Market TheoriesMd. Ahsan Ullah Raju

Sr. Market AnalystAlliance Capital Asset Mgt. Ltd.

The Efficient Markets Hypothesis (EMH)

The Random Walk Hypothesis (RWH)

Rubber Band Effect

Equilibrium Theory

Reflexivity Theory

Boom – Bust Sequence

In finance, the efficient-market hypothesis (EMH) asserts that financial markets are "informationally efficient". That is, one cannot consistently achieve returns in excess of average market returns on a risk-adjusted basis, given the information publicly available at the time the investment is made.

There are three major versions of the hypothesis: "weak", "semi-strong", and "strong".

Efficient-market hypothesis:

In weak-form efficiency, Weak EMH claims that prices on traded assets (e.g., stocks, bonds, or property) already reflect all past publicly available information.

Future prices cannot be predicted by analyzing prices from the past. Excess returns cannot be earned in the long run by using investment strategies based on historical share prices or other historical data.

Technical analysis techniques will not be able to consistently produce excess returns, though some forms of fundamental analysis may still provide excess returns. Share prices exhibit no serial dependencies, meaning that there are no "patterns" to asset prices. This implies that future price movements are determined entirely by information not contained in the price series. Hence, prices must follow a random walk. This 'soft' EMH does not require that prices remain at or near equilibrium, but only that market participants not be able to systematically profit from market 'inefficiencies'. However, while EMH predicts that all price movement (in the absence of change in fundamental information) is random (i.e., non-trending), many studies have shown a marked tendency for the stock markets to trend over time periods of weeks or longer and that, moreover, there is a positive correlation between degree of trending and length of time period studied. Various explanations for such large and apparently non-random price movements have been promulgated.

In semi-strong-form efficiency, it is implied that share prices adjust to publicly available new information very rapidly and in an unbiased fashion, such that no excess returns can be earned by trading on that information. Semi-strong-form efficiency implies that neither fundamental analysis nor technical analysis techniques will be able to reliably produce excess returns. To test for semi-strong-form efficiency, the adjustments to previously unknown news must be of a reasonable size and must be instantaneous. To test for this, consistent upward or downward adjustments after the initial change must be looked for. If there are any such adjustments it would suggest that investors had interpreted the information in a biased fashion and hence in an inefficient manner.

In strong-form efficiency, share prices reflect all information, public and private, and no one can earn excess returns. If there are legal barriers to private information becoming public, as with insider trading laws, strong-form efficiency is impossible, except in the case where the laws are universally ignored. To test for strong-form efficiency, a market needs to exist where investors cannot consistently earn excess returns over a long period of time. Even if some money managers are consistently observed to beat the market, no refutation even of strong-form efficiency follows: with hundreds of thousands of fund managers worldwide, even a normal distribution of returns (as efficiency predicts) should be expected to produce a few dozen "star" performers.

No underlying patterns exist in stock prices.A random walk occurs when future steps cannot be predicted by observing past steps.Flipping a coin produces a random walk.

Random Walk Theory:

Rubber band Effect:It works on humanIt works on PriceIt works on balls.

General equilibrium theory:

General equilibrium theory is a branch of theoretical economics. It seeks to explain the behavior of supply, demand, and prices in a whole economy with several or many interacting markets, by seeking to prove that a set of prices exists that will result in an overall equilibrium, hence general equilibrium, in contrast to partial equilibrium, which only analyzes single markets. As with all models, this is an abstraction from a real economy; it is proposed as being a useful model, both by considering equilibrium prices as long-term prices and by considering actual prices as deviations from equilibrium.

Nash equilibrium:

In game theory, Nash equilibrium (named after John Forbes Nash, who proposed it) is a solution concept of a game involving two or more players, in which each player is assumed to know the equilibrium strategies of the other players, and no player has anything to gain by changing only his own strategy unilaterally.

Reflexivity Theory:

Reflexivity refers to circular relationships between cause and effect. A reflexive relationship is bidirectional with both the cause and the effect affecting one another in a situation that does not render both functions causes and effects. In sociology, reflexivity therefore comes to mean an act of self-reference where examination or action "bends back on", refers to, and affects the entity instigating the action or examination.

To this extent it commonly refers to the capacity of an agent to recognize forces of socialization and alter their place in the social structure. A low level of reflexivity would result in an individual shaped largely by their environment (or 'society'). A high level of social reflexivity would be defined by an individual shaping their own norms, tastes, politics, desires, and so on. This is similar to the notion of autonomy.

In Economics reflexivity refers to the self-reinforcing effect of market sentiment, whereby rising prices attract buyers whose actions drive prices higher still until the process becomes unsustainable and the same process operates in reverse leading to a catastrophic collapse in prices.

The Boom-Bust Model:

The drama unfolds in eight stages. It starts with a prevailing bias and a prevailing trend.

In the initial stage:

(1) the trend is not yet recognized.

Then comes the period of acceleration (2), when the trend is recognized and reinforced by the prevailing bias. That is when the process approaches far-from-equilibrium territory.

A period of testing(3) may intervene when prices suffer a setback. If the bias and trend survive the testing, both emerge stronger than ever, and far-from-equilibrium conditions, in which the normal rules no longer apply, become firmly established

(4). Eventually there comes a moment of truth

(5), when reality can no longer sustain the exaggerated expectations, followed by a twilight period

(6), when people continue to play the game although they no longer believe in it.

Eventually a crossover point (7) is reached, when the trend turns down and the bias is reversed,

which leads to a catastrophic downward acceleration (8), commonly known as the crash.

All boom-bust processes contain an element of misunderstanding or misconception.

Market participants act on the basis of imperfect understanding at all times. Consequently market prices usually express a prevailing bias rather than the correct valuation. In the majority of cases, the valuations are proven wrong by subsequent evidence, and the bias is corrected only to be replaced by a different bias.

Social situation can be influenced by making statements about them.

Notes:

The Survey

In fact, a study by Robert Strong (1988) showed that over 60 percent of PhDs do not believe that technical analysis can be used as an effective tool to enhance investment performance. Because of the view of these academics, little emphasis has been placed on technical analysis in traditional finance curriculums in recent years, as shown in the Flanegin and

Rudd survey results.

Benoit Mandelbrot (1963) first noticed this phenomenon of fat tails, called a "leptokurtic distribution," in stock market returns in the early 1960s. Fat tails occur when one or more events cause stock prices to deviate extraordinarily from the mean.

Fat Tails

One of these events is the large decline in stock prices that occurred on October 19,1987. On this day, known as "Black Monday," the U.S. stock market crashed, sending the Dow Jones Industrial Averages down 22.6%.

Why Stock Markets Crash: Critical Events in Complex Financial Systems, Didier Sornette claims that, statistically, a crash as large as was seen on Black Monday would be expected to occur only once in 520 million years. Thus, the huge negative return seen in October of 1987 is clearly an outlier.

Black Monday represented an abnormally large one-day negative return in the stock market. Although this alone was a significant deviation from the mean stock return, even more significant is the fact that October 19 was preceded by three days of market losses. Market losses were 2%, 3%, and 6% on the three previous trading days. In other words, there were four consecutive days of trading losses, resulting in a 30% decline in the market.

For example, the probability of a one-day decline of 10% in the stock market is approximately 1 in 1000. In other words, a 10% drop would occur once every four years statistically. Although a drop of this magnitude would be a large deviation from the average daily stock return, it would fall within the normal distribution. If stock returns are independent, then the probability of two consecutive daily drops of 10% would be the product of the probability of the two independent events occurring, or 1/1000 multiplied by 1/1000. Likewise, the probability of three consecutive 10% drops, or a 30% drawdown, is 1/1000 X 1/1000 X 1/1000, or 1 in 1,000,000,000. This means, statistically, a 30% three-day drawdown could be expected to occur only once every four million years!

Drawdowns

As shown in Table 4.2, Sornette's research indicates that large drawdowns in the DJIA have occurred more often than can be statistically expected. When considering the three largest twentieth century stock market declines (1914, 1929, and 1987), Sornette calculates that statistically about fifty centuries should separate crashes of these magnitudes. He concludes that three declines of this magnitude occurring within three-quarters of a century of each other are an indication that the series of returns was not completely random.

There has to be both some form of credit or leverage and some kind of misconception or misinterpretation involved for a boom-bust process to develop.

Indicators Bollinger BandsMACDParabolic SARRSI (Relative Strength Index)ADX (Average Directional Index)

Bollinger BandBollinger bands are used to measure a market's volatility.

Basically, this little tool tells us whether the market is quiet or whether the market is LOUD! When the market is quiet, the bands contract and when the market is LOUD, the bands expand.

Notice on the chart below that when price is quiet, the bands are close together. When price moves up, the bands spread apart.

The Bollinger Bouncewhere the price might go next?

Bollinger SqueezeThe Bollinger squeeze is pretty self-explanatory. When the bands squeeze together, it usually means that a breakout is getting ready to happen.

MACD (Moving Average CD)

Parabolic SAR

Stochastic

When the Stochastic lines are above 80 (the red dotted line in the chart above), then it means the market is overbought. When the Stochastic lines are below 20 (the blue dotted line), then it means that the market is oversold.

Relative Strength IndexRelative Strength Index, or RSI, is similar to the stochastic in that it identifies overbought and oversold conditions in the market. It is also scaled from 0 to 100. Typically, readings below 30 indicate oversold, while readings over 70 indicate overbought.

Determining the Trend using RSI:

RSI is a very popular tool because it can also be used to confirm trend formations. If you think a trend is forming, take a quick look at the RSI and look at whether it is above or below 50.

If you are looking at a possible uptrend, then make sure the RSI is above 50. If you are looking at a possible downtrend, then make sure the RSI is below 50.

Average Directional IndexThe Average Directional Index, or ADX for short, is another example of an oscillator. It fluctuates from 0 to 100, with readings below 20 indicating a weak trend and readings above 50 signaling a strong trend. Unlike the stochastic, ADX doesn't determine whether the trend is bullish or bearish. Rather, it merely measures the strength of the current trend. Because of that, ADX is typically used to identify whether the market is ranging or starting a new trend.

….Divergence Trading

Divergence TradingRegular Divergence

Hidden Divergence

How To Trade Divergences

Momentum TricksWait for a crossover

Moving out of overbought / oversold

Draw trend lines on the momentum indicators themselves

….9 Rules for Trading Divergences

1. Make sure your glasses are clean

In order for divergence to exist, price must have either formed one of the following:

• Higher high than the previous high• Lower low than the previous low• Double top• Double bottom

Don't even bother looking at an indicator unless ONE of these four price scenarios have occurred.

2. Draw lines on successive tops and bottoms3. Do Tha Right Thang - Connect TOPS and BOTTOMS only4. Eyes on the Price

5. Be Fly like Pip Diddy

6. Keep in Line

7. Ridin' the slopes

8. If the ship has sailed, catch the next one

9. Take a step back

Divergence signals tend to be more accurate on the longer time frames. You get less false signals. This means fewer trades but if you structure your trade well, then your profit potential can be huge. Divergences on shorter time frames will occur more frequently but are less reliable.

We advise only look for divergences on 1-hour charts or longer. Other traders use 15-minute charts or even faster. On those time frames, there's just too much noise for our taste so we just stay away.

Putting it all together

Thank You