The average capital growth rate across firms declines sharply during a recession, and recovers only slowly. We provide a micro-founded explanation for this and several new stylized facts of investment asymmetry. Our investment model features various degrees of reversibility, cyclical macroeconomic shocks, and uncertainty about the state of the economy. Model simulations replicate strikingly different empirical patterns of capital growth rates at the aggregate and firm levels, featuring no slope asymmetry and a positive level asymmetry at the firm level, negative slope and level asymmetries at the aggregate level, and a positive relation between the industry-level slope asymmetry and asset illiquidity.

We study the implications of predictability on the optimal asset allocation of ambiguity-averse long-term investors and analyze the term structure of the multivariate risk–return trade-off considering parameter uncertainty. We calibrate the model to real returns of U.S. stocks, long-term bonds, cash, real estate, and gold using the term spread and the dividend–price ratio as additional predictive variables, and we show that over long horizons, the optimal asset allocation is significantly influenced by the covariance structure induced by estimation errors. The ambiguity-averse long-term investor optimally tilts his or her portfolio toward a seemingly inefficient portfolio, which shows maximum robustness against estimation errors.

We evaluate predictive regressions that explicitly consider the time-variation of coefficients in a comprehensive Bayesian framework. For monthly returns of the S&P 500 index, we demonstrate statistical as well as economic evidence of out-of-sample predictability: relative to an investor using the historic mean, an investor using our methodology could have earned consistently positive utility gains (between 1.8% and 5.8% per year over different time periods). We also find that predictive models with constant coefficients are dominated by models with time-varying coefficients. Finally, we show a strong link between out-of-sample predictability and the business cycle.

This paper shows that short debt maturities commit equityholders to leverage reductions when refinancing expiring debt in low-profitability states. However, shorter maturities lead to higher transaction costs since larger amounts of expiring debt need to be refinanced. We show that this trade-off between higher expected transaction costs against the commitment to reduce leverage in low-profitability states motivates an optimal maturity structure of corporate debt. Since firms with high costs of financial distress and risky cash flows benefit most from committing to leverage reductions, they have a stronger motive to issue short-term debt. Evidence supports the model’s predictions.