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Time-Varying Risk Aversion and the Predictability of Bond Premia

Author

Listed:
  • Oguzhan Cepni

    (Central Bank of the Republic of Turkey, Anafartalar Mah. Istiklal Cad. No:10 06050, Ankara, Turkey)

  • Riza Demirer

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

  • Rangan Gupta

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

  • Christian Pierdzioch

    (Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O.B.700822, 22008 Hamburg, Germany)

Abstract

We show that time-varying risk aversion captures significant predictive information over excess returns on U.S. government bonds even after controlling for a large number of financial and macro factors. Including risk aversion improves the predictive accuracy at all horizons (one- to twelve-months ahead) for shorter maturity bonds and at shorter forecast horizons (one- to three-months ahead) for longer maturity bonds. Given the role of Treasury securities in economic forecasting models and portfolio allocation decisions, our findings have significant implications for investors, policy makers and researchers interested in accurately forecasting return dynamics for these assets.

Suggested Citation

  • Oguzhan Cepni & Riza Demirer & Rangan Gupta & Christian Pierdzioch, 2019. "Time-Varying Risk Aversion and the Predictability of Bond Premia," Working Papers 201906, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201906
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    References listed on IDEAS

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    Cited by:

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    2. Bouri, Elie & Gupta, Rangan & Majumdar, Anandamayee & Subramaniam, Sowmya, 2021. "Time-varying risk aversion and forecastability of the US term structure of interest rates," Finance Research Letters, Elsevier, vol. 42(C).
    3. Balcilar, Mehmet & Gupta, Rangan & Wang, Shixuan & Wohar, Mark E., 2020. "Oil price uncertainty and movements in the US government bond risk premia," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    4. Dai, Zhifeng & Kang, Jie, 2021. "Bond yield and crude oil prices predictability," Energy Economics, Elsevier, vol. 97(C).
    5. Oguzhan Cepni & Rangan Gupta & I. Ethem Güney & M. Yilmaz, 2020. "Forecasting local currency bond risk premia of emerging markets: The role of cross‐country macrofinancial linkages," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 966-985, September.
    6. Bouri, Elie & Demirer, Riza & Gupta, Rangan & Wohar, Mark E., 2021. "Gold, platinum and the predictability of bond risk premia," Finance Research Letters, Elsevier, vol. 38(C).
    7. Çepni, Oğuzhan & Guney, I. Ethem & Gupta, Rangan & Wohar, Mark E., 2020. "The role of an aligned investor sentiment index in predicting bond risk premia of the U.S," Journal of Financial Markets, Elsevier, vol. 51(C).
    8. Wu, Xinyu & Xie, Haibin & Zhang, Huanming, 2022. "Time-varying risk aversion and renminbi exchange rate volatility: Evidence from CARR-MIDAS model," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).

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    More about this item

    Keywords

    Bond premia; Predictability; Risk aversion; Out-of-sample forecasts;
    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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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