of the Dissertation Essays on Return Predictability and Volatility Estimation

This paper proposes and tests a flow-based explanation for three important empirical findings on return predictability – the persistence of mutual fund performance, the “smart money” effect, and stock price momentum. Since mutual fund managers generally scale up or down their existing positions in response to investment flows, and since the portfolios of funds receiving capital generally differ...

In an economy where agents hold money, the short interest rate determines the trade-off between money holdings and consumption. Building on this idea, we develop a theoretical model that shows the transmission mechanism through which the short rate finds its way to stock-return predictability regressions. We construct a cointegration relation that links share prices and dividends to the short i...

I show that important conclusions about time-series return predictability change when using least squares estimates weighted by ex-ante return variance (WLS-EV) instead of OLS. In small-sample simulations, WLS-EV results in large efficiency gains relative to OLS, fewer false negatives, and avoids the bias associated with ex-post weighting schemes. Empirically, traditional predictors such as the...

A seminal paper by Fama and Bliss (1987) showed that a simple regression model could explain a significant portion of 1-year ahead excess returns. Cochrane and Piazzesi (2005) showed that their regression model could explain a significantly large portion of excess returns than Fama and Bliss’ model and that a single return-forecasting factor essentially encompassed the predictability of excess ...

The variance risk premium, defined as the difference between the actual and riskneutral expectations of the forward aggregate market variation, helps predict future market returns. Relying on new essentially model-free estimation procedure, we show that much of this predictability may be attributed to time variation in the part of the variance risk premium associated with the special compensati...

This paper examines return predictability when the investor is uncertain about the right state variables. A novel feature of the model averaging approach used in this paper is to account for finite-sample bias of the coefficients in the predictive regressions. Drawing on an extensive international dataset, we find that interest-rate related variables are usually among the most prominent predict...

We establish several new findings on the relation between open interest in commodity markets and asset returns. High commodity market activity, as measured by high open-interest growth, predicts high commodity returns and low bond returns. Openinterest growth is a more powerful and robust predictor of commodity returns than other known predictors such as the short rate, the yield spread, the ba...

The regression of stock returns on predictive variables, such as dividend yield, has proven useful in optimal portfolio selection when investment opportunities are timevarying. Conditional versions of factor models impose a restriction on that regression, thereby implying a particular portfolio choice. The study examines several pricing models from a perspective of conditional mean-variance opt...

This paper develops a new approach to examining the time variation of risk premia within the framework of conditional asset pricing models. By combining conditional factor models with approximate present-value relationships we derive a linear relationship between the log stock price and investors’ expectations of future factor loadings, risk premia, and cashlows. This framework allows us to est...