Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
The paper estimates and examines the empirical plausibility of asset pricing models that attempt to explain features of financial markets such as the size of the equity premium and the volatility of the stock market. In one model, the long-run risks (LRR) model of Bansal and Yaron, low-frequency movements, and time-varying uncertainty in aggregate consumption growth are the key channels for understanding asset prices. In another, as typified by Campbell and Cochrane, habit formation, which generates time-varying risk aversion and consequently time variation in risk premia, is the key channel. These models are fitted to data using simulation estimators. Both models are found to fit the data equally well at conventional significance levels, and they can track quite closely a new measure of realized annual volatility. Further, scrutiny using a rich array of diagnostics suggests that the LRR model is preferred. Copyright 2007, Wiley-Blackwell.