Asset Selection Model Based on the VaR Adjusted High-Frequency Sharp Index

Xikun SU, Liming CHEN


This paper uses high frequency intraday data to construct the VaR adjusted high-frequency sharp index model as an efficient method of asset selection and portfolio strategy in optimal portfolio problem. Both asset selection and perfect weight allocation are key processing. This paper constructs the VaR adjusted high-frequency sharp index to choose stocks, and uses several portfolio strategies to allocate stock weight. Through market data of shanghai stock exchange as out-of-sample empirical, we find that VaR adjusted high-frequency sharp index model can have a better result than high-frequency sharp index model and momentum stock choice model, and portfolio strategies based on the VaR adjusted high-frequency sharp index model have a higher risky return.

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