IFRM-Term Report Final
-
Upload
asma-ahmed -
Category
Documents
-
view
215 -
download
0
Transcript of IFRM-Term Report Final
-
8/9/2019 IFRM-Term Report Final
1/125
Top down investment risk research on banking
sector through
Market risk metrics analysis
Prepared for;
Syed Adeel Hussain
Institute of Business Management
Prepared by;
Naureen Ahmed, Asma Ahmed
December 14, 2014
-
8/9/2019 IFRM-Term Report Final
2/125
Top down investment risk research of the banking sector
2
Contents
CHAPTER 1: INTRODUCTION ................................................................................................................. 6
CHAPTER 2: PROBLEM STATEMENT................................................................................................ 9
CHAPTER 3: LITERATURE REVIEW ............................................................................................ 11
CHAPTER 4: METHODOLOGY .................................................................................................. 24
CHAPTER 5: ANALYSIS AND DISCUSSION..................................................................... 30
CHAPTER 5: CONCLUSION............................................................................................. 41
TABLE OF FIGURES
Figure 1: Skewness and kurtosis comparison ............................................................................................. 34
Figure 2: Risk measures compared ............................................................................................................. 37
-
8/9/2019 IFRM-Term Report Final
3/125
Top down investment risk research of the banking sector
3
Letter of Acknowledgement
First, we would like to present our gratitude to Almighty Allah, the merciful, Who provided us
with the strength and intellect for the completion of this research project. Then a sincere thanks
to our instructorMr. Adeel Hussain. Through exhibiting faith and confidence in us he provided
us with the opportunity to conduct the following research up till successful completion and with
the best of results.
-
8/9/2019 IFRM-Term Report Final
4/125
-
8/9/2019 IFRM-Term Report Final
5/125
Top down investment risk research of the banking sector
5
Executive Summary
When it comes to suitable investment avenues nearly every firm has been facing challenges
from top horizon risks impacting firms, arising from macroeconomic factors, geopolitical
changes to regulations at a local or regional level, or tax legislation changes. Therefore sound
risk management practices and procedure are essential to be devised. The purpose for the
conduct of this research study lies solely in the adoption of a sound risk identification strategy
for risk identification and present a through risk analysis using appropriate quantitative
technique.
The sector under consideration has been the banking sector of Pakistan covering about
thirteen banks listed at the Karachi Stock Exchange, the quantitative technique adopted is the
market risk metric analysis, incorporating significant statistical measures as indicators of risks
inherent in the economy. The fundamental focus has been on the market risk and investment risk
inherent in the bank equity trading and the strategic approach adopted has been the top-down risk
research. The significance of the study lies in providing a risk identification methodology that
will enable the readers to get a better understanding of the risks thereby enabling them to design
appropriate mitigation, measurement and control strategies as well as to identify the key factors
that elevate the particular risk type.
-
8/9/2019 IFRM-Term Report Final
6/125
Top down investment risk research of the banking sector
6
CHAPTER 1: INTRODUCTION
Successful fund management business not only involves investments in asset classes that ensure
sound returns and profitability but is equally about the need for sound risk identification and
management practices. When it comes to suitable investment avenues nearly every firm has been
facing challenges from top horizon risks impacting firms, arising from macroeconomic factors,
geopolitical changes to regulations at a local or regional level, or tax legislation changes.
Investment risk arises from the promise of performance, which remains undelivered. A key
element of the overall investment risk framework is the clear identification, documentation and
communication of the clients risk appetite, for that purpose a through risk analysis is essential.
Firms are becoming independent by ensuring that investment risk is ring-fenced from bias and
conviction on the part of fund managers or founders. There is still scope for performance
improvement when applying risk budgeting, single portfolio views, risk metrics, performance
attribution, liquidity management and treatment of model risks. Since sound investment risk
management requires a clear identification and measurement of inherent risks of the asset class,
therefore the sole purpose for the conduct of this research is to gain an understanding regarding
the risk identification methodology, for which top down investment risk research approach has
been adopted incorporating the market risk metric for equity analysis as a quantitative support.
Among the many stock classes available, we concentrate on the banking sector since the banking
industry of the country is quiet growing not only locally rather international operations have
continued to grow all over the world and particularly in emerging countries. The first grew
mainly through cross-border operations and more recently also through the establishment of
branches and subsidiaries abroad. This has changed the business potential as well as the structure
-
8/9/2019 IFRM-Term Report Final
7/125
Top down investment risk research of the banking sector
7
of risks not only faced and mitigated by the banking enterprise itself but also by the entities who
invest their capital not only for their regulatory requirements but also to earn suitable returns.
Banking crises have never been a strange episode in market economies. As long as banks are
major players in modern economies, a banking crisis would keep on emerging with its
accompanied multiple adverse consequences including out-put losses, monetary instability, and
other nonmonetary effects associated with information loss. Therefore a sound risk identification
and mitigation mechanism is essential for every banking institution. The causality between
macroeconomic conditions and financial instability goes together because declines in the value
of banks' portfolios can weaken the economy. In a world of forward looking economic agents
where everybody incorporates the eventual negative effects of a financial crash into his
economic decisions, not only financial crises, but also their likelihood of occurrence effects the
economy.
The incorporation of Market risk metrics application provides the means to establish periodic
measurements of basic risk factors, including key performance indicators (KPIs) and key risk
indicators (KRIs).For purposes of the Risk Management solution, the metrics application
facilitates the researcher in finding out key performance and risk indicators, identify their source,
and tie them to sector under consideration. The Metrics application provides the ability to
monitor quantitative metrics over time with respect to their impact on the organization as soon as
the risks are cataloged.
-
8/9/2019 IFRM-Term Report Final
8/125
Top down investment risk research of the banking sector
8
Research question
The fundamental question to be answered under the conduct of this research is the verification of
risks inherent in the equity investment in the banking sector through the use of quantitative
techniques (market risk metric) that would provide a perspective on the various risks through its
significant indictors.
Signi fi cance of the study
The employment of top down approach for the purpose of equity investment risk analysis would
serve as tool for the understanding of significant risks inherent in the assets class as well as the
industry under consideration (banking industry).Through the use of top-down approach not only
the interaction among various risk types would be prevalent but it will also provide impetus
regarding the losses resulting through such interactions. The risk types can include broad
macroeconomic risks, industry risks, sector risk and the related asset class risk. Risk
identification will enable the readers to get a better understanding of the risks thereby enabling
them to design appropriate mitigation, measurement and control strategies as well as to identify
the key factors that elevate the particular risk type.
L imi tations of the study
Limitations exist in the use of the underlying quantitative technique, the historical data may not
always be the predictor of the future and the history cannot always repeat itself, the indicators
-
8/9/2019 IFRM-Term Report Final
9/125
-
8/9/2019 IFRM-Term Report Final
10/125
Top down investment risk research of the banking sector
10
CHAPTER 2: PROBLEM STATEMENT
Background of the problem
The stock market is fraught with volatility, uncertainty and inherent risks that had been a
significant threat for the equity investors across the global markets, therefore risk identification
and measurement is the fundamental requirement for the equity investors pertaining to the
prevailing economic circumstances. The banking sector in particular is fraught with risks that are
quiet wide in their perspective and pertain to a variety of disciplines. The disciplines might
belong to the wider macro economic variables as well as the micro variables related to the
general industry considered.Banks are risky because their portfolio returns have their affects on
the strength of the economy which represents a non-diversifiable aggregate risk. Macroeconomic
risks affect business cycles because all agents suffer the effects of banking failures and
incorporate the endogenously determined probability of a crisis into their economic decisions.
Unforeseen interest-rate rise tends to breed banking sector problems. Furthermore, the country-
specific interest-rate spread is counter-cyclical because financial crises are less likely during
booms. All this leads to the conclusion of adopting a risk research strategy that help identify the
risks and also the interactions among various risks measures to gain a numerical perspective as
well.
Problem statement
The problem of this study lies in finding out the risks inherent in the equity investment of the
banking industry through the use of the top down risk research approach that will help identify
-
8/9/2019 IFRM-Term Report Final
11/125
Top down investment risk research of the banking sector
11
market risks covering all the relevant areas that include broader economy, industry, particular
institution and the asset class under consideration. The model adopted would be the market risk
metric analysis.
-
8/9/2019 IFRM-Term Report Final
12/125
Top down investment risk research of the banking sector
12
CHAPTER 3: LITERATURE REVIEW
Since the Investors depend heavily in equity investments to maximize their returns, the
perception of risk in equity investing have become increasingly important (DAngelo,
n.d.).Violent market moves have surprised many institutional investors and brought risk
management to the forefront (Caboodle, 2009). Some investors argue that current risk
management practices failed when they were needed most, and with multi-sigma events
extending across formerly uncorrelated asset classes.Institutional investors need to manage the
total risk of their investments, which means protecting themselves not only from asset liability
deficits, declines in broad asset classes and, non-fulfillment of investor obligations but also from
the risk of managers underperforming their benchmarks .To assess future risks, it is essential to
measure and monitor risk both at the aggregate level and at the factor level.
A risk management framework should be aligned with the investment objectives as well as the
investment horizon (Caboodle, 2009). The framework must tackle multiple aspects of risk along
with measuring, monitoring and managing exposures to economic and fundamental drivers of
risk and return across asset classes to avoid over exposures to any one risk factor. Finally, it
should also manage risk for normal times but must also recognize and aim to be prepared for
extreme events. Financial institution primarily banks are exposed to various kinds of risk due to
the nature of their business (Grundke, 2007). The responsibility of the risk management division
is to identify all these risks and find out the dependence between various risk factors. Two
theoretically sound approaches used in this regard are the top-downand bottom upapproaches.
Using a "top down" approach requires the identification of key business risks that can be
compliance, business, strategic or major operational risks (Managemen, 2011). These risks can
http://void%280%29/http://void%280%29/http://void%280%29/http://void%280%29/http://void%280%29/http://void%280%29/ -
8/9/2019 IFRM-Term Report Final
13/125
Top down investment risk research of the banking sector
13
be driven by several factors that might include major incidents or losses, regulatory compliance
requirements or systemic issues in operations of the business.
As these risks are cataloged then the risks can be monitored over time through periodic review,
loss tracking, implementing metric or other indicators. In the end, by going through this process,
the organization has implemented a consistent, continuous practice to address major risks in the
organization.
Every individual wants to invest for returns and productivity of ones funds (Dr. Taqadus Bashir,
2013). Any potential investor invests in shares of a company for return in form of dividend and
price appreciation in the market price of his holding. There were lot of options for investment
like equity, mutual bonds, company funds, gold/silver, bank deposits, real estate and life
insurance etc. But people prefer them according to their choices which were most appropriate
and suitable for them. Asset class evaluation is based on deciding what risks explain required
rates of return (Eric Girard, 2005). Portfolio theory suggests that only systematic risks can be
associated with a premium in financial markets however it is not evident now since it is not
evident on how to measure risk. While investing, many different approaches have been proposed
for pricing local financial or real assets. The degree of integration with the world financial
ECONOMY RISK
Macroeconomic analysis
SECTOR RISK
Microeconomic analysis
INDUSTRY RISK
co-relation with theeconomy
ASSETCLASS/ISSUER RISK
Business model/productrisk
-
8/9/2019 IFRM-Term Report Final
14/125
Top down investment risk research of the banking sector
14
market will determine what risks explain risk premiums in capital markets and a country asset
pricing model should use a multifactor framework with local and common risk attributes.
Risk Management is a discipline that covers many avenues and techniques (Managemen, 2011).
Every organization faces different risks and perhaps had differing business goals therefore their
procedures for risk management do vary. Risk management is not an exact science, thus for
implementing a comprehensive risk management program had always been a remarkable
challenge but once implemented a sustainable, consistent and thorough risk management
program can be a tremendous advantage for any organization.The cycle of cost growth, fee
competition, squeezed margins and the need for greater
Scale and acceleration trends had challenged asset managers to innovate to safeguard sustainable
profits (Anon., 2013).As change is constant, the need for proportionate risk management in the
form of appropriate governance, risk appetite, embedded procedures and effective use of risk
management frameworks/key risk indicators has became greater in the current business climate.
Given the tsunami of new directives and regulatory measures at global, regional and local levels,
the gap between risk management and regulatory management is narrowing. The recognition of
the investment risk as being ring-fenced from bias and conviction had became a badge of honor
however general views regarding the management of certain strands of investment risk, e.g., risk
budgeting, single portfolio views, advanced risk metrics, sensitivity analyses and management of
model risks still varies among potent risk researchers.
Stock market risk is the tendency of stock prices to decline due to the change in value of the
market risk factors (Sinha, 2013). The stock value is directly related to the market value of those
-
8/9/2019 IFRM-Term Report Final
15/125
Top down investment risk research of the banking sector
15
investments held by the stock market. Though banking and financial services sector funds have
accelerated on generating superior risk adjusted returns, they become victim to the risk of
portfolio concentration as a single stock accounts for equity portfolio in some gear. The market
value of those investments fluctuates depending on the financial performance of the issuers and
general economic, political, tax and market conditions.
Standard market risk factors include stock prices, interest rates, foreign exchange rates, and
commodity prices. Banks play a vital role in flourishing the economic activity and boasting
growth in the wide economy therefore their tendency to get affected from the financial crisis is
quiet evident. Banking and financial services sector funds have proved to be more volatile than
the pure diversified equity funds which make some of them a high risk proposition. Since the
banking industry is controlled by the central banks of the country their chances of being
adversely affected by inflation, interest rate, and money supply are more evident and so does the
a high instability in their share prices that reduces the real investors interest.
In complex systems, no single risk identification method can realistically identify all risks (The
board of the international organization of securities commission, 2014). Instead, risk
identification frameworks consist of various risk identification methods which can then be
combined into an overall approach for the identification and monitoring of risk. The use of top
down risk research approach for the identification of risks requires to be identified at the macro
level that includes the broader economic risks then moving down to the individual asset class
level risks that incorporate the industry as well as the company represented by the asset class.
Direct and individual risk management approach aims to identify all the risks to which the
company is exposed to, determination of the level of each risk, the risk appetite of the investor
-
8/9/2019 IFRM-Term Report Final
16/125
Top down investment risk research of the banking sector
16
and the surety of risk monitoring and management (Methods Commission, n.d.). Global and
indirect risk management however aims to develop a security policy based on evaluating risks, to
identify certain elements that can lead to risks, classify these elements by order of importance
and determine a policy and security goals.
The asset class volatility forecasting beyond horizons of ten or fifteen trading days is important
for risk management (Peter F. Christoffersen, 1998).No single relevant risk horizon for risk
management, instead risk horizon will generally vary by asset class, industry, position in the firm
and motivation along with the rest of other things. Thought must be given to the relevant horizon
on an application-by-application basis. The fact is quiet well known that short-horizon asset
return volatility fluctuates and can be highly forecasted , a phenomenon that forms the base of
the modern risk management paradigms, however not much information exists about the
forecasting capability of long-horizon volatility, and the speed and pattern with which it decays
as the horizon lengthens. To assess long-horizon volatility forecast capability, it is necessary to
have a measure of long horizon volatility.
TheMarket Risk Metrics approach incorporates significant statistical measures to quantify the
risks that investment managers may need for evaluating the market risk inherent in their
portfolios or when making decisions on asset selection, portfolio allocation and portfolio
optimization. The correlation coefficient for instance is an important tool for quantitatively
assessing the linear relationship between two instruments. Other significant measures include
mean, standard deviation and coefficient of determination. Standard deviation is a common
statistical measure of portfolio volatility that measures how much a portfolios total return varies
from its mean or average. The more a portfolios returns fluctuate from month to month, the
http://void%280%29/http://void%280%29/http://void%280%29/http://void%280%29/http://void%280%29/http://void%280%29/http://void%280%29/http://void%280%29/ -
8/9/2019 IFRM-Term Report Final
17/125
Top down investment risk research of the banking sector
17
higher its standard deviation and the greater its volatility. Correlationmeasures how a portfolios
asset classes move in relation to each other in response to market events (MFS, n.d.).It ranges
from +1 to -1. The closer two assets are to a +1 correlation, the more likely they are to move in
the same direction Anegative correlation indicates two assets moving in opposite directions. R2
(R-Squared) calculated by squaring the correlation coefficient is that part of a portfolios
volatility that can be explained by movements in its benchmark or market. An R2of 100% shows
that all movements of a portfolio are completely explained by movements in the benchmark or
market. A low R2 indicates that little of the portfolios movement can be explained by
benchmark or market movements.Alpha which is the intercept of the Security market line
measures a portfolios risk-adjusted performance against that of its benchmark a positivealpha
indicates relative outperformance and vice versa. It measures the firm specific/industry risk.Beta
measures the volatility of security or portfolio to market movements and covers the broader
economic (systematic risk) .A beta less than 1.0 indicates likely lower volatility than the market.
Systemic risk is the risk of disruption to financial services that is caused by an impairment of all
or parts of the financial system and has the potential to have serious negative consequences for
the real economy (The board of the international organization of securities commission, 2014).
Factors that are essential to identify systematic risk include size of the market, degree of
interconnectedness or interdependence among market participants, lack of
substitutes/concentration due to one or a few market participants providing a product or activity,
leverage, Typology and structure of assets and liabilitiesheld in the balance sheet or off the
balance sheet: some low quality assets (downgraded or non-investment grade assets, unprofitable
loans) or highly concentrated or immediately redeemable liabilities may endanger the
profitability of the financial institution concerned , liquidity risk arising from not being able to
http://void%280%29/http://void%280%29/http://void%280%29/http://void%280%29/http://void%280%29/http://void%280%29/http://void%280%29/http://void%280%29/ -
8/9/2019 IFRM-Term Report Final
18/125
Top down investment risk research of the banking sector
18
sell a security at its fair value, as a result either of a liquidity discount or the complete absence of
a market or buyers or of being unable to obtain funding. In addition, market liquidity risk and
funding liquidity risk can exacerbate each other, transparency about interconnections and in
information about markets or products to assess the market price, potential return, and risk
exposure and behavior of the participants can result in mispricing of assets and an accumulation
of risk in the financial system. Incorporating the "top down" approach, the organization
identifies key business risks and catalogs those risks into a central repository (Managemen,
2011). These risks are the firm specific non systematic risks can be related to compliance,
business, strategic or major operational risks and represent the executive level risks that are "top
of mind" for the organization. The risks could be driven by several factors such as major
incidents or losses, regulatory compliance requirements or systemic issues in operations. Once
these risks are cataloged they are monitored over time. This process can be then institutionalized
to keep major risks on the radar screen. Over time, these may become inactive through
mitigation by various controls and does not warrant monitoring, or the risk becomes outdated
and not pertinent to the organization. By going through this process, the organization has
implemented a consistent, repeatable practice to address major risks in the organization. The
concept of systematic, non diversifiable risk or beta was first discussed under the frame work of
capital asset pricing model (CAPM), presented by Sharpe (Nawazish Mirza, n.d.). The CAPM
framework is very simple under ideal conditions and stipulates that systematic risk attributes its
sensitivity to macroeconomic factors is reflected in the slope () while non-systematic risk, the
unexpected component due to unexpected events that are relevant only to the security, is
reflected in the intercept (). The expected return on an asset depends only on its systematic risk.
-
8/9/2019 IFRM-Term Report Final
19/125
Top down investment risk research of the banking sector
19
No matter how much total risk an asset has, only the systematic portion is relevant in
determining the expected return on that asset.
Historically, the banking sector has not been a preferred choice in the capital market since the
investors like to invest in deposits and saving accounts more than they would like to go for the
stocks of a bank or a financial institution due to the higher risk involved in stock markets
(Nawazish Mirza, n.d.). Thats why the banking sector has less representation in stock markets as
compared to other sectors. However, the absence of public equity also increases the risk of a
bank. The major chunk of assets and liabilities in a bank are of a financial nature. They are
subject to interest rate changes and respond quickly to the volatility in the economy. The
sleeping nature of banking stocks makes them an alien in the financial markets and their
sensitivity to economic events makes them more volatile as compared to other industries.
However banking stocks could be possible candidates for inclusion in a diversified portfolio but
the problem arises as to how these stocks respond to the stock markets and what level of
systematic risk they are exposed to in different markets, given certain economic circumstances.
Systematic risk usually covers the broad macroeconomic factors that have the tendency to impact
the stocks under study, the basic indicators include are the rate of inflation, economic growth,
interest rates and market concentration (Sudirman, n.d.).Policy interest rates defined by the
central banks have positive effect on the profitability of the bank, because higher the interest
rate, interest rate will be utilized by the bank as an alternative placement of funds with higher
yields.Economic growthis an important variable that determines profitability because economic
growth can affect the supply and demand for banking services. It has been argued that economic
growth may result in increased business activity and increased business performance of the
borrower which will lead to increased demand for bank credit that encourages banks increase
-
8/9/2019 IFRM-Term Report Final
20/125
Top down investment risk research of the banking sector
20
interest rates which have implications on improving profitability. The impact of inflation on
profitability depends on whether inflation is anticipated or not by the bank. If inflation is
anticipated, then when the bank adjusts interest rates, resulting in increasing interest rate margin,
which means an increase in profitability and vice verse. The value of the banks' portfolios may
fall because of a weak economic performance of the banks' borrowers due to risks that cannot be
diversified. A slowdown of the economy bankrupts a higher proportion of borrowers compared
to normal times and the downturn will be severe enough that the banks themselves are in distress
and cannot fully repay their creditors. This reasoning along with the greater volatility of
emerging market economies can account for the higher vulnerability of these economies to
waves of banking failure (Oviedo, 2013).The causality between macroeconomic conditions and
financial instability also goes the other way around because declines in the value of banks'
portfolios can weaken the economy for instance the effect of a negative term-of-trade shock
would be a rise in the cross border bankruptcies that will ultimately raise the riskiness of the
banking sector.
Macroeconomic conditions trigger banking crises because the likelihood of a crisis is
incorporated into the decisions of every economic agent, that how both macroeconomic risk and
financial fragility effect business cycles. Out of the business-cycle paradigm, both declining
aggregate productivity and rising interest rates are capable of bringing about a banking crisis.
However, not every recession, no matter how deep, causes a crisis; it certainly does when the
down-turn is both deep and unexpected.The banking sector in Pakistan has witnessed drastic
changes over a period of 64 years since countrys independence in 1947 (FBR, n.d.). Since late
2007, Pakistan faced a difficult macroeconomic environment, not as such due to the global crisis
-
8/9/2019 IFRM-Term Report Final
21/125
Top down investment risk research of the banking sector
21
but rather due to the gradual build up of macroeconomic imbalances. The Global Financial Crisis
(GFC) had an indirect impact in Pakistan indeed there was a decline in exports due to recession
in economies which are Pakistans major trading partners, and there was pressure on capital
flows where strained liquidity positioning global financial markets impacted foreign portfolio
investment considerable decline in foreign direct investment due to weak economic
fundamentals, high inflation, security concerns and above all, the mounting fiscal deficit
breaching previous records in the countrys economic history, all hada role to play in keeping
the process of economic recovery in Pakistan weak at best. The leading evidence of these various
pressures on domestic firms and industries is that their loan repayment capacity has been
compromised, with a consequent rise of non-performing loans (NPLs) on the banks balance
sheets.
The risks contained in the bank's principal activities, i.e., those involving its own balance sheet
and its basic business of lending and borrowing, are not all borne by the bank itself (Santomero,
n.d.).The institution will usually eliminate or mitigate the financial risk associated with a
transaction through proper business practices and in other cases it will shift the risk to other
parties through a combination of pricing and product design. The banking industry recognizes
that an institution need not engage in business in a manner that imposes risk upon it; nor should
it absorb risk that can be efficiently transferred to other
Participants; rather, it should only manage risks at the firm level that are more efficiently
managed there than by the market itself or by their owners in their own portfolios. According to
standard economic theory, managers of value maximizing firms ought to maximize expected
profit without regard to the variability around its expected value thats why firms opt for the
-
8/9/2019 IFRM-Term Report Final
22/125
-
8/9/2019 IFRM-Term Report Final
23/125
Top down investment risk research of the banking sector
23
increased the business potential of international banks, but has also changed the risk profile of
banks balance sheets in terms of country, market and liquidity risks, although it is difficult to
determine whether those risks, on the whole, have increased compared to those which
international banks used to incur with cross-border lending to emerging countries. As a
consequence, risk management of banks international activities has also changed. The main
difficulty confronting any empirical investigation into the roles that banks play in business cycle
fluctuations involves identification of credit supply shocks. Most economic disturbances that
affect the supply of credit likely have independent effects on real variables as well; for example,
an unanticipated change in the stance of monetary policy may change the interest rate on, or
quantity of, bank loans, but at the same time, that change may also affect spending and
production through its influence on expectations and interest rates. (Divisions of Research &
Statistics and Monetary Affairs, Washington, n.d.). There has been much discussion of the
RAROC and VaR methodologies as an approach to capture total risk management. Yet,
frequently, the decisions to accept risk and the pricing of the risky position are separated from
risk analysis. If aggregate risk is to be controlled, these parts of the process need to be integrated
better within the banking firm. Both aggregate risk methodologies presume that the time
dimensions of all risks can be viewed as equivalent. Finally, operating such a complex
management system requires a significant knowledge of the risks considered and the approaches
used to measure them.
-
8/9/2019 IFRM-Term Report Final
24/125
-
8/9/2019 IFRM-Term Report Final
25/125
Top down investment risk research of the banking sector
25
price of KSE-100 index over similar look-back period. The stock and index prices will be used to
calculate discrete returns on which selected market risk metrics will be applied to identify the
risks focused banks are subjected to and in doing that, gauge performance of banking sector
under consideration. Market risk metrics results will therefore be the main primary data that will
be subjected to data classification and analysis so that general theme pertaining to risks
Pakistans banking sector is exposed to could be identified. Market risk metrics that will be used
to assess risks facing banking sector mainly include mean, standard deviation, skewness and,
kurtosis of stock returns, minimum and maximum returns and, maximum draw down.
Covariance, Correlation, performance, firm, co-movement and systematic risk; known as relative
indicators, will also be calculated with the independent variable in the formula being KSE-100
index returns, and dependent variable being returns on sample stocks respectively.
Secondary data will mainly include findings reported in prior studies and journal articles
relevant to the research study under consideration; in an attempt to unravel historical trends and
statistics regarding risks in the banking industry through macroeconomic and microeconomic
analysis and deliver comprehensive verdict. In-depth and comprehensive secondary data
collection will be facilitated bytree search referencing; using which references of the journal
articles already utilized for the study can also be referred in the current study. The use of this
research method is justified considering its ability to identify misjudgments in the primary data
through comparing it against secondary data to intercept major discrepancies that could then be
manually assessed to determine any factor of irrationality. Additionally, use of secondary data in
isolation from primary data would not be practical as banking industry is dynamic and hence
current figures and recent statistics; stock prices, should be used to arrive at a more accurate
findings.
-
8/9/2019 IFRM-Term Report Final
26/125
Top down investment risk research of the banking sector
26
Sample Size
The sample size for this research study includes fifty per cent of the commercial banks
listed on the Karachi Stock Exchange as also mentioned above. Fifty percent of the commercial
banks make up twelve and a half rounded to thirteen banks of twenty five listed commercial
banks and so this research study is focused on thirteen listed commercial banks comprising banks
belonging to all three top tier (Big-5 group), middle tier and third tier. The banks include Allied,
Bank Al-Falah, Habib, Habib Metropolitan, Bank Al-Habib, Askari, United, NIB, National Bank
of Pakistan, Faysal, KASB, JS and Samba. The look back or historical period used for the study
starts from 2nd
January 2012 and continues until 31stOctober 2014, from which period daily
stock quotations will be used for returns calculation. This makes the total observations 701 in
number implying 702 trading days. Including all the tiers ensures fair representation of
Pakistans banking industry which is important for unbiased and hence reliable risk investment
research. The look back period is long enough to capture variations both upside as well as
downside and hence meaningful for the study under consideration.
Data Collection and Analysis
For primary data collection; where primary data comprises stock and KSE-100 index
prices or quotations for data collection purpose as prices are required for calculation of discrete
returns upon which market risk metrics will be applied to gather actual primary data, credible
websites will be used to download daily quotations for the banks selected for the study and KSE-
100. The number of observations will be 701 in correspondence to the number of trading days.
For the prices, http://www.ksestocks.com/QuotationsData will be used. The daily quotations of
-
8/9/2019 IFRM-Term Report Final
27/125
-
8/9/2019 IFRM-Term Report Final
28/125
Top down investment risk research of the banking sector
28
market represented by composite KSE-100 index. However, for six market risk metrics which
incorporate index discrete returns as independent variable in their function making this approach
effectively invalid, maxima and minima in itself would highlight highest and lowest risk points;
or risks in their best and worst form, pertaining banking sector, in that disclosing sectors
riskiness and attractiveness for investors. The above discussed analysis technique reflects
thematic analysis that will lead towards identification of central theme representing overall
riskiness of Pakistans commercial banking sector.
This method for data collection, classification and analysis is in line with current research
topic as it comprehensively unveils risks Pakistans commercial banking sector is subjected to,
through exploring the sector in light of highest/best and lowest/worst performance on risk
indicators. The significance of this method also manifests in its ability to point out if an investor
should consider Pakistans banking sector for making equity investments, whilst also
highlighting worthy commercial banksstocks for risk takers and risk-aversive investors alike,
from risk investment research perspective.
L iterature search
For literature search, Google search engine was primarily used along with various other
research databases. Google Scholar, ProQuest and EBSCO databases were accessed to view and
download relevant research studies which are also referred in the ongoing research study. Google
was used to search and navigate through to relevant peer-reviewed journal articles as well as
meta-analysis concerning current research topic. These are used in literature review of the study
as secondary data or sources. Search Tree technique was also adopted, as mentioned above, in
an attempt to undertake comprehensive data gathering through reviewing and using even those
research articles in the study that are referenced in the researches attained from databases
-
8/9/2019 IFRM-Term Report Final
29/125
Top down investment risk research of the banking sector
29
indicated above. Apart from this extensive data mining, the main source of secondary data
remains Google, ProQuest and EBSCO because of humungous quantity of data on relevant
variables as well as accessibility of the articles and studies therein.
-
8/9/2019 IFRM-Term Report Final
30/125
Top down investment risk research of the banking sector
30
CHAPTER 5: ANALYSIS AND DISCUSSION
This section will focus on the analysis part of the research study, analyzing the figures
and results generated by application of market risk metrics on discrete returns calculated for all
the thirteen stocks and selected index composite for a total of 702 trading days, making returns
equal 701 (n-1). As explained in chapter 3 in detail, analysis will primarily start with
classification of outcomes on selected market risk metrics for all thirteen stocks into minima and
maxima, to compare the results against indexs performance. Comparing with market
performance represented by KSE-100s performance will highlight the riskiness of banking
sectors stocks. The similar treatment could not be undertaken for market risk relative indicators,
which could be transformed into maxima and minima but could not be compared against any
benchmark. The analysis for these indicators will comprise maxima and minima investigation
and interpretation which in itself effectively highlights banking sectors risks. This thematic
analysis will be complemented by macro and microeconomic analysis to ensure identification of
predominant trend in Pakistans banking sector with respect to risk; as to whether the sector
offers highly risky or less risky stocks or even an amalgamation of both of them. At this point, it
is important to reiterate that this chapter will mainly focus on last two components of top-down
risk investment research model; that is correlation with economy and product and model risks.
For the first two components however, secondary data was more important and so it is covered in
chapter two; Literature Review, of the study to a significant extent.
-
8/9/2019 IFRM-Term Report Final
31/125
Top down investment risk research of the banking sector
31
Mean
Highest Mean Discrete Return Lowest Mean Discrete Return Index Mean Discrete Return
SBL: .326% NBP: .080% KSE-100: .145%
Mean refers to the average return paid by or earned over the stock. Highest mean daily
discrete stock return among 13 stocks representing commercial banking sector is .326% whilst
lowest mean is .080%. Both the highest and the lowest mean discrete returns are positive which
indicates favorable fluctuation in stock prices or returns from investment perspective. The higher
the price fluctuation facing an equity security, however, the higher is the risk factor harbored by
that particular stock. This is explained by risk-return trade-off theory as per which risk and return
are directly proportional making an equity security that posits high return subjected to higher
risk, manifesting in increased price fluctuations. Accordingly, Samba Bank Limited having
symbol SBL earning .326% on average is most risky stock in the sample and, National Bank of
Pakistan (NBP) giving an average return of .080% to its holder/investor; that is on any given day
the stock price is expected to increase by .080% on average, exhibits least risk among all the
stocks comprising study sample. Comparing stocks maximum and minimum return against
index mean return of .145%, SBL appears to be outperforming benchmark boasting more than
two times the indexs mean return as opposed to which, NBP is underperforming. This highlights
SBL as most suitable for risk-taker and NBP as most suitable for risk-averse investor.
-
8/9/2019 IFRM-Term Report Final
32/125
Top down investment risk research of the banking sector
32
Standard Deviation
Highest Standard Deviation Lowest Standard Deviation Index Standard Deviation
SBL: 4.526% HBL: 1.683% .836%
Standard deviation refers to the volatility/variability of discrete daily return from mean
return for any stock or index, for that matter. The spread between discrete daily and mean return
is more stringent risk measure; accounting for total risk, implying volatility of return. The
highest standard deviation among that of sample stocks is set at 4.526% which is projected by
SBL and the lowest standard deviation is exhibited by HBL at 1.683%. Index standard deviation
(SD) appears to be .836%. Interpreting the figures for investment purposes, SBL stock could be
classified as aggressive investment/security exhibiting not only higher return but also volatility.
In contrast, HBL exhibits significantly lower volatility of 1.683% as compared to that of SBL but
despite that, HBLs stock turns out to be two times more risky; positing greater systematic and
unsystematic risk, than KSE-100 index which stands at .836% with respect to expectation
regarding upside or downside movement from the average index return of .145%. Thus, in
comparison to SBL which features variance that is 5.4 times index SD, HBL could be classified
as moderate whilst SBL as aggressive. With the lowest variance featured in the sample being
twice the indexs variance, riskiness borne by Pakistans commercial banking sector is well
starting develop, however definite shape and risk position of the sector could only be discovered
once all the metrics have been analyzed. It is also because of the fact that variance assigns
greater weight to outliers resulting in lopsided interpretations.
-
8/9/2019 IFRM-Term Report Final
33/125
Top down investment risk research of the banking sector
33
Skewness
Highest Skewness Lowest Skewness Index Skewness
NIB: 5.0245 BAHL: -3.0281 .283
Skewness assesses the tendency of data to be asymmetrical around it means; the
concentration of large number of discrete returns towards either right or left tail making
respective tail fatter, with fat right tail signifying profits and fat left tail being associated with
losses. Fat left tail event makes the distribution of the variable negatively skewed, whilst vice
versa scenario, fat right tail event, renders distribution positively skewed. The highest skewness
among sample banks of 5.0245 is exhibited by NIB and the lowest skewness of -3.0281 is faced
by BAHL. Index skewness stands at -.283. Interpreting the figures, returns on NIB denote fat
right tail indicating higher frequency of profit; higher positive than negative returns, whereas
BAHLs returns form fat left tail indicating higher incidences of loss. Returns on index itself are
negatively skewed denoting more negative than positive returns and hence losses. Using the
figures to determine riskiness of commercial banking sector, BAHL raises red flag for risk-
aversive investors, denoting huge 10.89 times more frequent negative returns than KSE-100
which itself posits negative skewness. NIB, on the other hand, delivers higher positive than
negative returns while also outperforming benchmark index by more than 17.75x (5.0254/.283),
in terms of frequency of positive returns, appealing to risk appetite of risk-taking and risk-averse
investors alike. Accordingly, it can be said that banking sector has the potential to deliver higher
number of positive than negative returns, reducing loss potential while building investor
confidence.
-
8/9/2019 IFRM-Term Report Final
34/125
Top down investment risk research of the banking sector
34
Kurtosis
Figure 1: Skewness and kurtosis comparison
Highest Kurtosis Lowest Kurtosis Index Kurtosis
NIB: 67.8799 UBL: .9143 2.255
The above graph compares and subsequently summarizes risk commercial banking sector
is exposed to with respect to skewness and kurtosis. However, for a more meaningful analysis,
highest and lowest points in kurtosis will be discussed, conforming to treatment of prior risk
metrics focused earlier to facilitate risk investment research. The highest kurtosis of 67.8799 is
exhibited by NIB making the distribution leptokurtic (Kurtosis > 3) whereas lowest kurtosis of
.9143 is exhibited by UBL making the distribution platykurtic. The benchmark index is subjected
to the kurtosis of 2.255 indicating even platykurtic distribution; dispersal of volatility risk
throughout distribution of returns. High kurtosis of NIB indicates concentration of volatility risk
in fat tail events meaning overall risk of the stock is driven by extreme values or frequent large
-10.000
0.000
10.000
20.000
30.000
40.000
50.000
60.000
70.000
Skewness
Kurtosis
-
8/9/2019 IFRM-Term Report Final
35/125
Top down investment risk research of the banking sector
35
magnitude of returns towards tails, making it suitable for risk-takers, particularly when the
skewness of NIB is also the highest among sample banks. Preference by risk-takers is embedded
in that whilst kurtosis is higher and so risk of tail events, skewness is also higher (positive) which
means positive returns outweigh negative returns for NIB, thereby hinting on significant
likelihood of tail events to incline towards right tail making investment potentially worthwhile.
On the other hand, UBL appeals conservative investors more through its platykurtic distribution
of returns whereby overall risk resides in a predictable band exposing investors to moderate
amount of risk, as opposed to massive risk that characterizes stocks denoting leptokurtic
distribution of returns. Returns of benchmark index; denoting market, are also distributed in
platykurtic fashion, however, being less conservative than UBL with its relatively higher kurtosis
coupled with negative skewness highlights lower risk level of Pakistans commercial banking
sector, with respect to kurtosis. The deduction is reinforced by profit potential of stocks with
NIB boasting kurtosis significantly higher than index.
Maximum Draw Down
Risk Metrics Highest Lowest Index
Maximum Return NIB: 50.794% BAHL: 4.988% 2.856%
Minimum Return UBL: -5.966% NBP: -22.933% -4.456%
Maximum Draw Down NIB: 62.460% UBL: 10.966% 7.312%
The above chart summarizes three major market risk metrics; maximum and minimum
return and maximum draw down. Over the look-back period of 702 trading days, NIB appears to
-
8/9/2019 IFRM-Term Report Final
36/125
Top down investment risk research of the banking sector
36
have earned highest maximum return of 50.794% among the sample banks whereas lowest
minimum return has been recorded by NBP which was -22.933%. This statistic confirms NIB as
aggressive; which is what previous metric (skewness and kurtosis) also indicate. The most
important risk metric in this scenario is MDD however, as it is derived using maximum and
minimum returns, they are discussed together to present better picture. Its importance reflects in
its ability to make traders/investors bring their trading/investing activities to halt, particularly due
to strong drawdown usually triggered by market sell-off and leverage conditions; prevalent
conditions across Pakistan. NIB projects highest MDD implying its investors need to have
greater risk appetite than that of any other sample banks investor. This is in conformance with
risk-return trade-off theory highlighted earlier. On the other hand, UBL provides its investors
relatively safer haven exposing them to significantly low financial risk, as implied by its lowest
MDD among sample banks; 5.7 times below NIBs MDD. Despite appealing conservative
investors though, UBL remains unable to track up to indexs MDD which is 3.654% below
UBLs MDD. Nevertheless, UBLs lowest MDD among sample banks does further its investor
confidence, which is also reinforced by its lowest kurtosis. This highlights commercial banking
sector as an amalgamation of aggressive and moderate investments catering to almost all risk
appetites appropriately.
-
8/9/2019 IFRM-Term Report Final
37/125
Top down investment risk research of the banking sector
37
Covari ance and Correlation
Figure 2: Risk measures compared
Metrics Highest Lowest
Covariance NIB: .0001 HMB: .00001
Correlation UBL: .5238 HMB: .0747
The graph above the table compares risk of sample commercial banks as per certain
absolute and all selected relative risk indicators, presenting bigger picture however, all the
absolute risk metrics have been and relative risk metrics will be analyzed separately to facilitate
effective risk investment research. As the above table indicates, NIB is subjected to highest
covariance as opposed to HMB which enjoys lowest covariance. To understand the risk banking
sector is exposed to, it is important to interpret the above figures. NIB bank is most risky with
respect to covariance because among all the sample banks, its returns are most aligned with
market returns represented by returns on benchmark index. HMB however appears to be least
-0.20000
0.00000
0.20000
0.40000
0.60000
0.80000
1.00000
1.20000
1.400001.60000
1.80000
RsikMeasures
Banks
Covariance
Correlation
Coefficient of Determination
Firm Risk
Comovement Risk
Performance Risk
Standard Deviation
Minimum Draw down
-
8/9/2019 IFRM-Term Report Final
38/125
Top down investment risk research of the banking sector
38
risky as despite the movement of its returns being in tandem with market returns, it depicts least
covariance or alignment with market among sample banks. The overall risk of the commercial
banking sector as dictated by Covariance is nevertheless higher due to lack of diversification,
implied by positive covariance throughout the sample. Diversification mitigates risk and
diversified portfolio; preferred by investors, comprises stocks that have negative or low
covariance with respect to each other. Focusing on correlation, it is similar to covariance except
that its deductions are purely derived from sign convention whilst covariance primarily reflects
degree of correlation. Looking at correlation statistics, it confirms the observations covariance
triggered. With both the stocks that projects highest and lowest correlation with market being
positively correlated, it can be safely deduced that commercial banking stocks moves in lockstep
with the market. This is important to be factored into portfolio formation and analysis to mitigate
risk.
Coeff icient of Determination and F irm Risk
Risk Metrics Highest Lowest
Coefficient of Determination UBL: 27.436% HMB: .558%
Firm Risk HMB: 99.442% UBL: 72.564%
Coefficient of determination or correlation-squared (systematic risk) and Firm risk
(unsystematic risk) are complements of each other, because of which they are discussed together.
Highest systematic risk of UBL canbe interpreted as the changes/variations/movements in
UBLs price are explainable by the changes/movements in benchmarkindex, more than that of
-
8/9/2019 IFRM-Term Report Final
39/125
Top down investment risk research of the banking sector
39
any other stock. HMBs prices are least explainable by movements in benchmark index making
it less prone to market/systematic risk. However, despite UBLs performance being most in line
with market performance, it and hence the entire sector is devoid of substantial market risk as r-
squared value is not significant (between 85%-100%). 27.436% systematic risk or only 27.436%
movements in UBLs stock price being explained by broader market movements is akin to lower
correlation between the security and index. Focusing on unsystematic or firm risk though, it is
significant for the entire sector, with highest firm risk among the sample banks being 99.44% for
HMBs and lowest being 72.564% facing UBL. This calls for significant caution for the
investors when investing in the banking sector. The security that faces highest systemic risk is
exposed to lowest firm unsystematic risk. But with the systematic risk profile on the whole being
low, firm risk becomes more important to be assessed. As per these two metrics, returns on
commercial banking stock comprise an element of uncertainty; depending strongly on
managerial performance in any given tenure/period. This makes the sector more preferable for
risk-takers as hedge fund managers and less so for risk-averse investors as mutual funds.
Co-movement and Performance Risk
Risk Metrics Highest Lowest
Co-movement Risk JSBL: 1.6456 HMB: .1567
Performance Risk SBL: .0023 NIB: -.001192
Co-movement risk (beta) figures are only meaningful if systematic risk is higher; that is
greater than 50%, because it measures ability of investment to respond to market swings.
-
8/9/2019 IFRM-Term Report Final
40/125
Top down investment risk research of the banking sector
40
However, in our study where even highest systematic is around half of 50%, the beta or co-
movement risk figures stands baseless and, hence will be ignored. Focusing on performance
risk/alpha subsequently which comprehends ability of the stock to earn extra returns when
market is stationary, primarily due to organizational and managerial performance, SBL appears
to be most favorably positioned having outperformed the market by modest .0023%, whereas
NIB appears to be least so having underperformed by .001192%. This reiterates earlier deduction
derived from firm risk statistics, which also projected management as critical factor for
concerned equities performance. In the light of this metric, commercial banking sector turns out
to be risky with the propensity to underperform even when market sentiments are bullish. This
makes the sector less attractive for risk-averse investors.
-
8/9/2019 IFRM-Term Report Final
41/125
Top down investment risk research of the banking sector
41
CHAPTER 5: CONCLUSION
Current research study undertaken to explore commercial banking sector with respect to selected
market risk metrics is essential to understand the position of equity securities offered by listed
commercial banks incorporated in Pakistan. Only market risk metrics are used for this research
study despite the banking sector being exposed to five risk classes/types including liquidity and
credit risk. This is primarily because market risk metric interfaces credit ad liquidity risk. When
market is falling, it becomes challenging for investors to dispose/sell-off their
asset/equity/security, implying positive relationship between market risk and liquidity risk.
Credit risk is not present in equity market which further endorses use of market risk metrics for
this research study as appropriate and viable. Risk investment research is particularly important
for investors, analysts and even the banks itself for the purpose of informed decision-making.
Discrete daily returns have been used as it gives fair representation of volatility and hence risk.
702 trading days have been used as look-back period which has both, positive and negative
aspects. Reliance on historical data spanning past two years could highlight volatility such From
the above analysis, it appears that commercial banking sector is not conservative, rather equity
securities pertaining commercial banking sector ranges between aggressive and moderate, as
none of the sample stocks could be termed as appropriate for mutual fund managers or risk-
averse investors if decision is to be taken with relevance to the outcomes on elected market risk
metrics. The stocks posit tendency to benefit their investors from upside movement when the
market is bullish, however during bearish markets, significant downside risk prevails. Standard
deviation which denotes any securitys total risk; representing both systematic as well as
unsystematic risk, indicates lowest standard deviation among that of sample commercial banks
-
8/9/2019 IFRM-Term Report Final
42/125
Top down investment risk research of the banking sector
42
as twice the benchmark indexs variance. This relation, a lso stated earlier, essentially reflects
high overall volatility of Pakistans commercial banking sector making it significantly risky
comprising mainly aggressive equity securities. Skewness of the index which itself is inclined
towards higher negative returns being outweighed by commercial banking sectors stocks
confirms to the elevated degree of risk commercial banking sector is exposed to. The coefficient
of determination however signifies explained variation as low, implying performance of
commercial banking securities is not mainly dependent on the performance of the market. This
result attained on coefficient of determination metric is of pivotal importance in this study as it
implies performance of equity commercial banking performance is also dictated by factors other
than market movements. This finding is further corroborated by the results attained on firm and
performance risk which indicates organizational and managerial performance impacts
movements of stocks pertaining commercial banking sector by substantial magnitude. This
makes it important for prospective investors to closely follow developments in commercial
banking organizations; they are considering for making investment into, in addition to analyzing
the sector and individual banking companies in juxtaposition with the wider market represented
by relevant benchmark index. On the basis of this nevertheless, the sector appears to be
rewarding for risk-takers who depicts greater risk appetite and tolerance levels than risk-averse
investors projecting low risk appetite and tolerance level. For risk-averse investors, use of
diversification could make sector attractive which is important for formulation of a well-
balanced portfolio with constituent assets being negatively correlated or having low correlation
between them. This will lead to the mitigation of risk inherent in highly risky commercial
banking sector, but even with the use of diversification it is essential to revisit and revise
portfolio periodically to ensure portfolio continuously corresponds to investors risk appetite.
-
8/9/2019 IFRM-Term Report Final
43/125
Top down investment risk research of the banking sector
43
Annexure
KSE-100
IndexReturns
Allied Bank(ABL)
StockReturns
Askari Bank(AKBL)
StockReturns
11282.01 53.54 10.11
11402.04 0.011 56.21 0.050 10.25 0.014
11361.97 -0.004 54.02 -0.039 10.01 -0.023
11187.88 -0.015 57.21 0.059 10.01 0.000
11125.35 -0.006 55.19 -0.035 10 -0.001
11040.31 -0.008 54.12 -0.019 9.94 -0.006
10933.18 -0.010 57.84 0.069 10.03 0.009
10930.49 0.000 57.79 -0.001 10.12 0.009
10909.12 -0.002 54.6 -0.055 10.06 -0.006
11014.46 0.010 55.41 0.015 10.2 0.014
11112.65 0.009 55.12 -0.005 10.27 0.007
11305.16 0.017 56.31 0.022 10.3 0.003
11547.72 0.021 56.06 -0.004 10.44 0.014
11515.59 -0.003 57 0.017 10.36 -0.008
11774.68 0.022 58.86 0.033 10.3 -0.006
12037.66 0.022 61.03 0.037 10.7 0.039
11991.38 -0.004 60.6 -0.007 10.77 0.00711949.75 -0.003 61.14 0.009 10.64 -0.012
11883.92 -0.006 61.04 -0.002 10.66 0.002
11960.22 0.006 61.03 0.000 10.67 0.001
11883.01 -0.006 60.47 -0.009 10.35 -0.030
11874.89 -0.001 60.51 0.001 10.25 -0.010
11930.55 0.005 60.9 0.006 10.35 0.010
11929.78 0.000 61 0.002 10.25 -0.010
11982.62 0.004 60.6 -0.007 10.32 0.007
12136.92 0.013 61.37 0.013 11.06 0.07212284.62 0.012 62.03 0.011 12.06 0.090
12263.25 -0.002 62.51 0.008 11.96 -0.008
12213.24 -0.004 62.12 -0.006 11.25 -0.059
12231.6 0.002 62 -0.002 11.11 -0.012
12250 0.002 60.63 -0.022 11.01 -0.009
12261.85 0.001 61.02 0.006 11.48 0.043
-
8/9/2019 IFRM-Term Report Final
44/125
Top down investment risk research of the banking sector
44
12311.04 0.004 61.08 0.001 11.53 0.004
12404.24 0.008 61.67 0.010 11.66 0.011
12495.68 0.007 62 0.005 11.89 0.020
12517.9 0.002 61.09 -0.015 11.8 -0.008
12544.45 0.002 61.01 -0.001 12.16 0.031
12603.67 0.005 61.97 0.016 12.68 0.043
12515.92 -0.007 61.55 -0.007 12.62 -0.005
12706.52 0.015 62.47 0.015 12.73 0.009
12743.66 0.003 63.53 0.017 13.05 0.025
12739.22 0.000 63.32 -0.003 12.85 -0.015
12877.88 0.011 64.81 0.024 12.7 -0.012
12941.38 0.005 65.48 0.010 12.31 -0.031
13088.97 0.011 65.99 0.008 12.56 0.020
13278.31 0.014 66.22 0.003 12.97 0.033
13324.34 0.003 69.17 0.045 13.14 0.01313244.95 -0.006 68.49 -0.010 12.92 -0.017
13271.39 0.002 68.9 0.006 13.4 0.037
13352.74 0.006 69.08 0.003 13.52 0.009
13382.54 0.002 69 -0.001 13.95 0.032
13283.65 -0.007 68.89 -0.002 13.63 -0.023
13360.67 0.006 69.25 0.005 13.82 0.014
13451.07 0.007 69.89 0.009 14.23 0.030
13297.12 -0.011 69.13 -0.011 13.79 -0.031
13077.72 -0.016 67.91 -0.018 13.15 -0.04613303.33 0.017 60.51 -0.109 13.31 0.012
13293.12 -0.001 59.5 -0.017 11.59 -0.129
13273.29 -0.001 60.01 0.009 11.81 0.019
13286.73 0.001 59.54 -0.008 12.39 0.049
13449.73 0.012 60.28 0.012 12.95 0.045
13575.41 0.009 62.21 0.032 13.69 0.057
13559.1 -0.001 62.85 0.010 14.01 0.023
13761.76 0.015 64.08 0.020 14.64 0.045
13663.32 -0.007 64 -0.001 14.32 -0.022
13691.08 0.002 64.01 0.000 14.47 0.010
13945.3 0.019 65.76 0.027 14.88 0.028
13831.47 -0.008 65.25 -0.008 14.64 -0.016
13875.53 0.003 65 -0.004 13.77 -0.059
13864.68 -0.001 64.8 -0.003 14.26 0.036
13903.12 0.003 64.76 -0.001 14.51 0.018
-
8/9/2019 IFRM-Term Report Final
45/125
Top down investment risk research of the banking sector
45
13816.96 -0.006 65 0.004 14.65 0.010
13693.74 -0.009 64.5 -0.008 14.89 0.016
13799.43 0.008 65.2 0.011 14.55 -0.023
13770.7 -0.002 63.24 -0.030 14.04 -0.035
13764.22 0.000 63.28 0.001 14.31 0.019
13937.95 0.013 63.62 0.005 14.59 0.020
13929.47 -0.001 64.24 0.010 14.64 0.003
13936.48 0.001 65.53 0.020 14.47 -0.012
14083.44 0.011 68.8 0.050 15.16 0.048
14132.59 0.003 70.49 0.025 15.39 0.015
14217.74 0.006 69.83 -0.009 15.99 0.039
14066.09 -0.011 69.08 -0.011 15.56 -0.027
14042.77 -0.002 67.75 -0.019 15.24 -0.021
13990.38 -0.004 67.68 -0.001 15.65 0.027
14142.52 0.011 70 0.034 15.73 0.00514419.92 0.020 72.66 0.038 15.57 -0.010
14612.28 0.013 73.39 0.010 15.36 -0.013
14617.97 0.000 70.97 -0.033 15.27 -0.006
14513.96 -0.007 70.6 -0.005 15.02 -0.016
14613.59 0.007 70.03 -0.008 15.36 0.023
14420.19 -0.013 68.54 -0.021 15.39 0.002
14230.49 -0.013 66.81 -0.025 15.1 -0.019
14228.77 0.000 69.32 0.038 15.18 0.005
14313.67 0.006 68.61 -0.010 15.26 0.00514081.07 -0.016 67.01 -0.023 14.78 -0.031
14063.08 -0.001 67 0.000 14.77 -0.001
13857.78 -0.015 66.01 -0.015 14.38 -0.026
13875.74 0.001 65.98 0.000 14.15 -0.016
14142.08 0.019 66.49 0.008 15.11 0.068
14032.82 -0.008 65.95 -0.008 14.96 -0.010
13936.92 -0.007 65.31 -0.010 14.98 0.001
13925.06 -0.001 65.01 -0.005 15.05 0.005
14031.51 0.008 64.22 -0.012 14.8 -0.017
14071.85 0.003 63.99 -0.004 14.71 -0.006
13871.76 -0.014 62.91 -0.017 14.72 0.001
13786.62 -0.006 64.09 0.019 14.62 -0.007
13876.97 0.007 64.39 0.005 14.67 0.003
13757.92 -0.009 64.25 -0.002 14.54 -0.009
13708.23 -0.004 64.3 0.001 14.85 0.021
-
8/9/2019 IFRM-Term Report Final
46/125
Top down investment risk research of the banking sector
46
13745.73 0.003 63.55 -0.012 14.44 -0.028
13717.3 -0.002 63.16 -0.006 14.16 -0.019
13558.7 -0.012 63 -0.003 14.05 -0.008
13601.46 0.003 63.68 0.011 13.98 -0.005
13429.56 -0.013 63.99 0.005 13.58 -0.029
13368.89 -0.005 63.6 -0.006 13.49 -0.007
13656.2 0.021 63.96 0.006 13.79 0.022
13665.8 0.001 64.01 0.001 13.83 0.003
13754.13 0.006 64.01 0.000 13.75 -0.006
13682.99 -0.005 63.5 -0.008 13.52 -0.017
13667.18 -0.001 64.82 0.021 13.26 -0.019
13600.6 -0.005 64.55 -0.004 13.07 -0.014
13730.82 0.010 64.55 0.000 13.56 0.037
13642.2 -0.006 64.49 -0.001 13.34 -0.016
13656.04 0.001 64.28 -0.003 13.4 0.00413799.12 0.010 64.07 -0.003 13.59 0.014
13805.42 0.000 63.98 -0.001 13.61 0.001
13801.41 0.000 64.18 0.003 13.57 -0.003
14142.92 0.025 64.92 0.012 14.16 0.043
14200.79 0.004 64.37 -0.008 13.96 -0.014
14178.1 -0.002 64.65 0.004 13.89 -0.005
14170.91 -0.001 64.07 -0.009 13.7 -0.014
14310.18 0.010 64.25 0.003 13.69 -0.001
14379.54 0.005 64.61 0.006 13.75 0.00414374.34 0.000 64.64 0.000 13.8 0.004
14380.46 0.000 65 0.006 14.78 0.071
14401.74 0.001 65.79 0.012 14.64 -0.009
14332.29 -0.005 65.51 -0.004 14.46 -0.012
14384.58 0.004 65.93 0.006 14.34 -0.008
14445.28 0.004 67.02 0.017 15 0.046
14596.59 0.010 68.74 0.026 15.04 0.003
14568.21 -0.002 68.26 -0.007 14.82 -0.015
14564.49 0.000 68.97 0.010 15.72 0.061
14527.25 -0.003 69 0.000 15.54 -0.011
14512.07 -0.001 70 0.014 15.36 -0.012
14564.68 0.004 70.11 0.002 15.5 0.009
14553.29 -0.001 70.52 0.006 15.59 0.006
14526.41 -0.002 70 -0.007 15.46 -0.008
14511.54 -0.001 70.01 0.000 15.68 0.014
-
8/9/2019 IFRM-Term Report Final
47/125
Top down investment risk research of the banking sector
47
14577 0.005 70.52 0.007 15.52 -0.010
14716.86 0.010 70.5 0.000 15.56 0.003
14730.67 0.001 70 -0.007 15.43 -0.008
14676.43 -0.004 70 0.000 15.25 -0.012
14673.77 0.000 70.61 0.009 14.88 -0.024
14672.24 0.000 72.19 0.022 14.72 -0.011
14744.14 0.005 73.04 0.012 15.01 0.020
14759.59 0.001 73.96 0.013 14.98 -0.002
14761.49 0.000 71.13 -0.038 14.77 -0.014
14911.97 0.010 71.66 0.007 14.55 -0.015
14970.93 0.004 71.71 0.001 15.52 0.067
15000.08 0.002 72.2 0.007 15.37 -0.010
15080.55 0.005 72.98 0.011 16.12 0.049
15039.18 -0.003 74 0.014 15.73 -0.024
15171.66 0.009 73.57 -0.006 15.82 0.00615234.48 0.004 72.92 -0.009 15.74 -0.005
15151.31 -0.005 72.37 -0.008 15.5 -0.015
15253.71 0.007 72.48 0.002 15.88 0.025
15391.58 0.009 72.25 -0.003 15.89 0.001
15428.49 0.002 71.52 -0.010 15.81 -0.005
15388.13 -0.003 70 -0.021 15.68 -0.008
15293.39 -0.006 67.88 -0.030 15.42 -0.017
15188.53 -0.007 68 0.002 15.5 0.005
15253.96 0.004 67.5 -0.007 15.79 0.01915240.19 -0.001 67 -0.007 15.6 -0.012
15214.02 -0.002 68.31 0.020 15.57 -0.002
15278.48 0.004 68 -0.005 15.51 -0.004
15306.51 0.002 69.27 0.019 15.26 -0.016
15449.61 0.009 68.3 -0.014 15.31 0.003
15398.68 -0.003 67.69 -0.009 15.22 -0.006
15517.19 0.008 68.11 0.006 15.03 -0.012
15588.66 0.005 67.81 -0.004 15.16 0.009
15452.64 -0.009 67 -0.012 15 -0.011
15375.52 -0.005 66 -0.015 15.03 0.002
15373.46 0.000 66.04 0.001 15.42 0.026
15399.42 0.002 64.23 -0.027 15.26 -0.010
15357.59 -0.003 63.56 -0.010 15.3 0.003
15444.82 0.006 63.9 0.005 15.28 -0.001
15559.94 0.007 63.89 0.000 14.97 -0.020
-
8/9/2019 IFRM-Term Report Final
48/125
Top down investment risk research of the banking sector
48
15648.29 0.006 64.56 0.010 15.41 0.029
15712.21 0.004 65.01 0.007 15.47 0.004
15788.96 0.005 67.82 0.043 15.31 -0.010
15754.39 -0.002 68.4 0.009 15.22 -0.006
15652.01 -0.006 70.1 0.025 15.47 0.016
15688.24 0.002 69.83 -0.004 15.58 0.007
15753.82 0.004 68.21 -0.023 15.67 0.006
15845.3 0.006 69 0.012 15.86 0.012
15694.21 -0.010 68.6 -0.006 15.74 -0.008
15746.9 0.003 68.02 -0.008 15.73 -0.001
15674.3 -0.005 69.17 0.017 15.66 -0.004
15654.62 -0.001 71.19 0.029 15.62 -0.003
15679.19 0.002 71.42 0.003 15.52 -0.006
15792.75 0.007 70.93 -0.007 16.51 0.064
15848.63 0.004 69 -0.027 16.83 0.01915853.84 0.000 68.5 -0.007 16.55 -0.017
15865.53 0.001 68.28 -0.003 16.39 -0.010
15812.72 -0.003 69.99 0.025 16.45 0.004
15795.93 -0.001 69.13 -0.012 16.64 0.012
15910.11 0.007 69.5 0.005 16.57 -0.004
15962.37 0.003 69.9 0.006 16.84 0.016
16101.55 0.009 69.2 -0.010 16.75 -0.005
16156.36 0.003 68.91 -0.004 16.95 0.012
16051.14 -0.007 69.67 0.011 16.86 -0.00516218.01 0.010 69.49 -0.003 16.8 -0.004
16243.27 0.002 68.36 -0.016 16.62 -0.011
16213.68 -0.002 68.5 0.002 16.58 -0.002
16129.72 -0.005 69 0.007 16.37 -0.013
16120.52 -0.001 68.95 -0.001 16.31 -0.004
16143.07 0.001 68.61 -0.005 16.3 -0.001
16197.74 0.003 67.53 -0.016 16.36 0.004
16251.38 0.003 68.5 0.014 16.2 -0.010
16251.79 0.000 69 0.007 16.25 0.003
16233.19 -0.001 68.67 -0.005 16.27 0.001
16251.01 0.001 69 0.005 16.54 0.017
16237.59 -0.001 69.94 0.014 16.78 0.015
16270.48 0.002 70.03 0.001 16.72 -0.004
16364.77 0.006 70.51 0.007 16.63 -0.005
16424.03 0.004 71.65 0.016 16.48 -0.009
-
8/9/2019 IFRM-Term Report Final
49/125
Top down investment risk research of the banking sector
49
16527.08 0.006 71.77 0.002 16.56 0.005
16573.86 0.003 72 0.003 16.61 0.003
16537.98 -0.002 73.58 0.022 16.53 -0.005
16650.15 0.007 75 0.019 16.47 -0.004
16675.7 0.002 75.18 0.002 16.63 0.010
16824.55 0.009 75.3 0.002 16.87 0.014
16807.91 -0.001 74.74 -0.007 16.77 -0.006
16787.54 -0.001 75.05 0.004 17.07 0.018
16701.69 -0.005 74.01 -0.014 16.87 -0.012
16744.6 0.003 74.01 0.000 16.84 -0.002
16806.58 0.004 74.5 0.007 16.82 -0.001
16845.09 0.002 74.51 0.000 16.79 -0.002
16801.02 -0.003 74 -0.007 16.74 -0.003
16858.68 0.003 74 0.000 16.83 0.005
16869.83 0.001 73.95 -0.001 16.74 -0.00516908.02 0.002 73.63 -0.004 16.75 0.001
16865.34 -0.003 73.5 -0.002 16.63 -0.007
16891.94 0.002 73.49 0.000 16.5 -0.008
16927.34 0.002 73.49 0.000 16.5 0.000
16892.32 -0.002 72.15 -0.018 16.75 0.015
16943.19 0.003 71 -0.016 17.41 0.039
16905.33 -0.002 71 0.000 17.22 -0.011
16794.87 -0.007 72.5 0.021 17 -0.013
16489.99 -0.018 71 -0.021 17.06 0.00416588.54 0.006 71.5 0.007 17.25 0.011
16648.84 0.004 71.58 0.001 17.63 0.022
16502.65 -0.009 70.71 -0.012 17.84 0.012
16645.76 0.009 71.5 0.011 18.84 0.056
16742.22 0.006 70.97 -0.007 18.85 0.001
16529.92 -0.013 70.33 -0.009 18.67 -0.010
16634.71 0.006 70 -0.005 18.69 0.001
16633.18 0.000 71.5 0.021 18.79 0.005
16107.89 -0.032 73.05 0.022 17.82 -0.052
16181.47 0.005 74.98 0.026 17.79 -0.002
16291.09 0.007 75.54 0.007 18.12 0.019
16601.77 0.019 74.83 -0.009 18.72 0.033
16640.81 0.002 75.15 0.004 18.71 -0.001
16894.09 0.015 73.49 -0.022 18.79 0.004
16908.67 0.001 75 0.021 18.57 -0.012
-
8/9/2019 IFRM-Term Report Final
50/125
Top down investment risk research of the banking sector
50
17056.36 0.009 74.02 -0.013 18.51 -0.003
17004.99 -0.003 74 0.000 18.43 -0.004
17172.04 0.010 73.9 -0.001 18.64 0.011
17205.27 0.002 73.88 0.000 18.21 -0.023
17242.74 0.002 73.75 -0.002 18.29 0.004
17266.23 0.001 73.5 -0.003 18.44 0.008
17288.07 0.001 73.33 -0.002 18.67 0.012
17408.52 0.007 73.5 0.002 18.53 -0.007
17383.32 -0.001 73.8 0.004 18.7 0.009
17477.94 0.005 73.5 -0.004 19.69 0.053
17548.54 0.004 71.97 -0.021 19.45 -0.012
17611.4 0.004 69.97 -0.028 19.5 0.003
17696.45 0.005 69.76 -0.003 19.15 -0.018
17765.82 0.004 68.51 -0.018 19.12 -0.002
17797.22 0.002 68.65 0.002 19.08 -0.00217865.61 0.004 69.01 0.005 19.03 -0.003
17817.71 -0.003 69.75 0.011 18.62 -0.022
17947.07 0.007 69.06 -0.010 18.8 0.010
17921.02 -0.001 68.43 -0.009 18.98 0.010
18074.27 0.009 68.97 0.008 18.77 -0.011
18020.5 -0.003 68.5 -0.007 18.69 -0.004
17894.9 -0.007 68.4 -0.001 18.63 -0.003
18080.91 0.010 68.55 0.002 18.88 0.013
18173.67 0.005 68.94 0.006 18.74 -0.00718185.19 0.001 68.77 -0.002 19.42 0.036
18126.77 -0.003 68.01 -0.011 19.53 0.006
18053.32 -0.004 67.74 -0.004 19.33 -0.010
18000.45 -0.003 66.89 -0.013 19.26 -0.004
17992.91 0.000 68.15 0.019 19.27 0.001
17964.18 -0.002 68 -0.002 19.28 0.001
17522.56 -0.025 68.13 0.002 18.74 -0.028
17872.85 0.020 68 -0.002 18.88 0.007
17760.44 -0.006 66 -0.029 18.7 -0.010
17740.69 -0.001 67.07 0.016 18.6 -0.005
17664.83 -0.004 59.47 -0.113 18.54 -0.003
17492 -0.010 59.75 0.005 18.3 -0.013
17693.37 0.012 60 0.004 18.05 -0.014
17753.97 0.003 59.02 -0.016 18.13 0.004
17913.62 0.009 59 0.000 18.38 0.014
-
8/9/2019 IFRM-Term Report Final
51/125
Top down investment risk research of the banking sector
51
17963.12 0.003 58.93 -0.001 18.39 0.001
17961.91 0.000 58.6 -0.006 18.61 0.012
17872.15 -0.005 58.95 0.006 18.66 0.003
17926.14 0.003 59.6 0.011 18.67 0.001
17947.76 0.001 59.4 -0.003 18.66 -0.001
18043.31 0.005 58.43 -0.016 19.16 0.027
18272.11 0.013 57.97 -0.008 19.28 0.006
18345.74 0.004 57.16 -0.014 19.05 -0.012
18575.88 0.013 58 0.015 19.04 -0.001
18613.44 0.002 57.64 -0.006 19.24 0.011
18636.03 0.001 58 0.006 19.13 -0.006
18653.06 0.001 57.56 -0.008 18.77 -0.019
18713.61 0.003 57.67 0.002 18.96 0.010
18723.35 0.001 56.55 -0.019 19.08 0.006
18764.55 0.002 55.93 -0.011 19.1 0.00118714.28 -0.003 56 0.001 19.08 -0.001
18524.5 -0.010 56.14 0.003 18.77 -0.016
18361.87 -0.009 55.49 -0.012 18.72 -0.003
18394.12 0.002 56 0.009 18.71 -0.001
18614.36 0.012 55.63 -0.007 17.71 -0.053
18631.21 0.001 56.69 0.019 16.71 -0.056
18605.55 -0.001 56.54 -0.003 15.71 -0.060
18647.29 0.002 56.6 0.001 15.3 -0.026
18779.66 0.007 56 -0.011 15.75 0.02918885.61 0.006 55.01 -0.018 16.75 0.063
18917.71 0.002 55.89 0.016 16.74 -0.001
18822.85 -0.005 58.68 0.050 17.47 0.044
18982.42 0.008 60.02 0.023 18.45 0.056
19034.53 0.003 58.44 -0.026 18.4 -0.003
19226.63 0.010 58.45 0.000 18.2 -0.011
19256.7 0.002 58.95 0.009 17.34 -0.047
19262.74 0.000 59.4 0.008 16.91 -0.025
19472.55 0.011 61.05 0.028 16.83 -0.005
19661.46 0.010 63.68 0.043 16.68 -0.009
19916.27 0.013 66.5 0.044 17.07 0.023
20244.82 0.016 67.29 0.012 17.4 0.019
20474.62 0.011 68.66 0.020 17.59 0.011
20566.69 0.004 69.9 0.018 17.23 -0.020
20416.6 -0.007 69 -0.013 17.2 -0.002
-
8/9/2019 IFRM-Term Report Final
52/125
Top down investment risk research of the banking sector
52
20537.03 0.006 69.83 0.012 16.84 -0.021
20814.14 0.013 69.77 -0.001 16.95 0.007
21168 0.017 69.99 0.003 17.1 0.009
21458.9 0.014 69.75 -0.003 16.88 -0.013
21342.65 -0.005 69.45 -0.004 16.71 -0.010
21283.77 -0.003 68.85 -0.009 15.82 -0.053
20958.86 -0.015 68.77 -0.001 15.64 -0.011
21501.72 0.026 68.38 -0.006 15.47 -0.011
21441.12 -0.003 66.43 -0.029 15.28 -0.012
21590.66 0.007 68.96 0.038 15.55 0.018
21823.05 0.011 70.12 0.017 16.41 0.055
22080.85 0.012 70.2 0.001 16.23 -0.011
22274.51 0.009 72 0.026 15.87 -0.022
22092.42 -0.008 69.56 -0.034 16.1 0.014
22276.7 0.008 70.99 0.021 16.71 0.03822358.96 0.004 70.21 -0.011 16.73 0.001
22150.74 -0.009 72.41 0.031 16.59 -0.008
22209.07 0.003 73.53 0.015 16.56 -0.002
22324.57 0.005 72.33 -0.016 16.49 -0.004
22757.72 0.019 71.29 -0.014 16.53 0.002
22541.64 -0.009 70.68 -0.009 16.9 0.022
22216.46 -0.014 71.43 0.011 16.75 -0.009
21919.63 -0.013 71 -0.006 16.53 -0.013
22135.72 0.010 68.55 -0.035 16.46 -0.00422015.04 -0.005 69.65 0.016 16.69 0.014
21698.35 -0.014 69.3 -0.005 16.12 -0.034
21048.08 -0.030 68.58 -0.010 15.5 -0.038
21110.34 0.003 68.54 -0.001 15.55 0.003
21002.57 -0.005 70 0.021 15.33 -0.014
21015.34 0.001 71 0.014 15.35 0.001
21005.69 0.000 71.5 0.007 15.22 -0.008
21363.16 0.017 73.53 0.028 15.55 0.022
21644.17 0.013 76.46 0.040 15.59 0.003
21802.86 0.007 76.58 0.002 15.57 -0.001
21966.96 0.008 78.65 0.027 15.73 0.010
22178.34 0.010 80 0.017 15.85 0.008
22365.72 0.008 78.64 -0.017 15.48 -0.023
22721.22 0.016 79 0.005 16.1 0.040
22984.94 0.012 81.39 0.030 15.82 -0.017
-
8/9/2019 IFRM-Term Report Final
53/125
Top down investment risk research of the banking sector
53
22747.13 -0.010 81.5 0.001 15.51 -0.020
23037.32 0.013 81 -0.006 15.69 0.012
23172.35 0.006 78.69 -0.029 15.95 0.017
23160.89 0.000 79 0.004 15.94 -0.001
22994.72 -0.007 78.52 -0.006 15.73 -0.013
23114.97 0.005 77.81 -0.009 15.91 0.011
23428.93 0.014 80.88 0.039 16.66 0.047
23657.81 0.010 80.56 -0.004 16.33 -0.020
23683.27 0.001 80.14 -0.005 15.55 -0.048
23776.22 0.004 78.7 -0.018 14.68 -0.056
23573.68 -0.009 78.03 -0.009 14.82 0.010
23497.07 -0.003 78.03 0.000 14.98 0.011
23315.15 -0.008 78 0.000 14.93 -0.003
23284.81 -0.001 76 -0.026 14.86 -0.005
23312.78 0.001 77.29 0.017 14.82 -0.00323091.87 -0.009 78.48 0.015 14.68 -0.009
22701.3 -0.017 77.79 -0.009 14.22 -0.031
22621.93 -0.003 78.39 0.008 14.23 0.001
23237.19 0.027 79.62 0.016 14.44 0.015
23437.99 0.009 78.8 -0.010 15.09 0.045
23613.2 0.007 78.5 -0.004 15.05 -0.003
23687.89 0.003 79.57 0.014 15.1 0.003
23673.3 -0.001 78.24 -0.017 15.16 0.004
23600.23 -0.003 77.73 -0.007 15.53 0.02423487.23 -0.005 78.25 0.007 15.46 -0.005
23015.27 -0.020 77.5 -0.010 15.29 -0.011
22714.32 -0.013 77 -0.006 15.48 0.012
22714.68 0.000 76.66 -0.004 15.84 0.023
22922.24 0.009 76.95 0.004 15.85 0.001
22523.71 -0.017 77.47 0.007 15.92 0.004
22236.33 -0.013 76.47 -0.013 13.42 -0.157
22214.73 -0.001 75.5 -0.013 13.06 -0.027
22160.85 -0.002 76 0.007 13.19 0.010
21724.68 -0.020 77.68 0.022 13.24 0.004
21808.48 0.004 78.55 0.011 13.46 0.017
21875.83 0.003 77.47 -0.014 13.27 -0.014
22451.46 0.026 77.5 0.000 13.59 0.024
22765.87 0.014 77.75 0.003 13.67 0.006
22838.84 0.003 77.28 -0.006 13.78 0.008
-
8/9/2019 IFRM-Term Report Final
54/125
Top down investment risk research of the banking sector
54
22992.17 0.007 77 -0.004 13.89 0.008
23231.68 0.010 80.43 0.045 14.49 0.043
23222.21 0.000 78.31 -0.026 14.19 -0.021
23168.04 -0.002 79.25 0.012 14 -0.013
23242.68 0.003 83.21 0.050 14.2 0.014
23066.5 -0.008 85.11 0.023 14.02 -0.013
22930.06 -0.006 86.03 0.011 13.63 -0.028
23456.98 0.023 85.25 -0.009 14.29 0.048
23595.61 0.006 84.26 -0.012 13.78 -0.036
23639.97 0.002 82.25 -0.024 13.83 0.004
23088.49 -0.023 78.4 -0.047 13.59 -0.017
23060.9 -0.001 77.17 -0.016 13.56 -0.002
22780.82 -0.012 78.59 0.018 13.42 -0.010
22387.31 -0.017 78.49 -0.001 13.31 -0.008
21832.68 -0.025 76.9 -0.020 12.79 -0.03921980.42 0.007 76.75 -0.002 12.86 0.005
22189.67 0.010 77.83 0.014 12.76 -0.008
22152.35 -0.002 76.6 -0.016 12.66 -0.008
22085.96 -0.003 74.91 -0.022 12.6 -0.005
21864.85 -0.010 77.15 0.030 12.21 -0.031
22080.47 0.010 79 0.024 12.05 -0.013
21657.22 -0.019 79.5 0.006 11.68 -0.031
21674.98 0.001 80 0.006 11.54 -0.012
21775.39 0.005 81.5 0.019 11.7 0.01421599.78 -0.008 80.98 -0.006 12.01 0.026
21754.95 0.007 81 0.000 11.38 -0.052
22230.43 0.022 83.15 0.027 11.3 -0.007
22347.29 0.005 83.5 0.004 11.29 -0.001
22360.85 0.001 84.98 0.018 11.14 -0.013
22445.59 0.004 85.18 0.002 10.98 -0.014
22353.2 -0.004 82 -0.037 10.93 -0.005
22276.65 -0.003 84.99 0.036 11.01 0.007
22310.6 0.002 84.79 -0.002 10.93 -0.007
22775.85 0.021 84.25 -0.006 10.88 -0.005
22649.09 -0.006 83.94 -0.004 10.82 -0.006
22377.83 -0.012 84.75 0.010 10.76 -0.006
22790.7 0.018 84.96 0.002 10.85 0.008
23165.21 0.016 85.4 0.005 10.84 -0.001
23220.21 0.002 84.55 -0.010 10.85 0.001
-
8/9/2019 IFRM-Term Report Final
55/125
Top down investment risk research of the banking sector
55
23367.15 0.006 85 0.005 11.34 0.04