[We conduct an analysis of the risk and return characteristics of a number of widely used fixed-income arbitrage strategies. We find that the strategies requiring more "intellectual capital" to implement tend to produce significant alphas after controlling for bond and equity market risk factors. These positive alphas remain significant even after taking into account typical hedge fund fees. In contrast with other hedge fund strategies, many of the fixed-income arbitrage strategies produce positively skewed returns. These results suggest that there may be more economic substance to fixedincome arbitrage than simply "picking up nickels in front of a steamroller."]

Active equity mutual funds managed by insurance companies underperform peer funds by over 1% per year. There is no evidence that insurance funds make less risky investments; instead they have lower risk-adjusted returns and their fund flows are less sensitive to performance when they perform poorly. Across insurance funds, those with heavy advertising, directly established by insurers or using parent firms' brandnames, and those whose managers simultaneously manage substantial non-mutual-fund assets, are more likely to underperform. We conclude that insurers' efforts to cross-sell mutual funds aggravate agency problems that erode fund performance.

ABSTRACT Short‐sales practices in the Hong Kong stock market are unique in that only stocks on a list of designated securities can be sold short. By analyzing the price effects following the addition of individual stocks to the list, we find that short‐sales constraints tend to cause stock overvaluation and that the overvaluation effect is more dramatic for individual stocks for which wider dispersion of investor opinions exists. These findings are consistent with Miller's (1977) intuition and other optimism models. We also document higher volatility and less positive skewness of individual stock returns when short sales are allowed.

We conduct an analysis of the risk and return characteristics of a number of widely used fixed-income arbitrage strategies. We find that the strategies requiring more “intellectual capital” to implement tend to produce significant alphas after controlling for bond and equity market risk factors. These positive alphas remain significant even after taking into account typical hedge fund fees. In contrast with other hedge fund strategies, many of the fixed-income arbitrage strategies produce positively skewed returns. These results suggest that there may be more economic substance to fixed-income arbitrage than simply “picking up nickels in front of a steamroller.”

This paper proposes asymmetric GARCH-Jump models that synthesize autoregressive jump intensities and volatility feedback in the jump component. Our results indicate that these models provide a better fit for the dynamics of the equity returns in the US and emerging Asian markets, irrespective whether the volatility feedback is generated through a common GARCH multiplier or a separate measure of volatility in the jump intensity function. We also find that they can capture several distinguishing features of the return dynamics in emerging markets, such as, more volatility persistence, less leverage effects, fatter tails, and greater contribution and variability of the jump component.

IPO auctions, which provide an impartial way of determining IPO pricing and share allocations, offer a natural setting for examining whether institutional investors possess private information, and for measuring how valuable their information is. Analyzing detailed bidding data from Taiwan’s discriminatory (pay-as-bid) auctions, we find that, relative to retail investors, institutional investors tend to bid higher in auctions when IPO shares are more valuable, and that underpricing is larger in auctions with relatively higher institutional bids. These results imply that institutional investors are better informed about IPO value, and that they obtain higher information rents when they bid higher relative to retail investors. We estimate the value of institutional investors’ private information to be worth about 8.68% of return, which is the extra rate of return they command on their informational advantages over retail investors.

Previous research finds insignificant market-timing ability for mutual funds using tests based on fund returns. The return-based tests, however, are subject to the “artificial timing” bias. In this paper, we propose and implement new measures of market timing based on mutual fund holdings. Our holdings-based measures do not suffer from the artificial timing bias. We find that, on average, actively managed U.S. domestic equity funds have positive timing ability. Market timing funds use non-public information to predict market returns, tend to have high industry concentration, large fund size, a tilt toward small-cap stocks, and are active in industry rotation.

ABSTRACT We study the asset pricing implications of learning in an environment in which the true model of the world is a multivariate one, but agents update only over the class of simple univariate models. Thus, if a particular simple model does a poor job of forecasting over a period of time, it is discarded in favor of an alternative simple model. The theory yields a number of distinctive predictions for stock returns, generating forecastable variation in the magnitude of the value‐glamour return differential, in volatility, and in the skewness of returns. We validate several of these predictions empirically.