Validita modelu CAPM na akciovém trhu USA

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2014-03
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Mark
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Vysoké učení technické v Brně, Fakulta podnikatelská
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Purpose of the article: The present article is focused on the Capital Asset Pricing Model (CAPM) and its implementation into American Stock Market. It attempts to empirically test the validity of the CAPM to estimate individual stock returns based on historical stock data of selected companies. Security Market Line (SML) was used on the data collected from a wide range of investment horizons (periods of 1, 3, 5, and 10 years). The results show that the coefficient beta is incapable of explaining returns of single assets and the relation between systematic risk and expected return is weak. Methodology/methods: Empirical analysis is make on the time period 2001–2011. Selected stocks has to by trade on AMEX, NASDAQ or NYSE minimal since year 2000. Concrete 10 stock were selected with using branch analysis and were divide in two groups (a) cyclic stocks and (b) other (neutral-anticyclic) stocks. By every stock was watch the closing price which was adjusted of dividends and contain splits. Scientific aim: The aim of this article is by using the model of Security Market Line (SML) verify the validity of CAPM model by assets pricing. According to Alfa coefficient is determine how much differentiate is the yield set by CAPM model and the market yield in selected investment horizons. Findings: Selected length of investment horizon has important effect on the results. Worst results were found by the shortest length (1 year). With the growing of the investment horizon are the results better, but the Alfa coefficients is still to higher and the model inaccurate. Selected stocks with lower beta coefficient has higher yield that yield set by the CAPM model. Conclusions: For explanation of the yields by selected stocks we can´t recommend use the CAPM model nor on the biggest stock market, on US stock market. The relation between beta coefficient and stock yield is very weak. But other site CAPM model in the shape of SML curve can be recommended by using as discount factor.
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© Vysoké učení technické v Brně, Fakulta podnikatelská
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