engleski

Revisiting CAPM model with quantile regression: creating investment strategies on the Zagreb Stock Exchange

This research explores whether conditional CAPM holds at different points of the return distribution by focusing on data from the Zagreb Stock Exchange and quantile regression methodology. There are several reasons for this specification of modelling: quantile regression does not require strong assumptions on return distributions and handles heteroskedasticity of data. Moreover, the CAPM model has not yet been observed by using quantile regression on the Croatian and several similar CEE markets as well. In that way, it can be observed if this methodology is useful for estimating systematic risk on the Croatian stock market conditioned on different quantiles of the return distribution. Weekly data on 5 sector indices, market return on CROBEX and return on Treasury bills (91 days) for the period January 2012 – April 2018 will be collected in order to empirically evaluate the CAPM model via quantile regression. Economic interpretations of results are given as guidance for investors. Moreover, the contribution of this research is given in the simulation part, where several specifications of investment strategies based on estimation results are discussed. Previous literature does not focus on utilizing estimation results as guidance for dynamic investment strategies. Based upon simulations of several strategies, it was shown that quantile regression strategies could be beneficial for more conservative investors. Since this study is one of the few which try to link statistical aspects of estimating finance models with investment strategies, there is hope that this research contributes to the existing literature on the aforementioned matters.

downside beta ; quantile regression models ; stock market ; volatility ; systematic risk

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