We study a significant innovation with widespread consequences for the mutual fund industry: the introduction of multiple-class funds that give investors a choice among alternative load and fee structures. The transition to a multiple-class structure represents an important step in the evolution of the mutual fund industry. It also provides a well-controlled setting for research on the structure of funds, on investor clienteles and their impact on fund performance and, more generally, about the manner in which financial innovations tend to be adopted. We develop a simple model of a fund's decision on whether and when to introduce new classes and empirically investigate the model's predictions that: (a) Funds with more skilled management, less sensitivity of flows to performance, smaller size, higher existing loads and membership in larger families are better positioned to benefit and, therefore, more likely to switch to a multiple-class structure earlier; (b) The new classes increase the level and volatility of fund inflow by attracting investors with short and uncertain investment horizons – which, in turn, can negatively impact fund performance. Our empirical results are generally supportive of the model's predictions.

We propose a new measure, active fundamental performance (AFP), to identify skilled mutual fund managers. AFP evaluates fund investment skills conditioned on the release of firms’ fundamental information. For each fund, we examine the covariance between deviations of its portfolio weights from a benchmark portfolio and the underlying stock performance on days when firms publicize fundamental information. Because asset prices on these information days better reflect firm fundamentals, AFP can more effectively identify investment skills. From 1984 to 2014, funds in the top decile of high AFP subsequently outperformed those in the bottom decile by 2% to 3% per year. Received August 25, 2016; editorial decision December 17, 2017 by Editor Andrew Karolyi.

This paper provides direct evidence supporting the tax‐loss selling hypothesis as an explanation of the January effect. Examining turn‐of‐the‐year return and volume patterns for municipal bond closed‐end funds, which are held mostly by tax‐sensitive individual investors, we document a January effect for these funds, but not for their underlying assets. We provide evidence that this effect can be largely explained by tax‐loss selling activities at the previous year‐end. Moreover, we find that funds associated with brokerage firms display more tax‐loss selling behavior, suggesting that tax counseling plays a role.

We examine the informativeness of fund risk disclosure by combining fund returns and textual data. We develop a novel measure, INF, to capture the explanatory power of disclosed risks for fund returns. Average INF is 55% after controlling for market risk and remains 26–29% after excluding risks related to fund name or strategy. We explain variations in INF through disclosure costs and benefits: (1) Funds with less informative disclosures face SEC comment letters and reduced flow, (2) informative disclosures attract institutional flows, and (3) performance concerns may disincentivize disclosure. Overall, funds face trade-offs between transparency and maintaining their competitive advantage.

Our paper analyzes the geographical preferences of hedge fund investors and the implication of these preferences for hedge fund performance. We find that funds of hedge funds overweigh their investments in hedge funds located in the same geographical areas and that funds with a stronger local bias exhibit superior performance. Local bias also gives rise to excess flow comovement and extreme return clustering within geographic areas. Overall, our results suggest that while funds of funds benefit from local advantages, their local bias also creates market segmentation that can destabilize the underlying hedge funds.

We provide novel evidence that hedge fund performance is persistent following weak hedge fund markets but is not persistent following strong markets. Specifically, we construct two performance measures, RET_DOWN and RET_UP, conditioned on the level of overall hedge fund sector returns. After adjusting for risks, funds in the highest RET_DOWN quintile outperform funds in the lowest quintile by approximately 7% in the subsequent year, whereas funds with better RET_UP do not outperform subsequently. The RET_DOWN measure can predict future fund performance over a horizon as long as 3 years, for both winners and losers and for funds with few share restrictions.

We examine the extent to which a fund's cash flows are affected by the stellar performance of other funds in its family — and consequences of such spillovers. We show that star performance results in greater cash inflow to the fund and to other funds in its family. Moreover, families with higher variation in investment strategies across funds are shown to be more likely to generate star performance. We argue that spillovers may induce lower ability families to pursue star-creating strategies. Consistent with our conjecture, families with high variation in investment strategies across funds significantly underperform low-variation families.

We study how passive investing affects asset prices. Flows into passive funds disproportionately raise the stock prices of the economy’s largest firms, especially those large firms in high demand by noise traders. Because of this effect, the aggregate market can rise even when flows are entirely due to investors switching from active to passive funds. Intuitively, passive flows increase the idiosyncratic risk of large firms in high demand, which discourages investors from correcting the flows’ effects on prices. Consistent with our theory, prices and idiosyncratic volatilities of the largest S&P500 firms rise the most following flows into that index.

Despite extensive disclosure requirements, mutual fund investors do not observe all actions of fund managers. We estimate the impact of unobserved actions on fund returns using the return gap—the difference between the reported fund return and the return on a portfolio that invests in the previously disclosed fund holdings. We document that unobserved actions of some funds persistently create value, while such actions of other funds destroy value. Our main result shows that the return gap predicts fund performance. (JEL G11, G23) Despite extensive disclosure requirements, mutual fund investors do not observe all actions of fund managers. For example, fund investors do not observe the exact timing of trades and the corresponding transaction costs. On the one hand, fund investors may benefit from unobserved interim trades by skilled fund managers who use their informational advantage to time the purchases and the sales of individual stocks optimally. On the other hand, they may bear hidden costs, such as trading costs, agency costs, and negative investor externalities. In this paper, we analyze the