Forecasting yield spreads under crisis-induced multiple breakpoints

Abstract

We perform a real time, out-of-sample forecasting exercise concerning seven fixed income spreads sampled at weekly frequency over a sample that spans the US financial crisis. We compare the predictive accuracy obtained from univariate, mean-reverting models of spreads that ignore the evidence of structural breaks in correspondence of the crisis, with models that take estimated and exogenous break dates into account. We also benchmark these predictive performances to standard random walk models. We find little or no evidence that accounts for breaks in the conditional mean process of yield spreads that would have improved real time predictive accuracy. We speculate on the reasons of such failure and we find informal indications that poor estimation of the breakpoint and the higher variance characterizing the post-break period is responsible for our results.