Portfolio concentration and mutual fund performance
with Jon Fulkerson
Mutual fund managers should choose to increase the concentration of their portfolio when they possess information of great enough expected value to offset the risks of increased concentration. Consistent with that idea, we find that fund performance improves after concentration increases. Because the riskiness of increased concentration varies between funds and over time, the expected value of the information required by managers before choosing to increase concentration should also vary. Among other results, we show that the concentration-performance relation is stronger for funds with less institutional ownership and when investor sentiment is low.
Skill and persistence in mutual fund returns: Evidence from a six-factor model
with Bradford Jordan
The addition of the Fama and French (2015) profitability (RMW) and investment (CMA) factors to the standard four-factor model reveals persistent positive alpha after fees for mutual funds. Over the period 2000 – 2014, about 65 percent of fund managers have at least some skill, and about 15 percent have skill in excess of fees. The best performing funds have significant negative exposures to both factors, while the worst performing funds have significant positive exposures. Because of that pattern, failure to account for these factors masks a difference in alpha between the best and worst performers of almost 7 percent per year.
Do investors chase performance or skill? Evidence from mutual fund flows
with Jon Fulkerson
When evaluating a manager, investors should attempt to separate luck from skill. We find a mutual fund manager’s demonstrated skill better predicts future performance than past fund performance. Despite that fact, investors tend to buy the funds with the best past performance, not the funds whose managers have demonstrated the most skill. Further, investors react strongly to fund performance even when it contains no information about manager skill. By failing to separate luck from skill, investors make inferior capital allocations.
I use exchange traded funds to construct low cost benchmarks for actively managed mutual funds. The benchmarks can be identified in advance, require no leverage or shorting, and require only annual rebalancing. The average fund underperforms its benchmark by 1% per year after expenses, a difference in performance equivalent to a $25 billion per year opportunity cost for investors selecting active management. The fees charged by actively managed funds are the primary reason they underperform. Active management comes at a significant cost, but without any offsetting benefit.
Wall Street Journal
On average, stocks with high prior-period volatility underperform those with low prior-period volatility, but that simple comparison paints an incomplete, and potentially misleading, picture. As we show, high volatility is an indicator of both positive and negative future abnormal performance. Among high volatility stocks, those with low short interest experience extraordinary positive returns, while those with high short interest experience equally extraordinary negative returns. Our results show that there is a surprisingly strong connection between the volatility and short interest puzzles and that studying the two together yields new and sharper insights into both.
We deconstruct the Active Share measure proposed by Cremers and Petajisto (2009) and find that two-thirds of the outperformance of high Active Share mutual funds can be attributed to the ability of those funds to select out-of-benchmark stocks. However, this outperformance is limited to high Active Share funds that use out-of-benchmark positions sparingly. Funds with large out-of-benchmark positions show little ability to select out-of-benchmark stocks. Our results suggest that the best active funds generally stay within their benchmark, deviating only for particularly good purchases.
Mutual fund liquidity costs
We study the costs mutual funds incur to provide liquidity to investors. Expanding the analysis of Edelen (1999) to a larger and more recent time period, we find liquidity costs are significantly lower than previously estimated. One dollar in purchases or redemptions generates an average cost of about $0.006 for U.S. equity funds. However, significant cross-sectional differences exist between funds. Funds with relatively illiquid portfolios, funds with relatively concentrated portfolios, and funds with larger portfolios have significantly greater average liquidity costs. Finally, we show that average liquidity costs are similar for U.S. bond funds and U.S. equity funds.
We examine the U.S. mutual fund industry with particular attention paid to fund flows, the liquidity of fund portfolios, and the interaction of those characteristics. Mutual funds in investment categories that hold potentially less liquid assets are growing quickly and often have volatile flows. Alternative strategies have both the highest average net flow and the highest average net flow volatility of any investment category. Among many other empirical results, we show that the liquidity of the equity portfolio of U.S. equity funds is greater when flow volatility is greater and that the liquidity of those same portfolios decreases after large outflows.
Journal of Financial Economics, 118, 2015, 289-298
In a standard four-factor framework, mutual fund return volatility is a reliable, persistent, and powerful predictor of future abnormal returns. However, the abnormal returns are eliminated by the addition of a “vol” anomaly factor contrasting returns on portfolios of low and high volatility stocks. Consistent with Novy-Marx (2014) and Fama and French (2014b), the Fama and French (2014a) profitability and investment factors are equally effective at eliminating the abnormal returns. Failure to account for the vol anomaly, either directly or indirectly, can lead to substantial mismeasurement of fund manager skill.
Journal of Empirical Finance, 28, 2014, 249-260
The top 5 percent of actively managed U.S. equity mutual funds in 2012 had greater aggregate TNA than the remaining 95 percent of funds combined. This skewness in size has implications for mutual fund research: What is true of the average fund is not necessarily true of the average dollar. We explore several key findings in the literature with an eye on this distinction. Our results indicate that if the goal of mutual fund research is to understand the importance of the industry to investors, then researchers should consider the experience of the average dollar, rather than the average fund.
Journal of Fixed Income, 23 (3), 2014, 50-63
We study the persistence of bond ETF premiums and discounts. Following a day of high or low premiums or discounts over NAV, ETFs tend to maintain a premium or discount for up to 30 days. Premiums and discounts also predict distinct patterns of returns after daily closing. Overnight returns are negative following a high premium, while ETFs with large discounts are followed by positive overnight returns. The large discount ETFs have substantially higher returns than high premium ETFs over the subsequent thirty days. We find that traditional liquidity measures, along with prior deviations from NAV, are significant in explaining a fund’s premiums/discounts. Finally, we examine a long-short portfolio strategy to exploit the observed deviations from NAV, and find it generates an alpha of .96% per month or about 11.5% per year.
We make use of a unique dataset of SEC Form N-SAR filings to examine the gross flows of U.S. bond funds. We find that gross inflows and outflows average around 4% of TNA per month, but net flows average only 0.26%. When modeling these flows, we see that, like equity funds, bond fund investors chase returns. Most of the return chasing is done by inflows. Funds with the highest decile of returns average 1% higher net flow and inflow per month, while the lowest decile funds lose nearly 0.6% in assets per month. Next, we find that positive net flows cause bond funds to diversify their holdings regardless of fund size. Finally, we test whether flows predict returns and find that an inflow weighted portfolio generates alphas of 0.8% per year. Bond inflows appear to be “smart money.”
Do absolute return mutual funds have absolute returns?
with Christopher Clifford and Bradford Jordan
Journal of Investing, 22 (4), 2013, 23-40
We study the universe of absolute return mutual funds and find no evidence they deliver positive alpha. Additionally, these funds can have significant factor exposures. Compared to ordinary equity funds, absolute return funds have much higher fees and turnover. They perform worse than their hedge fund counterparts. Overall, our results indicate that investors seeking absolute returns using mutual funds are likely to be disappointed.