Erasmus university rotterdam

CONCLUSION

This paper has studied the relatively understudied financial markets of Egypt, Israel, Morocco and Turkey within the context of the Capital Asset Pricing Model. The countries analyzed in this study are emerging markets which have different characteristic compared to established financial markets.

The weekly stock returns were investigated by testing different versions of the CAPM, namely the Global CAPM, the Three Moment CAPM, the Four Moment CAPM and the local CAPM. Moreover, the models were tested under differing financial conditions. The study used weekly return from 516 companies listed on the CASE, ISE, TASE, CSE from January 2001 to September 2009.

The main question in this article was whether the CAPM is applicable in emerging markets, and if so, which model performs best. The CAPM was expected to be applicable in emerging markets and a linear relationship between the expected return on a security and its risk was expected. The betas values that were found show mixed evidence. Some values were positive which indicates that there exists a positive risk return relationship in the emerging markets. However, negative beta values were also found. This would indicate that higher risk is associated with lower returns. In addition, higher risk was expected to be associated with higher expected return and risk aversion. The results do not support the hypothesis that there exists a positive risk return relationship in the emerging markets. The findings in this article are not supportive of the theory’s basic hypothesis that higher risk is associated with a higher level of return, this is in line with findings of Michalidis, Tsopogluo, Papanastasiou, and Mariola, (2006) who examined the validity of the CAPM for the Greek stock market. Since higher risk is not always associated with higher returns, international investors should be cautious when investing in emerging markets. Nevertheless, since correlations between the emerging markets and the world market are low, emerging markets possess interesting diversification benefits. However, during times of financial crisis the correlations increase. The CAPM’s prediction for the intercept is that it should equal zero. The findings of this study do not clearly reject the above hypothesis. The CAPM states that no other measure besides beta can explain the cross-section of returns, however in light of previous research multifactor models were expected to add information. The findings in this study are mixed and do not clearly support multifactor models, so in this light the CAPM cannot be indisputably rejected.

The results of the analysis conducted on the emerging market stock exchanges do not appear to clearly reject the CAPM. However, this does not mean that the data support the CAPM. The emerging equity markets returns used in this study are not normally distributed in most time periods. Bekaert et al. (1998) state that when faced with non-normal returns, the mean-variance framework brakes down.

No straightforward answer can be given on the question which model performs bets. The model that seems to perform best, depends on which country and which time period is considered. The CAPM models do not perform well in explaining emerging stock markets returns. Interestingly the CAPM performs better during times of financial crisis, in particular the Local CAPM. However, it must be noted that the data period during the crisis is short. In line with Erb, Harvey and Viskanta (1996) the evidence suggests that the CAPM shows some merit in emerging markets, but caution is warranted. The main difficulty with the CAPM is finding the right proxies for the risk-free rate and the market, this is even more difficult when investigating emerging markets. The availability of data makes investigation of these markets a difficult endeavor. Evidence showed that Size and Book to Market data help explain the cross-section of returns, however for emerging markets the data is often not available or incomplete. As a result the findings of Fama and French (1973) could not be replicated in this study. Moreover, the value of beta depends on the length of the time series taken. In addition beta changes over time. The results confirm that beta changes over time and depends on the length of the time series. Depending on which time period is considered beta is better able to explain returns. Furthermore, the ability to explain stock returns also depends on which model is chosen. It is difficult to determine which time period should be considered when estimating beta, the differences of which model to choose only add to the complexity.

This study aimed to shed some light on the applicability of the CAPM in emerging markets, nevertheless future research is needed. Since data on emerging markets is becoming more readily available and reliable, future research should be better able to address the questions posed in this study on the applicability of the CAPM in emerging markets.

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