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Investment horizon in the CAPM: A comparison of a wavelet-based decomposition and the fractal regression
Spousta, Radek ; Krištoufek, Ladislav (advisor) ; Vácha, Lukáš (referee)
This thesis study two promising methods used to define the multiscale CAPM - the wavelet-based decomposition and the fractal regression. Their estimates, obtained on monthly excess return on ten portfolios formed on beta in the US market, are compared in the period from November 2000 to October 2020 and, subsequently, in the period from November 1965 to October 2020. In the first period, the multiscale beta is not significantly different from the original single-scale beta for most of the portfolios. Contrary, both methods uncover significant multiscale behavior of the beta in the second period. Specifically, the high-beta portfolios have higher multiscale beta at longer investment horizons, mainly at wavelet scale 3 and scales 12-24 of the fractal regression. Overall, both methods deliver consistent results, and seem suitable for extending the CAPM with an investment horizon. JEL Classification Keywords G12, C20 CAPM, asset pricing, multiscale analysis, wavelets, fractal regression Title Investment horizon in the CAPM: A comparison of a wavelet-based decomposition and the fractal regression
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Fama-French Model: Multiscale Portfolio Analysis
Spousta, Radek ; Kraicová, Lucie (advisor) ; Teplý, Petr (referee)
This thesis studies the empirical relationship between excess asset returns and the Fama−French risk factors at various scales using a combination of the Fama−French model and wavelet-based methods. We re-examine previously published results obtained for six portfolios formed on size and book-to-market ratio in the U.S. market, and focus on the influence of different scales on the original results. We conclude that the most the total variance of the risk factors and excess portfolio returns is concentrated at scale 1 and 2, which corresponds to periodicities of 2-4 months and 4-8 months, respectively. Next, we observe significant variation in estimated parameters across different scales. Furthermore, some of the Fama−French risk factors are strongly correlated at scale 2, 3 and 4, which is unobservable in standard correlation matrix. Overall, the multiscale approach seems beneficial for analysis of the Fama−French three-factor model as it reveals information that remains hidden to traditional methods.
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