The term structure of interest rates as predictor of stock market volatility

Anastasios Megaritis, Alexandros Kontonikas, Nikolaos Vlastakis and Athanasios Triantafyllou ()
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Anastasios Megaritis: HUBS - Hull University Business School - University of Hull [United Kingdom]
Alexandros Kontonikas: Essex Business School - University of Essex
Nikolaos Vlastakis: UEA - University of East Anglia [Norwich]
Athanasios Triantafyllou: LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - ULCO - Université du Littoral Côte d'Opale - Université de Lille - CNRS - Centre National de la Recherche Scientifique

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Abstract: We examine the forecasting power of the volatility of the slope of the US Treasury yield curve on US stock market volatility. Consistent with theoretical asset pricing models, we find that the volatility of the slope of the term structure of interest rates has significant forecasting power on stock market volatility for forecasting horizon ranging from 1 up to 12 months. Moreover, the term structure volatility has significant forecasting power when used for volatility predictions of the intra‐day returns of S&P500 constituents, with the predictive power being higher for stocks belonging to the telecommunications and financial sector. Our forecasting models show that the forecasting power of yield curve volatility is higher to and absorbs that of Economic Policy Uncertainty and Monetary Policy Uncertainty, showing that the main channel through which the yield curve volatility affects the stock market is not only related with uncertainty about monetary policy actions or policy rates, but also with uncertainty regarding the future cash flows and dividend payments of US equities. Lastly, we show that the forecasting power of term structure volatility significantly increases during the post‐2007 Great recession period which coincides with the Fed adopting unconventional monetary policies to stimulate the economy.

Date: 2024-08-16
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Published in International Journal of Finance and Economics, 2024, 30 (3), pp.3212-3229. ⟨10.1002/ijfe.3029⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05376728

DOI: 10.1002/ijfe.3029

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