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Research shows that many investors are loss averse (reluctant to sell investments that have lost value). However, there is open debate about whether mutual fund investors suffer from loss aversion. We use over 300,000 Chinese mutual fund investor accounts from five open‐end funds to test for loss aversion using survival analysis controlling for time‐varying covariates (Cox analysis). We find strong evidence of loss aversion as these investors are between 60% and 91% less likely to sell a fund that is down in value across the five funds. We also find that more sophisticated investors are less loss averse.

Research on decision-making under uncertainty has highlighted that individuals often use simple heuristics and/or exhibit behavioural biases. Specifically, with respect to portfolio decisions, research has indicated that investors are subject to the disposition effect, i.e. they are reluctant to sell assets that have performed poorly (losers) and prone to sell assets that have performed well (winners). We find that the mutual fund investors in our sample are subject to the disposition effect when they withdraw the redemption proceeds from their account, but not when they reallocate the proceeds within the account. The evidence is consistent with Shefrin and Statman’s hypothesis that framing a transaction as a transfer as opposed to a sale mitigates the disposition effect.

This study investigates why homeowners make mortgage curtailment payments. Using data from the Federal Reserve's Survey of Consumer Finances (1992, 1995, 1998, 2001, and 2004) to analyze household mortgage curtailments, we consider the propensity to save and relative risk and return as possible factors in the curtailment decision. We find that higher propensities to save are strongly positively correlated with the probability of curtailing the mortgage and nearly double the probability of such payments. Liquidity risk is also a factor in the curtailment decision.

Using a proprietary data set to study how past performance affects the determinants of mutual fund flows for a sample of load fund investors, I provide evidence that the determinants of fund flow depend on market conditions for both redemptions and purchases. Specifically, I show that, for redemptions, relative performance and risk adjusted performance are important determinants during a period of record flows into mutual funds. Conversely, during a period of poor performance, absolute performance becomes much more important and relative performance and risk adjusted performance become less important. For purchases, absolute performance, risk adjusted performance, and most relative performance measures become more important during the bear market.

Widely used test statistics for non-zero mean abnormal returns in short-horizon event studies ignore cross-firm variation in event effects. Cross-sectional regression analyses of abnormal returns often either ignore heteroskedasticity in model disturbances or ignore plausible implications of unexplained variation in effects for the structure of heteroskedasticity. We use a simple model of event effects and simulations patterned after Brown and Warner (1980, 1985) and Boehmer, Musumeci, and Poulsen (BMP, 1991) to highlight the resulting biases and the importance of using test procedures that appropriately allow for cross-sectional variation. We demonstrate analytically how cross-sectional variation produces "event-induced" variance increases and biases popular tests for non-zero mean abnormal returns. Our simulations provide evidence of that bias and of test power for several theoretically robust tests for non-zero means, including the standardized cross-sectional test statistic suggested by BMP, which we show equals the mean standardized prediction error divided by a heteroskedasticity-consistent standard error, and cross-sectional regression tests that condition on relevant regressors. We also analyze and provide evidence of bias and power for alternative tests for non-zero slopes in abnormal return regression models with heteroskedastic errors attributable to cross-firm variation in event effects and market model disturbance variances. Neither OLS nor WLS has good properties. WLS with robust standard errors and maximum likelihood estimation assuming non-proportional heteroskedasticity may represent useful supplements to OLS with robust standard errors.