Using data from the Tokyo Stock Exchange, we study how beta, size, and ratio of book to market equity (BE/ME) account for the cross-section of expected stock returns over different lengths of investment horizons. We find that $\beta$, adjusted for infrequent trading or not, fails to explain the...

Using data from the Tokyo Stock Exchange, we study how beta, size, and ratio of book to market equity (BE/ME) account for the cross-section of expected stock returns over different lengths of investment horizons. We find that $\beta$, adjusted for infrequent trading or not, fails to explain the...

In this paper, we point out that the widely used stochastic discount factor (SDF) methodology ignores a fully specified model for asset returns. As a result, it suffers from two potential problems when asset returns follow a linear factor model. The first problem is that the risk premium...

A major problem in finance is to understand why different financial assets earn vastly different returns on average. In this paper, we survey various econometric approaches that have been developed to empirically examine various asset pricing models used to explain the difference in cross...

This paper reviews the literature on Bayesian portfolio analysis. Information about events, macro conditions, asset pricing theories, and security-driving forces can serve as useful priors in selecting optimal portfolios. Moreover, parameter uncertainty and model uncertainty are practical...

We study an investor’s asset allocation problem with a recursive utility and with tradable volatility that follows a 2-factor stochastic volatility model. Consistent with previous findings under the additive utility, we show that the investor can benefit substantially from volatility trading...

Within the past few years several articles have suggested that returns on large equity portfolios may contain a significant predictable component at horizons three to six years. Subsequently, the tests used in these analyses have been criticized (appropriately) for having widely misunderstood...