Macroeconomic Risks and Asset Pricing: Evidence from a Dynamic Stochastic General Equilibrium Model

We study the relation between macroeconomic fundamentals and asset pricing through the lens of a state of the art dynamic stochastic general equilibrium (DSGE) model considered in Christiano, Trabandt and Walentin (2011). We provide a full-information Bayesian estimation of the model using macro variables and extract three fundamental shocks to the economy through the model: neutral technology (NT ) shock, investment-specific technological (IST ) shock, and monetary policy (MP ) shock. While it has been shown that the DSGE model matches a wide range of macroeconomic variables well, we are the first to empirically examine the asset pricing implication of the model. The three shocks explains 49% of the cross-sectional return variations among 10 size, 10 book-to-market, and 10 asset growth portfolios and the pricing error is statically indifferent from zero. The risk premiums associated with IST , MP , and NT shocks are 1.35%, −0.35%, and 0.12% per quarter, respectively, with the first two statistically significant at 1% level and the third one at 10% level. Moreover, the three shocks have significant and robust predictive power of the returns of a wide range of financial assets, which include stocks, long-term corporate and government bonds. Compared to some well-known predictors in the literature, such as cay of Lettau and Ludvigson (2001) and output gap of Cooper and Priestley (2009), the three shocks are obtained from a structural model, closer to economic fundamentals, represent more exogenous shocks to the economy, and have stronger predictive power of the returns of not only stocks but also other asset classes. Our results show that DSGE models, which have been successful in modeling macroeconomic dynamics, have great potential in capturing asset price dynamics as well.