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Multiscale optimal portfolios using CAPM fractal regression: estimation for emerging stock markets

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  • Oussama Tilfani
  • Paulo Ferreira
  • My Youssef El Boukfaoui

Abstract

Based on the mean-variance portfolio model and on the capital asset pricing model, we propose the construction of multiscale optimal portfolios, for four emerging stock markets: China, the Czech Republic, Hungary and Russia. We compare the results with the German market, in order to understand possible differences. We use fractal regressions based on detrended cross-correlation analysis, allowing us to study portfolios for different time scales. This feature helps us to identify whether investors are homogeneous or heterogeneous in their expectations and if they have common or different investment horizons. Results show that for most shares, a unique CAPM parameter explains asset pricing well. However, for some shares, behaviour is different between short and long run scales, consistent with the fractal market hypothesis. Moreover, Chinese and Czech markets are closer to what happens in the German market, while Russian and Hungarian investors behave differently, with investors preferring risk-free assets.

Suggested Citation

  • Oussama Tilfani & Paulo Ferreira & My Youssef El Boukfaoui, 2020. "Multiscale optimal portfolios using CAPM fractal regression: estimation for emerging stock markets," Post-Communist Economies, Taylor & Francis Journals, vol. 32(1), pages 77-112, January.
    • Handle: RePEc:taf:pocoec:v:32:y:2020:i:1:p:77-112
    DOI: 10.1080/14631377.2019.1640983
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    Cited by:

    1. Barreto, Ikaro Daniel de Carvalho & Dore, Luiz Henrique & Stosic, Tatijana & Stosic, Borko D., 2021. "Extending DFA-based multiple linear regression inference: Application to acoustic impedance models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    2. Hu, Debao & Li, Xin & Xiang, George & Zhou, Qiyao, 2023. "Asset pricing models in the presence of higher moments: Theory and evidence from the U.S. and China stock market," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).

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