Aggregate Price Effects of Institutional Trading: A Study of Mutual Fund Flow and Market Returns

We study the relation between market returns and aggregate flow into U.S. equity funds, using daily flow data. The concurrent daily relation is positive. Our tests show that this concurrent relation reflects flow and institutional trading affecting returns. This daily relation is similar in magnitude to the price impact reported for an individual institution's trades in a stock. Aggregate flow also follows market returns with a one-day lag. The lagged response of flow suggests either a common response of both returns and flow to new information, or positive feedback trading.

On the Perils of Security Pricing by Financial Intermediaries: The Case of Open-End Mutual Funds

There are many instances where financial claims trade at prices set by intermediaries. Pricing by an intermediary introduces the potential for economic distortions from innumerable sources. As one example, we show that nonsynchronous-trading generates predictable, readily exploitable, changes in mutual fund-share prices (NAV). The exploitation of predictable changes in mutual fund NAVs involved a wealth transfer from buy-and-hold fund investors to active fund traders and is costly to all fund investors. A simple modification to the mutual fund pricing algorithm eliminates much of this predictability, but nonsynchronous trading is just one of the issues intermediaries face when setting prices.

Crowding and tail risk in momentum returns

Several theoretical studies suggest that coordination problems can cause arbitrageur crowding to push asset prices beyond fundamental value as investors feedback trade on each others' emands. Using this logic we develop a crowding model for momentum returns that predicts tail risk when arbitrageurs ignore feedback effects. However, crowding does not generate tail risk when arbitrageurs rationally condition on feedback. Consistent with rational demands, our empirical analysis generally finds a negative relation between crowding proxies constructed from institutional holdings and expected crash risk. Thus our analysis casts both theoretical and empirical doubt on crowding as a stand-alone source of tail risk.info:eu-repo/semantics/submittedVersio