Conditional Return Smoothing in the Hedge Fund Industry

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Abstract
We show that if true returns are independently distributed and a manager fully reports gains but delays reporting losses, then reported returns will feature conditional serial correlation. We use conditional serial correlation as a measure of conditional return smoothing. We estimate conditional serial correlation in a large sample of hedge funds. We find that the probability of observing conditional serial correlation is related to the volatility and magnitude of investor cash flows, consistent with conditional return smoothing in response to the risk of capital flight. We also present evidence that conditional serial correlation is a leading indicator of fraud.

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