Research proposal

The feasibility and sustainability of London Stock of Exchange: What other factors influence LSE except Beta

Table of contents

Particulars Page number Background 3

Literature review 4Research methodology 9

Data analysis 11Ethics, validity and presentation 13

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Background

Equity pricing has always been a vague area of the modern finance academia. Firstly it is a demand and supply based phenomenon and then academicians can actually add on different shades and different sources of price justification to the pricing model (Asgharian and Hansson, 2000). But as a whole it is a complicated game and there are different empirical model to understand the pricing dynamics of assets.

CAPM is considered to be one of the famous and one of the oldest of the lot where assets are priced based on its co-movement with the market under two basic assumptions – market risk takes care of all the risks and when a rational investor diversifies he or she actually should take care of only the portfolio risk and nothing else.

But over the decades it had been proven that beta is dead as there are number of other factors which affect security pricing (Asgharian and Hansson, 2000). This research paper is going to test the effectiveness of beta in case of stock rotation policy as a part of the active portfolio management activism and alternative pricing methods is also expected to be derived in order to maximize the alpha.

1.1 Problem statement

London stock exchange has long been considered as a problematic stock exchange and there needs to be a quick reversal of the pattern in terms of more trade, more profit and more participant. LSE which used to be one of the finest and largest stock exchange across the globe is now just shivering in the competitive world (Berk, 1995). Since global stock exchanges are lot more decentralized and as everyone can trade in every country through international fund managers the need of LSE is really dampening up. So, the student has taken up this research as a moral and academic duty to understand the trading, profit making and pricing dynamics of LSE.

1.2 Rationale for scenario chosen

Over the years, London Stock exchange has failed to generate the required rate of return which was actually expected from it and improper asset pricing is surely going to be the major reason. As per the return standards of different asset classes it is the cash and cash equivalent items which should get the lowest return as the risk exposure of these assets are the lowest (Griffin and Lemmon, 2002). The equity items both the domestic equity items and the international equity items should secure the highest ratings in terms of the return offering but actually the performance of the stock exchange has been pretty low.

Since the stock exchange is not offering anything superior in return on a relative scale it has been a great challenge to make investors attracted to the business and it was also very challenging for everyone involved to earn a fair share in the overall proceedings – like the issuers have failed to fetch a good price, the brokerage house has not been able to earn good trading profit and the

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investors as already mentioned have been on the lower note about earning the profit (Griffin and Lemmon, 2002).

Since the stock exchanges very proposition of earning good amount of profit is at stake since the market model of stock pricing is not working the whole game of the financial market is under a threat. So, from that very point of view it is immensely important to track down the sustainability and the feasibility of the LSE business model.

1.3 Aims and objectives

Research idea – The researcher is going to test the feasibility and sustainability of London stock exchange with specific reference to the asset pricing model’s effectiveness.

Research objectives:

To understand the level of feasibility of London stock exchange based business module To pinpoint the sustainability of London stock exchange under the global competitive

pressure To pinpoint the effectiveness of the traditional CAPM model in better industry selection

and alpha generation for stocks enlisted in LSE – London stock exchange To prescribe a better asset pricing model to maximize the alpha in London stock

exchange

Literature review

2.1 Conceptual framework – Tracking the SWOT of LSE

By far the analysis goes, the core problem has been pinpointed several times – it is the loss of attraction and it is the loss of the trading volume and it is the non-inclination to participate in the stock exchange business of the UK based investors. London Stock Exchange – LSE is lagging from the NYSE, from the TSE, from the HKSE. Fund raisers do not feel that it is the best place to fetch a good price for the IPOs – initial public offering, the stock investors do not feel that profit is guaranteed here and eventually the global lucrativeness of the business module has dampened (Berk, 1995). In order to be a good competitor on a global scale, each and every stock exchange all across the globe needs to be efficient, effective, innovative and responsive to the stock exchange participant’s need.

So, a rigorous SWOT analysis will be needed to understand the future sustainability of the business. By understanding the strength and weakness of the business module the researcher can understand the internal environment of the business and by tracking the opportunities and threats of the business module the researcher can understand the external environment of the business

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(Griffin and Lemmon, 2002). From a bird’s eye view the business reputation and the greater image of the business module can be termed as the strength of the model and the absence of OTC bulletin board and pink sheets can be a classical example of operational deficiency.

Business re-survival and business feasibility is based on a number of successful implementation of strategies. There needs to be multiple layers of strategies – operational, business level and corporate level strategies to successfully implement. As an example, one can easily term digitalization of the overall procedure a very good initiative to ensure operational efficiency and the provision of inter-day trading can be another good example of operational strategy (Griffin and Lemmon, 2002). On the other hand, the inclusion of quality global stock can be another very good example of the business level strategy. These strategies need to be traced down.

2.2 Literature review:

The literature review portion of the study will discuss different issues like the evolution of CAPM – capital asset pricing model, calculation of industry beta, the critical arguments raised against CAPM – capital asset pricing model, alternative pricing models. The researcher is going to start with the evolution of the CAPM.

CAPM – the evolution: CAPM is the equilibrium model of asset pricing where market risks is considered to be the one and only measurement risk and t is assumed that market as indicated by beta captures all sorts of risk (Griffin and Lemmon, 2002). The very construction of CAPM is very straight-forward. It is assumed under the CAPM model that the price of any asset will compensate the investors for the risk free rate and the unique risk of the asst in comparison to the market riskiness. So, under the CAPM model it is assumed that the expected return on a security will be equal to the risk free rate and the extra compensation for getting involved in a separate asset category (Berk, 1995).

Expected return on asset = Risk free rate + market risk premium * beta

Beta is a measure of systematic risk and since under the CAPM models only the portfolio risks matters by using beta the covariance risk of the security with the market is taken into account. Under the CAPM model it is assumed that all the investors will act as a rational investor and since all the investors are ultimately rational it is expected that ultimately they will fully diversify the portfolio and only the relevant risk for the portfolio will be the contribution risk of the assert into the portfolio (Berk, 1995).

From the simple model, one logical conclusion can easily be derived by the researcher. Higher the beta of the portfolio or higher the beta of the individual asset higher will be the expected return. On the contrary, it is assumed that lower the beta of the portfolio and lower the beta of the individual asset lower will be the expected return (Berk, 1995). But based on a ex-post analysis it

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was later revealed that such simplifying of relationship does not hold good in reality as on a longer period basis the academicians have not found any such kind of a very straight cut relationship and actually the relationship is confusing and there had been number of doubts raised by academicians whether the single period asset pricing model can actually capture all the facts and facets of assert pricing (Griffin and Lemmon, 2002).

The criticism of CAPM – Is beta dead? : The first and foremost criticism which has been raised against CAPM proponents is the existence of the market portfolio and whether the theoretical market portfolio actually holds good or not (Danthine and Donaldson, 2002). It has been established that the definition of the market portfolio should not merely constitute just the stocks and fixed income generating security, rather in the true sense the definition of market portfolio should constitute fixed income, stocks, income generating g properly, land, human capital and assets coming from all the sphere of life (Danthine and Donaldson, 2002). So, from that perspective it will be impossible to build up such a market portfolio and judge the intrinsic value of the asset based on that market portfolio.

The assumption of risk-free asset is also considered to be false argument and in really life all the asset classes have significant extent of embedded risk. For example, even if government Treasury bill is considered as a risk-free item but in reality the Treasury bill has interest rate risk, liquidity risk and a number of risk factors which are not properly compensated through investing in government based securities. So, the proxy for risk-free asset is not actually properly determined (Berk, 1995). Moreover the century long tradition of thinking that treasury securities are default risk free are not going to hold true as it has been established during the recent financial turmoil that governmental securities also do default. Perhaps the concept of risk-free asset can be better understood by the inclusion of zero-beta portfolio (Danthine and Donaldson, 2002). In the feasible set of portfolio an investor can find out number of portfolios which are uncorrelated with the market portfolio with a correlation of zero. So, if an investor can pick up a zero-beta portfolio where there is no systematic risk it can be used as a better proxy for risk-free asset rather than relying on the tradition driven definition of risk free asset which are found only in the government backed treasure securities.

It is assumed under the CAPM model that people can lend and borrow at the risk-free rate. The reality is far more different at the individual level. An individual investor can lend at the risk-free rate but unless the individual is a big gun in the share market even the brokerage firm will not get credit at a risk-free rate. Moreover due to higher denomination at different assets – an individual will not have the access to all types of securities just because these securities are not perfectly divisible. Even more importantly CAPM talks about a frictionless market where there will be no information processing cost, no tax etc (Lakonishok et al., 1994). But the reality is far too different as here individuals have to pay taxes of different genres and information processing is supposed to be a costly game and there is nothing like symmetric information whatsoever. CAPM is a single- period model but all the components which are inbuilt under the model are

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dynamic and these refer to the continuous time frame. From that angle, for forecasting multi-period return CAPM may not be a very good choice.

Perhaps there is big problem lying in the decision making model of the individuals. It is generally assumed that the decision making power of the individual under the CAPM model is a rational one. But reality is far different from anything closer to rational decision making. Theoretically it is assumed that people will make rational decisions – decisions free from any biases and decisions free from any choices (Engsted and Tanggaard, 2004). For example, a portfolio that generally sets a trading rule that he is going to sell off his or her portfolio after having a 20% loss in the value may not be doing the same with a selected security. While constructing the portfolio, that investors may have decided that the particular stock is for the financing a pleasure trip. So, even if the portfolio manager should be more concerned about the portfolio value rather than concerning on the value of an individual stock in this very case the portfolio manager is completely focused on the value of the stock as he or she has some other types of business to be done with this very stock (Lakonishok et al., 1994). So the traditional thinking of just the portfolio and nothing else is not going to work here. Moreover many a times, a portfolio manager has picked up a stock after rigorous level of business research and after conducting that rigorous business research that very stock may not even click. Still the portfolio manager may escalate all the possible levels of errors with that very decision. So, this is a type of framing which is generally done by the investors. So, the rational decision making model is for sure not the proper way of making an assumption. CAPM is based on the assumption of homogenous expectation and it is assumed that all the investors will have a very precise idea about the probability distribution of the return with the assumed risk level and the investors will have a very precise idea about the dividends to be paid and all other cash related endowments (Engsted and Tanggaard, 2004). But reality is far away from that. Information possessing does vary and the different layers of information possession eventually distort the whole process of decision making. Under the CAPM model it is generally assumed that individual will be risk averse and for taking each amount of extra risk there will be some extra return (Lakonishok et al., 1994). But once again the reality can be very different as for scanty amount of investments investors may be prepared to take chances and the compensation may not be working on. Perhaps for taking on major risks according to each one’s investment value people can become risk adverse. CAPM is built on number of assumptions and all these assumptions can be challenged in real life.

Industry beta: What if an investor wants to shuffle his or her portfolio into stocks of different industries based on the sector rotation policy and who wants to do an active portfolio management. Surely industry beta can be a handful device to fulfill the investment strategy. During the time of contraction and during the time of economic recession, defensive industry shares are better choices since their beta will be less than one and it is a sign of lower sensitivity with the market (Lakonishok et al., 1994). On the other hand, during the time of market boom and business expansion, the cyclical, high-tech and the durable industry shares are going to work

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on in the better way. This aforementioned industry’s beta is more than one – an indication of higher market sensitivity. So, as a whole industry beta can be a good predictor to understand the industry’s sensitivities to the market and these basic themes can be used to construct active portfolio which will foster sector rotation based investment strategy.

In this part of the study the researcher is going to discuss how an industry beta can be calculated. There is a one easy solution – instead of calculating the beta an industry index can be used directly. What will happen if there is no industry beta data? This is obviously going to be a very critical scenario but there is a very easy solution. On a weighted average basis, the researcher has to calculate the industry indices and beta is just the covariance of the industry indices and the market divided by the variance of the stock market (Bartholdy and Peare, 2001).

So, by calculating the industry beta one investor can go for investing under the sector rotation policy guideline. Higher industry beta Company selected at the booming time and lower industry beta company selected at the recession time. But as per the earlier discussion the readers must have observed that in real life the assumptions of CAPM does not work and beta let it be individual or let it be a portfolio or let it be an industry is not going to be the perfect solution for fully utilizing the insights.

Alternative asset pricing model: For pricing an asset, there are multiple facets of models available not just the prevalent one – beta. For example, any researcher can go well with the no-arbitrage model where it is assumed that if an asset is mispriced the combined activism of the market participant will diffuse that price contradiction (Danthine and Donaldson, 2002).

For example, if a particular security is currently undervalued than the arbitrager is going to short sell the portfolio and buy the undervalued one using the proceed of the sale. If after the stipulated investment horizon the security price goes to the desired level then the security will be sold and using the proceed the portfolio will be hold and the investor will obviously pocket the differences. Quite on the contrary, if a particular security is currently overvalued, then the investor will short sell the security and purchase the desired portfolio using the sales proceed (Bartholdy and Peare, 2001). Once the security comes to the desired level, then it is purchased by selling the portfolio and whatever the level of arbitrage profit is derived it is actually pocketed. So, if all the rational investors start to do the same there will be no real scope of making a profit. So, the no-arbitrage opportunity actually helps the investor to better price securities and any opportunities and arbitrages are not going to be there forever (Engsted and Tanggaard, 2004).

Addition to the basic CAPM model can also be done and academicians have done and rectified the model to the very perfection over the years. Under the Fama-French module of asset pricing there are two more additional factors added into the traditional asst pricing module – size factor and value factor (Engsted and Tanggaard, 2004). It is empirically proven that since small sized company has generally a higher tendency to default just because of their small size there needs to be a premium paid to the investors for holding the relatively small size companies. On the other

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hand, the mispricing based on the market value and book value ratio is going to be another big source of premium or discount.

On the other hand, based on the return decomposition model, the expected price of an asset can be referred as a sum of premiums to be paid for consuming different layers of risks – for example foreign exchange risk, liquidity risk, inflation risk and different types of risks (Bartholdy and Peare, 2001). So, if the valuation expert accurately knows the different possible sources of risks by investing in the particular stock then he or she will also be able to price these risks.

Conclusion

The existing academic textbooks and journals have already analyzed the effect of market models and APT models on the asset pricing statistics of LSE but there had not been any real analysis to incorporate the behavioral issues like market anomalies and the expectation of market participants in the operating module. So, there is certainly a gap in the academic literature – a gap which will be addressed in the following study.

Research methodology

Business research is a systematic journey; it starts with the development of research idea, question and objectives. Once the literature has been properly reviewed by the researcher the researcher knows how to design the sampling framework and how to collect the information from the respondents (Ragin, 1994). After the data is collected, the researcher uses the different mechanisms at hand to analyze the data set and test the pre-formed hypothesis based on the collected data. Finally a workable solution to the research problem is identified and a new sphere of knowledge is generally created (Saunders, et al., 2003). In this research methodology part of the study the researcher is going to discuss the research philosophy, research approach, the research strategy, research design, the data collection mechanism and the sampling framework.

Style of business research: Research philosophy – Research philosophy is the conceptual framework which determines the quality of the business research. Positivism and phenomenology is the two major stream of research philosophies which are generally used to understand the possible path of research conduction (Mikkelsen, 2005).

The proponents of the positivism believe that statistical data and statistical inference says it all and there is no need to consider the irrational decision making model and the cognitive biases while interpreting the data (Ragin, 1994). Moreover there is no real need to take the help from a social scientist while conducting the study. The proponents of the phenomenology believe that statistical data and statistical inference cannot say it all and there will be every need to consider the irrational decision making model and the cognitive biases while interpreting the data

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(Saunders, et al., 2003). Moreover if it is needed, further help can be explored from a social scientist.

This business research is going to be a phenomenological journey as the asset pricing does have a number of cognitive biases and behavioral traits.

Style of business research: Research approach – For conducting the study the researcher is going to follow the deductive approach. So, null hypothesis is going to be built up and these null hypotheses are going to be tested by the collected data (Saunders, et al., 2003). Theory formulation is not an objective of the researcher but theory is certainly going to be the major guide for this research.

Style of business research: Research strategy – Because of the superior concentration and because no primary data is needed, this business research is going to be a survey.

Style of business research: Research method – There are a number of research methods majorly the quantitative, qualitative and the mixed ones. In case of the quantitative research the input and the output of the research is numerical; it is easier to form the hypothesis and it is even easier to test the research validity and reliability (Silverman, 2005). On the other hand, in case of the qualitative study, the inputs and outputs of the business research is going to be non-numeric; it is difficult to form the null hypothesis but data collection will be easier (Saunders, et al., 2003). For conducting this business research the method is going to be quantitative.

Research question: From analyzing the research area of interest the following research questions can be genuinely derived.

What is the extent of feasibility of London stock exchange based business module? Whether London stock exchange can conduct a sustainable business in midst of the

global competitive pressure? What is the extent of effectiveness of the traditional CAPM model in better industry

selection and alpha generation for stocks enlisted in LSE – London stock exchange? What can be the better asset pricing model to maximize the alpha in London stock

exchange?

Methods of analysis – Correlation, regression based data analysis tools will be needed to analyze the data points and higher time series modules are also going to be used to analyze the data set.

Correlation refers to the linear relationship between two research variables and regression expresses the mathematical functionality between the variables (Marshall & Rossman, 2006).

Data sources – Both primary and secondary data is going to be used by the researcher. The trading volume, profitability data, CAPM related data sets are going to be extracted by the secondary sources. The researcher also wants to highlight the expectations of different key

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stakeholders throughout the study and in order to do so; a primary research by means of questionnaire based survey will be needed (Silverman, 2005). The questions will be kept simple and coherent.

The secondary information to be used for the study is going to be relevant, reliable and verifiable (Silverman, 2005). So, before the usage of the secondary information these quality of the data and information needs to be checked and rechecked at a regular basis (Ragin, 1994). Industry report, London stock exchange report etc. are going to be the source of the secondary data.

Sampling issues – For collecting the primary data, a questionnaire survey will be needed and since all the participants cannot be addressed throughout the survey, the researcher needs to conduct sampling to collect the data (Silverman, 2005).

Simple random sampling is going to be the sampling device and all the participants of the population can be a part of the population. The sample size is 100 and this is surely pretty enough to take care of the sampling biases.

Data analysis

As the research objectives have been set up, this business research is focused on building up an empirical model where regression driven study is going to be used to explore the relationship between stock pricing.

Since the regression based relationship is going to be understood through OLS – ordinary least square technique the researchers have to make it ascertain that the autocorrelation level, the stationary level and the trendiness issues have been taken cared of as while using time series data in case of a regression one needs to ensure that there is no trend, no autocorrelation and no stationary in the data set (Patton, 2002). Now the researcher is going to present a diagnostic test before the formal report starts on.

Research variable

Diagnostic test Correction

Risk-free rate It was revealed from the diagnostic test that there was trend in the data set, there was cyclicality in the data set and the data set did not possess the stationary feature. So, initially data set was not ready for usage. By trend the researcher is referring to any sign of upward and downward significant movement in the data set and by cyclicality the researcher is referring to any specific pattern which incurs time after time. For a stationary data set, the mean, median

By using the first degree of change or by using the first differentiation – the trendiness, the cyclicality is the data set was removed. So, the data is ready for analysis just by removing the first degree of changes. After the correction, the time series data was prepared to be used in further business research since the mean and median was equal, there was no real season specific movement and the upward and downward significant pattern was removed by the first degree of

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and mode of the data set is going to remain the same.

differencing.

Market risk premium

It was revealed from the diagnostic test that there was trend in the data set, there was cyclicality in the data set and the data set did not possess the stationary feature. So, initially data set was not ready for usage. By trend the researcher is referring to any sign of upward and downward significant movement in the data set and by cyclicality the researcher is referring to any specific pattern which incurs time after time. For a stationary data set, the mean, median and mode of the data set is going to remain the same.

By using the first degree of change or by using the first differentiation – the trendiness, the cyclicality is the data set was removed. So, the data is ready for analysis just by removing the first degree of changes. After the correction, the time series data was prepared to be used in further business research since the mean and median was equal, there was no real season specific movement and the upward and downward significant pattern was removed by the first degree of differencing.

Industry beta It was revealed from the diagnostic test that there was trend in the data set, there was cyclicality in the data set and the data set did not possess the stationary feature. So, initially data set was not ready for usage. By trend the researcher is referring to any sign of upward and downward significant movement in the data set and by cyclicality the researcher is referring to any specific pattern which incurs time after time. For a stationary data set, the mean, median and mode of the data set is going to remain the same.

By using the first degree of change or by using the first differentiation – the trendiness, the cyclicality is the data set was removed. So, the data is ready for analysis just by removing the first degree of changes. After the correction, the time series data was prepared to be used in further business research since the mean and median was equal, there was no real season specific movement and the upward and downward significant pattern was removed by the first degree of differencing.

Business size premium

It was revealed from the diagnostic test that there was trend in the data set, there was cyclicality in the data set and the data set did not possess the stationary feature. So, initially data set was not ready for usage. By trend the researcher is referring to any sign of upward and downward significant movement in the data set and by cyclicality the researcher is referring to any specific pattern which incurs time after time. For a stationary data set, the mean, median and mode of the data set is going to

By using the first degree of change or by using the first differentiation – the trendiness, the cyclicality is the data set was removed. So, the data is ready for analysis just by removing the first degree of changes. After the correction, the time series data was prepared to be used in further business research since the mean and median was equal, there was no real season specific movement and the upward and downward significant pattern was removed by the first degree of differencing.

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remain the same. BV/Price ratio It was revealed from the diagnostic

test that there was trend in the data set, there was cyclicality in the data set and the data set did not possess the stationary feature. So, initially data set was not ready for usage. By trend the researcher is referring to any sign of upward and downward significant movement in the data set and by cyclicality the researcher is referring to any specific pattern which incurs time after time. For a stationary data set, the mean, median and mode of the data set is going to remain the same.

By using the first degree of change or by using the first differentiation – the trendiness, the cyclicality is the data set was removed. So, the data is ready for analysis just by removing the first degree of changes. After the correction, the time series data was prepared to be used in further business research since the mean and median was equal, there was no real season specific movement and the upward and downward significant pattern was removed by the first degree of differencing.

P/E ratio It was revealed from the diagnostic test that there was trend in the data set, there was cyclicality in the data set and the data set did not possess the stationary feature. So, initially data set was not ready for usage. By trend the researcher is referring to any sign of upward and downward significant movement in the data set and by cyclicality the researcher is referring to any specific pattern which incurs time after time. For a stationary data set, the mean, median and mode of the data set is going to remain the same.

By using the first degree of change or by using the first differentiation – the trendiness, the cyclicality is the data set was removed. So, the data is ready for analysis just by removing the first degree of changes. After the correction, the time series data was prepared to be used in further business research since the mean and median was equal, there was no real season specific movement and the upward and downward significant pattern was removed by the first degree of differencing.

Ethics, validity and presentation

Business research is an ethical process and the basic features of an ethical conduct have to be well ensured while conducting a business research (Silverman, 2005). This research is not going to be an exception and by adhering to the following issues the ethical concerns are going to be entertained by the researcher.

The secondary sources from where academic help has been garnered will be properly acknowledged.

The collected data will be properly kept under strong maintenance and good preservation. Nobody will have the access to the collected data except the supervisor and the researcher (Maxwell, 2005).

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Before the participation in the primary research, all the participants will know about the research objectives exactly and it is going to be a voluntary business research. Moreover, their description will remain anonymous and necessary permission before interviewing will be obtained.

Work plan

Activities Percentage of the allocated time

Research idea, objectives and question development 20%Literature review 32%

Methodology design and the development of sampling framework 28%Collection of the data through secondary sources and analysis of the data 15%

Write-up of the report 5%

Gantt chart

Particulars 1st

week 2nd

week3rd

week4th

week5th

week6th

week7th

week8th

week Research idea, objectives and question development Literature review Methodology design and the development of sampling framework Collection of the data through secondary sources and analysis of the data Write-up of the report

Possible limitations

Since this research is partially based on sample survey, sampling biases should affect the proper conduction of business research. Moreover, the irrational decision making model, the cognitive biases are going to affect the research results.

Expected outcomes

After conducting the business researcher, the researcher is quite certain to find solution to the survival question of LSE – London stock exchange. The researcher is also going to come up with a good solution to the appropriate asset pricing models which can be used to price the stocks to be traded in the business.

This business research is quite certainly going to be valid one as all the research objectives are going to be achieved during the regular course of research conduction (Patton, 2002). This

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business research is obviously going to be a reliable business research as little changes in the methodology will not bring about too much of a change in the research findings.

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References

Asgharian, H. and B. Hansson (2000) ‘Cross-Sectional Analysis of Swedish Stock Returns with Time-Varying Beta: The Swedish Stock Market 1983-96’ European Financial Management, Vol. 6, No. 2, pp. 213.

Bartholdy, J. and P. Peare (2001) ‘The Relative Efficiency of Beta Estimates’ Aarhus School of Business.

Berk, J. B. (1995) ‘A Critique of Size-Related Anomalies’ Review of Financial Studies, Vol. Summer 95, Vol. 8 Issue 2

Danthine, J. and Donaldson, B. (2002) Intermediate Financial Theory (Prentice Hall, Upper Saddle River, N.J

Engsted, T. and Tanggaard, C. (2004) ‘The Comovement of Us and Uk Stock Markets’ European Financial Management, Vol. 10, No. 4, pp. 593-607.

Griffin, J. and Lemmon, M. (2002) ‘Book-to-Market Equity, Distress Risk, and Stock Returns’ Journal of Finance, Vol. 57, No. 5, pp. 2317-2336.

Lakonishok, et al. (1994) ‘Contrarian Investment, Extrapolation, and Risk’ Journal of Finance, Vol. 49, No. 5, pp. 1541-1578.

Marshall, C. & Rossman, G. (2006) Designing Qualitative Research. London, SAGE.

Maxwell, J. (2005) Qualitative Research Design: An Interactive Approach. Second Edition.

California, SAGE.

Mikkelsen, B. (2005) Methods for Development Work and Research: A New Guide for

Practicioners. New Delhi: Sage Publications.

Patton, M. (2002) Qualitative Research Evaluation Methods. Third edition. United States, SAGE.

Ragin, C. (1994) Constructing Social Research: The Unity and Diversity of Method, Pine Forge Press, Thousand Oaks.

Saunders, et al. (2003) Research methods for Business Students. Third Edition. New Jersey, Pearson Education.

Silverman, D. (2005) Doing qualitative research: a practical handbook, Second edition. United States, SAGE.

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