Working Paper

No-Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates

Abstract: We derive a Bayesian prior from a no-arbitrage affine term structure model and use it to estimate the coefficients of a vector autoregression of a panel of government bond yields, specifying a common time-varying volatility for the disturbances. Results based on US data show that this method improves the precision of both point and density forecasts of the term structure of government bond yields, compared to a fully fledged term structure model with time-varying volatility and to a no-change random walk forecast. Further analysis reveals that the approach might work better than an exact term structure model because it relaxes the requirements that yields obey a strict factor structure and that the factors follow a Markov process. Instead, the cross-equation no-arbitrage restrictions on the factor loadings play a marginal role in producing forecasting gains.

Keywords: Term structure; volatility; density forecasting; no arbitrage;

JEL Classification: C32; C53; E43; E47; G12;

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Bibliographic Information

Provider: Federal Reserve Bank of Cleveland

Part of Series: Working Papers

Publication Date: 2020-09-22

Number: 202027