A1813
Title: Dissecting anomalies in conditional asset pricing
Authors: Valentina Raponi - IESE Business School (Spain) [presenting]
Paolo Zaffaroni - Imperial College London (United Kingdom)
Abstract: A methodology is developed for estimating and testing the effect of anomalies in conditional asset pricing models when premia vary over time. By showing that conventional approaches are ill-suited to estimate time-varying anomalies premia, we develop a new method based on simple ordinary and weighted least square estimation and provide closed-form standard errors that can be used to make inferences on the premia parameters. To quantify the effect and the economic significance of anomalies, a new cross-sectional R-squared test is also proposed. Using a dataset of 20,000 individual US stock returns, we find that most of the anomalies, although statistically significant, explain only a small fraction (less than 10\%) of the cross-sectional variation of expected returns. Moreover, their effect tends to be more important during economic and financial crises.
