Portfolio Optimization Efficiency Test Considering Data Snooping Bias

Authors

  • Aleš Kresta VSB – Technical University of Ostrava, Faculty of Economics, Czech Republic
  • Anlan Wang VSB – Technical University of Ostrava, Faculty of Economics, Czech Republic

Keywords:

data snooping bias, financial crisis, hypothesis test, minimum-risk portfolio, portfolio optimization

Abstract

Background: In the portfolio optimization area, most of the research is focused on insample portfolio optimization. One may ask a rational question of what the efficiency of the portfolio optimization strategy is and how to measure it. Objectives: The objective of the paper is to propose the approach to measuring the efficiency of the portfolio strategy based on the hypothesis inference methodology and considering a possible data snooping bias. The proposed approach is demonstrated on the Markowitz minimum variance model and the fuzzy probabilities minimum variance model. Methods/Approach: The proposed approach is based on a statistical test. The null hypothesis is that the analysed portfolio optimization strategy creates a portfolio randomly, while the alternative hypothesis is that an optimized portfolio is created in such a way that the risk of the portfolio is lowered. Results: It is found out that the analysed strategies indeed lower the risk of the portfolio during the market’s decline in the global financial crisis and in 94% of the time in the 2009-2019 period. Conclusions: The analysed strategies lower the risk of the portfolio in the out-of-sample period.

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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Published

2020-09-30