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Factor portfolio and target volatility management: An analysis of portfolio performance in the U.S. and China

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  • Xiong, Haifang
  • Yang, Gaofei
  • Wang, Zhiqiang

Abstract

Based on factor portfolios, we analyze the crash risk of factors in the Chinese stock market and compare them with those in the U.S. stock market. We construct three target volatility strategies to analyze which strategy can significantly improve the returns and Sharpe ratios of factor portfolios. We find that the dynamic target volatility strategy based on factor volatility can improve the performance of most factor portfolios in the U.S. stock market. In the Chinese A-share market, market realized volatility can predict the return of most factor portfolios. The dynamic stop strategy that takes the realized volatility of the market as the target volatility, can significantly improve performance of strategy. This paper complements evidence that dynamic target volatility strategy is the better method to manage crash risk and market realized volatility is more important in China.

Suggested Citation

  • Xiong, Haifang & Yang, Gaofei & Wang, Zhiqiang, 2022. "Factor portfolio and target volatility management: An analysis of portfolio performance in the U.S. and China," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 493-517.
    • Handle: RePEc:eee:reveco:v:79:y:2022:i:c:p:493-517
    DOI: 10.1016/j.iref.2022.02.011
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    References listed on IDEAS

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    Cited by:

    1. Brahmana, Rayenda Khresna, 2022. "Do Machine Learning Approaches Have the Same Accuracy in Forecasting Cryptocurrencies Volatilities?," MPRA Paper 119598, University Library of Munich, Germany.

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    More about this item

    Keywords

    Crash risk; Target volatility; Realized volatility; Performance analysis;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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