Essays on Idiosyncratic Risk and Return Predictability

The first paper provides formal arguments and empirical evidence that justifies the use of the cross-sectional variance as a measure of average idiosyncratic volatility. The observability at any frequency of this measure allows new results on the relation of idiosyncratic risk and future returns. The paper shows that the cross-sectional variance predicts the return of the equally-weighted market portfolio over short horizons and that the predictability power of idiosyncratic risk is further increased when adding a measure of cross-sectional skewness to the crosssectional variance factor in the predictive regressions. Finally, it provides evidence that average idiosyncratic volatility is a positively rewarded risk factor. 

The second paper proposes a method to estimate the structural breaks in the mean of the dividend-price ratio. This bayesian technique incorporates the uncertainty about the location and magnitude of the breaks and yields the currentregime mean of this classic stock return's predictor. Adjusting the dividend-price ratio by its current regime mean, improves the explanatory power of the dividend-price ratio of future returns in-sample, as well as its out-of-sample forecasting ability to a very signicant extent.

The third paper decomposes the growth rate of the standard portfolio insurance strategy and unveils the (perhaps) surprising role that the correlation between the underlying assets plays on the performance of this type of investment strategy. The paper also introduces the growth optimal portfolio insurance strategy, which combines the growth-rate maximization objective with the constraint of insuring a fixed proportion of the portfolio, expressed in terms of the value of a given stochastic benchmark. The results suggest that the growth optimal strategy outperforms the equivalent standard parametrization of the strategy over long horizons.