A smooth non-parametric estimation framework for safety-first portfolio optimization

Haixiang Yao, Yong Li and Karen Benson

Quantitative Finance, 2015, vol. 15, issue 11, 1865-1884

Abstract: In this paper, we adopt a smooth non-parametric estimation to explore the safety-first portfolio optimization problem. We obtain a non-parametric estimation calculation formula for loss (truncated) probability using the kernel estimator of the portfolio returns' cumulative distribution function, and embed it into two types of safety-first portfolio selection models. We numerically and empirically test our non-parametric method to demonstrate its accuracy and efficiency. Cross-validation results show that our non-parametric kernel estimation method outperforms the empirical distribution method. As an empirical application, we simulate optimal portfolios and display return-risk characteristics using China National Social Security Fund strategic stocks and Shanghai Stock Exchange 50 Index components.

Date: 2015
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Citations: View citations in EconPapers (4)

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DOI: 10.1080/14697688.2014.971857

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