spectrum instead of taking loans. This also has a very positive effect on psyche of all investors.

So as an analyst or an investor you need to remember that if the fiscal deficit is kept low and it is not financed by borrowing or printing notes, then it is positive for stock market

Monetary Policy, Interest rates, Price level & Inflation While the government is in charge of fiscal policy the Reserve Bank of India is the regulator for the monetary policy. RBI decides what the interest rate scenario should be. For this purpose it uses tools like Bank Rates, Repo Rates to control money flow. So the analyst looks at monetary policy to get the trend in interest rate and liquidity in the economy. Before we understand how RBI uses monetary policy to control inflation, it is essential to understand the link between inflation, interest rates and monetary policy.

Inflation means the increase in prices during a period. The inflation is normally measured on a year-to-year basis though we also like to see shorter trends to fine tune our understanding. Inflation is given out by Government at two levels. One is at the wholesale level and this is called the Wholesale Price Index (WPI). The other is the increase in prices at the consumer level which is the Consumer Price Index (CPI). Inflation of around 5% to 6% per annum is good for the economy as it encourages producers to produce more and give increments on wages and salaries also. But anything above that is not good for the economy. Inflation affects consumer because it reduces their purchasing power. Progressively it also affects demand for the products of the companies.

Why is there inflation? It is because “too much money is chasing too few goods”! Let us take a simple example. If there is a product which is selling at Rs 100 and there are people queuing up for the product, the shop keeper will surely increase the price to Rs 105. He is sure that even at that price there will be people to buy his product. The price rises. On the other hand if there are no takers, he will start a discount sale and offer it at Rs 95. The price falls. So we realize that inflation is because there is too much demand for a product and the market price adjusts itself upward and vice versa. Sometimes inflation is “supply side”. What this means that because there is a shortage of supply the prices go up and not because there is extra demand. We saw in the beginning of 2010 in India due to a severe shortfall in the crop we had a steep increase in the prices of rice, wheat, pulses and vegetables. As the supply started improving, the prices started coming down. Some amount of inflation is desirable for growth but not beyond a point.

How does RBI control inflation and what is the effect that RBI’s actions have on the stock market? RBI uses monetary tools at its command to do this. All RBI’s actions are done through the banking system it



oversees and this in turn affects the functioning of banks. (the banks have a pervasive influence on the entire financial system). The first tool RBI uses is the Cash Reserve Ratio (CRR) which is the level of cash that it “impounds” from banks and keeps with itself. When it finds that inflation is going up and it uses the CRR, the cash in the system is reduced. And when less cash is chasing the same quantity of goods, the prices fall. This is an indirect method and if this does not have the desired effect it increase the Repo rate. The Repo rate is the rate at which the RBI lends money to banks in its constitutional role as “lender of last resort”. By doing so it makes money more expensive for commercial banks. They in turn increase the rate at which they lend to their customers. When the borrowing cost goes up, customers – whether they are individuals buying cars and homes- or companies buying steel and cement will feel the pinch and buy less. That brings down prices. Last but not the least it can raise the Bank rate itself which is the general rate in the economy around which banks peg their lending rates. This is the most direct method and is seldom used.

Now that we have understood inflation, interest rates and monetary policy let us see how the fundamental analyst uses these in his stock picking. Inflation attacks stock market through interest rates. Firstly he identifies those sectors which are very much influenced by inflation and interest rates. This is the tough part. The second step is to buy those sectors when interest rates are going down and inflation is low. On the other hand when inflation is high and interest rates are rising he will move out of those sectors.

Monetary Policy and Stock Prices

Let us apply this logic to Indian conditions. In 2008 due to high oil prices inflation rose, RBI tightened monetary policy by increasing CRR and Repo rates. While all stocks did fall, Real Estate, Banking and Automobiles just crashed out. The shares of DLF fell nearly 90%! In 2009 the reverse happened. RBI seeing that there is global recession wanted to give stimulus to economy. So it reduced Repo rates and CRR significantly, to half the levels of 2008. Banks started lending in a big way for real estate and auto sectors. So from March 2009 onwards these shares witnessed a huge rally. Such Sectors are called “rate sensitives”. Investors should go overweight in these sectors if inflation and interest rates are falling and lighten them if monetary policy is tightening.

Regulatory Policy Last but not the least regulatory policies and changes have a big effect on markets. Regulatory Policy refers to the changes government makes to the economic laws to benefit the nation. These could be taxation, policy changes regarding foreign investments etc .Each of these policy changes could dramatically change the fortunes of market and the companies For example when Economic Reforms were introduced in India in 1991 markets doubled within a year.

The Government policy on foreign investment has a big impact on markets. If foreign investment is opened up or the percentage ceiling is increased, that is significant for players in the field and also for those who are planning to enter. Sometimes it may affect the market as a whole. For example when there was a news item that Government may open up Retail sector for foreign investment, all shares in Retail segment shot up! One needs to study the impact of regulatory policy at two levels. The first is overall changes which affect the whole economy positively or adversely. Generally one can say when government opens up foreign investment that is good for all companies and for stock market as a whole.

Economic growth in the country • Growth in domestic economy • Growth in domestic savings • Investment level in the economy

Just as we saw how important global GDP growth is, the GDP growth in a particular country is also of great importance to decide whether to invest in stocks. The GDP is over all growth in the economy and it normally consists of Agriculture, Manufacturing and Service sectors. In India agriculture accounts for 18% of the GDP, Manufacturing represents about 26% and Service sector the balance 56%. So the analyst looks at all these three sectors to decide overall GDP growth. If the monsoon is bad, agriculture growth falls. If



infrastructure becomes a problem, then manufacturing is affected. If consumer sentiment falls then service sector suffers. One could generally say that an improving GDP is very important for stock market growth. In 2008 we saw that India’s GDP fell sharply from 9% to 6.7% the stock market crashed. Again with the GDP improving stock markets have started improving.

Within the GDP it is also the sectoral growth that should be examined. If agriculture is doing well then rural demand goes up and shares of two wheelers and FMCG companies are benefited. The logic is simple. The farmers have more money in their pockets and they will spend it on these things. On the other hand if manufacturing sector growth is high due to low interest rates or infrastructure spending then Capital Goods, Engineering, and Construction shares go up. If Service sector growth numbers go up, that is positive for stocks of Banking, IT and hospital companies

Savings & Investments

Another important parameter for analysts is the savings and the investments in the economy. When there is good savings and investment rates are high then the economy grows and also more funds are available for stock markets. In India we have a very high savings rate of about 35% of GDP. However a lot of it goes into Provident Fund, life insurance, bank deposits but these days the trend is changing and more and more of the savings in the economy is coming into the stock market. And this is a good sign for the market as a whole.

The level of investment in the economy is also extremely important for market players. The higher the investments, it helps the economy through creating better environment for companies. We have seen in the last two years how investments by government in roads, ports, airports, power have increased the ratio of investments to GDP from 32% to 37%. This has a multiplier affect as private industry also which makes investments to meet the demand. So for the analyst rising savings and investments is good news for the market as whole and vice versa.

Other Macro Factors in the Domestic Economy Impact of rise and fall in Interest Rates Balance of Payment, Exchange Reserves, & Exchange Rate Business confidence and sentiment Among all the factors that affect the stock market, interest rate is one of the most critical. When interest rates are low that is very beneficial for companies because their cost of capital will come down. This will improve their profitability. For consumers also low interest rates are very good. It will help them to take cheaper loans for assets like homes, cars, durables etc. Another positive fall out of low interest rates is that many investors and savers will move their assets from bonds and deposits to stock, there by pushing share prices up

Conversely if interest rates are high they will have a negative impact on corporate profits and consumer demand. Cost of borrowing money for buying stocks will go up sharply. In fact interest rates are so important that many stock market analysts base their entire investment strategy on watching interest rates. We have seen earlier that inflation and monetary policy have a great impact on interest rates.

The Foreign Exchange Reserve and Exchange Rate are also critical for capital markets. When the Foreign Exchange reserve goes up the country is in a position to import more for growing the economy. The currency also becomes strong which is very good for foreign investors. This is because their Indian assets will go up in value in their local currency. We have seen how in India when the Foreign Exchange reserve rose from USD 40mn to USD 200mn, stock market had a huge bull run.

Last but not least market analysts also track business confidence. Business confidence refers to how confident businessmen are about the future. A high level of business confidence means that companies are bullish about the future and will make new investments. On the other hand if the business confidence is low that means that future outlook for economy may not be bright. Similar to business confidence is consumer sentiment. Consumers may have money but unless they actually go out and buy things there will not be any



growth in the economy Unless they have a bullish feeling about the future, they would not buy stocks. Hence the consumer sentiment is as important as business confidence for the health of stock market.

In developed economies like the U.S. they also track a few more fundamental factors. These are Unemployment Rate, Homes Sales, Consumer Confidence, etc. In India we do not have sophisticated tracking of these factors but as time goes up by will also start publishing and tracking them.

To sum up let us make a table of macro factors and their impact on stock markets

Macro Factor Impact on stock market

Increase in Global growth Positive

Increase in risk aversion Negative

Increase in global liquidity Positive

Increase in Fiscal deficit Negative

Increase in Bank and Repo Rate Negative

Increase in inflation Negative

Opening up Foreign Direct investments Positive

Increase in Savings rate Positive

Increase in infrastructure investment Positive

Increase in interest rates Negative

Increase in value of Rupee Positive

Industry Analysis

Life cycles Pioneer Stage- Sunrise Rapid Growth Stage- Star Maturity & Stabilization stage- Cash Cow Decline Stage- Sunset

Now that we have understood the manner in which macro factors globally and domestically affect markets, let us turn our attention to industries and how to analyse them. A basic concept in industry analysis is to understand the Life Cycle of industries. A popular way of looking at life cycles is to classify them as pioneer stage, rapid growth stage, stabilization/maturity stage and decline stage.

New ideas are born everyday and entrepreneurs try to commercialize them. When they are the first to do they become Pioneers and the industry is called a Sunrise industry.. If they get it right the gains are huge because they have the Early Mover Advantage in terms of pricing and market share. The Internet industry probably saw its pioneering stage in the mid 1990’s and a rapid growth stage in the late 90’s and early 00’s. In India also we are now finding that the education sector is in pioneer stage as far as stock market is concerned.

Telecom sector on the other hand is in the rapid growth stage. It was in the Pioneer stage in the mid-90s when the sector was opened up for private participation. Now it is in a Growth or Star stage as profits have got normalized though big growth is still very much there. Sectors like Banking and FMCG are in a maturity and stabilization stage. They have been around for more than 50 years and profits are very



predictable. They are Cash Cows! Market shares are well understood. India being such a strong fast growing economy no sector is really in decline stage. We could say that technology has made some industries obsolescent. Mini paper and mini cement plants are examples. It is important for the analyst to understand which stage of its life an industry is. He can then make his investments decisions based on that.

Making investment decisions using life cycles

• Display caution during pioneering stage – usually appeals to speculators • Respond quickly & expand commitments- rapid growth stage • Moderate investments- maturity stage • Sensibly disinvest when signals of decline are evident

Pioneer or Sunrise Stage investing

The pioneering or Sunrise stage is the most exciting stage for making investments but unfortunately it is also the stage where making the assessment is the toughest. Speculators who have a high risk bearing capability love this stage. In India also we have seen how shares in Internet, education companies have gone up many times in two or three years. This is because of three reasons. Firstly these companies do not have a track record to go by. Secondly there are no peer groups to compare. Thirdly there is not much research available on the prospects etc.

Rapid Growth or Star companies

After the pioneering stage some industries become grow very rapidly. They show 100% growth in top and bottom line every year for few years. During this stage the investment is less risky but still very profitable. A share of Bharti which was quoting around 45 in 2002 has gone up 20 times in seven years. Long term investors love this type of stocks. At this stage some of the mystery has gone out of these shares. They do have a track record and they have peers. But the growth is terrific and competition has not killed the profit margins. We can sense that Telecom shares in India may be moving from High Growth to maturity stage. Capital goods, Computer software are other examples of Star industries.

Maturity Stage or Cash cow companies

After the high growth stage industries mature and their growth slows down. Competitors enter and bring down the profit margins. The market reaches saturation and the analyst who is able to understand these signs gradually reduces his exposure to such shares in high growth portfolios. Pension funds etc do not mind these shares as they give quite high dividends since they have to make periodic pay outs and need cash inflows.

Decline or Sunset Stage

The last stage is when that particular industry starts actually declining. This happens most often because of technology changes. Mini paper and mini cement were mentioned earlier. Investors definitely try to get out of such stock before their capital starts depreciating. It is most important for the analyst to understand the life cycle of the industry so that he can time his entry and exit very well.

Industry Analysis- Macro approach There are several macro factors that seriously affect the fortunes of industries and an analyst needs to understand them well. Let us learn a few of them.

• Export Markets • Import Competitiveness • Technology changes • Regulations and impact on functioning



Changes in Export markets

Many industries depend largely upon export markets so are subject to all the global changes. To illustrate the quoted companies in the Indian IT sector totally depend on exports and when the American economy crashed in 2008 even large companies like Infosys were seriously affected. In the same way the textile industry is also very export driven. It has found the going very tough last few years as competition from other developing countries is severe. The analyst has to be very careful to understand how competitive that industry is by global standards and how much impact changes in export markets will have.

Import competitiveness

Just like exports imports also pose a challenge to domestic industry. For example there is lot of dumping of steel from abroad in to India which affects steel companies. Capital goods manufacturers find Chinese capital goods giving them lot of competition so we need to understand whether the industry can withstand imports. In India one could say that imports have had a big impact on the fortunes of many companies in the last 15 years. Before the economy was reformed in 1991, we had severe restrictions on imports in the form of high import duties, quantitative restrictions, banned lists etc. Now these have all been dismantled and many products are freely available at low prices. Analyst needs to understand this point very carefully while analysing industries.

Technological changes

A crucial point when studying an industry is technology. In 90s cassettes were very popular but now they have been replaced by CDs. So cassette manufacturers have run aground. With internet coming up so fast almost all air bookings are done through internet. So travel agencies are dying slowly. There are many such examples where change in technology has affected whole industries. The impact may not be so startling but bad all the same. Hindustan Motors with its Ambassador car and Premier Automobiles with its Fiat were two of the most profitable companies in the 70s and 80s. The advent of Maruti with its superior technology in the late 80s meant that these companies lost out.

Last but not the least government regulations have a big impact. During reforms we saw that government reduced import duties and many domestic companies became unviable. We also saw how foreign investment was allowed and foreign companies came and took away the market share of Indian companies. Tax incentives for exports and in excise have benefited many companies and made them good investments. So an analyst has to keep a watch on government policies and plan his investments accordingly.



Porter’s Five Force Model

PORTER’S FIVE FORCE MODEL

Michael Porter was a well known Harvard Professor who looked at industry in a very novel way and provided for a framework that shows an industry as being influenced by five forces. One seeking to understand the industry context in which the firm operates can use this model to analyze the forces governing a firm’s entry in a particular industry

Competitive Rivalry- The intensity of rivalry among the firms varies across the industry. The intensity of rivalry is influenced by the number of firms in the industry, market growth, fixed cost, switching cost, storage cost, product differentiation etc. There is cut throat competition in telephone and airline industries.

Porter suggested that firms use some tactics to handle this threat. These include creating exit barriers for customers, becoming niche or quality players, showing product differentiation, switching costs, not concentrating on a single industry, ensuring that the products are positioned in such a way that there is a diversity of competitors.

Threat of substitutes- These are the products that are viewed as an alternative for other products. The threat of substitute exists when demand for a product is affected by the price change of a substitute product. A firm’s ability to raise prices in an industry is constrained by the existence of close substitute products. Examples are Copper and aluminum for wiring, fruit juices and aerated waters, trucks and rail, etc. These are handled by ensuring that performance is superior to substitutes, making switching expensive etc.

Buyers Power-The power of buyers is the influence that customers have on producing industry. The buyers are powerful when they are concentrated (A few buyers with significant market share), when buyers purchase a significant proportion of output. Example is the auto ancillary industry which has many suppliers supplying to a few firms. This is handled by ensuring many buyers, handling volumes, having price elasticity, developing distinct brand identity, etc

Suppliers Power- Suppliers are the providers of raw material to the producing industry. Suppliers are powerful if the cost of switching from an existing supplier is high, or when the suppliers are concentrated, or when there is forward integration threat by the suppliers. The freeing up of imports has reduced the Suppliers power considerably but ore manufacturers supplying to steel companies, sugar cane growers



supplying to sugar companies examples even today. This threat is reduced by having a number of sources, developing substitutes, etc.

Barriers to Entry- A firm’s existence is not only threatened by the incumbent firms in the industry but also by the new firms that can enter the industry. Barriers reduce the rate of entry of the new firms and thus a level of profits is maintained for the existing firms. The barriers to entry may arise from several sources like government created barriers (banks), patents (pharmaceuticals), internal economies of scale (automobiles), raw materials (cement) etc. Companies create barriers by scaling up, patenting, having unique technologies etc.

Company Analysis • Management quality • Products • Raw material supplies • Market share • Competitive Position • Technology obsolescence

Management Quality

The fundamental yet most difficult to gauge aspect of a company is the quality of management. A saying in the market is “The story may be good but see who the story teller is”. Good managements are characterized by professionalism, high level of corporate governance and transparency, depth, good pay out policies, core competence, not taking money out of the company etc. The market often gives a better multiple for such companies. While looking at a management one also needs to read carefully the composition of the Board of Directors, the comments made by Auditors in their reports. These give good insights into the management process. Markets reward good managements with higher Multiples- Infosys often quoted as a case in point.

Products

The products of the company ultimately ensure its profits and growth. The products should be high quality, meeting the needs of the market and have a good brand value. FMCG, Pharma and such companies have a major share of their value just in their brands and so for these companies the product is vital. On the other hand for IT companies Construction units and commodities the uniqueness of the product is not so important. So the analyst evaluates the product from all angles.

Market share

It is not enough if a product is good but it should also command a good market share. This is again very important for companies which have a brand or which have an identifiable market. Colgate has a stranglehold on toothpaste market and Times of India on newspaper industry. Globally Microsoft dominates the Internet Browser space. Market share gives pricing power to the company and also makes it very tough for competitors to threaten the company.

Competitive Position

The competitive position is another vital factor. A company derives its competitive position vis-a-vis its rivals in many ways. One example is a patent for a product. If a pharma company has a patent nobody can make that product. For the cement company it could be either nearness to the market or to raw material. For an export oriented company it could be proximity to the port. It could also be a licence. For example the government may decide not to give any more telecom licences. Immediately the existing licences acquire value.

Technology Obsolescence

We have already seen how technology changes can have a big influence on the future of industry. Same goes for a company also if the company has not updated its technology then it is trouble. For example many



cement companies which were using the Wet Process folded up when the Dry Process came in. Many fertilizer companies did not convert the feed stock into gas and have suffered a lot. Compliance to Euro standards is becoming very important and those that do not comply will have to close down. So a financial analyst will see how up to date the technology of the company is.

Fundamental Valuation

Valuation Model Now that we have understood the qualitative aspects namely macro and macro economic factors that affect companies and also how industries and companies have to be analysed, let us get to the quantitative aspects. Here our sources are the audited accounts and future projections given out by management from time to time. While all that we have learnt will tell us “what to buy”, the valuation will answer the question “is it good to buy at current prices?” Quantitative methods also point out financial shortcomings and may make us turn away from a security. We have already learnt DCF valuation earlier and these methods have to be used in conjunction with DCF.

Use of PBV-ROE Matrix The PBV-ROE matrix is a method that juxtaposes two important parameters and tries to identify undervaluation.

Overvalued

Low ROE

High PBV

High ROE

High PBV

Low ROE

High PBV

Undervalued

High ROE

Low PBV

ROE

PBV Ratio

Low

High

Low High

PBV-ROE Matrix

PBV- Market Price of share to Book Value Ratio

ROE – Return on Equity

The Return on Equity and Price to Book Value have a direct relationship. Increase in return on equity leads to an increase in P/BV. Given this relationship, it is not surprising to see firms which have high returns on equity selling for above book value and firms which have low return on equity selling below book value. The firms which provide a mismatch of ROE and P/BV ratio should draw the attention of the investors. The securities with low ROE and high P/BV are said to be overvalued as the return from the security does not justify the price paid. Similarly a security with high ROE and low PBV is said to be undervalued.



Let us take an example. The Price/ BV ratio of Reliance Power Ltd belonging to ADAG group on 6th Aug 2010 was 2.72. The Return on Equity was 1.8%. This shows that the P/BV is 1.5 times ROE. In comparison let us consider Bank of Baroda. On the same day BOB had a P/BV of 1.8 while its ROE was 21.5%. This means that the ROE was just 0.083 times the ROE. Hence from this Matrix, BOB is very much undervalued compared to RPL.

Valuation Ratios • Valuation ratios indicate how the equity stock of the company is assessed

in the capital market • Market value of equity reflects the combined influence of risk and return

Valuation ratios are the most comprehensive measures of a firm’s performance. This is particularly used by investors who have different investment options and need to make decisions on whether to purchase or dispose off the shares of the company.

PE Ratio (also called The Multiple) = Market Price per Share/ Earnings Per Share

EV/EBITDA Ratio= (Market Price x No of equity shares) + Term debt (called Enterprise value (EV) / Earnings before interest, taxes, depreciation, and amortization (EBITDA)

Marker Cap/Sales Ratio : (Market Price x No of equity shares)/Sales Turnover

PEG Ratio = PE/ (Expected Growth in Earnings Per share).

Price/ Book Value Ratio= Market value per share/Book value per share

The above ratios are the most important ratios used for valuation and these have been dealt with in detail in Unit I in the section Relative Valuations. You should revise that thoroughly before proceeding further.

Pay Out Ratios and Yield on Shares

Pay out relates to the dividend a company gives out every year. Insurance companies and Pension funds look for companies with good and consistent pay outs as these incomes come in useful for them for meeting claims, payments etc. Retired persons look for these as they may not like to sell the shares but get a periodic return from them.

Dividend Payout Ratio (also called Payout Ratio) =Dividend Per share (DPS) /Earnings Per Share (EPS).

Retention Ratio=1-Dividend Payout Ratio (Proportion of earnings retained for investments)

After paying tax, companies are left with Profit after taxes and a portion of this they distribute as dividends. It is normally expressed as a percentage of the share face value. For example if a company declares 25% dividend then it means that a person who has a share of face value Rs 10 will receive Rs 2.50 in his hands. It is very difficult to judge that a company is good just because the Pay Out ratio is high but as stated earlier certain classes of share holders like dividends. Also a high dividend shows the confidence of a company that it can maintain its profits. Retention ratio is linked to pay out and tracks the profits that the company “retains” in its books rather than pay it out. Profits retained may come back as Bonus shares to shareholders.

While Dividend pay outs are important, investors also look at yields and the yield is the dividend you get when compared to the Market Price per share. Let us say a company declares 25% dividend on a Rs 10 face value share which is trading at 125 in the market. The dividend percentage is 25% but the yield percentage is Rs 2.5/ Rs 125 which is 2% only. Sometimes investors compare this yield with yields from Bonds and bank deposits though it should be remembered that a substantial portion of the profits comes to investors from capital gains and not dividends which are rarely more than 5 or 6%.



Mini Case study on Stock-Picking using Fundamental Analysis

Now we will work through a live case using all the qualitative and quantitative points learnt so far. This case study is based on data as of 13th Aug 2010

Shriram Transport Finance Company Ltd

Company Overview

Shriram started its operations in Chennai in 1979 and has been a pioneer in the field of financing of second hand commercial vehicles. This is a segment which commercial banks do not enter because of the possibility of bad loans. But Shriram has earned a niche by building an organisation that has very deep inroads in the road transport industry and its bad debts are not higher than the banks. Its net interest margins on the other hand are more than 7% as compared to the banking industry which has net interest margins of 2.0 to 4%. It has grown much faster than the industry and is a leader in its line in which hardly any big players are present.

Latest quarter results

In the quarter ended 30th June 2010, Shriram has shown impressive results. Its Total Income for the quarter was Rs 737.3 crs which was 53% higher on y-o-y basis. Its Net Profit was Rs 288.9 crs an increase of 76% y-o-y. According to the management it told analysts that it expected that for the year as a whole the Total income would be Rs 2680 crs and the Net Profit Rs 1136 crs. Management said that big Government spending on infrastructure and the improvement in manufacturing sector have created boom conditions in the commercial vehicle industry though it expressed concerns about rising interest rates.

Share action

As you sit down to make the decision, you see that the share is close to life time high and trading at 716 on the National Stock Exchange. (see price chart below) Its 52-wk Hi/Lo is 720/346. At Sensex level of 17880, the forward P/E of the Sensex based on estimates of 2010-11 earnings according to a Broker’s Poll conducted by CNBC is 17.5. The EV/EBIDTA is expected to be 11.5. Sensex P/E was 20.5 and EV/EBIDTA was 14 based on 2009-10 actuals.

Last 12 month Price Chart of SFTL.



Problems to be analysed

In this case you have to answer the following questions

• Is Shriram Transport worth investing and if so give 5 reasons why you will invest in it.

• What is the target price you may like to fix on a 12 month time frame?

• What are your concerns about this stock which you will keep an eye on?

From your data base you have downloaded the latest audited numbers of Shriram which are given below.

Shriram Transport Finance Company Ltd. Source: Accord Fintech - Financials Statements - Audited REPORTING DETAILS Name Y-2009 Y-2010 End date of reporting period 31/03/2009 31/03/2010

Original Units as Reported INR Tens of Millions

INR Tens of Millions

Displaying units INR Tens of Millions

INR Tens of Millions

Provider Accord Fintech Accord Fintech Balance Sheet Name Y-2009 - Indiv. Y-2010 - Indiv.

Exchange rate used for currency conversion (*) 1 1

Share Capital 249.06 233.16 Equity Share Capital 203.51 225.52 Face Value 10 10 Reserves & Surplus 2067.57 3609.22 Networth 2271.09 3834.74 Shareholder's Funds 2316.64 3842.39 Total Debts 20121.31 18459.91 Total Liabilities 22437.95 22302.29 Net Block 134.27 46.45 Investments 654.76 1856.02 Market Value of Quoted Invstmnts 5.35 40.31 Inventories 1.27 Sundry Debtors 3.99 Cash and Bank 5784.90 4537.33 Loans and Advances 20730.94 20435.73 Total Current Assets 26521.10 24973.06 Current Liabilities 2128.83 3908.61 Provisions 2769.74 776.43



Less: Total Current Liabilities 4898.58 4685.03 Net Current Assets 21622.52 20288.02 Net Deferred Tax 26.39 74.72 Total Assets 22437.95 22302.29 Profit and Loss Account Y-2009 - Indiv. Y-2010 - Indiv. Operating Income 3690.17 4440.23 Interest Income 3690.17 4440.23 Dividends 4.87 8.75 Increase/Decrease in Stock 6.87 Other Operating Income 338.96 680.09 Net Sales 3690.17 4440.23 Other Income 48.63 64.9 Profits on sale of FA 0.62 Other 48.63 64.28 Total Income 3738.79 4505.13 Interest Paid 1977.67 2246.79 Establishment Expenses 243.92 237.48 Miscellaneous Expenses 344.78 452.28 Total Expenditure 2777.75 3165.58 Operating Profit 961.05 1339.55 Profit before depn interest and tax 2938.72 3586.34 Depreciation and Amortisation 40.41 14.96 Profit before interest and tax 2898.3 3571.38 Profit Before Tax 920.63 1324.59 Tax 308.23 451.47 Profits After Tax 612.4 873.12 Equity Dividend % 50 60 Earnings Per Share 30.09 38.72 Book Value 111.59 168.4 Equity Dividend % 50 60 Reported EPS(Rs) 30.09 38.72 Adjusted EPS(Rs) 30.09 38.72 Book NAV/Share(Rs) 111.59 168.4

ROA(%) 3.14 3.9 ROE(%) 30.28 28.95 ROCE(%) 14.85 15.99 PER(x) 6.09 13.54 PCE(x) 5.71 13.31 Price/Book(x) 1.64 3.11 Yield (%) 2.73 1.14 EV/Net Sales(x) 4.9 5.8 EV/EBIT(x) 6.23 7.21 Net Sales Growth(%) 49.21 20.33 Dividend payout Ratio (Net Profit) 13.31 10.7 Earning Retention Ratio 12.49 10.52 Price Book Value 1.64 3.11



Solution

We suggest you try to solve the questions on your own and then check back to see whether you have gone on the right lines

Q 1 Is Shriram Transport worth investing and if so give 5 reasons why you will invest in them.

To decide on this we should use both the Quantitative and Qualitative approach of Fundamental analysis.

Shriram is in the Indian domestic auto financing space and hence its fortunes will be closely linked to the growth in the Indian economy. India’s GDP growth, which had slackened to 6.7% in 2008-09 is now going up and will be in the region of 8.5% to 9% this year. This is expected to go more in 2010-11. The infrastructure spending and movement of goods from factories which govern the demand for trucks and indirectly the fortunes of Shriram are growing at an impressive pace. The company is not affected by slackening in global growth. All this makes one believe that the macro environment is very positive for Shriram.

A negative for Shriram is the high inflation and hardening interest rates in the economy. When interest rates go up, the cost of borrowings and even the availability of finance will become issues. Further, there might be resistance from borrowers to take loans at the relatively higher rates Shriram charges.

In the industry all banks are reporting good results and the Banking and Financial Services sector is finding favour with investors. So this would mean that the industry is looking good.

The company is not under any major threats in its markets. However some banks are looking at entering the used truck financing space and may undercut Shriram in pricing if they do. Its brand value is high and apart from interest there are no significant cost pressures. Its business is not subject to exchange risks

All things considered the pros appear to outweigh the cons for the next 12 months as far as qualitative macro factors are concerned.

Looking at the quantitatives, we find that sales have grown 20.33% in FY 2009-10, which is good though less in percentage terms than previous year. However the latest results indicate that the sales have gone up by an impressive 55% in the first quarter of 2010-11 on y-o-y basis. As far as profits are concerned, the growth in Net profit was 42% higher in 2009-10 at Rs 87.3 crs and this momentum has continued into 2010-11 with the Net Profit going up by 76% to Rs 288.9 crs in Q1. Clearly the sales and profits are on an upward path.

Let us turn to valuations. The Price/Book Value ratio is 3.11 up almost 100% compared to previous year. This is a bit worrying since this means that market price is going up much faster than the Book Value. The ROE for 2009-10 was 28.95% which in absolute terms is very good. The ratio of PBV/ROE is 0.12 and can be considered undervalued as we saw in the case of Bank of Baroda.

The Price Earnings multiple at the current price of 716 is 18.5 based on FY 2009-10 EPS of 38.72 ( note that P/E was just 13.54 on 31st March 2010 according to the data base but has gone up since then due to share going up!) Shriram is quoting only slightly less than the Sensex Trailing Twelve Months P/E of 20.5. What is the likely scenario for 2010-11? Company has projected a Net profit of Rs 1136 crs which gives an EPS of Rs 50.3 on an equity base of Rs 225.52 crs. Considering the first quarter performance, this



projection is reasonable and may be surpassed. At the Current Market Price (CMP) of 716, Shriram is having a Forward P/E of 14.2 compared to the Sensex Forward P/E of 17.5. This way it is clearly undervalued. The EV/EBIDTA is 7.21 which less than the Sensex EV/EBDITA. As far as dividend record is concerned, the Company has declared an enhanced dividend of 60% as compared to 50% in 2008-09 but still the Pay Out ratio has dropped considerably to 10.7 from 13.31. This is heartening.

Looking at the PEG ratio, the P/E now on TTM is 18.5. The EPS Growth percentage for 2010-11 will be (50.3/38.72) x 100 = 29.9%. The PEG is 18.5/29.9 = 0.62. Anything less than 1 is considered under valuation.

So over all on valuation parameters, Shriram is undervalued and worth buying.

In summary both on qualitative and quantitative parameters, Shriram is a good buy at 716.

Five reasons are

• Positioned to take advantage of booming economy

• Strong growth in Commercial vehicle industry

• Strong financials and profit growth

• Future 12 months growth momentum even better

• Decent valuations and good upside potential from current levels.

Q 2. What is the target price you may like to fix on a 12 month time frame?

There are several views on Target Price which is defined as the Price at which a stock can be sold. Investment icons like Peter Lynch do not believe in a Target Price and his view is that a share should be held until such time its fundamentals have worsened. Some fix target Price based on PEG and some on Market P/E or Industry P/E.

Looking at Market P/E approach, at Forward Sensex P/E of 17.5, for 2010-11 and the expected EPS of 50.3 for 2010-11, the target based on Sensex is 50.3x17.5 = 889. In other words if you buy at 716 you can book profits if the price goes to 885.

The second way is to see the price at which the PEG becomes 1. For that to happen the P/E must equal the expected EPS growth percentage. We saw above that the EPS growth forecast for 2010-11 is 29.9. Based on that the target Price is 29.9x50.3 = 1503. In other words only at this level will PEG signal a Sell. What this means is that as long as Shriram grows at this speed one should not be in a hurry to sell the stock.

There are some specialised refinements used by Fund managers to target price fixation based on P/E bands and historic premium/ discount to peers and market. Interested students can go deeply into these also.

Q 3 What are your concerns that you will keep an eye on?

All good investors continuously monitor the stocks in their portfolio to see if some hiccups are getting thrown up. Based on our analysis done so far I am listing a few concerns

• If interest rates keep going up faster than anticipated, relook at Shriram’s profitability and make sure the projected EPS is not affected.



• If the growth in the commercial vehicle sector slows down, see if the disbursements targets are threatened and what is the impact. Also see if these lead to increase in Bad loans.

• If Commercial banks enter used truck financing in a big way gauge the impact.

• Share has run up very fast last few months as P/E and P/BV indicate. It is trading at its all time highs.

• Sometimes regulators increase capital adequacy norms for finance companies. These will dilute EPS. Keep a watch.



References

Suggested reading

One Up On Wall Street- Peter Lynch

Beating The Street – Peter Lynch

A Random Walk Down Wall Street – Burton Malkiel

Questions 1 A fundamental analyst looks at

A. Global economic growth

B. Inflation in the economy

C. Stock Price charts

D. Only 2 of above

2. An increase in the central fiscal deficit

A. Is good for stock market

B. Is not good for stock market

C. Does not influence stock prices

3. The biggest component of India’s GDP is

A. Agriculture

B. Manufacturing

C. Services

4 Inflation and stock market are linked through

A. Economic growth

B. Risk aversion

C. Interest rates

D. Infrastructure spending

4. Maturity stage companies

A. Have high growth

B Low growth



C. Stable profits

D. B & C above

5. Reduction of import duties has adversely affected Indian companies involved

A. Steel making

B. Information technology

C. Banking

D. None of these

6. For reducing Competitive Rivalry Porter Model suggests

A. Becoming a volume player

B. Becoming a niche player

C. Lobbying with Government to impose controls

D. All of above

7. A security with low ROE and high P/BV is

A. Undervalued

B. Overvalued

C. These two cannot be related

8 Enterprise Value depends on

A. Market price

B. Number of equity shares

C. Long Term Debt

D. All three

9. Companies with high earnings growth prospects compared to PE have

A. High PEG

B. Low PEG

C. Not related at all

10. High Dividend payout

A. Sign of a fast growing company

B. Sign of a mature company

C. Not related



10. A company has an Equity capital of Rs 10 crs and make a Profit after tax of Rs 7 crs. Its capital will remain the same in the coming year but its Profit after tax will go up to Rs 10.5 crs. Its Market Price is Rs 140. Its PEG

A. 0.5

B. 0.4

C. 2.5

D. 2

Technical Analysis 29


2. Technical Analysis

Learning Outcomes In this section we will be discussing the technique of Technical Analysis which is becoming very popular with traders. We will start by understanding the difference between Fundamental and Technical analysis. We will then explain the Dow Theory and trend analysis. Then we will move on to understanding some important Chart Patterns. The course with then take up Moving Averages, important Momentum indicators. Next we will discuss Fibonacci ratios and their application to stock market. The section will conclude with a fairly detailed look at Candle Stick charting and how to make predictions using them At the end of this section you should be able to all these tools independently and in conjunction and arrive at Buy, Hold and Sell decisions.

Overview Tool used by analysts to predict future stock prices Study of historical prices adequate for predicting stock prices No special knowledge of economics or corporate finance required Share prices like commodities are a function of supply and demand

Technical analysis is a tool used by analysts to predict the future price movement of stocks. It is also used in other areas like foreign exchange, commodities etc. Technical analysts believe that based on past historical trends of share prices, one can make good estimates of its future price. For such an analyst the price and only the price determine the future price movement. Unlike in fundamental analysis no special knowledge of economics or corporate finance is required. It is supply and demand that influences share prices. Another important assumption that such an analyst makes is that historical trends always repeats themselves.

Technical Analysis (TA) versus Fundamental Analysis (FA)

Technical Analysis Fundamental Analysis

looks at a share as a commodity looks at share as unique by itself

studies only about historical share

prices and their trend analyses future outlook and growth

feels history repeats itself looks for re-rating of stocks

gives lot of importance to

sentiment and very little for value attempts to get the intrinsic value of

a stock and get undervaluation

The technical analyst feels a share is a commodity where as fundamental analyst sees each share is unique by itself. TA believes that past track record of share price is all that matters to predicts future trends. The



FA believes that the future price depends on the prospects of economy, industry, company and the valuation. TA feels that history will repeat itself and FA believes that a share can get totally re-rated due to change in fundamentals. TA feels sentiment is most important and intrinsic value has little relevance. FA feels that while sentiment does play a small role it is primarily the intrinsic value of share that matters.

Dow Theory and Trend Analysis

Dow Theory Market movement can be separated into trends Long Term Trend Intermediate Trend Short Term Trend Investors with different time horizons track the trend they want

Charles Dow- after whom the New York Stock Exchange Index is named – can be called the Father of technical analysis. Dow identified three types of price movements for the market index. These he called them the long term trend, the intermediate trend and the short term trend. Dow in his works did not try to go away from fundamental approach but said it was akin to the movement of an economy during business cycles when economies go through Recession, recovery, expansion, contraction and again to recession.

The long term trend is the longest among the three and we call a market a bull market or a bear market depending on whether this long term trend is up or down. According to Dow these trends can last anywhere between one year and four to five years.

One can think of a primary trend as having 10-20 intermediate trends and an intermediate trend as one having 3–4 short term trends. Long term investors who adopt buy and hold strategies like pension funds, insurance companies give more emphasis to the long term trend. Active fund managers and positional traders who are trying to capture smaller moves operate in the intermediate trend. Traders and derivative players who have a time horizon of just a few days prefer to concentrate on short term trend. Different technical analysis methods are used depending on the type of investor you are.

The intermediate trend can last anything between four and twelve weeks. A long tern trend will consist of several such intermediate trends. The intermediate trend happens when people book profits in a bull rally or there are some events like election, union budget, corporate results which weigh the investor’s sentiments. Intermediate trends can be both up or down; when it is down people are booking profits and when it up then they are again re-entering.

Consider the Bull market in India which has started in March 2009. As the economy was turning around and the valuations were enticing, the bull market started with great ferocity in March 2009. The Nifty went up from 2518 on 12th March 2009 to 4655 in 10th June 2009. Then it went into an Intermediate downtrend which lasted 5 weeks when the Nifty corrected about 15% and went to 3974. Then again the uptrend was resumed. This was a typical example of an intermediate downtrend and was mainly on account of first reports of a poor monsoon. Now you are getting an idea of how even in a bull market we get periods of corrections.

The short term trend is as its name itself indicates short term in nature and can last from a few days to three weeks. Short term trends happen not due to any fundamental reasons but internal reasons of the market e.g. many long positions created and traders have to close positions, may be closure of derivative cycle, long holidays etc.



Trend Line • Trend line in an uptrend is a line drawn connecting the higher lows • Represents a key support level when stocks correct • In a Down trend it connects lower highs and represents key resistances • Channels are two parallel trend lines

A trend line is a useful charting technique where line is drawn to a trend chart to represent the trend itself. An upward trend line shows up when we draw the line connecting the successive higher lows in an upward trend. This line is also called the support line since it gives support to the share when it touches the trend line. This line is very important for traders as it helps then to anticipate the point at which a stock price will begin moving upward again. Similarly in a down trend a downward trend line is drawn connecting the successive lower highs of the downward trend. This line represents the resistance line which the stock is unable to cross.

A channel is two parallel trend lines that act as areas of support and resistance. The upper trend connects the series of highs and the lower trend line connects a series of lows. The channel is very important for traders as any breakout outside the channels indicates a trend reversal.

Trend lines shown graphically

Understanding Patterns

Resistance and Support • Important levels where the bulls and bears fight for control • Levels represent points from which shares correct repeatedly or recover

often • Breakdowns are viewed seriously by traders as trend reversals



Support and resistance are important concepts which analysts use. These represent levels at which bulls and bears are battling and the struggle is going on between demand and supply. Resistance level is the level drawn by joining the tops which the share makes and unable to cross. Support is the level drawn by joining the bottoms that the share makes and which it is unable to cross.

Breakages of these levels are very crucial and represent major changes in the way traders look at the stock. For example, once resistance level is broken traders rush to buy the stock and once support level is broken they rush to sell the stock. One interesting thing to know about resistance and support levels is that once a resistance level is broken it becomes a support level for future movements. In the same way once a support level is broken it becomes the resistance level for the future. The breaking of the support and resistance levels is referred to as Trend Reversals

Resistance and Support

Chart Patterns • Chart pattern is a formation which gives signals • Head and Shoulders • Inverted Head and Shoulders • Double tops and double bottoms



A chart pattern is a distinct formation on a price chart which gives a signal of future price movement. Chart pattern is used pattern both for continuation and reversal of trends. A continuation pattern is a pattern which confirms that the existing trend will continue after the pattern is complete. Reversal pattern is one which tells us that the existing trend is about to be broken decisively.

Head and Shoulders is one of the most important and used reversal chart patterns. Head and Shoulder is a pattern that is formed at the top of an uptrend and signals that the uptrend is about to end. The pattern consists of three tops in the trend line. The centre top (called the Head) is higher than the two on the left and right (called the Shoulders). A horizontal line drawn connecting the bottom of the two shoulders is called Neck line.

The interpretation of H-S line is as under. The left shoulder forms a peak which is the high point of the ongoing uptrend. Than the stock reacts up to the neck line; from there the stock again starts moving up and the share reaches a level higher than the previous high and peaks out and this is the head. After peaking it reverses back to neck line. It again starts going up. It forms the second shoulder but instead of going up further and going higher than the head, it starts correcting again. At this stage the uptrend is under threat. The share is trying to go up but fails to do so. In fact it is not even able to reach the previous high shown as the head. This time in the correction it breaks the neck line. The trend has reversed from up to down. When traders see the charts of H-S pattern they just stop increasing their positions. When the neckline is broken (with volumes) then they start shorting. The inverted head and shoulder is correspondingly a very bullish pattern but it is not used that much as the regular H-S pattern.

Head and Shoulders

Double tops and double bottoms are other important charts patterns which are popular. The double top denotes a trend reversal and this pattern is found after a sustained uptrend and signals that the trend is about to reverse. The double top is created when the price movement tries twice to move above a certain level but fails. After making this unsuccessful attempt the trend reveres and the price falls sharply. The opposite of this case is double bottom which is a bullish trend reversal. There are also other patterns like triangles, flags, pennants and wedge which are some times used by traders.



Double Tops and Bottoms

Figure 1

Volume Confirmation • Volume refers to number of shares traded in the chosen period • Volume serves as a confirmation of conclusions drawn from charts • Conclusions not backed by volume are not acted upon by traders

Traders always look to volume for confirming what the charts tell them. Volume is simply the number of shares that are traded over a given period; usually a day. The higher the volume is the more active the share. Volume bars can be seen at the bottom of any chart. The golden rule about volume is that it confirms the trends. Any movement with high volume is taken more seriously than movements without volume. Another point about volume is that it normally comes before a trend change e.g. if a stock is in uptrend and the volume is drying up that is dangerous since that uptrend will end soon. Smart traders look to the product of price and volume to take a final decision.



Volume illustrated

Moving Averages • Extremely popular tool with chartists • Simple and exponential moving averages • Exponential is more popular as it gives more weightage to more recent

data

The moving average is an extremely popular technique used by chartists and is used both for monitoring the continuation of a trend and for predicting a trend reversal. It is also often used to mark out resistance and support levels of the stock.

A moving average is nothing but the average price of security over a set period of the time. Traders use a moving average to smooth out the price movements. Once the day-today fluctuations are removed using the average technique, it is easier to identify the true trend and increase the probability that the prediction is correct.

There are two types of moving averages; simple moving average (SME) and the exponential moving average (EME). The SME is the most common method used to calculate the moving average price and it simply takes the sum of all the past closing prices over that time period and divides the results by the no of prices used. For example in a 10 day moving average the last ten closing prices are added together and then divided by ten to get the value. For the next day the first day price is removed and the eleventh day (latest day) is included that way the chart is built up. The SMA has one disadvantage because in this type of average each point of the data series has the same impact on the result whether it’s last data point or the first. To get around this problem the exponential moving average (EMA) is used. All charting packages will do this calculation of giving higher weightage to recent data and so one need not do the calculation.



SMAs and EMAs

Interpretation of Moving Averages • 30,100 and 200 DMAs • Show the nature of the trend • Represent supports and resistances for short medium and long term

trends • Break downs are important • Crossovers are reversal points

The most popular use of the moving averages is to see whether the moving average is in an uptrend or in down trend. For this purpose three moving averages are normally used. These are thirty day moving average (30 DMA) which denotes the short term trend; the 100 DMA which tracts the intermediate trend and the 200 DMA which tracts the long tern trend. Depending on which one is up we can say that particular trend is up. If the share price is above the 200 DMA the long trend is up; If it is above 100 DMA intermediate trend is up ; if above its 30 DMA short term trend is up . The best pattern is when share price is above all three DMAs.

Another very important use for the moving averages is to study the crossovers. When the price moves through a moving average it is called a crossover and seen as trend reversal. For e.g. when a price of a share which have been in an up trend cuts its 30DMA from above that means that uptrend is reversing. Another important cross over is a crossover of a shorter period DMA over a longer period DMA. For instance, if the 30DMA crosses the 100 DMA from below it is very bullish.

The third use of the moving averages is to identify the support and the resistance levels. Simply put the share which is in a uptrend and starts correcting but gets support on a DMA then that implies that the DMA is important support level. Alternatively once the share has fallen below that support level it turns into a resistance level. So, traders often use DMAs to identify resistances and supports.



DMAs illustrated

Momentum Indicators • Momentum refers to the speed of change • Relative Strength Index • Stochastic Oscillator • Can sometimes give misleading signals also • Need to be confirmed with other tools

Momentum refers to the speed of the price change over time. Measuring speed is a useful gauge of impending change; for example when a car is slowing down after going fast one can assume it is going to stop. Momentum indictors are also called oscillators. In precise terms an oscillator is an indicator that moves up and down across a reference line between 0 and 100.

The RSI is one of the most popular momentum indicators. RSI is an excellent indicator to signal whether stock is overbought or oversold. Being a leading indicator it is popular with short term traders.

The Stochastic oscillator is another popular momentum indicator used in technical analyses. It is somewhat similar to RSI but more sensitive. The disadvantage with Stochastic is its a hyper sensitive index compared to RSI and sometimes gives misleading whipsaw signals.



Relative Strength Index (RSI)

Relative Strength Index (RSI)

The RSI is one of the most popular momentum indicators. The formula for RSI is as under

RSI = 100-{100/ (1+RS)}

Where RS = no of up days / no of down days

RSI is an excellent indicator to signal whether stock is overbought or oversold. The RSI is plotted between 0 and 100. Reading above 70 shows that stock is overbought and will correct while reading below 30 shows it is oversold and will move up. RSI is calculated using 14 trading days as the basis. Being a leading indicator it is popular with short term traders.



Stochastic Oscillator

Stochastic Oscillator

The Stochastic oscillator is another popular momentum indicator used in technical analysis. It is somewhat similar to RSI but more sensitive. Like the RSI the SO is plotted within 0 to 100 ranges and signals overbought above 80 and oversold below 20. The SO contains two lines; %K which can be thought of as a fast moving average and %D which can be thought of as a slow moving average. A trigger can also be generated when the fast moving %K cuts the slow moving %D. The best way to use SO is to wait till both lines go below 20 and turn up and buy at that stage. Conversely when both lines go above 80 and turn down it is time to get out. The disadvantage with Stochastic is it is a hyper sensitive index as compared to RSI and quite often gives misleading whipsaw signals.

Fibonacci Ratio • Statistical tool created by 13th Century Italian mathematician Fibonacci • Uses a Divine Proportion to predict retracement levels • Used by chartists to make trend reversal calls

A rather romantic tool used by technical analysts is the Fibonacci Ratio. Some readers at least will remember this from Dan Brown’s best seller Da Vinci Code where Professor Robert Langdon uses this mysterious number to crack the Code. First lets take a peek at a bit of history. The Fibonacci Proportion was first discovered by an Italian mathematician Leonardo Fibonacci who lived in the early 13th Century. It is believed he took it from old Indian Vedic mathematical works.

What is the Fibonacci sequence? It is simply a sequence created from natural numbers starting from 1 where each succeeding term is nothing by adding the previous two terms. So the first numbers of the Fibonacci sequence are



1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144,…

Now you divide a number by its previous number and the fun starts.

2: 1= 2.0 (0.5)

3: 2 = 1.50 (0.67) 5: 3 = 1.67 (0.60)

8: 5 = 1.60 (0.625) 13:8 = 1.625 (0.615)

21:13 = 1.615 (0.619) 34:21 = 1.619 (0.617)

55:34 = 1.6176 (0.618) 89: 55= 1.61818 ( 0.618)

(Figures in brackets are reciprocals)

You arrive at the amazing fact that we are coinciding closer and closer to 1.618 and its reciprocal 0.618! The golden number as Fibonacci number is often called is 1.618! This is often denoted by the Greek letter Phi. The reciprocal number is also often used and is 0.618! You may ask “ True this is a mathematical beauty; but why is it so important for our analysis?”. The reason is this number seems to be Nature’s own- some will call God’s own- number. Many things in nature and in human activity seem to follow this number. To illustrate this, I can do no better than quote from Prof Langdon from Dan Brown’s book itself.

“ PHI’s ubiquity in nature clearly exceeds coincidence and so the ancients assumed the number PHI must have been pre ordained by the Creator of the universe. Early scientists heralded 1.618 as the Divine Proportion… Ever studied the relationship between females and males in a honeybee community? The females always out number the males. And if you divide the number of female bees by the number of males in ANY beehive in the world it is 1.618!”.. “ spiraled pine cone petals, leaf arrangement on plant stalks, insect pigmentation- all display astonishing obedience to the Divine Proportion!.....”

“Now the most exciting thing. Divide the distance between tip of your head to the floor by the distance from the belly button to the floor. The number you get is 1.618! Now, measure the distance from your shoulder to your finger tips by the distance of the elbow to the finger tips. The number….. again 1.618!”.

Now you see why Chartists also got excited? How do we use this Divine Proportion?

When used in technical analysis, the golden ratio is typically translated into three percentages: – 38.2%, 50% and 61.8%. However, more multiples can be used when needed, such as 23.6%, 161.8%, 423% and so on. There are four primary methods for applying the Fibonacci sequence to finance: retracements, arcs, fans and time zones. We will discuss Retracements only.

Fibonacci retracements use horizontal lines to indicate areas of support or resistance. They are calculated by first locating the high and low of the chart. Then five lines are drawn: the first at 100% (the high on the chart), the second at 61.8%, the third at 50%, the fourth at 38.2%, and the last one at 0% (the low on the chart). After a significant price movement up or down, the new support and resistance levels are often at or near these lines. Take a look at the chart below, which illustrates some retracements:



It is clear that the trend has reversed very close to the Fibonacci ratios. This ratio though not infallible gives very good signals indeed. One should not however swear by Fibonacci and should use it along with other indicators.

Candlesticks Charting The Japanese have not done much for investments or stock markets. All their expertise is more evident in automobiles, electronics etc but there is one part of investments where the world has borrowed one of their age old techniques. It is the art of Japanese candlesticks or just Candlesticks. This style of charting was invented by the Japanese traders in 1700s when trading rice. These traders observed that the price of rice was not just linked to the demand and supply of rice but also emotions of the traders who traded rice. They developed the Candlestick techniques to take into account this phenomenon.

Let us understand how a candlestick looks and how it works.

It is similar to a bar chart and the daily candle stick lines contain the market’s open, high, low and close of a specific day. Now the system starts looking very different. The candle stick has a wide part called the



Real Body. This Real Body denotes the range between the open and close of that day’s trading. When the Real Body is filled with black or colour it means that the closing price is lower than the opening price. If the Real body is empty it means the closing price was higher than the opening price.

You will see from the figure above that the Real Body also has the two lines which are called the Shadows. The Shadows show the high and low prices of that day’s trading. If the upper Shadow is short and the Body is black it means that the open price was close to the high of the day. A similar short upper shadow on wide body means that the close was near the high of the day. So you can see that the candlestick is a three dimensional thing. It gives lot more information than the bar chart.

While this is the basic building block of candlestick charting, different patterns are studied to use candlesticks for interpreting movements of shares. This is a very big subject and one can’t understand all of them. However we can discuss the more important one and see how to use them profitably.

The Doji The Doji is a common and oft used pattern. It comprises of one candle and is formed when the open and the close occurs at the same level or very close to the same level. The Real Body then almost becomes a line as you can see from the figure. It looks a lot like star and upon seeing a Doji pattern in an over bought or over sold situation, chartists smell a high chance of a trend reversal. That is to say when a Doji appears at the top of a trend it’s a strong sign that a fall is imminent. Conversely if a Doji appears at the bottom of the trend it is likely that buying is going to start.

Engulfing Patterns The engulfing pattern is also an important trend reversal pattern. It basically comprises of two opposite coloured bodies. A bullish engulfing pattern is shown below.

You can see that the white body candle is bigger than the black body candle. Not only that, it has “engulfed” the previous one. It means that the stock opened lower than the previous day close but ended higher than the previous days open. For this to be considered a bullish trend reversal, the black candle must be at the end of at definite down trend.



The reverse is true in the bearish engulfing pattern. The white body is formed at the end of the uptrend and is followed by bigger black body that ominously engulfs it. Please see the chart below

Hammers The hammer is just one candle with small body having a shadow at least twice bigger than the body. It looks a lot like the hammer which we use in life. If found at the bottom of the down trend, it is strong evidence that the stock is turning bullish. The colour of the small body is not important but the shadow must be much longer than the body and should occur at the down trend.

Harami Patterns Harami in Japanese means a pregnant woman and implies a body with in a body. We will see how the word fits the pattern we are going to discuss.

Bullish Harami This pattern appears often and it is composed of a two candle formation at the end of the down trending market. The body of the first candle is dark and the body of the second candle is white but smaller. In a classic Harami the smaller candle is inside the bigger candle.



What this means is after a strong down trend the bulls open the stock higher than the previous close. The shorts get covered and bulls win the day and price finishes higher. If we get a white candle the next day that will confirm the trend reversal

Bearish Harami This is the exact opposite of the previous one and occurs at the end of the uptrend. The first is white body is bigger than the second which is black and smaller.

It shows the bearish trend reversal and if the share falls the next day the pattern is confirmed.

Morning Star

This is a trend reversal pattern from bearish to bullish. As we have seen the Japanese name their patterns very beautifully and this pattern is called the Morning Star because it portends better days. Mercury is the morning star and appears at sun rise. Its appearance itself indicates a bright day ahead. The pattern itself consists of a long black body coming at the end of a period of decline. The next day is a gap down day but the candle body is much smaller. The third day is a white candle day and this represents that the bulls have stepped in and seized control of things.



For a Morning Star to be strong two points are worth mentioning. The Morning Star itself must have a gap with the days before and after. Secondly the white candle on third day must be at least 50% of the way up compared to the black candle of the first day.

The psychology of the Morning Star is that on the day of the Morning star the bulls have started stepping in and the bears seem to be in the mood to give up control. On the third day the bulls take charge and a clear trend reversal has happened.

Evening star

This is opposite of the morning star and happens at the top of the bull trend. It is named after the planet Venus and signifies the darkness (bearishness) that is about to set in.

The arguments here are exactly opposite with the condition that the black candle of the last day be at least half way up the white candle of the first day.

Shooting Star This is bearish signal coming at the end of a bull trend. The Japanese called it Shooting Star because the pattern looks like a Shooting Star falling from sky with big tail.



It comprises of one white candle with a small body and a shadow which is at least two times greater than the body. It is not essential that the shooting star should be black body but the day after that there has to be black body.

The logic behind this pattern is that a strong bull trend has been in existence for long time but it appears as if on this particular day the bears have stepped in and started taking control. This is because the body is small but the shadow is large. This type of conclusion one can never get from the Western Style bar charts. If a black candle appears on the day after the morning star it is a perfect bearish pattern.

Inverted Hammer It is just opposite of the Shooting star and means that the party is over for the bears and bulls are taking charge. The Inverted Hammer is a small body candle with a long shadow at least twice in length. It is normally a white body but it is not essential. However a white candle on the day after Inverted Hammer is a very Bullish follow up sign.

Volume confirmation for these patterns increases the probability that the pattern is working. A large volume on the day of the Shooting Star means that almost definitely the bull trend is over. In the same way a large volume on the day of the Inverted Hammer increases the chances that panic selling has already happened and the trend has reversed.

Candle stick patterns are become very popular because of their simplicity and much of the interpretation can be done just by looking at the patterns. Also most of them are trend reversal patterns which are always interesting for investors. But one should remember that these are short term patterns unlike moving averages which are long term patterns. Nowadays practically all chartists prefer them to old style bar charts. It is suggested that these should be used in conjunction with other charts like RSI.



References

Technical Analysis Explained- Martin J Pring Japanese Candlestick Charting Techniques– Steve Nison

Questions Q1: Technical analysis concentrates on

A Future cash flows

B Future chart patterns

C Historical chart patterns

D Historical accounts

Q2: In Dow Theory, the Long Trend consists of

A Several intermediate and short term trends

B Several short term trends

C Just a few intermediate and short term trends

D Just a few intermediate trends

Q3: A Trend Line is drawn connecting

A Succeeding bottoms on the Chart pattern

B Succeeding tops on the Chart pattern

C Succeeding intermediate points

D None of these

Q4: When a share goes below the neck line in a H-S pattern is

A Very bearish

B Very bullish

C Needs a confirmation before one can say anything

D Continuation pattern



Q5: When the share price is above the 200 DMA and below the 100 DMA it means that

1. Long term trend is up

2. Long term trend is down

3. Intermediate trend is up

4. None of these

Q 6 Chartists prefer Exponential Moving Average to Simple Moving Average because

1. It is easier to calculate

2. It is more modern

3. It gives more weightage to more recent prices

4. It gives more weightage to more distant prices

Q 7: Momentum indicators are good for

A Day trading

B Positional trading

C For both

D Long term investing only

Q 8: When the 14 Day RSI is at 75, it is better to

A Sell the share

B Buy the share

C Hold the share

D Can’t say

Q 9: The Fibonacci Number is

A 0.618

b1.618

c 1.168

d 1.816

Q 10 : Fibonacci numbers are useful for



A Spotting trend reversals

B Spotting increasing in trend momentum

C End of a trend but not beginning of a new trend

D Nothing to do with trend at all.

Q 11. Candlestick charts are superior to Bar Charts because

A They look prettier

B They give an idea of the sentiment during the day

C They are more convenient to draw and use

D The results are more decisive

Q 12. A Hammer is

A Always bullish

B Always bearish

C Bullish only if it has a white body

D Bullish only the shadow is five times longer than the body.

Q 13 Harami patterns are

A Shooting patterns

B Engulfing patterns

C Single candle patterns

D None of these

Q 14 In a Bearish Harami pattern,

A A small black body candle is engulfed by a previous big white body

B A small white body is engulfed by a previous big black body

C A big black body engulfs a previous small white body

D A big white body engulfs a previous small black body.

Portfolio Management 50


3. Portfolio Management

Learning Outcomes In this section we will start by discussing the Efficient Market Hypothesis which is one of the most fundamental principles in Investment management. Then we will move on to Risk, what different types of risk are and how risk is measured. Then we will learn about Modern Portfolio Theory which is the technique of building a portfolio of assets keeping in mind risks and returns. Towards this end, we will study about Diversification, Covariance and Coefficient of Correlation. We will then learn about Markowitz Theory, Capital market Theory, CAPM. Then the concept of Beta and Security Market Line will be discussed. The section will conclude with different portfolio management and rebalancing strategies, evaluation measures like Sharpe, Treynor and Jensen’s Alpha. At the end of this course, you must be in a position to

• Judge the efficiency of the market from the EMH point of view • Understand the risks in each asset class classify and dimension them. • Use different portfolio theories to construct portfolios • Be able to measure portfolio performance using sophisticated tools.

Overview Portfolio management is an emerging part of the world of investment management. It is concerned with the risks associated with investment in securities and classifies risks and quantifies them. It then uses this concept of risk to develop portfolio management theories which tell us how to build portfolio of securities which optimize returns for a given amount of risk. These theories are widely used by fund managers all over the world to manage investments. Finally it deals with portfolio evaluation measures which will enable one to assess portfolio performance.

Efficient Markets Hypothesis

• Prices immediately and fully reflect all available information • It is not possible to outperform the overall market through expert stock

selection • EMH implies that markets are inherently unpredictable

Since the Efficient market theory is a basic theory in portfolio management let us understand it before going into Portfolio theories in detail. Markets are efficient when prices reflect available information fully and immediately. This happens when capital markets become so advanced technologically, and when there is such a large number of players in the market transacting continuously, that the time it takes for economic and corporate news to get reflected in the price of a share tends to reduce to zero.

An example of this would be that of an investor reading of a company’s results in the newspaper and then going out and purchasing the share based on this information. In an efficient capital market there would be no way that this investor would be able to make a consistent profit, because by the time she goes to place the order the market has already incorporated the effect of the news item in the share price. This would have happened because there will be others who are able to transact even earlier than this investor who has had to wait for the newspaper, and hence they would have driven the price of the share up by buying it.



EMH is an investment theory that states it is impossible to "beat the market" because stock market efficiency causes existing share prices to always incorporate and reflect all relevant information. According to the EMH, stocks always trade at their fair value on stock exchanges, making it impossible for investors to either purchase undervalued stocks or sell stocks for inflated prices. As such, it should be impossible to outperform the overall market through expert stock selection or market timing, and that the only way an investor can possibly obtain higher returns is by purchasing riskier investments.

An efficient market is inherently unpredictable, because if there was a method of predicting future prices based on currently available information then that method would be exploited instantaneously, leading to the price reflecting its new value, and hence there would again be no predictability of future price. EMH simply states that prices now reflect everything that is known or implied about the future value of the asset in question.

Efficient Market Hypothesis: Types The three forms of Efficient Markets Hypothesis are weak, semi-strong and strong. These forms are in an increasing order of efficiency and the stronger form encompasses the features of the weaker form of efficiency. For instance the semi-strong form says that all public information is reflected in share prices while strong form says that all public and private information is reflected in share prices, so a strongly efficient market is at least as efficient as a semi strong one and so on.

Types of EMH

• Weak Form• Semi-strong Form • Strong Form

Weak Form

Semi-strong

Strong

All information Public & Private

All Public Information

All Historical Prices & Returns The implication is that markets, as they get more technologically advanced and more transparent, will move towards greater efficiency, as information is spread out more quickly and widely to all the participants, who then are able to change their price expectations accordingly.

EMH: Weak Form • Past prices, volumes and other market statistics provide no information

that can be used to predict the future. • If stock prices are random then, past prices cannot be used to forecast

the future prices.



Weak Form of Efficiency basically says that past prices are not an indicator of forecasting future prices. The argument is, that if there were a reliable method of predicting future prices using past price trends, then the knowledge of this method would be exploited by traders immediately and the prices of shares would reach a point which would not allow the excess return to be generated. In other words, the predictive method would carry within it the cause of its own failure.

If markets are weakly efficient then technical analysis would not work. Because technical analysts use charts and diagrams of past prices to create trends and predict future prices based on these trends. EMH says that these ‘trends’ are merely after the fact justifications and patterns that we impose on what is essentially a random process.

EMH: Semi strong form • Prices fully reflect all publicly available information & expectations about

the future. • Accordingly, prices adjust rapidly to new information & old information

cannot be used to earn superior returns The next level of efficiency is the semi –strong one, which says that prices reflect all publicly available information, not just historical share price data. This would imply that there is nothing to be gained by trading once one has read a news item about, say, an increase in company profitability, because the price should already reflect this increase. This is a fairly controversial assumption because it implies that there is no point in trying to do research on corporate performance or economic trends, because it says that someone would have already done it, and so, you per se, may not benefit from doing the research. While weak form rules out technical analysis as a consistent way of predicting prices, semi-strong rules out both fundamental and technical analysis.

But then why is it that investment banks and mutual funds exist, and spend millions of rupees on precisely this sort of research? There are two answers to this question and the one you pick depends on your point of view. One is that, they spend this money because they have it. i.e. Investors believe that there is a point to professionally managed investments and thus if one takes the view that a professionally managed investment is better than one that is made purely randomly, then it would be logical to do as much research as one can before making an investment decision.

The second argument is, that markets achieve efficiency precisely by the fact that companies are doing research and invest based on equity research, and when prices reflect the new ‘true’ values, they make a profit. The EMH needs to have this taking place in order for the markets to become efficient and so in equilibrium there should be some value in this kind of activity. It would appear however, that as markets get more and more efficient, the amount of mispricing that is available for analysts to exploit should be less and less, and the window of opportunity for the investor to make use of these mispricings as and when they arise, should get smaller.

EMH: Strong form • The strong form says that prices fully reflect all information, whether

publicly available or not. • Even the knowledge of material, non-public information cannot be used to

earn superior results. Strong form of efficiency implies that even insiders, i.e. persons with privileged information about a stock cannot make money by trading on it. For instance the owners or managers of companies, lawyers, accountants or others who might have access to price sensitive information before the rest of the public is given this information, they could potentially stand to gain by trading before the information is made public.



This practice, called insider trading, is banned in most markets as it gives unfair advantage to some market participants over others, and may lead to market manipulation. Strong form efficiency says that even insiders cannot benefit from their knowledge because markets discount even this inside information. Most studies have found that the markets are not efficient in this sense, so there is a potential financial benefit from, though a moral and legal risk in using, inside information.

Exceptions to Efficient Market Hypothesis Anomalies are unexplained empirical results that contradict the EMH: • The Size effect. • The January Effect • P/E Effect • Day of the Week (Monday Effect).

These are a few pricing anomalies, which have persisted over time, and allow investors to make excess returns time and again, which appear to be in direct conflict with the EMH. These are based on empirical data and let us try to understand possible reasons behind them.

Size Effect • Beginning in the early 1980’s a number of studies found that the stocks

of small firms typically outperform (on a risk-adjusted basis) the stocks of large firms.

Size effect is also known as the small cap effect. It means the tendency of the small cap shares outperforming the large cap over the long term. This is even true among the large-capitalization stocks within the S&P 500. The smaller (but still large) stocks tend to outperform the really large ones. Investors should regard it as most relevant when constructing a portfolio of shares that they are likely to hold for the long term as the out performance of these stocks tends to get offset by the transaction cost.

A 1976 study by Michael S. Rozeff and William R. Kinney, called "Capital Market Seasonality: The Case of Stock Returns", found that from 1904-74 the average amount of January returns for small firms was around 3.5%, whereas returns for all other months was closer to 0.5%.This suggests that the monthly performance of small stocks follows a relatively consistent pattern, which is contrary to what is predicted by conventional financial theory. Therefore, some unconventional factor (other than the random-walk process) must be creating this regular pattern.January Effect

• Stock returns appear to be higher in January than in other months of the year.

• This may be related to the size effect since it is mostly small firms that outperform in January.

• It may also be related to end of year tax selling. The January effect (happens in U.S. market) for instance is a well documented fact that stock returns are higher in January than in other months. Now one of the main reasons posited for this effect is that there is end of the year tax related selling by mutual funds and then the corresponding increase in buying in January, which cause the returns for that month to be higher.

This would appear to indicate that the markets in the US in the mid eighties were not very efficient as there should be no reason for the effect to be sustained several years and indicates a certain predictability in the market returns. Of course, an efficient markets advocate would argue that one could always find in retrospect months of higher return than average with any dataset and so there is nothing unusual about it.



And that one could always, in retrospect, find reasons for a particular market price behaviour, it is just difficult for the price behaviour to be predicted beforehand.

One explanation is that the surge in January returns is a result of investors selling loser stocks in December to lock in tax losses, causing returns to bounce back up in January, when investors have less incentive to sell. While the year-end tax sell off may explain some of the January effect, it does not account for the fact that the phenomenon still exists in places where capital gains tax does not occur. This anomaly sets the stage for the line of thinking that conventional theories do not and cannot account for everything that happens in the real world.

P/E effect • It has been found that portfolios of “low P/E” stocks generally outperform

portfolios of “high P/E” stocks. • This may be related to the size effect since there is a high correlation

between the stock price and the P/E. • It may be that buying low P/E stocks is essentially the same as buying

small company stocks. It is the finding that the portfolios of low P/E stocks generally outperform the portfolios of high P/E stocks.

A low P/E typically signals any of the following:

Stocks which the market is not interested in at the moment.

Stocks suffering from previous excesses of pessimism on their prospects (negative overreaction),

Businesses that have the potential to recover (positive under-reaction).

It is also seen that low P/E stocks also have small P/Es leading one to believe that both these phenomena are one and the same.

Monday Effect • Based on daily stock prices from 1963 to 1985 Keim found that returns are

higher on Fridays and lower on Mondays than should be expected. It is the finding that returns on Fridays are higher and on Mondays are lower. This is partly due to the fact that Monday returns actually reflect the entire Friday close to Monday close time period (weekend plus Monday), rather than just one day. Moreover, after the stock market crash in 1987, this effect disappeared completely and Monday became the best performing day of the week between 1989 and 1998.

Risk & Return

What is return? • The primary motivating force that drives investments. • Represents the financial reward for undertaking an investment.

Return Return is often expressed as a percentage of the initial investment. For example, an initial investment of Rs 100 that generates an income of Rs 12 per annum for the investor is said to have a 12% return. This is



return in the form of income. Sometimes return can be obtained by the asset being purchased increasing in value. For example if I buy a house for Rs 10 lacs and real estate prices go up and I manage to sell it for Rs 15 lacs then I have got a 50% return on investment.

Calculating Return

Rate of Return = Annual Income + Ending Price – Beginning PriceBeginning Price Beginning Price

Current Yield Capital gain/loss

Components of Return: To formalize the previous examples,

Current Return: It is the periodic cash flow (income), such as dividend or interest, generated by the investment.

Capital Return: It is the price appreciation (or depreciation) divided by the beginning price of the asset. Return is often a combination of the two aspects. Consider the following case, A Rs 100 investment is used to purchase a to buy a piece of equipment that generates an annual income of Rs 12 for two years but can be sold only for Rs 90 at the end of the period.. What is my return?

My cash outflow is -100 at the beginning of the year

My total cash inflows are 24 + 90 = 114

Therefore my return is Rs 14 for 2 years or 7% per annum

So, while the equipment is generating Rs12 of income a year it is also losing Rs 5 of its value per year, giving us its average return of 7%

Time Value Of Money

• The Time Value of Money implies that returns generated in the future are less valuable than current returns.

• The IRR of an investment tells you what the return is on an investment after taking Time Value of Money into account.



We have already studied this in Unit I but we are just refreshing here. The principle of time value of money arises from the fact that if one has money today, one can invest it to get interest, and so will be worth more in the future. Note that in the example given below, we have ignored the time value of money i.e we have considered the cash flows at the end of year1 and year 2 to be identical in value. The Internal Rate of Return or IRR of this investment is the rate of return that would reflect the fact that the cash flows from year 1 can be reinvested to produce returns, and therefore are more valuable than the cash flow from year 2. Thus the cash flows in succeeding years need to be discounted by an interest rate (IRR), which will make the investment in the equipment equivalent to the cash generated by it.

The IRR for the example given before would be the solution to the following equation

100 = 12/(1+IRR) + 12/(1+IRR)2 + 90/(1+IRR)2

Solving the quadratic equation gives us IRR = 7.12%

Use of Historical returns • Measurement of historical realized returns is necessary to assess

how well the investment manager has done. • Also, historical returns are often used as an important input in

estimating future (prospective) returns. Historical returns are nothing but the returns generated in the past, found by analyzing historical data. We must however, be cautious when looking at historical data because returns in the past are not always an indicator of returns in the future as we just now saw in the study of EMH.

Expected Return

Expected Return, E(R)



Expected return is the average of possible returns in different scenarios weighted by the probability or likelihood of these scenarios taking place. The above table gives expected return from two stocks in different scenarios. In other words

E(Rs) = Σ pi ri

Where pi is the probability of state i taking place, and ri is the return of the security in state i.

From the example given above we will calculate the expected return on Oriental Shipping.

E(Roriental) = (0.30) (40%) + (0.50) (10%) + (0.20) (-20%) = 13.0%

Risk

• Risk refers to the possibility that the actual outcome of an investment will differ from its expected outcome.

• The wider the range of possible outcomes, the greater the risk. The concept of financial risk is different from the everyday usage of the word risk in that financial risk pertains to the spread of possible outcomes (above and below expectations) whereas risk in its everyday sense refers only to the possibility of losses or downside risk.

Risk, volatility or standard deviations, which is used synonymously in finance, are normally, denoted by the Greek letter sigma (σ)

Sources of risk

• Business Risk • Interest Rate Risk • Market Risk

Business Risk – Holders of corporate securities, are exposed to the risk of poor business. This could be due to heightened competition, change in technology, poor management, shifts in consumer preferences, etc.

Interest Rate Risk – Refers to the change in interest rates. An increase in the interest rate leads to a fall in the market price of fixed income securities and vice-versa. Also changes in interest rates would affect profitability of companies and thus give rise to fluctuation in equity prices as well.

Market Risk – Prices of securities tend to fluctuate often due to the psychology of the investors. This is often referred to as sentiment. Generally, changes in the sentiment or mood of the investor cause change in risk preference and may cause price volatility. This is reflected in the phrases such as ‘bull market’ or ‘bear market’ which refer to the trends in the market as a whole, which may affect individual securities prices.

Types of risk • Systematic risk • Unsystematic risk or diversifiable risk



Another way of classifying risks is in terms of Systematic and Unsystematic risk

Systematic: Risk that is attributable to economy-wide factors like sentiment, growth of GDP, level of government spending, money level, inflation rate, etc. These factors affect the system as a whole. This risk cannot be diversified away as they affect all firms to a greater of lesser extent.

Unsystematic : Risk that stems from the firm-specific factors like development of new products, a labour strike, or emergence of a new competitor. Such factors often affect the individual firm, thus can be diversified by combining it with other stocks. Hence, it is known as diversifiable risk.

Calculating risk

• The principal measures for calculating risk are standard deviation and variance are σ and σ2

• Variance measures the dispersion of returns around the mean value, µ.

22 )( µσ −=∑ ir

Example

If the return on a security for 3 periods is 10, 6 and -4 %

Mean µ is Σ (rn) / n = (10+6-4)/3 = 4%

Variance σ2 is Σ (rn - µ)2 / n = ((10-4)2 + (6-4)2 + (-4-4)2)/3 = 34.67

Standard deviation σ = 5.88

In financial theory, an asset is assumed to be completely classified by the probability distribution of its returns. That is an investor is concerned with the performance of the security in different scenarios and the likelihood of these scenarios taking place.

Standard Deviation Standard Deviation is an important concept in statistics and we use it a great deal in assessing risk. Let us

understand it fully.



Standard Deviation

We have calculated the variance of a security when the outcomes were equally likely. What if the returns are not equally likely? In such cases probabilities are assigned to various outcomes. The mean and variance of returns are then calculated using the following formula.

E(R) (µ) = Σ pi ri

Then Standard Deviation is nothing but

Variance σ2 = Σ pi (r- µ)2

= 441.

And Standard Deviation σ = 21.0%

Normal Distribution If a variable is normally distributed i.e. when the probability distribution of returns has this bell shaped property, its mean and standard deviation contain all the information about its probability distribution. Two thirds of its returns lie within one standard deviation from its average value.



Normal Distribution

Risk Aversion • If a person prefers to take the expected value of a gamble or bet rather

than the bet itself, then he or she is said to be risk averse. • For such a person risky investments must offer correspondingly higher

returns in order to be chosen. An investor who prefers the investment with a lower risk when faced with two investments with a similar expected return but different risks is termed as a risk averse investor.

Consider the following scenario, where there is an investment with two equally likely outcomes. One where there is a profit of 50% and one where there is a loss of 10%

Expected value of the investment is = (0.5)(50) + (0.5)(-10) = 20%

A risk averse investor would prefer a assured 20% return over the risky investment

A risk neutral investor would be indifferent to the two.

A risk loving investor would prefer the 50: 50 bet over the assured 20% return.

Investors are generally risk-averse. Thus means that risky investments must offer higher expected returns than less risky investments to induce people to invest in them. Thus, risk and return go hand in hand.

Risk Premium • Risk premium is defined as the additional return investors earned in

the past,for assuming additional risk.



Types of risk premiums

• Equity risk premium • Bond horizon premium • Bond default premium

Equity risk premium – difference between the return on equity stocks as a class and the risk-free rate represented commonly by the return on Treasury bills

Bond horizon premium – difference between the return on long term government bonds and the return on short term Treasury bills

Bond default premium – Difference between the return on long term corporate bonds (which have some probability of default) and the return on long term government bonds (which are free from default risk)

Modern Portfolio Theory

Typically investors hold portfolios of securities across • Sectors • Markets • Asset Classes

The risk and return characteristics of portfolios, i.e. combinations of securities are different from those of individual stocks. Usually investors can benefit from ‘diversification’, as this leads to lower risk. Modern Portfolio Theory studies the interaction of the various factors involved in portfolios and tries to quantify the expected return and risk reduction benefits of different portfolios. The MPT model is also called the Markowitz model after its pioneer.

Portfolio Return • The expected return on a portfolio is the weighted average of the

expected returns on the individual securities in the portfolio E (Rρ) = Σ wi E(Ri)

The total return expected on a portfolio is the weighted average of the expected returns on the individual securities forming the portfolio.

Where E(Rρ) = expected return on the portfolio

wi = weight of the security i in the portfolio

E(Ri) = expected return on security i

n = number of securities in the portfolio



Diversification • Strategy to reduce exposure to risk by investing in variety of assets. • Does not reduce the systematic risk. • Does not work for perfectly correlated assets

Diversification in portfolio management refers to the strategy of reducing the overall risk of the portfolio by investing in assortment of securities or different sectors. When we speak of risk reduction through diversification, we mean only the unsystematic risk ( diversifiable risk like business risk, financial risk etc.) and not the systematic risk (un-diversifiable risk like interest rate risk, inflation risk etc.). The main idea behind holding different securities in a portfolio is that the returns from all the securities do not move in a single direction, some may generate positive returns some may not. Holding a well diversified portfolio reduces the risk of fall in the portfolio value caused by investing in a particular security as the negative/low returns from one security is offset by positive/high returns in another security. . Hence, it can be said that the market in which the securities are perfectly positively correlated, diversification is not possible.

Portfolio Risk • Risk of a portfolio is measured by the variance (or standard deviation) of

its return. σρ2 ≠ Σwi2σi2

Unlike portfolio return, portfolio risk is not the weighted average of the risks of the individual securities in the portfolio (except when the returns are uncorrelated). The inequality in the above equation shows, the investors can achieve the benefit of risk reduction through diversification. To develop an equation for calculating the portfolio risk, information is required on the weightage of individual securities and Co-movements between the returns of securities included in the portfolio. Co-movements between the returns of securities are measured by covariance & coefficient of correlation (a relative measure) denoted by ρ .

Formula:

Assuming there are three securities in the portfolio.

σρ = [ w12 σ1

2 + w22σ2

2 + w32σ3

2 + 2 w1w2 ρ12σ1σ2 + 2 w1w3 ρ13σ1σ3 + 2 w2w3 ρ23σ2σ3 ]1/2

This formula can be extended further in the similar manner to include more than three securities. For ‘n’ securities, number of covariance terms required would be n(n-1)/2.

Example: A portfolio consists of 2 securities, A and B in the proportions 0.6 & 0.4. The standard deviations σ of the returns on the securities A and B are σA=10 & σB=16. The coefficient of correlation (ρ) between the securities is 0.5.

What is the standard deviation of the portfolio return?

Solution: σρ=[0.6 2 * 10 2 + 0.4 2 * 16 2 +2 * 0.6 * 0.4 * 0.5 * 10 *16] ½

=10.7 %



Diversification - exampleConsider a portfolio with 50:50 mix of A and B

A

A

B

B

15

-10

-5

0

5

10

15

20

25

Hot Cold

AB

Weather Probability A's Return B's Return 50:50 mixHot 0.50 20% -5% 7.50%

Cold 0.50 -10% 15% 2.50%

Expected ReturnA 5%B 5%

50:50 5%

A&B

A&B

-15

-10

-5

0

5

10

15

20

25

Hot Cold

Individual Securities

Combination

Let us understand the concept of diversification with the help of an example.

Firm A makes ice cream and has a return of +20% in hot weather and -10% in cold weather

Firm B makes heaters and has a +15% return in cold weather and -5% return in hot weather

Since it is equally likely that there will be hot or cold weather, the expected return is the average of the return in hot weather and cold weather states.

In the case of Firm A its an average of 20 and -10, in the case of firm B its an average of -5 and 15.

For the portfolio with a fifty-fifty mix of A and B’s shares, the expected return is an average of 7.5 and 2.5.

In all three cases the expected return is 5%

Notice that the combination of the securities A and B gives the investor a positive return in both hot and cold cases. And the variability of returns is also reduced when securities are combined rather than putting all the money in either A or B. However the maximum returns of 20 and 15 are given up when the securities are combined. Thus an investor who is willing to take the risk of making a loss of -5 or -10 would invest in the individual securities.

Expected return however is another story. This, as we recall is the, average of the security’s return across all probable states of nature, weighted by the likelihoods of these states taking place. In this case as we have seen in the previous slide, expected return is 5% for the securities A and B individually as well as the portfolio combined.



Diversification - example

But what about the Risk?

Weather Probability A's Return B's Return 50:50 mixHot 0.5 20% -5% 7.50%Cold 0.5 -10% 15% 2.50%

Standard DeviationA 15.0B 10.0A + B 2.5

Standard deviation as we recall is the average dispersion of a variable around its mean value.

Variance of security A

σ2 A = Σ p( rA - µA)2

Here,

σA2 = Variance

σA = Standard deviation

p = Probability

rA = Returns from the security

µA = Average return from the security A

In the above example

σA2 = 0.5 x ( 20 - 5)2 + 0.5 x ( -10 - 5)2

σA2= 225, therefore σ A = 15

Variance of security B

σ2 B = Σ p( rs - µB)2

Here,

σB2 = Variance

σB = Standard deviation

p = Probability

rB = Returns from the security

µB = Average return from the security B

In the above example = 0.5 x ( - 5 - 5)2 + 0.5 x ( 15 - 5)2= 10



σ A+B = Σ p( rA+B - µA+B)2

= 0.5 x ( 7.5 - 5)2 + 0.5 x ( 2.5 - 5)2

= 2.5

This is the fundamental result of portfolio diversification. By adding securities to the mix, the investor is able to lower his risk, while maintaining his level of returns and so will attempt to hold a diversified portfolio. The basic assumptions underlying this result are as follows:

The investor is risk averse. I.e. the investor would choose to take the expected return of a gamble or a bet, rather than the bet itself. I.e, in our previous example, the investor would rather take the 5% expected return than have the possibility of a upside of 20% but a possible downside of 10%.

The assets have low or negative covariance. We will study this concept in detail further on, but what this basically means is that the more independently the assets move the better. And if they move in opposite directions, it is ideal as we have seen in the previous example. This maximizes the risk reduction benefits of holding all the assets, as the independent movements of the assets tend to cancel each other out. In practice, it is rare to find assets that move in opposite directions, because all financial assets are affected by certain common economic factors such as interest rates, demand, inflation etc , therefore all assets in reality show some commonality of movement (which we shall call market risk) and so the search is to find a maximal independence of movement of asset prices given this scenario.

Diversification graphically

Return%

Risk % (Standard Deviation)

Asset X

50:50 mix of X and Y

Asset Y

The risk of a the mix would be less than an average of the 2 standard deviations

The risk of the portfolios formed by combining X & Y would be lower than a simple weighted average of the SD’s of X and Y, which is represented by the dotted line. The simple average of the two standard deviations would put the risk of the 50:50 portfolio at the midpoint of the two risks.

The curve above the dotted line indicates the risk/return characteristics of various portfolios combining assets X and Y. The risk of the portfolio is lower than the average of the risks of the two individual securities.



Covariance Covariance is the Degree to which two variables move together

relative to their individual mean values over time. For two financial assets i and j, Covij = Σ p [Ri – E(Ri)] [Rj – E(Rj)] Covij= Covariance between security i and j P = probability Ri = Return on security I Rj = Return on security j E(ri )= Mean return on security I E(rj )= Mean return on security j

Covariance can take positive or negative values. If a covariance value between two asset returns is negative, it means that the asset returns are generally moving in opposite directions, just like we have seen in the previous diversification example. This happens because, on average, while one asset is showing returns above its mean value (like the ice cream vendor in hot weather) the other asset is showing a return below its mean value. Therefore the two terms in the Covariance equation have opposite signs on average, and hence give rise to a negative covariance value. On the other hand if the assets tend to move in the same direction simultaneously, both the terms would be positive and would give rise to a positive covariance.

When both the assets move independently of each other, and there is no clear pattern of movement, the covariance value is less because again, on average there is no clear trend related to the two terms being multiplied.

Coefficient of Correlation ji

ijij

Covr

σσ=

Varies between –1.0 & + 1.0 -1.0 - perfect negative correlation 0 - no correlation +1.0 - perfect positive correlation Coefficient of correlation is simply the covariance between any two securities divided by the product of their individual risk measures (standard deviation). It is calculated in order to get a standardized measure of the covariance between any two variables. Also if there is a moderate value of covariance between two assets, it could either be the case that they do not move that much in common with each other, but have high intrinsic volatility or standard deviation, or it could be the case that they have low volatilities but move highly in step with each other. So dividing the covariance values by the standard deviations, gives us a better indication of how closely the two assets are synchronized with each other.



Covariance Calculation

The returns on securities 1 and 2 under five possible states of nature are given below:

State of Nature Probability Return on security 1 Return on security 2 1 0.10 -10% 5%2 0.30 15% 12%3 0.30 18% 19%4 0.20 22% 15%5 0.10 27% 12%

The expected return on security 1 is:

E(R1) = 0.10 (-10%)+ 0.30 (15%)+0.30 (18%)+0.20 (22%)+0.10 (27%) = 16%

The expected return on security 2 is:

E(R2) = 0.10 (5%)+ 0.30 (12%)+0.30 (19%)+0.20 (15%)+0.10 (12%) = 14%

Covariance

State of Nature

(1)

Probability (2)

Return on security 1

(3)

Deviation of the

return on security 1 from its mean

(4)

Return on security 2

(5)

Deviation of the

return on security 2 from its mean

(6)

Product of the

deviations times

probability (7)

1 0.10 -10% -26% 5% -9% 23.42 0.30 15% -1% 12% -2% 0.63 0.30 18% 2% 19% 5% 3.04 0.20 22% 6% 15% 1% 1.25 0.10 27% 11% 12% -2% -2.2

Sum =26.0

The covariance between the returns on the two securities is 26.0



Markowitz model • Generates an ‘Optimum Frontier” showing set of all efficient portfolios. • There can be no further diversification benefits as portfolio is already

‘efficient’. The concept of efficient portfolio is the cornerstone of the Markowitz Model. It generates an efficient market frontier which is a set of all efficient portfolios. By efficient portfolios, we mean the portfolios giving maximum returns for the given level of risk or having minimum risk for a given level of returns. It rests on a number of assumptions which are as follows:

• Investors consider each investment alternative as being represented by a probability distribution of expected returns over some given holding period.

• Investors maximize one period expected utility.

• Investors estimate the risk of the portfolio based on the variability of expected returns

• Investors base their decisions solely on expected returns and risk.

• For a given risk level, investors prefer higher returns to lower returns. Similarly for a given level of return investors prefer less risk to more risk.

Markowitz derived both the expected return and risk measures for a portfolio of assets and showed how to effectively diversify portfolios of assets by reducing their risks.



Efficient Frontier

Return%

Risk % (Standard Deviation)

Low Risk / Low Return

Medium Risk/Medium Return

High Risk/High Return

Optimal portfolios should lie on this curve (known as the efficient frontier).

Portfolios below the curve are not efficient because for the same risk one could achieve a greater return

A Portfolio above this curve is not possible

Efficient Frontier Any investor would choose a portfolio lying on the efficient frontier, because this would generate the highest possible return for a given amount of risk taken. The implications for the portfolio manager are that he or she should choose securities and allocate their weightage in the portfolio in such a way that for the risk level chosen by the client, the expected returns of the portfolio lie on the frontier.

The expected returns and the standard deviation of the securities in the portfolio can be calculated from historical data as well as the covariance characteristics of the portfolio. The result so obtained can be compared against the efficient frontier of the market to arrive at the optimal mix of assets in the portfolio. Another useful result of the Markowitz analysis is that it gives us the framework to judge the impact of the addition or removal of securities from the portfolio on its risk return characteristics.

Capital Market Theory • Based on Markowitz Portfolio model • Investors choose to invest in portfolios on the frontier. • Adding risk free asset to the portfolio reduces the overall risk and return

This theory is based on the Markowitz portfolio model. Some assumptions have been made in this model which are as follows:

• Investors base their decisions on the risk return profile. They choose to invest in portfolios along the efficient frontier.

• Investors borrow and lend at a risk-free rate



• All investments are completely divisible, implying fractional shares can be purchased.

• Investors decisions are not affected by taxes and transaction cost.

• Investors have same investment horizon.

• Markets are efficient and no mispricings exist in the market.

Capital Market Theory states that the overall risk of a portfolio can be reduced by adding a risk free asset to it. But this risk reduction comes with a cost. With the addition of risk free asset the overall returns from the portfolio fall. This happens because for a given level of return the risk free asset has a standard deviation/variance equal to zero. Given the lower level of returns and risk, adding risk free asset to the portfolio reduces the overall return and risk.

Let us understand this with the help of an example. Assume that an investor has a portfolio consisting of only risky assets with an expected return of 15% and a standard deviation of 10%. He wishes to reduce the level of risk in the portfolio and hence decides to transfer 20% of his portfolio in risk free asset with a return of 5%. With the addition of this risk free asset in the portfolio the expected return and risk gets affected.

As explained before, the expected return of a portfolio is calculated as the weighted average of the individual asset return. This comes out to be 13%( .80 X .15 + .20 X .05), a reduction of 2%. The standard deviation of the two-asset portfolio with a risky asset is calculated by multiplying the weight of the risky assets in the portfolio by its standard deviation. This comes out to be 8% ( .80 X .10), a reduction of 2%.

Capital Market Line (CML)Capital Market Line

E(RM)

RF

Risk

σM

L

M

x

yM= The entire market portfolio

σM= Standard deviation, risk

Rf= Risk free rate

Capital Market Line (CML) As explained before, including a risk free asset in the portfolio, an investor can easily change his risk profile. In the context of capital market line, market portfolio consists of the combination of all risky assets and the risk-free asset. Hence we can say that SML is a line used in the capital asset pricing model that plots the rates of return for efficient portfolios against the level of risk (standard deviation) for a particular portfolio. Markowitz’ efficient frontier did not take into account the risk-free asset. The CML does and, as such, the frontier is extended to the risk-free rate. The Capital Market Line looks only at the market portfolio and linear combinations of the market portfolio and the risk free rate, not at individual securities.



If a person invests only in the risk free rate then the return will be RF and the risk will be 0. If the person invests only in the Market portfolio, then he or she will be at point M on the CML, where the return is the expected market return E(Rm) and the risk will be σm. any Any point below any other point on the line will deliver lower returns but the same risk, and is therefore not ideal.

Slope of the CML is the market price of risk for efficient portfolios, or the equilibrium price of risk in the market

Relationship between risk and expected return for portfolio P (Equation for CML):

E(Rp) = RF + (E(RM) – RF) * σp/σM

The equation of the CML is given by the point-slope equation for any straight line, given its slope m and y intercept c, that is,

Y = mx + c

For the CML, the y variable is expected return of portfolio, E(Rp), the x variable is the risk of the portfolio σp and the slope m of the capital market line, as we have seen in the pervious slide is given by

Slope m = [E(RM) - RF]/ σm

Plugging in these variables into the first equation, we get

E(Rp) = RF + (E(RM) – RF) * σp/σM

Capital Asset Pricing Model Predicts the relationship between risk of an asset and its expected return. In CAPM the expected return on a stock E(Ri), is the sum of the risk free rate

of interest, rF, and the premium for bearing the stock’s market risk

)()( fmifi rrrrE −+= β The framework that we have studied till now establishes that an investor would hold the market portfolio of diversified assets, but it does not tell us as to what is the risk and required return of any given risky asset. This is achieved by the Capital Asset Pricing Model or CAPM. With the help of following equation the expected return on a risky a risky asset can be ascertained.

E( ri)= Rf + β( Rm- Rf)

The CAPM model builds on the assumption that the expected return of an asset is related to the amount of non-diversifiable or systematic risk it has i.e. the beta of the security.



Beta is a standardized measure of risk which is calculated as the covariance of the an assets return with the market portfolio divided by the variance of the market portfolio. Beta is therefore a measure of the co-movement of the asset with the market. Usually when we calculate the markets return we use the returns of an index of securities. If an asset has a beta of 1.5 it means that for every one percent rise (or fall) in the value of the index, the value of the given asset would rise ( or fall) by 1.5 per cent. If an asset has a beta of 0.5 on the other hand, a one percent rise or fall of the market return would cause a half percent change in the value of the asset itself. The beta of the market portfolio is 1, by definition because the covariance of an asset to itself is equal to its variance.

Note that under CAPM investors are compensated only for non diversifiable risk, hence the usage of β and not σ, which is the stock’s individual volatility. This holds true because CAPM assumes that stock market investors have diversified portfolios of stocks, so the individual (non-market dependent) component of the share movements cancel each other out.

Rm –Rf denotes the equity risk premium, i.e the excess return that investors expect for holding stocks. Equity risk premium is an important concept in the CAPM. If a stock market investor holds the index itself, which has a beta of 1, then the investor can get a market return of Rm. Thus, the investor receives Rm – Rf as excess return for holding equities as opposed to investing in the risk free rate. It varies from market to market, depending on the nature of market volatility.

Example: CAPM model

Determine the expected return on XYZ’s stock using the capital asset pricing model. XYZ's beta is 1.2. Assume the expected return on the market is 12% and the risk-free rate is 4%. Answer: E(R) = 4% + 1.2(12% - 4%) = 13.6%. Using the capital asset pricing model, the expected return on Newco's stock is 13.6%

CAPM Assumptions • Risk averse investors • One period model • Assets are infinitely divisible • Risk free assets exist • No market imperfections • Individuals have homogeneous expectations

Assumptions made in CAPM are essentially the same as the ones made in the Modern Portfolio Theory (MPT). Indeed CAPM uses the MPT framework seen earlier, as a means to evaluate the return on individual assets.

Risk Averse Investors

It is assumed that the investors dislike risk and have preference for returns and hence try to maximize their utility of wealth.

One Period model

Investors have a single period investment horizon and hence maximize the expected utility of their end of the period wealth.

Assets are Infinitely Divisible



All assets are perfectly divisible and priced in a perfectly competitive manner. Hence it is possible for the investors to hold securities in fractions.

Risk free assets exist

There exist risk free assets and investors can borrow and lend these assets at a risk-free rate.

No market imperfections

There are no market imperfections like taxes, regulations, or restrictions on short selling( borrowing a security and then selling it in the market).

Individuals have homogenous expectations

All investors have homogenous expectations about asset returns. This implies that all investors have identical opportunity sets and same information at the same time.

Note that some of these assumptions are not relevant in the real world. For instance, the assumption that there are no taxes or transactions costs, assets are infinitely divisible etc does not hold true in the real world; also that assets are infinitely divisible etc.

However, CAPM provides a reasonable estimate for security returns and furthermore, when there is a difference between the CAPM predicted returns and the actual returns, one could explain the discrepancy by relaxing one or more of the assumptions of the model.

Beta • Known as systematic risk of a security • Measures a stock's relative volatility • Higher the Beta of a security, higher its expected return

Beta is a measure of a stock’s relative volatility i.e. it shows how much the price of a particular stock price moves up and down compared with how much the stock market as a whole moves up and down.

It is also known as systematic or non-diversifiable risk as it represents that portion of the risk that cannot be reduced with diversification. The linear relationship between beta and the expected return is the fundamental result of the Capital Asset Pricing Model (CAPM). That is to say, investors are only compensated for non-diversifiable risk taken. Therefore the beta of any security is the variable that determines any security’s return.

Beta calculation βi = COV.(X,Y)/ Var (X) Where, X stands for returns from market Y stands for returns from stock COV(X,Y)= covariance between stock and market returns Var(X)= Variance of market returns. Now that we have understood the meaning of beta, let us now learn how it is calculated.

Beta is calculated by the formula:

βi = COV.(X,Y)/ Var (X)



Where,

COV(X,Y)= Covariance between security and market return and is measured as:

COV(X,Y)=

= Σ [(X- E(X))(Y- E(Y)) ]

N

Here,

X stands for returns from market

Y stands for returns from stock

E(X)= average return from holding stock

E(Y)= average return from market

N= number of periods

Variance (σ2)

=Σ( X – E(X))2

N

It represents the average squared deviation of a stock return X from its mean return.

Security Market Line

Security Market Line• Beta = 1.0

B as risky as market

• Beta > 1.0Security A more risky than the market,

• Beta < 1.0 Security C is less risky than the market

ABC

E(RM)

Rf

0 1.0

SML

β

Er

A security market line plots the results of the capital asset pricing model i.e. it plots the risk against the returns. The measure of risk used here is given by beta. SML helps in determining whether the asset being included in the portfolio offers a reasonable expected return compared to the risk undertaken. When plotting SML, the x axis is represented by beta and the y axis by expected return of the whole market. The line begins with the risk free rate and then moves upward and to the right. An investor with a lower risk appetite will prefer an investment at the beginning of the security market line as the risk on the investment increases as we move up along the security market line. Similarly an investor with a higher risk appetite will prefer an investment higher along the security market line. SML is represented mathematically as:



Es = rf + Bs { E(Rm) – rf} Where: rf = the risk-free rate Bs = the beta of the investment E (Rm) = the expected return of the market Es = the expected return of the investment/security

Here we can see that the slope of the SML is given by Rm-Rf i.e. the market risk premium. Recall that the risk premium of an investment is the excess return required by an investor to help ensure a required rate of return is met. As the slope of the SML changes the return required by the investor changes.

Any security above the SML represents an undervalued security and as it gives a return higher than that calculated by CAPM for a particular level of risk. Similarly a security plotting below the SML represents an overvalued security.

Estimating SML This involves estimating the three key variables of CAPM • The risk free rate • Expected Market return • Betas for individual securities

Treasury Bill rate or in India the 10 year Government security is used to estimate the risk free rate (rf)

Expected market return is unobservable so this is done by using past market returns and taking an expected value. The assumption is, that past market returns are a reasonable indicator of the returns expectation of the present market.

Betas for individual securities again are estimated using regression methods. The slope of the line of best fit, between the returns of the market versus the returns of the individual security gives us the estimated beta of the security (see previous slides). The important assumption here, of course, is that the beta values are stable, or in other words they do not change significantly over time, because we are using historical data to estimate the current (and future) beta values of asset returns. This would imply that beta is a fairly intrinsic property of an asset, because it is a risk measure that is dependent on structural properties of the firm e.g. the nature of the industry it is operating in, its leverage etc which do not change so easily over time.

Managing portfolios and evaluating performance

Portfolio Management • Security Analysis- assessing the risk return characteristics of the

available investment alternatives • Portfolio Selection- choosing the best possible portfolio from the set of

visible portfolios



Security Analysis involves choosing the best securities for the portfolio. These may not necessarily be the ones with the highest return. The ‘best’ would imply those securities that are the best fit to the risk and return objectives of the investor. The process of security analysis involves doing research, collecting historical data and analyzing investment performance over a period of time, to understand the risk return characteristics of the various investment alternatives.

Portfolio selection is the next step, i.e. putting together an investment portfolio which comprises the assets that we have selected in step one, i.e security analysis. The investment portfolio so created must meet the risk return preferences of the investor and should fulfill any other investment objectives that the investor might have, such as industry preferences, tax structure, investment horizon etc. The portfolio while meeting these constraints, should be optimal relative to these constraints. That is, it must be an ‘efficient’ portfolio in terms of risk and return, maximizing return for a given amount of risk taken, or minimizing risk in order to meet a specific return constraint.

Portfolio Rebalancing Portfolios tend to become inefficient over a period of time due to: • Drifting of asset allocation away from its target • Alteration in the risk & return characteristics of various securities • Change in objective & preference of investors

Portfolios tend to become inefficient over time due to various factors and hence require to be rebalanced. Rebalancing is the process of buying and selling portions of your portfolio in order to set the weight of each asset class in a manner that best fits ones investment objectives. Following are the factors that cause a portfolio rebalancing.

Drifting of asset allocation from target

When an investor builds a portfolio, he usually starts with setting a benchmark portfolio. It is possible that in due course of time the asset allocation drifts away from this benchmark portfolio. If this happens an adjustment to achieve the target portfolio would be required.

Altering Risk & return characteristics of securities

The asset mix originally created by an investor inevitably changes as a result of differing returns among various securities and asset classes. As a result, the percentage that you've allocated to different asset classes will change. This change may increase or decrease the risk of your portfolio and so a need for rebalancing may arise.

Change in objectives & preference of investors

Before building a portfolio an investors risk appetite and return expectations are clearly know. If somehow an investor's tolerance for risk or investment strategy changes, he or she can use rebalancing to readjust the weightings of each security or asset class in the portfolio to fulfil a newly devised asset allocation.

Portfolio rebalancing strategies • Buy and hold policy • Constant mix policy • Portfolio insurance policy



Buy & hold policy - initial portfolio is left undisturbed: irrespective of what happens to relative values, no rebalancing is done.

Example: initial portfolio has a stock-bond mix of 50:50 and after six months the stock-bond mix changes to say 70:30 because the stock component has appreciated & bond component has stagnated. Under this policy, no change is effected.

Constant mix policy - maintains the proportions of stocks and bonds in line with their target value. For example: if the desired mix of stocks & bonds is 50:50, the constant mix policy calls for rebalancing the portfolio when the relative values of the components change, so that the target proportions are maintained

Portfolio insurance policy – ensures that portfolio value does not fall below a floor level. This calls for increasing the exposure to stocks when the portfolio appreciated in value and decreasing the exposure to stocks when the portfolio depreciates in value.

Portfolio Upgrading • Re-assessing the risk-return characteristics of various securities (stocks

as well as bonds), • Selling over-priced securities, and • Buying under-priced securities

This is done on a less frequent basis than rebalancing, as it deals with issues arising from structural changes in the securities underlying the portfolio. The securities that are in the portfolio might have changed their risk reward characteristics over time or in relation to event specific factors, and newer investment alternatives might have come up that are better options than the securities present in the portfolio and thus might warrant a change in the investment portfolio. Portfolio upgrading may also entail other changes the investor may consider necessary to enhance the performance of the portfolio.

Performance Evaluation Key dimensions of portfolio performance evaluation are: • Assessing rate of return • Evaluating risks taken to get those returns • Assessing the performance with respect to the linkage with investment

objectives

The risk and return of the portfolio are both important in evaluating the performance of a portfolio. It is not just the return alone that is important in analyzing portfolio performance. If the returns are not consonant with the risk taken by the portfolio manager in getting them, then the portfolio has not done sufficiently well. For example the portfolio might achieve high rate of return but might have done so but taking an unacceptable amount of risk, or might have deviated from the asset allocation strategy that was mandated to the portfolio manager. So performance evaluation must take into account these factors as well.

It emerges from this that it is important to have some kind of benchmark to measure the performance of a fund. For example if a fund has taken 1.5 times the risk of a benchmark index, then it would be reasonable to expect the portfolio to achieve 1.5 times the return as well. If a portfolio strictly deals with IT stocks as mandated by the client, then, it would make sense to construct a benchmark of IT stocks to compare the risk and returns of the portfolio.



Rate of Return – review The rate of return from a portfolio for a given period is measured as follows: (dividend income +terminal value – initial value) Initial value

For calculating the average rate of return, over a period of several years, the following measures may be employed :

Arithmetic average of annual rates of return

IRR ( money weighted-weighted rate of return)

Geometric average of annual rates of return (time-weighted rate of return)

Risk Review Risk can be measured in various ways. Most common ones are : • Variability: intrinsic volatility • Beta: market dependent

As we have seen earlier, risk in financial terms refers to the likelihood of outcomes that are different from ones expectations. Since, a financial asset can be looked at as a probability distribution of possible outcomes, the mean of that probability distribution gives us the expected return of the financial asset. As we saw earlier, The variance of the distribution gives us the spread of possible outcomes, in other words the risk of the financial asset. Variance is denoted by the Greek letter σ2 (sigma squared) and standard deviation is denoted by the Greek letter σ.

Intrinsic volatility refers to the variance or standard deviation of the asset all by itself. AS we saw just now, the other measurement variable of risk is β (beta). This measures the correlation of the assets returns with that of the market. It a measure of the component of the risk of the asset that is dependent on the market or index movements.

Beta ( β )is an important metric, because it tells us the component of the risk or volatility of a share that cannot be reduced by diversification. The part of the risk that is unique to a share or asset, can be reduced by adding more assets to the portfolio mix as we have seen earlier, and the individual price changes tend to cancel each other out thereby reducing the risk to the investor. The market component of the risk being common to all assets in the portfolio, cannot be reduced by diversification and therefore beta is an important metric to understand the impact of a share on an already diversified portfolio.

Portfolio Measurements • Key aspect of any investment decision • Performance measures- Treynor, Sharpe and Jensen’s ratio • Combine both risk and return measures into a single value.

Portfolio performance measurements are key aspects of any investment decision process. These tools help an investor in assessing as to how effectively their money is being invested. It is not only the returns but also the risk that an investor should look at to get a clear investment picture. Stock portfolio analysis brings together the conflicting goals of maximizing portfolio return while minimizing risk through risk



management and diversification. The measurement of each goal is crucial to finding the optimal balance between risk and reward for the long-term success of portfolio.

We will study three performance measures that help in portfolio evaluation, the Treynor, Sharpe and Jensen’s ratio. These ratios combine both the risk and return measures into a single value but all three are slightly different from each other.

Sharpe ratio Estimates the excess return over the risk free rate achieved by the portfolio, per

unit risk taken. The greater a portfolio's Sharpe ratio, the better its risk-adjusted performance

has been. A

fAA

rRSharpe

σ−

=

The concept of Sharpe ratio was developed in the year 1966 by William Sharpe and since then its popularity is attributed to its simplicity. It is broken down into just three components: asset return, risk-free return and standard deviation of return. After calculating the excess return, obtained as the excess of asset returns over risk free return, it is divided by the standard deviation of the risky asset to get its Sharpe ratio This ratio tells us how much excess return an investor is earning for the extra volatility that he bears for holding a risky asset in his portfolio. The greater the ratio the better the performance. This ratio helps in comparing the performance of one portfolio to that of the other. It is a commonly used metric to determine mutual fund performance. Sharpe ratio is more appropriate for a well diversified portfolios, because it more accurately takes into account the total risk of the portfolio.

Note that Sharpe ratio uses the intrinsic volatility σ sigma to measure risk, and not market dependent

β beta).

Sharpe Ratio: Example• Suppose that 10 yr annual return on Nifty is 10% while

the average annual return on 10 yr government bonds is 6%. Nifty has a standard deviation of 18% over the 10 yr period. Determine the Sharpe ratio for the following portfolio managers.

0.2718%Manager Z

0.2116%Manager Y

0.1215%Manager X

Portfolio Standard DeviationAnnual ReturnManager

Solution



Sharpe ratio ( market ) = (.10 - .06)/ .18

= .22

Sharpe ratio ( manager X ) = (.15 - .06)/ .12

= .75

Sharpe ratio ( manager Y ) = (.16 - .06)/ .21

= .47

Sharpe ratio ( manager z ) = (.18 - .06)/ .27

= .44

Here we can see that all the fund managers have outperformed the market and the superior portfolio is not the one with the highest return but the one with the highest risk adjusted returns. Manager X though has earned the least annual returns, but the risk adjusted return earned by him is the highest.



Treynor ratio Treynor ratio is also called reward-to-variability ratio Compares portfolio risk premium to the diversifiable risk of the portfolio. A

fAA

rRTreynor

β−

=

Treynor ratio was first described by Jack L. Treynor. He suggested that there were two components of risk: the risk arising from the volatility in the market and the risk arising from volatility in the individual securities. Unlike Sharpe ratio, Treynor ratio takes into account only the systematic risk. It is assumed that the investor already has an adequately diversified portfolio and hence his unsystematic risk is not taken into consideration.

Treynor ratio is basically Sharpe ratio but with the sigma (σ) replaced by beta (β). It is measured by the following formula:

Treynor = RA – rf

βA

Treynor ratio does not quantify the value added of active portfolio management. It is a ranking criterion only. The reason for that being if one assumes that the fund pool is a large diversified entity, and that the portfolio being added has a fixed beta then the issue of actively managing the portfolio to reduce its unsystematic risk etc becomes redundant.

Treynor Ratio: Example

1.3016%Manager C

1.0415%Manager B

0.8011%Manager A

BetaAverage Annual ReturnManagers

Suppose that 10 yr annual return on Nifty is 10% while the average annual return on 10 yr government bonds is 6%. Nifty has a standard deviation of 18% over the10 yr period. Determine the Treynor ratio for the following portfolio managers

Solution:

Treynor ratio (market) = (.10 - .06)/ .18 =

Treynor ratio (manager X) = (.11 - .06)/ .80 =

Treynor ratio (manager Y) = (.15 - .06)/ 1.04 =

Treynor ratio (manager Z) = (.16 – .06)/ 1.30 =



Jensen’s AlphaαA = Actual return – CAPM predicted return

= RA − (Rf + βA(RM − Rf ))

• α is the deviation from SML

• Use it in conjunction with other metrics as a measure of performance.

Jensen’s alpha αA = Actual return – CAPM predicted return = RA − (Rf + βA(RM − Rf )) α is the deviation from SML Use it in conjunction with other metrics as a measure of performance.

The Jensen’s alpha (α) is the most popular measure of calculating portfolio performance, mainly because of the easiness in computation. It measures the excess return of the portfolio over the return that would be generated by a portfolio of the same systematic risk (Beta) using the CAPM equation.

A positive alpha (α) would indicate that a fund manager has achieved a return that is higher than a market portfolio of the same risk level. Of course, this does not imply that the strategies used by the manager would sustain the excess return over the next period or that they were not the result of random fluctuations. So, as with other metrics of performance, alpha should be taken cautiously as high alpha of a portfolio while an indication of a return higher than the average, need not imply high alpha in the future, i.e. that the particular investment strategy ‘works’ every time.



Jensen’s Alpha: Example• Assume a risk-free rate of 5% and a market return of

10%, what is the alpha for the following funds?

1.3016%Manager C

1.0415%Manager B

0.8011%Manager A

BetaAverage Annual ReturnManagers



References

Modern Portfolio Theory and Investment Analysis- Elton and Gruber

Essentials of Investments- Bodie Kane and Marcus

Questions 1. A portfolio comprises of two stocks A and B. Stock A gives a return of 8%and stock B gives a return of 7%. Stock A has a weight of 60% in the portfolio. What is the portfolio return? A) 9% B) 11% C) 10% D) 8% 2. Price movement between two Information Technology stocks would generally have a ______ co-variance. A) Zero B) Positive C) Negative 3. Prices (returns) which are not according to CAPM shall be quickly identified by the market and brought back to the __________. A) Average B) Standard deviation C) Mean D) Equilibrium 4. The ______ refers to the length of time for which an investor expects to remain invested in a particular security or portfolio, before realizing the returns. A) Investment horizon B) Credit cycle horizon C) Duration horizon D) Constraint horizon 5. A company's net income for a period is Rs. 15,00,00,000 and the average shareholder's fund during the period is Rs. 1,00,00,00,000. The Return on Average Equity is : A) 13% B) 12% C) 15% D) 16% 6. Average Return of an investor's portfolio is 10%. The risk free return for the market is 8%. The Beta of the investor's portfolio is 1.2. Calculate the Treynor Ratio. A) 4 B) 8 C) 2 D) 6



7. The share price of PQR Company on 1st April 2009 and 31st March 2010 is Rs. 20 and Rs. 24 respectively. The company paid a dividend of Rs. 5 for the year 2009-10. Calculate the return for a shareholder of PQR Company in the year 2009-10. A) 45% B) 65% C) 75% D) 55% 8. Portfolio management is the art of managing the expected _______ requirement for the corresponding ________. A) Income, expenditure B) Gain, losses C) Profit, loss tolerance D) Return, risk tolerance 9. In addition to the perceived benefits of professional fund management, the major reason of investment into funds is the ______ they afford the investor. A) Specialisation B) Diversification C) Variety D) Expansion 10. Price movement between two Steel company stocks would generally have a ______ co-variance. A) Positive B) Negative C) Zero 11.The measurement of risk by ex ante standard deviation is A) Weighted average of conditional returns with probabilities of occurrence for each state as weights B) Weighted average of deviations from the expected return C) Simple average of deviations from the expected return. D) None of the above 12. Risk affecting all securities in a market is/are A) Risk due to variability in returns due to changed investors’ expectations B) Financial risk C) Inflation risk D) Both A and C 13. The risk of the whole market measured by “beta” is A) 1 B) 0 C) -1 D) >1 14. If the market return is below risk free rate, then the stocks which possess high systematic risk give returns which_______as compared to stocks which have low systematic risks. A) Are lower B) Are higher C) Cannot be determined D) None of the above 15. Of the following, systematic risk encompasses A) Business risk B) Inflation risk



C) Interest rate risk D) Both B and C 16. While plotting a graph with risk on X-axis and expected return on y-axis, a line drawn with

coordinates (0, Rf) and ( iβ , Rm) is called as the A) Security market line B) Characteristic line C) Capital market line D) None of the above 17. Securities that are plotted above the SML line are A) Underpriced B) Those whose intrinsic value is equal to the market value C) Overpriced D) Both A and C 18. Consider the data given below Rate of inflation= 5.1% Beta=.85 Real rate of return=4.2% Market return=12.6% The risk premium for the above security will be A) 2.5% B) 2.65% C) 2.805% D) 2.95% 19. Covariance between a stock and a market index and the variance of the market index were found to be 33.56 and 19.15 respectively. The beta of the stock is A) 1.55 B) 1.75 C) 1.85 D) 1.95 20.Ratio of the covariance of a stock with the market and its beta is A) Equal to the standard deviation of the stock returns B) Equal to the variance of the market returns C) Equal to the correlation coefficient D) Both B and C 21. A stock will not have a finite beta if A) Its correlation with the market is neagative B) The stock is highly volatile C) The market is stagnant D) Both B and C 22. The beta of a stock is 1.12 and its covariance with the market is 220. the standard deviation of market return is_____ A) 16% B) 14% C) 12% D 11.3% 23. The beta for a portfolio is equal to



A) The arithmetic average of the individual security betas B) The weighted average of the individual security betas C) Individual security betas adjusted for correlation D) Individual security betas adjusted for covariance between the stocks returns 24. The capital market line depicts the risk-return relationship for A) Aggressive securities B) Zero beta portfolios C) Efficient portfolios D) Securities which are neither less nor more volatile than the market 25.Which of the following is a source of systematic risk for a company? A) Falling margins due to raising operational costs. B) Labor problem in the factory C) Sectoral slowdown due to cheaper imports D) Reduction in interest rates due to cut in CRR by RBI 26. Which of the following statements is true? A) Slope of SML is known as beta B) Slope of CML is known as beta C) CML includes inefficient portfolios D) CML is a relationship between total risk and required return. 27. Study the following data Rf=10%, Rm=15%, Beta of A=.95, beta of B=1.05 The required rate of return on two stocks A and B are A) 11%% and 15% B) 14.75% and 18.25% C) 18.25% and 15.25% D) 14.75% and 15.25% 28. The current price of the stock is 110. the stock does not pay any dividends. End of year price Probability Rs. 100 .1 Rs. 105 .2 Rs. 110 .4 Rs. 120 .2 Rs. 125 .1 The expected return is A) 1.25 B) 1.36 C) 1.75 D) 2.31 28. Which of the following is/are true? A) Beta measures the diversifiable risk B) Beta for the market is equal to 1 C) Higher the beta, lower the return D) A stock with a beta of .8 is better than the a stock with a beta of 1.2 for aggressive investment 29.The shares of B Ltd. were bought for Rs. 50 per share on January 1,2000. A dividend of Rs. 5 per share was received on June 30,2000 . The share was sold ex-dividend on the same day for Rs. %% per share. The total holding period return is_______ A) 10% B) 20% C) 30% D) 44%



30.You wish to calculate the correlation coefficient between the returns of stock A and stock B. Which set of information would you require? A) Expected return of a stock A, expected return of stock B, beta of either stock A or stock B B) Beta of stock A, Variance of stock B C) Beta of stock A, Beta of stock B D) Covariance between returns on stock A and stock B, Standard deviation of returns on stock A, standard deviation of returns on stock B 31. “Riskiness” of a security in the context of security analysis essentially means A) Variability of the security’s return B) Variability of returns above a benchmark mentioned by clients C) Market risk D) Unsystematic risk 32. Consider the following information Stock Variance Weight in the portfolio A 441% 441 .7 B 11% 256 .3

Return

If the variance of the portfolio is 122, the coefficient of correlation between the stocks is A) 1.86 B) -.83 C) -1.2 D) 1.2 33. Consider the following information Particulars Security A Security B Expected return 15 18 Standard deviation of returns 18 22 Beta .90 1.4 Variance of the returns on the market is 225. the correlation coefficient between the returns on securities A and B is .75 The systematic risk of a portfolio consisting of these securities in equal proportions is A) 24.63 B) 125.78 C) 297.56 D) 606.73 34. A portfolio has 40% of its funds invested in security A and the balance in security B. the standard deviation of security A’s return is 10% and its correlation coefficient with security B’s return is .5. If the variance of the portfolio is 133 %, the standard deviation of security B’s return is A) 10% B) 18% C) 15% D) 12% 35. Portfolios tend to become inefficient over a period of time due to A) Drifting of asset allocation away from its target B) Alteration in the risk & return characteristics of various securities C) Change in objective & preference of investors D) All the above 36. Key dimensions of portfolio performance evaluation are A) Assessing rate of return



B) Evaluating risks taken to get those returns C) Assessing the performance with respect to the linkage with investment objectives D) All the above

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