DP10104 Bond Return Predictability: Economic Value and Links to the Macroeconomy
|Author(s):||Antonio Gargano, Davide Pettenuzzo, Allan Timmermann|
|Publication Date:||August 2014|
|Keyword(s):||Bayesian estimation, bond returns, model uncertainty, stochastic volatility, time-varying parameters|
|JEL(s):||G11, G12, G17|
|Programme Areas:||Financial Economics|
|Link to this Page:||cepr.org/active/publications/discussion_papers/dp.php?dpno=10104|
Studies of bond return predictability find a puzzling disparity between strong statistical evidence of return predictability and the failure to convert return forecasts into economic gains. We show that resolving this puzzle requires accounting for important features of bond return models such as time varying parameters and volatility dynamics. A three-factor model comprising the Fama-Bliss (1987) forward spread, the Cochrane-Piazzesi (2005) combination of forward rates and the Ludvigson-Ng (2009) macro factor generates notable gains in out-of-sample forecast accuracy compared with a model based on the expectations hypothesis. Importantly, we find that such gains in predictive accuracy translate into higher risk-adjusted portfolio returns after accounting for estimation error and model uncertainty, as evidenced by the performance of model combinations. Finally, we find that bond excess returns are predicted to be significantly higher during periods with high inflation uncertainty and low economic growth and that the degree of predictability rises during recessions.