[Using a variety of different definitions of "neutrality," this study presents significant evidence against the neutrality to market risk of hedge funds in a range of style categories. I generalize standard definitions of "market neutrality," and propose five different neutrality concepts. I suggest statistical tests for each neutrality concept, and apply these tests to a database of monthly returns on 1423 hedge funds from five style categories. For the "market neutral" style, approximately one-quarter of the funds exhibit significant exposure to market risk; this proportion is statistically significantly different from zero, but less than the proportion of significant exposures for other hedge fund styles.]

[We investigate whether stock betas vary with the release of firm-specific news. Using daily firm-level betas estimated from intraday prices, we find that betas increase on earnings announcement days and revert to their average levels two to five days later. The increase in betas is greater for earnings announcements that have larger positive or negative surprises, convey more information about other firms in the market, and resolve greater ex ante uncertainty. Our results are consistent with a learning model in which investors use information on announcing firms to revise their expectations about the profitability of the aggregate economy.]

One can consider the concept of market neutrality for hedge funds as having breadth and depth: "breadth" reects the number of market risks to which a fund is neutral, while "depth" reects the "completeness" of the neutrality of the fund to market risks. We focus on market neutrality depth, and propose ve different neutrality concepts. "Mean neutrality" nests the standard correlation-based denition of neutrality. "Variance neutrality", "Value-at-Risk neutrality" and "tail neutrality" all relate to the neutrality of the risk of the hedge fund to market risks. Finally, "complete neutrality" corresponds to independence of the fund to market risks. We suggest statistical tests for each neutrality concept, and apply the tests to a combined database of monthly "market neutral" hedge fund returns from the HFR and TASS hedge fund databases. We nd that around one-quarter of these funds exhibit some signicant exposure to market risk.

We investigate whether stock betas vary with the release of firm-specific news. Using daily firm-level betas estimated from intraday prices, we find that betas increase on earnings announcement days and revert to their average levels two to five days later. The increase in betas is greater for earnings announcements that have larger positive or negative surprises, convey more information about other firms in the market, and resolve greater ex ante uncertainty. Our results are consistent with a learning model in which investors use information on announcing firms to revise their expectations about the profitability of the aggregate economy. The Author 2012. 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.

Equal compensation across assets for the same risk exposures is a bedrock of asset pricing theory and empirics. Yet real-world frictions can violate this equality and create apparently high Sharpe ratio opportunities. We develop new methods for asset pricing with cross-sectional heterogeneity in compensation for risk. We extend k-means clustering to group assets by risk prices and introduce a formal test for whether differences in risk premiums across market segments are too large to occur by chance. We find significant evidence of cross-sectional variation in risk prices for almost all combinations of test assets, factor models, and time periods considered.