No-Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates
Todd Clark and
No 202027, Working Papers from Federal Reserve Bank of Cleveland
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 (search for similar items in EconPapers)
JEL-codes: C32 C53 E43 E47 G12 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-mac and nep-ore
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https://doi.org/10.26509/frbc-wp-202027 Full Text (text/html)
Working Paper: No Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedcwq:88748
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