Rational theories of the closed‐end fund premium puzzle highlight fund share and asset illiquidity, managerial ability, and fees as important determinants of the premium. Several of these attributes are difficult to measure for mutual funds, and easier to measure for hedge funds. This paper employs new data from a secondary market for hedge funds, discovers a closed‐hedge fund premium that is highly correlated with the closed‐end mutual fund premium, and shows that the closed‐hedge fund premium is well explained by variables suggested by rational theories. Sentiment‐based explanations do not find support in the data.

Using a new technique, and weekly data for 25 countries from 1994 to 1998, we analyze the relationship between institutional cross-border portfolio flows, and domestic and foreign equity returns. In emerging markets, institutional flows forecast statistically indistinguishable movements in country closed-end fund NAV returns and price returns. In contrast, closed-end fund flows forecast price returns, but not NAV returns. Furthermore, institutional flows display trend-following (trend-reversing) behavior in response to symmetric (asymmetric) movements in NAV and price returns. The results suggest that institutional cross-border flows are linked to fundamentals, while closed-end fund flows are a source of price pressure in the short run.

We study a natural experiment in which 1.5 million investors participate in allocation lotteries for Indian IPO stocks. Investors who win the lottery and obtain IPO stocks that rise in value increase portfolio trading volume in non-IPO stocks relative to lottery losers; the effects are negative for lottery winners obtaining IPO stocks that fall in value. A model in which agents learn from random experience about their ability to operate in the market environment best explains the results. Investors who have received multiple past IPO allocations show smaller responses, suggesting that learning/selection moderates these responses to noise shocks.

Many questions about institutional trading can only be answered if one tracks high-frequency changes in institutional ownership. In the United States, however, institutions are only required to report their ownership quarterly in 13-F filings. We infer daily institutional trading behavior from the “tape”, the Transactions and Quotes database of the New York Stock Exchange, using a sophisticated method that best predicts quarterly 13-F data from trades of different sizes. We find that daily institutional trades are highly persistent and respond positively to recent daily returns but negatively to longer-term past daily returns. Institutional trades, particularly sells, appear to generate short-term losses—possibly reflecting institutional demand for liquidity—but longer-term profits. One source of these profits is that institutions anticipate both earnings surprises and post-earnings announcement drift. These results are different from those obtained using a standard size cutoff rule for institutional trades.

We construct a simple measure of the aggregate illiquidity of hedge fund portfolios, based on the cross-sectional average first-order autocorrelation coefficient of hedge fund returns, and show that it has strong and robust in- and out-of-sample forecasting power for 72 portfolios of international equities, U.S. corporate bonds, and currencies over the 1994 to 2013 period. The forecasting ability of hedge fund illiquidity for asset returns is in most cases greater than, and provides independent information relative to, well-known predictive variables. We rationalize these findings using a simple equilibrium model, in which hedge funds provide liquidity in asset markets.

We discover a new currency strategy with highly desirable return and diversification properties, which uses the predictive ability of currency volatility risk premia for currency returns. The volatility risk premium—the difference between expected realized volatility and model-free implied volatility—reflects the costs of insuring against currency volatility fluctuations. The strategy sells high insurance-cost currencies and buys low insurance-cost currencies. A distinctive feature of the strategy’s returns is that they are mainly generated by movements in spot exchange rates instead of interest rate differentials. We explore explanations for the profitability of the strategy, which cannot be understood using traditional risk factors.

We propose a new method to model hedge fund risk exposures using relatively high‐frequency conditioning variables. In a large sample of funds, we find substantial evidence that hedge fund risk exposures vary across and within months, and that capturing within‐month variation is more important for hedge funds than for mutual funds. We consider different within‐month functional forms, and uncover patterns such as day‐of‐the‐month variation in risk exposures. We also find that changes in portfolio allocations, rather than in the risk exposures of the underlying assets, are the main drivers of hedge funds' risk exposure variation.

We build an equilibrium model of commodity markets in which speculators are capital constrained, and commodity producers have hedging demands for commodity futures. Increases in producers' hedging demand or speculators' capital constraints increase hedging costs via price-pressure on futures. These in turn affect producers' equilibrium hedging and supply decision inducing a link between a financial friction in the futures market and the commodity spot prices. Consistent with the model, measures of producers' propensity to hedge forecasts futures returns and spot prices in oil and gas market data from 1979 to 2010. The component of the commodity futures risk premium associated with producer hedging demand rises when speculative activity reduces. We conclude that limits to financial arbitrage generate limits to hedging by producers, and affect equilibrium commodity supply and prices.

We evaluate the impacts of tax policy on asset returns using the U.S. municipal bond market. In theory, tax-induced ownership segmentation limits risk sharing, creating downward-sloping regions of the aggregate demand curve for the asset. In the data, cross-state variation in tax privilege policies predicts differences in in-state ownership of local municipal bonds; the policies create incentives for concentrated local ownership. High tax privilege states have muni bond yields that are more sensitive to variations in supply and local idiosyncratic risk. The effects are stronger when local investors face correlated background risk and/or diminishing marginal nonpecuniary benefits from holding local assets.