Using a novel dataset, I show that hedge fund managers connected through shared employment histories hold and trade more of the same stocks than unconnected managers. A long-short portfolio of connected-unconnected overlapped trades generates 3.6% of annual alpha. Results are greater between fund-pairs with stronger social connections and longer relationships implying a socially reinforcing channel is responsible. Shock based tests confirm social channels lead to the main findings, supporting models of manager coordination. The findings identify common sources of risk and return for employment-linked hedge funds, except during severe drawdowns when common holdings are protected from fire sales.

Modern mutual fund families include more than active mutual funds (AMFs). AMFs in families with greater index mutual fund (IMF) presence generate higher category-adjusted gross returns. Performance is positively related to the levels of passive and active fees, suggesting moral hazard. Intrafamily competition from IMFs in the same Morningstar category incentivizes managers to exert effort. Financial resources do not contribute to the performance effect. Cross-trading with IMFs occurs with some positive effect on performance. ETFs have no impact on performance. IMFs reduce flow-performance sensitivity and flow volatility of AMFs in the family. IMFs and ETFs uniquely contribute to expense pressure.

Material private information transmits through social networks. Using manually collected information on networks of alumni reunion cohorts, we show that hedge fund managers connected to directors of firms engaged in merger deals increase call-option holdings on target firms before deal announcements. Effects are larger when reunion events for connected cohorts occur just before announcements. Independent directors, directors with short tenure, and directors with low stock ownership are more likely to transmit information. Our results are robust to confounding factors and alternative specifications. These findings highlight the role of social networks as channels of private-information dissemination.

We introduce an estimator that measures factor exposures and alphas of individual private equity funds, with minimal assumptions about the fund return data-generating process (DGP). Simulations using varying assumptions about the DGP indicate that our estimator exhibits lower mean-squared-error (bias plus variance) than competing time-series estimators. Applying our model to a newly available commercial dataset, PitchBook, we uncover new findings of economic importance: buyout managers have higher average skill levels than claimed by past studies; portfolios are marked with forward-looking and lagged multiples of factors; and skill and systematic exposures vary significantly over time.