Testing the Validity of the Capital Asset Pricing Model: Empirical Evidence from the Singapore Exchange

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School of Business | Bachelor's thesis
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Date

2019

Department

Major/Subject

Mcode

Degree programme

(Mikkeli) Bachelor’s Program in International Business

Language

en

Pages

53 + 9

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Abstract

Objectives This paper attempts to address the question regarding the applicability of the CAPM in the context of the Singaporean stock market during the 2007-2012 period. By examining the strength of the relationship between systematic risk as measured by Beta and the actual rate of return, the research can answer whether the CAPM performs reliably in the sampled stock market. Summary The research collects historical data of 29 most liquid and eligible stocks listed on the Singapore Exchange (SGX) to form the sample and the Straits Time Index (STI) is chosen as the market benchmark index. The thesis employs the simple linear regression method to test for linearity between Beta values and the actual rate of return on various time-frequencies daily, weekly and monthly for the 2007-2018 period. Moreover, portfolios are constructed by combining 5 stocks with highest Betas using data of the 2007-2012 period. Then, in the subsequent 2012-2018 period, the portfolios’ return rates are regressed on the return rate of the STI to examine whether stocks with higher systematic risk outperform the return of the market. Conclusions The results collected from the regression tests shows that Beta and actual rate of return do not have a significant positive linear relation on weekly and monthly basis while such relation is found on the daily basis. However, the portfolios of stocks with highest Betas do not beat the market return on all 3 time-frequencies daily, weekly and monthly. Thus, the paper concluded that investors bearing greater systematic risk, which is measured by Beta of past data, are not compensated with higher return in the future.

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Thesis advisor

Stepanov, Roman

Keywords

Capital Asset Pricing Model, CAPM, Singapore stock market, simple linear regression, systematic risk

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