This paper investigates whether dealer firms’ trading and pricing decisions are governed by their equivalent inventories, based on Ho and Stoll (1983) or Froot and Stein (1998), or by their ordinary inventories. It finds that ordinary inventories best explain dealer firms’ quote placement strategy, which dealer firm executes trades, and the quality of execution offered to the trades. This finding is consistent with decentralized nature of market-making where individual dealers focus on the position risk of stocks managed by them and not the position risks of stocks managed by other dealers in the firm.

This paper investigates empirically whether uncertainty about equity market volatility can explain hedge fund performance both in the cross section and over time. We measure uncertainty via volatility of aggregate volatility (VOV) and construct an investable version through returns on lookback straddles on the Chicago Board Options Exchange (CBOE) volatility index, VIX. We find that VOV exposure is a significant determinant of hedge fund returns. After controlling for fund characteristics, we find a robust and significant negative risk premium for VOV exposure in the cross section of hedge fund returns. We corroborate our results using statistical and parameterized proxies of VOV over a longer sample period.

This paper evaluates hedge fund performance through portfolio strategies that incorporate predictability based on macroeconomic variables. Incorporating predictability substantially improves out-of-sample performance for the entire universe of hedge funds as well as for various investment styles. While we also allow for predictability in fund risk loadings and benchmark returns, the major source of investment profitability is predictability in managerial skills. In particular, long-only strategies that incorporate predictability in managerial skills outperform their Fung and Hsieh (2004) benchmarks by over 17% per year. The economic value of predictability obtains for different rebalancing horizons and alternative benchmark models. It is also robust to adjustments for backfill bias, incubation bias, illiquidity, fund termination, and style composition.