Economics and Finance pfsimage_0_0
Dissertation: Validity of Fama and French Three Factor Model: Empirical Evidences from KLSE (Part 5/5)

Chapter 5: Conclusion and Recommendations

5.1 Conclusions

In this section, conclusion will be made. Research objectives outlined earlier in Chapter 1 will be discussed in light of the research findings and literature review presented earlier. Referring to Chapter 1, two research objectives can are formulated as follow: (a) to review the relevant theories and literatures related to multifactor equity pricing model; and (b) to test the validity of Fama and French three factor model in Kuala Lumpur Stock Exchange, Malaysia, i.e., to investigate if both firm size and book-to-market value ratio is indeed priced risk factors in Malaysia stock exchange. Both of the research objectives are fulfilled successfully in this dissertation. In the following section, discussion on the research objectives will be provided.

5.1.1 Discussion for Research Objectives 1

Research objective is about to review the relevant theories and literatures related to multifactor equity pricing model. A comprehensive literature review found that the concept of multifactor equity pricing model is initially originated from the introduction of Capital Asset Pricing Model (CAPM) – the modern finance theory that changed how the entire industry think about risk and return issues in financial market. However, despite the compellingly logical and rational the theory is, CAPM simply fail to explain the variation of stock returns around the world satisfactorily. Empirical testing on CAPM does not yield meaningful results, and beta as the risk measures has been receiving a great deal of critiques from both scholars and practitioners.

Multifactor equity pricing model is then derived and employed to further improve the theory of CAPM. Origination of multifactor equity pricing model comes from the realization that the poor empirical results of CAPM is primarily due to beta as the only single measure of risk, while the risks pertaining to financial market should be multi-dimensional. Since then, multifactor models are increasingly being studied and tested. Today, there are many popular and theoretically sound multifactor models available. However, one of the most famous multifactor models is the three factor model proposed by Fama and French (1992).

Having comprehensive understandings on the development and backgrounds on multifactor equity pricing model, Fama and French three factors model is employed to test the cross sectional average stock returns in Kuala Lumpur Stock Exchange (KLSE) in Malaysia. Fama and French three factors model is selected due to its popularity. A lot of tests had been performed on the model in different countries around the world, but the empirical results available are not conclusive. For this reasons, Research Objectives 2 is necessary.

5.1.2 Discussion for Research Objectives 1

As lengthily articulated in Chapter 2, empirical evidences concerning Fama and French three factor model are not conclusive. Empirical evidences supporting Fama and French three factor model include: Javid (2008); Singh (2009); Hearn (2010); Naughton and Veeraraghavan (2005); Walid (2009); Dempsey (2010); Kassimatis (2008); and Simlai (2009). Then, researchers found mixed empirical evidences on Fama and French three factor model are Drew, Naughton and Veeraraghavan (2005) and Nartea, Ward & Djajadikerta (2009). Lastly, there are studies indicating that Fama and French three factor model has no explanatory power in explaining variation of stock returns in certain countries. Example of such studies include: Mirza & Afzal (2011); and Novak & Petr (2010).

In Research Objective 2, the primary goal is to test the validity of Fama and French three factor model in Kuala Lumpur Stock Exchange, Malaysia, i.e., to investigate if both firm size and book-to-market value ratio is indeed priced risk factors in Malaysia stock exchange. The findings are generally consistent with previous studies conducted by Hearn (2010); Walid (2009); Kassimatis (2008); Nartea, Ward & Djajadikerta (2009), Drew et. al. (2003); and Naughton & Veeraraghavan (2005). Firstly, it is found that the factor loading for risk factor (Rmt-Rft) is mixed. There is very little empirical evidences supporting that risk factor (Rmt-Rft) is capable of explaining the explained variable, namely (Rpt-Rft) for the six portfolios. This strongly suggests that the predictive power of beta fall miserably when risk factors such as SMBt, and HMLt are added into the regression analysis. Secondly, it is found that factor loading for risk factor SMBt are positive for all of the six portfolios; suggesting that Fama and French (1992) assertion that smaller firms are generally riskier is true, even in the Malaysian context. To further explain, it is witnessed from the descriptive statistics of average stocks returns of smaller sized firms tend to be more volatile; suggesting that these smaller firms are indeed are riskier investment options. For example, from year 2006 to 2010, the global economy is indeed entering into a recession and stock market plummeted. In such a situation, smaller sized firms are observed to suffer in greater magnitude, as business risks of the smaller firms tend to be greater during recessionary era.

One interesting finding is that the factor loading for risk factor HMLt are negative for all of the six portfolios is not consistent with assertion proposed by Fama and French (1992). Theoretically speaking, as suggested by Fama and French (1992), stocks traded with higher ratio of book value to market value ratio tend to outperform those stocks with lower book value to market value ratio because the stocks with higher book value to market value ratio are more likely to be in a financially distressed position, and thus, these securities should have higher expected returns, to compensate for the higher risks associated with them. The inconsistency of research findings on sign of factor loading for risk factor HMLt can be explained by reasons provided by Drew et. al. (2003). Accordingly, the existence of negative returns indicates that value firms are not riskier than growth firms. There are emerging evidences in the international context on the unusual behaviors of the HML portfolio. Availability or discoveries of such findings in emerging countries are probably caused by lack of well developed stock analysis and research in these nations. As such, stock returns could be more subjected to market sentiment, rather based on the fundamentals of the stocks. In Malaysia, these reasons are rational, because as an emerging country, the nature of stock market in Malaysia could be similar to the situation in other emerging countries.

5.2 Suggestions of Research Topic and Areas in the Future

The journey of understanding multifactor equity pricing model as well as its validity in real life should not stop here. There are many different types of studies to be conducted in order to understand how these different theoretical models can be applied in the real financial markets around the world.

In this study, Fama and French three factors model is the only multifactor equity pricing model tested in the context of Malaysia. However, as discussed in Chapter 2, there are many different types of multifactor models. The different types of multifactor models include: Chen, Roll and Ross multifactor model; Burmeister, Roll and Ross multifactor model; and Carhart multifactor model. The validity and explanatory power of these models in the context of Malaysia is unknown. In other words, it is remaining unknown if these multifactor models are valid in a small emerging country such as Malaysia? Secondly, which multifactor model is more powerful or useful in explaining cross sectional average stock returns in the Malaysian context? Future studies are necessary to understand these issues in greater details.

Then, the validity of Fama and French three factor model in the other countries, particularly in the South East Asia region is not understood. A more comprehensive study on the validity of the three factors model in other countries, such as Vietnam, Philippines, and Thailand will be required, to investigate if the findings are consistent across the smaller emerging countries in the region. In fact, purely based on the observation in this study, strong and conclusive statement on validity and relevancy of Fama and French’s assertion on risk factors pertaining to stock returns is hardly possible.

Apart from that, it is also acknowledged that the research period investigated in this study is short. In order to understand how the three factors model withstood the test of time, from a longer research period perspective, future study can perform a similar study for longer time span. Indeed, a study on how the three factors model performs in the different economy climate is also possible; to further understand the environmental changes and impacts towards the model.


Abdullah, D. A., & Hayworth, S. C. (1993). Macroeconometrics of stock price fluctuations. Quarterly Journal of Business and Economics, 32(1), 50-67.

Bernstein, P. L. (2007). Capital ideas evolving. New Jersey: John Wiley & Sons, Inc.

Binder, J. J., & Merges, M. J. (2001). Stock market volatility and economic factors. Review of Quantitative Finance and Accounting, 17(1), 5-26.

Black, A., Fraser, P., & Groenewold, N. (2003). Fundamental UK stock prices as determined by the macroeconomy. Journal of Asset Management, 4(1), 5-9.

Bodie, Z., Kane, A., & Marcus, A. J. (2007). Essentials of investments. New York: McGraw Hill.

Bodurtha, J. N., Cho, D. C., & Senbet, L. W. (1989). Economic forces and the stock market: an international perspective. The Global Finance Journal, 1(1), 21-46.

Chan, L. K. C., Karceski, J., & Lakonishok, J. (1998). The risk and return from factors. Journal of Financial and Quantitative Analysis, 33(2), 159-188.

Chen, N. F. (1991). Financial investment opportunities and the macroeconomy. The Journal of Finance, XLVI(2), 529-554.

Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. Journal of Business, 59(3), 383-403.

Chernov, M., Gallant, A. R., Ghysels, R., & Tauchen, G. (2003). Alternative models for stock price dynamics. Journal of Econometrics, 116(1,2), 225-257.

Connor, G. (1995). The three types of factor models: a comparison of their explanatory power. Financial Analysts Journal, 42-46.

DeLurgio, S. A. (1998). Forecasting principles and applications. New York: McGraw Hill/ Irwin.

Dempsey, M. (2010). The book-to-market equity as a proxy for risk: evidence from Australian. Australian Journal of Management, 35(1), 7-21.

DeStefano, M. (2004). Stock returns and the business cycle. The Financial review, 39, 527-547.

Drew, M. E., Naughton, T., & Veeraragavan, M. (2005). Pricing of Equities in China: Evidence from the Shanghai Stock Exchange. Managerial Finance, 31(12), 46-57.

Drew, M. E., Naughton, T., & Veeraraghavan, M. (2003). Firm size, book-to-market equity and security returns: Evidence from the Shanghai Stock Exchange. Australian Journal of Management, 28(2), 119-139.

Eviews 5 Users Guide. (2004). Irvine CA: Quantitative Micro Software, LLC.

Fabozzi, F. J., Focardi, S. M., & Kolm, P. N. (2006). Financial modeling of the equity market: from CAPM to cointegration. New Jersey: John Wiley & Sons, Inc.

Faff, R., & Chan, H. (1998). A multifactor model of gold industry stock returns: Evidence from the Australian equity market. Applied Financial Economics, 8(1), 21-28.

Fama, E. F. (1990). Stock returns, expected returns, and real economic activities. The Journal of Finance, XLV(4), 1089-1108.

Fama, E., & French, K. (1992). The cross-section of expected stock returns. Journal of Finance, 47, 427-465.

Ferson, W. E., & Harvey, C. R. (1991). Sources of predictability in portfolio returns. Financial Analysts Journal, 47(3), 49-56.

Ferson, W. E., & Harvey, C. R. (1991). The variation of economic risk premiums. The Journal of Political Economy, 99(2), 385-415.

Fifield, S. G. M., Power, D. M., and Sinclair, C. D. (2002). Macroeconomic factors and share returns: an analysis using emerging market data. International Journal of Finance & Economics, 7(1), 51- 62.

Flannery, M. J., & Protopapadakis, A. A. (2002). Macroeconomic factors do influence aggregate stock returns. The Review of Financial Studies, 15(3), 751-782.

Francis, B. B., & Hunter, D. M. (2004). The impact of the euro on risk exposure of the world’s major banking industries. Journal of International Money and Finance, 23(7,8), 1011-1042.

Gangopadhyay, P. (1994). Risk-return seasonality and macroeconomic variables. The Journal of Financial Research, XVII(3), 347-361.

Gerlach, S., & Yiu, M. S. (2005). A dynamic factor model of economic activities in Hong Kong. Pacific Economic Review, 10(2), 279-292.

Greene, W. H. (2008). Econometric analysis (6th ed.). New Jersey: Pearson Prentice Hall.

Gujarati, D. N. (2003). Basic econometrics (4th ed.). New York: McGraw Hill/ Irwin.

He, J., & Ng, L. K. (1994). Economic forces, fundamental variables, and equity returns. The Journal of Business, 67(4), 599.

Hearn, B. (2010). Time varying size and liquidity effects in South Asian equity markets: A study of blue-chip industry stocks. International Review of Financial Analysis, 19(4), 242.

Hearn, B. (2011). Modelling size and liquidity in North African industrial sectors. Emerging Markets Review, 12(1), 21-46.

Hearn, B., & Piesse, J. (2010). Modelling size and illiquidity in West African equity markets. Applied Financial Economics, 20(13), 1011.

Hondroyiannis, G., & Papapetrou, E. (2001). Macroeconomic influences on the stock market. Journal of Economics and Finance, 25(1), 33-49.

Howton, S. W., & Peterson, D. R. (1999). A cross-sectional empirical test of a dual-state multi-factor pricing model. The Financial Review, 34(3), 47-63.

Ilmanen, A. (2003). Stock-bond correlations. The Journal of Fixed Income, 13(2), 55-70.

Javid, A. (2008). Forecasting Performance of Capital Asset Pricing Models in Case of Pakistani Market. The Business Review, Cambridge, 11(2), 290-297.

Kassimatis, K. (2008). Size, Book to Market and Momentum Effects in the Australian Stock Market. Australian Journal of Management, 33(1), 145-159,161-168.

Kavussanos, M. G., Marcoulis, S. N., & Arkoulis, A. G. (2002). Macroeconomic factors and international industry returns. Applied Financial Economics, 12, 923-931.

Kim, M. K., & Wu, C. (1987). Macro-economic factors and stock returns. The Journal of Financial Research, X(2), 87-98.

Koedijk, K. G., & Dijk, M. A. (2004). Global Risk Factors and the Cost of Capital. Financial Analysts Journal, 60(2), 32-38.

Kraft, J. & Kraft, A. (1977). Determinants of common stock prices: a time series analysis. The Journal of Finance, XXXII(2), 417-425.

Kwon, C. S., & Shin, T. S. (1999). Cointegration and causality between macroeconomic variables and stock market returns. Global Finance Journal, 10(1), 71-81.

Kwon, C. S., Shin, T. S., & Bacon, F. W. (1997). The effect of macroeconomic variables on stock market returns in developing markets. Multinational Business Review, 5(2), 63-70.

Maginn, J. L., Tuttle, D. L., Pinto, J. E., & McLeavy, D. W. (Eds). (2007). Managing investment portfolios: a dynamic process (CFA Institute investment series). New Jersey: John Wiley & Sons, Inc.

Mei, J.  (1993). Explaining the cross section of returns via a multi-factor APT model. Journal of Financial and Quantitative Analysis, 28(3), 331.

Mirza, N., & Afzal, A. (2011). Size and Value Premium in International Portfolios: Evidence from 15 European Countries. Finance a Uver, 61(2), 173-190.

Nartea, G. V., Ward, B. D., & Djajadikerta, H. G. (2009). Size, BM, and momentum effects and the robustness of the Fama-French three-factor model :Evidence from New Zealand. International Journal of Managerial Finance, 5(2), 179-200.

Naughton, T., & Veeraraghavan, M. (2005). A Multifactor Model Explanation of the Anomalies in the Cross-Section of Expected Stock Returns: Evidence from Indonesia, Singapore and Taiwan. Finance India, 19(1), 135-157.

Novak, J., & Petr, D. (2010). CAPM Beta, Size, Book-to-Market, and Momentum in Realized Stock Returns. Finance a Uver, 60(5), 447-460.

Patra, T., & Poshakwale, S. (2006). Economic variables and stock market returns: evidences from the Athens stock exchange. Applied Financial Economics, 16, 993-1005.

Patro, D. K., Wald, J. K., & Wu, Y. (2002). The impact of macroeconomic and financial variables on market risk: evidences from international equity returns. European Financial Management, 8(4), 421-447.

Pesaran, M. H., & Timmermann, A. (1995). Predictability of stock returns: robustness and economic significance. The Journal of Finance, L(4), 1201-1228.

Qi, M., & Maddala, G. S. (1999). Economic factors and the stock market. Journal of Forecasting, 18(3), 151-167.

Reilly, F. K., & Brown, K. C. (2003). Investment analysis & portfolio management (7th ed.). Ohio: Thomson, South-Western.

Shukla, R., & Trzcinka, C. (1991). Research on Risk and Return: Can Measures of Risk Explain Anything? Journal of Portfolio Management, 17(3), 15.

Singh, R. (2009). Company Attributes and Stock Returns in India: A Panel Data Analysis. IUP Journal of Applied Finance, 15(2), 46-57.

Stamp, D. (2002). Market prophets: can forecasters predict the financial future? Great Britain: Reuters.

Tsoukalas, D., & Sil, S. (1999). The determinants of stock prices: evidences from the United Kingdom stock market. Management Research News, 22(5), 1-14.

Umstead, D. A. (1977). Forecasting stock market prices. The Journal of Finance, XXXII (2), 427-441.

Walid, E. (2009). New Evidence on Risk Factors, Characteristics and the Cross-Sectional Variation of Japanese Stock Returns. Asia – Pacific Financial Markets, 16(1), 33-50.

Wu, H. (2011). The Value and Size Effect – Are There Firm-Specific-Risks in China’s Domestic Stock Markets? International Journal of Economics and Finance, 3(3), 26-37.

Zweig, M. E. (1997). Winning on Wall Street: how to spot market trends early, which stocks to pick, and when to buy and sell for peak profits and minimum risk. New York: Warner Books, Inc.



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