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Measuring the Time Series of High-Frequency Risk Attitude from Volatility Risk Premium: The Case of Emerging Markets

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  • Chao Zhu
  • Yuwei Zhang
  • Zhen Yi

Abstract

This study establishes a state-space model and measures the time-varying relative risk aversion using the volatility risk premium from stock market data. This model can measure the time series of high-frequency risk aversion. Based on the stock market data of Brazil, Russia, India, and China, the measurement results of this study show that during the period between January 1, 2009, and December 31, 2020, the mean values of the corresponding implied risk aversion coefficients are 5.6543, 5.7561, 7.5345, and 6.3675, respectively. Our method can solve the mismatch between low-frequency risk aversion and high-frequency market data.

Suggested Citation

  • Chao Zhu & Yuwei Zhang & Zhen Yi, 2022. "Measuring the Time Series of High-Frequency Risk Attitude from Volatility Risk Premium: The Case of Emerging Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 58(8), pages 2407-2422, June.
    • Handle: RePEc:mes:emfitr:v:58:y:2022:i:8:p:2407-2422
    DOI: 10.1080/1540496X.2021.1990752
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