Asset selection based on high frequency Sharpe ratio and robust correlation coefficient

doi:10.7523/j.ucas.2022.039

Abstract

Abstract: High frequency Sharpe ratio, a measure of return and risk, is commonly used in current portfolio construction method since it can avoid covariance matrix in high dimensional analysis. The newly proposed D-SEV measures the correlation between stock's return and high frequency Sharpe ratio index to further construct portfolio. However, there are some problems with the measure used in D-SEV, such as its lack of robustness and slow computational speed. In this paper, we propose to use a new correlation coefficient proposed by Sourav Chatterjee instead. The new correlation coefficient guarantee robustness, specifically it can reduce the impact of abnormal data on correlation, such as significant events that have a large impact on the asset prices. It is also extremely fast in its calculations. Extensive simulation demonstrate that new correlation coefficient outperforms D-SEV and other traditional methods in several different models. Actual Shanghai Securities Exchange (SSE) and Shenzhen Securities Exchange (SZSE) stock market data for 2019 and 2020 also show that the assets selected by new correlation coefficient earns 8% more excess annualized return than D-SEV, while it also owns a higher Sharpe ratio.

Key words: portfolio, high frequency Sharpe ratio, robust correlation coefficient

CLC Number:

ZHANG Shanhua, ZHANG Sanguo. Asset selection based on high frequency Sharpe ratio and robust correlation coefficient[J]. Journal of University of Chinese Academy of Sciences, 2023, 40(6): 834-842.

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