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Time-Varying Risk Aversion and Realized Gold Volatility

Author

Listed:
  • Riza Demirer

    () (Department of Economics and Finance, Southern Illinois University Edwardsville, Edwardsville, USA)

  • Rangan Gupta

    () (Department of Economics, University of Pretoria, Pretoria, South Africa)

  • Christian Pierdzioch

    () (Department of Economics, Helmut Schmidt University, Holstenhofweg 85, Hamburg, Germany)

Abstract

We study the incremental in- and out-of-sample predictive value of time-varying risk aversion for realized volatility of gold-price returns via extended heterogeneous autoregressive realized volatility (HAR-RV) models. Our findings suggest that time varying risk aversion possesses predictive value for gold volatility both in- and out-of-sample. The predictive power of risk aversion is robust to the inclusion of realized higher-moments, jumps, gold returns, leverage effect as well as the aggregate market volatility in the forecasting model. Interestingly, risk aversion is found to absorb in sample the predictive power of stock-market volatility at a short forecasting horizon, while out-of-sample results show that risk aversion adds to predictive value at a medium and long forecast horizon. Additional tests suggest that the short-run (long-run) out-of-sample predictive value of risk aversion is beneficial for investors who are more concerned about over-predicting (under-predicting) gold market volatility. Overall, our findings show that time-varying risk aversion captures information useful for predicting (bad, good) realized volatility not already contained in the other predictors, and allows more accurate out-of-sample forecasts to be computed at a medium and long forecast horizon.

Suggested Citation

  • Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2018. "Time-Varying Risk Aversion and Realized Gold Volatility," Working Papers 201881, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201881
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    Cited by:

    1. Asai, Manabu & Gupta, Rangan & McAleer, Michael, 2020. "Forecasting volatility and co-volatility of crude oil and gold futures: Effects of leverage, jumps, spillovers, and geopolitical risks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 933-948.
    2. Manabu Asai & Rangan Gupta & Michael McAleer, 2019. "The Impact of Jumps and Leverage in Forecasting the Co-Volatility of Oil and Gold Futures," Energies, MDPI, Open Access Journal, vol. 12(17), pages 1-17, September.
    3. Riza Demirer & Rangan Gupta & Hossein Hassani & Xu Huang, 2020. "Time-Varying Risk Aversion and the Profitability of Carry Trades: Evidence from the Cross-Quantilogram," Economies, MDPI, Open Access Journal, vol. 8(1), pages 1-12, March.
    4. Afees A. Salisu & Rangan Gupta & Elie Bouri & Qiang Ji, 2020. "The Role of Global Economic Conditions in Forecasting Gold Market Volatility: Evidence from a GARCH-MIDAS Approach," Working Papers 202043, University of Pretoria, Department of Economics.
    5. Matteo Bonato & Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2020. "A Note on Investor Happiness and the Predictability of Realized Volatility of Gold," Working Papers 202004, University of Pretoria, Department of Economics.

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    Keywords

    Gold-price returns; Realized volatility; Forecasting;

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