Roger M. Edelen

Investor flows and the assessed performance of open-end mutual funds

Abstract Open-end equity funds provide a diversified equity positions with little direct cost to investors for liquidity. This study documents a statistically significant indirect cost in the form of a negative relation between a funds abnormal return and investor flows. Controlling for this indirect cost of liquidity changes the average funds abnormal return (net of expenses) from a statistically significant −1.6% per year to a statistically insignificant −0.2% and also fully explains the negative market-timing performance found in this and other studies of mutual fund returns. Thus, the common finding of negative return performance at open-end mutual funds is attributable to the costs of liquidity-motivated trading.

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 institutions 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.

Issuer surplus and the partial adjustment of IPO prices to public information

This study develops a model in which rational issuers maximize the expected surplus from going public by choosing an offer price that weighs the benefit of higher proceeds if the offer is completed against the cost of foregone surplus if the offer fails. Increases in the market valuation of comparable firms during the waiting period imply higher surplus associated with going public; issuers respond with a partial revision in the offer price to elevate the probability of completion. The model offers insights into many facts associated with initial public offering pricing, including partial adjustment to market returns, the inverse relation between withdrawal and market returns, the asymmetric price adjustment to up versus down market returns, hot-issue markets, and unconditional underpricing. r 2005 Published by Elsevier B.V.

On the Perils of Financial Intermediaries Setting Security Prices: The Mutual Fund Wild Card Option

Economic distortions can arise when financial claims trade at prices set by an intermediary rather than direct negotiation between principals. We demonstrate the problem in a specific context, the exchange of open-end mutual fund shares. Mutual funds typically set fund share price (NAV) using an algorithm that fails to account for nonsynchronous trading in the funds underlying securities. This results in predictable changes in NAV, which lead to exploitable trading opportunities. A modification to the pricing algorithm that corrects for nonsynchronous trading eliminates much of the predictability. However, there are many other potential sources of distortion when intermediaries set prices. Copyright The American Finance Association 2001.

Scale Effects in Mutual Fund Performance: The Role of Trading Costs

Berk and Green (2004) argue that investment inflow at high-performing mutual funds eliminates return persistence because fund managers face diminishing returns to scale. Our study examines the role of trading costs as a source of diseconomies of scale for mutual funds. We estimate annual trading costs for a large sample of equity funds and find that they are comparable in magnitude to the expense ratio; that they have higher cross-sectional variation that is related to fund trade size; and that they have an increasingly detrimental impact on performance as the funds relative trade size increases. Moreover, relative trade size subsumes fund size in regressions of fund returns, which suggests that trading costs are the primary source of diseconomies of scale for funds.

S&P 500 Indexers, Tracking Error, and Liquidity

It is widely known that stocks added to the S&P 500 index experience abnormal returns on announcement. Why then do S&P 500 indexers not trade at the opening price immediately following announcement of a change in the index, which would gain them an average of 19.2 additional basis points of return per year? The catch is a much higher standard deviation of tracking error. To achieve the low tracking errors observed in practice, an indexer must closely follow an exact-replication strategy. That two of the largest indexers have enhanced their returns indicates more active management than just holding all 500 stocks in the exact same proportions as the index. Practitioners interviewed suggest?and the empirical evidence confirms?that many indexers are effectively compensated for entering into bilateral agreements with providers of liquidity to trade at the closing price. The patterns of abnormal returns for changes in the index are exactly those that are needed to compensate liquidity providers for the risks that they assume in providing liquidity to indexers.

Institutional Investors and Stock Return Anomalies

We examine institutional investor demand for stocks that are categorized as mispriced according to twelve well-known pricing anomalies. We find that institutional demand during the year prior to anomaly portfolio formation is typically on the wrong side of the anomalies’ implied mispricing. That is, we find increases in institutional ownership for overvalued stocks and decreases in institutional ownership for undervalued stocks. Moreover, abnormal returns for all twelve anomalies are concentrated almost entirely in stocks with institutional demand on the wrong side. We consider several competing explanations for these puzzling results.

Relative Sentiment and Stock Returns

The sentiment of retail investors relative to that of institutional investors was measured by comparing their respective portfolio allocations to equity versus cash and fixed-income securities. The results suggest that fluctuations in retail sentiment are a primary driver of equity valuations for reasons unrelated to fundamentals. In the study reported, we measured the sentiment of retail investors versus the sentiment of institutional investors by comparing their respective portfolio allocations to equity versus cash and fixed-income securities. And we considered whether fluctuation in relative sentiment is associated with variation in expected stock market returns. Whereas several other studies used indirect proxies for aggregate investor sentiment, we used actual asset allocation decisions of investors as direct evidence of their sentiment. We could thus focus on the essential meaning of sentiment: a time-varying propensity to invest in risky assets that is unrelated to fundamentals. The cost of our approach, however, is that asset allocations can reveal only the sentiment of one group of investors relative to the sentiment of another group. We found that relative sentiment is uncorrelated with indicators of absolute investor sentiment and appears to have considerable value as a (contrarian) market-timing tool at a quarterly frequency. High levels of relative retail sentiment are associated with significantly lower future excess equity returns, and the change in relative sentiment is strongly positively related to concurrent market returns. This pattern is consistent with the hypothesis that retail sentiment is more variable than institutional sentiment and retail investors move prices as they update their asset allocations to reflect their shifting sentiment rather than for reasons related to fundamentals. The relationships between relative sentiment and stock returns that we documented are economically as well as statistically significant. For example, sorting on values of our index of relative sentiment yielded an annualized average market return in the following quarter equal to 25.6 percent when relative sentiment was low (in the lower quartile of the distribution) and only 4.5 percent when relative sentiment was high (in the upper quartile). Although we follow convention in labeling shifts in retail demand for equities independent of fundamentals as “sentiment driven,” our results are fully consistent with a rational interpretation of retail-side behavior. Shifts in retail risk tolerance lead to precisely the same pattern as shifts in the optimism of cash flow forecasts (relative to fundamentals). Increases in risk tolerance will induce contemporaneous increases in both prices and retail equity allocations as the retail sector bids up shares from the institutional side and will be followed by lower future expected returns. Increases in risk aversion will work similarly. In our framework, sentiment should be interpreted broadly—and not necessarily pejoratively—as also encompassing variation in risk tolerance. Our results are consistent with a smart money/dumb money view of the world in which all investors use the same risk-adjusted discount rate but one group (institutions) is better at forecasting future prospects. The key distinction between this view and a rational interpretation (that the difference in behavior comes from time-varying risk tolerance) lies with investors’ expectations. In the smart money/dumb money interpretation, if retail investors knew the conditional expected returns that we have documented, they would alter their behavior. In the rational interpretation, they would not. Unfortunately, these two interpretations are not readily distinguished by empirical analysis.

Agency Costs of Institutional Trading

Under the typical institutional trading arrangement a portfolio manager makes the trade decision and a trading desk executes the trade, with execution performance evaluated against a benchmark such as the volume weighted average price (VWAP). We show that this trading arrangement provides incentives to the trader that are at odds with the objectives of the portfolio manager. Specifically, traders maintain a relatively low ask quote during rising markets to expedite sell trades and a relatively high bid quote during falling markets to expedite buy trades. This process inhibits the securitys natural tendency to rise (or fall) with the market. We provide empirical evidence of several properties of price-adjustment delays that are consistent with this model.

Post-SEO Performance and Institutional Investors

We document a strong link between institutional investors and long-run stock return and operating performance following seasoned equity offerings (SEOs). Virtually all of the underperformance is confined to the top two quintiles of stocks with the largest increase in number of institutional investors prior to the post-issue underperformance. Moreover, non-SEO stocks with matching changes in institutional investors exhibit similar long-run underperformance to that of SEO stocks. Thus, we conclude that post-SEO underperformance is not due to the SEO per se but rather is a manifestation of more general effects associated with changes in institutional interest in a firm’s stock.