Portfolio Inefficiency and the Cross-Section of Expected Returns

A plot of expected returns versus betas obeys virtually no relation to an inefficient index portfolio's mean-variance location. If the index portfolio is inefficient, then the coefficients and R- squared from an ordinary-least-squares regression of expected returns on betas can equal essentially any desired values. The mean-variance location of the index does determine the properties of a cross- sectional mean-beta relation fitted by generalized least squares (GLS). As the index portfolio moves closer to exact efficiency, the GLS mean-beta relation moves closer to the exact linear relation corresponding to an efficient portfolio with the same variance. The goodness-of-fit for the GLS regression is the index portfolio's squared relative efficiency, which measures closeness to efficiency in mean-variance space.

Endogenous benchmarks

This paper develops a new approach that controls for commonalities in actively managed investment fund returns when measuring their performance. It is well-known that many investment funds may systematically load on common priced factors omitted from popular models, exhibit similarities in their choices of specific stocks and industries, or vary their risk-loadings in a similar way over time. We propose a parsimonious model that uses the return on the group of mutual funds as a benchmark for each individual fund within that group. We demonstrate that this model substantially reduces the correlation between fund residuals from standard models used for equity and fixed-income funds, and improves the estimates of fund α's and β's from commonly used equity and fixed-income models

Portfolio Inefficiency and the Cross-Section of Expected Returns

The Capital Asset Pricing Model implies that (i) the market portfolio is efficient and (ii) expected returns are linearly related to betas. Many do not view these implications as separate, since either implies the other, but we demonstrate that either can hold nearly perfectly while the other fails grossly. If the index portfolio is inefficient, then the coefficients and from an ordinary least squares regression of expected returns on betas can equal essentially any values and bear no relation to the index portfolio\u27s mean-variance location. That location does determine the outcome of a mean-beta regression fitted by generalized least squares

Asset Returns and Intertemporal Preferences

A representative-agent model with time-varying moments of consumption growth is used to analyze implications about means and volatilities of asset returns as well as the predictability of asset returns for various investment horizons. A comparative-statics analysis using nonexpectedutility preferences indicates that, although risk aversion is important in determining the means of both equity returns and interest rates, implications about the volatility and the predictability of equity returns are affected primarily by intertemporal substitution. Lower elasticities of intertemporal substitution are associated with greater variance in the temporary component of equity prices

On the Predictability of Stock Returns: An Asset-Allocation Perspective

Sample evidence about the predictability of monthly stock returns is considered from the perspective of a risk-averse Bayesian investor who must allocate funds between stocks and cash. The investor uses the sample evidence to update prior beliefs about the parameters in a regression of stock returns on a set of predictive variables. The regression relation can seem weak when described by usual statistical measures, but the current values of the predictive variables can exert a substantial influence on the investor\u27s portfolio decision, even when the investor\u27s prior beliefs are weighted against predictability

Expectations and Volatility of Consumption and Asset Returns

We find that conditional means and variances of consumption growth vary through time, and this variation appears to be associated with the business cycle. A pricing model with fluctuating means and variances of consumption growth provides implications about conditional moments of returns for both short and long investment horizons, and these implications are explored empirically. The U-shaped pattern of first-order autocorrelations of returns, as well as business cycle patterns in the price of risk, appears to be consistent with the model, but our exploration suggests that other implications about conditional return moments are at odds with the data

On the Predictability of Stock Returns: An Asset-Allocation Perspective

The predictability of monthly stock returns is investigated from the perspective of a risk-averse investor who uses the data to update initially vague beliefs about the conditional distribution of returns. The optimal stocks-versus-cash allocation of the investor can depend importantly on the current value of a predictive variable, such as dividend yield, even though a null hypothesis of no predictability might not be rejected at conventional significance levels. When viewed in this economic context, the empirical evidence indicates a strong degree of predictability in monthly stock returns.