A cash-in-advance model of a monetary economy is used to derive a money-based capital asset pricing model (M-CAPM), which allows the authors to implement tests of asset pricing restrictions without consumption data. A test as in Eugene F. Fama and James D. Macbeth (1973) of the model suggests that the money betas have some explanatory power for the cross-sectional variation of expected returns; however, the model is rejected using conditional information. Consistent with their predictions, estimates of the curvature parameter are lower than those of the consumption capital asset pricing model (C-CAPM) and pricing errors of the M-CAPM tend to be smaller than those of the C-CAPM.

We provide evidence that the spread between commodity spot and futures prices (the basis) reflects the macroeconomic risks common to all asset markets. The basis of many commodities is correlated with the stock index dividend yield and corporate bond quality spread. Explanatory power is related to exposure to macroeconomic fluctuations: about 40 percent of the variation in the basis of a portfolio of commodities with high business cycle sensitivity is explained by the stock and bond yields. Further diagnostics indicate that these associations are largely due to the presence of risk premiums, rather than spot price forecasts, in the basis.

We examine the intraday relationship between returns and returns volatility in the stock index and stock index futures markets. Our results indicate a strong intermarket dependence in the volatility of the cash and futures returns. Price innovations that originate in either the stock or futures markets can predict the future volatility in the other market. We show that this relationship persists even during periods in which the dependence in the returns themselves appears to weaken. The findings are robust to controlling for potential market frictions such as asynchronous trading in the stock index. Our results have implications for understanding the pattern of information flows between the two markets.

We examine differences in structural characteristics that lead firms of different sizes to react differently to the same economic news. We find that a small firm portfolio contains a large proportion of marginal firms-firms with low production efficiency and high financial leverage. We construct two size-matched return indices designed to mimic the return behavior of marginal firms and find that these return indices are important in explaining the time-series return difference between small and large firms. Furthermore, risk exposures to these indices are as powerful as log(size) in explaining average returns of size-ranked portfolios.

Academic and practitioner research evaluates portfolio performance using size and value/growth attributes or factors. We assess the merits of popular evaluation procedures based on matched-characteristic benchmark portfolios or time-series return regressions by applying them to a sample of active money managers and passive indexes. Estimated abnormal returns display large variation across approaches. The benchmarks typically used in academic research--attribute-matched portfolios from independent sorts, the three-factor time-series model, and cross-sectional regressions of returns on stock characteristics--track returns poorly. Some simple alterations improve the performance of these methods. The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: [email protected]., Oxford University Press.

Most mutual funds adopt investment styles that cluster around a broad market benchmark. Few funds take extreme positions away from the index, but those who do are more likely to favor growth stocks and past winners. The bias toward glamour and the tendency of poorly performing value funds to shift styles may reflect agency and behavioral considerations. After adjusting for style, there is evidence that growth managers on average outperform value managers. Though a fund’s factor loadings and its portfolio characteristics generally yield similar conclusions about its style, an approach using portfolio characteristics predicts fund returns better.

ABSTRACT We examine whether stock prices fully value firms' intangible assets, specifically research and development (R&D). Under current U.S. accounting standards, financial statements do not report intangible assets and R&D spending is expensed. Nonetheless, the average historical stock returns of firms doing R&D matches the returns of firms without R&D. However, the market is apparently too pessimistic about beaten‐down R&D‐intensive technology stocks' prospects. Companies with high R&D to equity market value (which tend to have poor past returns) earn large excess returns. A similar relation exists between advertising and stock returns. R&D intensity is positively associated with return volatility.

There is a significant foreign influence on the risk premium for U.S. assets. Using a bivariate GARCH-in-mean process, we find that the conditional expected excess return on U.S. stocks is positively related to the conditional covariance of the return of these stocks with the return on a foreign index but is not related to its own conditional variance. Further, we are unable to reject the international version of the CAPM. We present evidence for different model specifications, multiple-day returns, and alternative proxies for foreign stock returns.

This paper compares the intra-day patterns on the NYSE and AMEX of volatility, trading volume and bid-ask spreads for European and Japanese dually-listed stocks with American stocks of comparable average trading volume and volatility. It is shown that the intra-day patterns for these stocks are remarkably similar even though public information flows differ markedly across these stocks during the trading day. In the early morning, all stocks have higher volatility than later in the day, but this phenomenon is most pronounced for Japanese stocks and affects American stocks the least. We argue that these patterns are consistent with markets reacting to the overnight accumulation of public information but are inconsistent with the view that early morning volatility can be attributed to monopolistic specialist behavior.