Bond Return Predictability: Economic Value and Links to the Macroeconomy

Abstract

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 volatility dynamics and unspanned macro factors. A three-factor model comprising the Fama and Bliss (1987) forward spread, the Cochrane and Piazzesi (2005) combination of forward rates and the Ludvigson and Ng (2009) macro factor generates notable gains in out-of-sample forecast accuracy compared with a model based on the expectations hypothesis. Such gains in predictive accuracy translate into higher risk-adjusted portfolio returns after accounting for estimation error and model uncertainty. Consistent with models featuring unspanned macro factors, our forecasts of future bond excess returns are strongly negatively correlated with survey forecasts of short rates.

Credit Spreads, Business Conditions, and Expected Corporate Bond Returns

“…(Welch and Goyal 2008) examine a long list of predictors from the literature and find that they cannot provide better stock return forecasts than a simple forecast based on the historical mean return. On the other hand, a number of studies have shown that returns are predictable (see, for example, Rapach et al 2010;Thornton and Valente 2012;Gargano et al 2019). The vast literature has focused on the predictability of stock and Treasury bond returns.…”

“…v 1,k −v 0,k is the difference in the certainty equivalent returns for the two different portfolio choices, which gives a direct measure of economic significance based on utility gains. (Thornton and Valente 2012;Gargano et al 2019;Sarno et al 2016) suggest a joint asset allocation approach when studying the predictability of Treasury market returns. Using this approach, we examine the robustness of results by testing economic significance of multiple risky assets jointly.…”

Challenging the spanning hypothesis at short horizons: Evidence from Norway

“…is the one-period N-year yield change at time t + 1, c is a constant, and t + 1 is the error term. Equation 8 implies that the benchmark forecast depends on the historical average of yield changes up to period t. 16 The same method is employed by Gargano, Pettenuzzo, and Timmermann (2019) for Bayesian return prediction models. 10-year yields with today's short-term, medium-term, and long-term interdealer order flows, respectively.…”

Time-varying risk aversion and the predictability of bond premia

“…Given the significance of Treasury securities both in economic forecasting models as well as portfolio allocation decisions, a massive and burgeoning literature exists on forecasting excess returns of U.S. government bonds (e.g. Cochrane and Piazzesi 2005;Ludvigson andNg 2009, 2011;Gargano et al 2017;Ghysels et al 2018). In general, the empirical evidence highlights the role of macro and financial factors (often extracted from large data sets) in predicting bond premia, over and above the so-called CP factor of Cochrane and Piazzesi (2005), constructed as a linear combination of forward rates.…”