This paper investigates the implications of investor learning for the sensitivity of mutual fund flows to past performance. We illustrate theoretically that when some sophisticated investors learn from past fund performance to form their posterior expectations of managerial ability, the flow-performance sensitivity should be weaker for funds with more volatile past performance and longer track records. Moreover, the dampening effects of performance volatility and fund age on the flow-performance sensitivity should be stronger for funds attracting more sophisticated investors. We provide supporting evidence for this investor learning hypothesis using mutual fund flows and compare the relative level of sophistication among investors in load versus no-load funds, institutional versus retails funds, and star versus non-star funds.

How to prevent runs on open-end mutual funds? In recent years, markets have observed an innovation that changed the way open-end funds are priced. Alternative pricing rules (known as swing pricing) adjust funds’ net asset values to pass on funds’ trading costs to transacting shareholders. Using unique data on investor transactions in U.K. corporate bond funds, we show that swing pricing eliminates the first-mover advantage arising from the traditional pricing rule and significantly reduces redemptions during stress periods. The positive impact of alternative pricing rules on fund flows reverses in calm periods when costs associated with higher tracking error dominate the pricing effect.

I investigate mutual fund flows at the individual fund and at the fund family level. At the individual, I use SEC filings to decompose fund flows into inflows and outflows. This decomposition of net flows into its component parts provides a way to examine differences in how search costs and investor learning affect investors who are entering a fund (or adding to their investments) versus those investors who are leaving a fund (or decreasing their investments). I then examine the effect of the existence of an advertisement for the fund on these investors. At the mutual fund family level, I examine how the characteristics and performance of mutual fund families affect the flows to the family as a whole. I then examine the effects of advertising expenditures on flows to the fund family.

To study attention and learning effects in financial markets, we investigate the role of media coverage in investment decisions of mutual fund investors and the consequent effects on fund flows. Employing a database of nearly 10,000 news articles and controlling for endogeneity in media coverage, we find that fund characteristics affect the probability of a news story and that the existence and stance of media coverage affects net investor flows into the fund in ways consistent with investor attention and learning.

I show that the shape of flow-performance relationship among open-end funds varies with investor sentiment. This link is stronger when the market tone is optimistic. Cross-sectional comparison reveals that the convexity of the relationship is more pronounced among funds of the type that receives less demand; especially among risky funds in low-investor-sentiment quarters. Managers of such funds that are under-performing have incentives to increase the risk of their portfolios; they do this by betting more on the market index and buying larger stocks in low-sentiment quarters. Applying Baker and Wurgler's (2006) findings suggests that this strategy is sub-optimal.

This paper studies the relation between individuals' mutual fund flows and fund characteristics, establishing three key results. First, consistent with tax motivations, individual investors are reluctant to sell mutual funds that have appreciated in value and are willing to sell losing funds. Second, individuals pay attention to investment costs as redemption decisions are sensitive to both expense ratios and loads. Third, individuals' fund-level inflows and outflows are sensitive to performance, but in different ways. Inflows are related only to "relative" performance, suggesting that new money chases the best performers in an objective. Outflows are related only to "absolute" fund performance, the relevant benchmark for taxes.

We develop a model of performance evaluation and fund flows for mutual funds in a family. Family performance has two effects on the estimate of a member fund's skill and its inflows: a positive common-skill effect, and a negative correlated-noise effect. The overall spillover is either positive or negative, depending on the weight of common skill and correlation of noise in returns. Its absolute value increases with family size, and declines over time. The sensitivity of flows to a fund's own performance is affected accordingly. Empirical estimates of fund flow sensitivities show patterns consistent with rational cross-fund learning within families.