Time-Varying Risk Aversion and Forecastability of the US Term Structure of Interest Rates

Elie Bouri (elie.elbouri@lau.edu.lb), Rangan Gupta, Anandamayee Majumdar and Sowmya Subramaniam (sowmya@iiml.ac.in)
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Sowmya Subramaniam: Indian Institute of Management Lucknow, Prabandh Nagar off Sitapur Road, Lucknow, Uttar Pradesh 226013, India

No 202098, Working Papers from University of Pretoria, Department of Economics

Abstract: In this paper, we analyse the forecasting ability of a time-varying metric of daily risk aversion for the entire term structure of interest rates of Treasury securities of the United States (US) as reflected by the three latent factors, level, slope and curvature. Using daily data covering the out-of-sample period 22nd June, 1988 to 3rd September, 2020 (given the in-sample period 30th May, 1986 to 21st June, 1988) within a quantiles-based framework, the results show statistically significant forecasting gains emanating from risk aversion for the tails of the conditional distributions of the level, slope and curvature factors at horizons of one-day, one-week, and one-month-ahead. Interestingly, a conditional mean-based model fails to detect any evidence of out-of-sample predictability. Our findings have important implications for academics, bond investors, and policymakers in their quest to better understand the evolution of future movement in US Treasury securities.

Keywords: Yield Curve Factors; Risk Aversion; Out-of-Sample Forecasts (search for similar items in EconPapers)
JEL-codes: C22 C53 E43 G12 G17 (search for similar items in EconPapers)
Pages: 15 pages
Date: 2020-10
New Economics Papers: this item is included in nep-fmk, nep-for, nep-mac, nep-ore and nep-rmg
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Journal Article: Time-varying risk aversion and forecastability of the US term structure of interest rates (2021)
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