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Can Mixed-Frequency Data Improve the Higher-Order Moments Portfolio Performance?

Author

Listed:
  • Shuang Zhao
  • Wanbo Lu
  • Muhammad Wajid Raza
  • Dong Yang

Abstract

In the presence of non-normally distributed asset returns, an optimal portfolio selection should consider higher-order (co-)moments when no sampling errors exist. However, the curse of dimensionality has already been a serious concern in mean-variance analyses; higher-order (co-)moments also face the same dilemma. This study uses mixed-frequency (MF) data under the assumption that stock returns are generated by a mixed-data sampling (MIDAS) regression model, which shows to provide well-improved estimates for the covariance, co-skewness, and co-kurtosis matrices for higher dimension. We discover that the new, improved estimates used in higher-order (co-)moment portfolio selections can dominate the other existing structured estimates from an out-of-sample perspective in most instances.

Suggested Citation

  • Shuang Zhao & Wanbo Lu & Muhammad Wajid Raza & Dong Yang, 2021. "Can Mixed-Frequency Data Improve the Higher-Order Moments Portfolio Performance?," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(15), pages 4473-4493, December.
    • Handle: RePEc:mes:emfitr:v:57:y:2021:i:15:p:4473-4493
    DOI: 10.1080/1540496X.2020.1785862
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    Cited by:

    1. Jinxin Cui & Aktham Maghyereh, 2022. "Time–frequency co-movement and risk connectedness among cryptocurrencies: new evidence from the higher-order moments before and during the COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-56, December.
    2. Cui, Jinxin & Maghyereh, Aktham, 2023. "Time-frequency dependence and connectedness among global oil markets: Fresh evidence from higher-order moment perspective," Journal of Commodity Markets, Elsevier, vol. 30(C).
    3. Cui, Jinxin & Maghyereh, Aktham, 2023. "Higher-order moment risk connectedness and optimal investment strategies between international oil and commodity futures markets: Insights from the COVID-19 pandemic and Russia-Ukraine conflict," International Review of Financial Analysis, Elsevier, vol. 86(C).

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