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Time-Varying Risk Aversion and the Profitability of Carry Trades: Evidence from the Cross-Quantilogram

Author

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  • Riza Demirer

    (Department of Economics & Finance, Southern Illinois University Edwardsville, Edwardsville, IL 62026-1102, USA)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria 0002, South Africa)

  • Hossein Hassani

    (Research Institute of Energy Management and Planning (RIEMP), University of Tehran, Tehran 1417466191, Iran)

  • Xu Huang

    (Faculty of Business and Law, De Montfort University, Leicester LE1 9BH, UK)

Abstract

This paper examines the predictive power of time-varying risk aversion over payoffs to the carry trade strategy via the cross-quantilogram methodology. Our analysis yields significant evidence of directional predictability from risk aversion to daily carry trade returns tracked by the Deutsche Bank G10 Currency Future Harvest Total Return Index. The predictive power of risk aversion is found to be stronger during periods of moderate to high risk aversion and largely concentrated on extreme fluctuations in carry trade returns. While large crashes in carry trade returns are associated with significant rises in investors’ risk aversion, we also found that booms in carry trade returns can be predicted at high quantiles of risk aversion. The results highlight the predictive role of extreme investor sentiment in currency markets and regime specific patterns in carry trade returns that can be captured via quantile-based predictive models.

Suggested Citation

  • 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, vol. 8(1), pages 1-12, March.
  • Handle: RePEc:gam:jecomi:v:8:y:2020:i:1:p:18-:d:329010
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    References listed on IDEAS

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    2. Gordon Schulze, 2021. "Carry Trade Returns and Segmented Risk Pricing," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 49(1), pages 23-40, March.

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    More about this item

    Keywords

    quantile; correlogram; dependence; predictability;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F31 - International Economics - - International Finance - - - Foreign Exchange

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