Research

Working Papers:

Catering through Globalization: Cross-border Expansion and Misallocation in the Global Mutual Fund Industry, with Massimo Massa and Hong Zhang

Abstract: Efficient financial globalization should reward high-skilled financial institutions and punish low-skilled institutions. We show that the globalization of the mutual fund industry in the beginning of the century has exhibited the opposite pattern: low-skilled companies can benefit from globalization by catering to the demand of unsophisticated investors for foreign investment. This catering strategy attracts capital for fund companies but fails to deliver performance or diversification benefits to investors. Moreover, its associated cross-border capital flows reduce price efficiency and liquidity in the target country. Our results highlight the potential existence of a short-term behavioral component of financial globalization in distorting efficiency.

“Private Company Valuations by Mutual Funds”, with Vikas Agarwal, Brad Barber, Allaudeen Hameed, and Ayako Yasuda

Abstract: Mutual funds that hold private securities value these securities at considerably different prices. Prices vary across fund families, are updated every 2.5 quarters on average and are revised dramatically at follow-on funding events. The infrequent, but dramatic price changes yield predictable fund returns, though we find little evidence of fund investors exploiting this opportunity by buying (selling) before (after) the follow-on funding events. Consistent with fund families opportunistically marking up private securities, we find that funds near the top of league tables increase private valuations more around year-end follow-on funding events than funds ranked lower.

Machine Learning versus Economic Restrictions: Evidence from Stock Return Predictability”, with Doron Avramov and Lior Metzker

Abstract: This paper shows that machine learning methods often fail to clear standard economic restrictions. Machine learning-based investments extract profitability primarily from difficult-to-arbitrage stocks and during alleviated limits-to-arbitrage market states. Value-weighting returns and excluding microcaps or distressed stocks considerably attenuate profitability. Performance further deteriorates in the presence of trading costs due to high turnover or extreme positions in the tangency portfolio implied by the pricing kernel. Despite their opaque nature, machine learning methods identify mispriced stocks consistent with most anomalies. Beyond economic restrictions, deep learning signals are profitable in long positions, remain viable in recent years, and command low downside risk.

“Investor Heterogeneity and Liquidity”, with Kalok Chan and Allaudeen Hameed

Abstract: We find that stocks held by institutions with similar investment horizon are less liquid and have higher volatility of liquidity. Consistent with correlated demand for liquidity, fund flows are highly correlated among funds with similar investment horizon but not when funds differ in their investment horizons. Also, extreme flow-induced trading by institutional funds has a bigger price impact when stocks have less heterogeneous investor base. Additionally, we find that the premium associated with illiquid stocks is concentrated in stocks with low investor heterogeneity. Our findings are stronger in the recent decades, emphasizing the effect of increased institutional investor participation.

“Short-Sale Constraints and the Pricing of Managerial Skills”, with Massimo Massa and Hong Zhang

Abstract: We investigate the impact of the absence of short selling on the pricing of managerial skills in the mutual fund industry. In the presence of divergent opinions regarding managerial skills, fund managers can strategically use fees to attract only the most optimistic capital. The recognition of this fee strategy helps explain a set of stylized observations and puzzles in the mutual fund industry, including the underperformance of active funds, the existence of flow convexity, and the negative correlation between gross-of-fee α and fees.

Publications:

“Time-Varying Liquidity and Momentum Profits”, with Doron Avramov and Allaudeen Hameed, 2016, Journal of Financial and Quantitative Analysis 51, 1897─1923. [Published Version]

Abstract: A basic intuition is that arbitrage is easier when markets are most liquid. Surprisingly, we find that momentum profits are markedly larger in liquid market states. This finding is not explained by variation in liquidity risk, time-varying exposure to risk factors, or changes in macroeconomic condition, cross-sectional return dispersion, and investor sentiment. The predictive performance of aggregate market illiquidity for momentum profits uniformly exceeds that of market return and market volatility states. While momentum strategies have been unconditionally unprofitable in the United States, in Japan, and in the Eurozone countries in the last decade, they are substantial following liquid market states.

“Short-Term Reversals: The Effects of Past Returns and Institutional Exits”, with Allaudeen Hameed, Avanidhar Subrahmanyam, and Sheridan Titman, 2017, Journal of Financial and Quantitative Analysis 52, 143─173. [Published Version]

Abstract: Price declines over the previous quarter lead to stronger reversals across the subsequent 2 months. We explain this finding based on the dual notions that liquidity provision can influence reversals and that agents who act as de facto liquidity providers may be less active in past losers. Supporting these observations, we find that active institutions participate less in losing stocks and that the magnitude of monthly return reversals fluctuates with changes in the number of active institutional investors. Thus, we argue that fluctuations in liquidity provision with past return performance account for the link between return reversals and past returns.

“Scaling Up Market Anomalies”, with Doron Avramov, Amnon Schreiber, and Koby Shemer, 2017, Journal of Investing 26, 89─105. [Published Version]

Abstract: This paper implements momentum among a host of market anomalies. Our investment universe consists of the 15 top (long-leg) and 15 bottom (short-leg) anomaly portfolios. The proposed active strategy buys (sells short) a subset of the top (bottom) anomaly portfolios based on past one-month return. The evidence shows statistically strong and economically meaningful persistence in anomaly payoffs. Our strategy consistently outperforms a naive benchmark that equal weights anomalies and yields an abnormal monthly return ranging between 1.273% and 1.471%. The persistence is robust to the post-2000 period, and various other considerations, and is stronger following episodes of high investor sentiment.

The Unexpected Activeness of Passive Investors: A Worldwide Analysis of ETFs”, with Massimo Massa and Hong Zhang, Review of Asset Pricing Studies, forthcoming.

Abstract: The global ETF industry provides more complicated investment vehicles than low-cost index trackers. Instead, we find that the real investments of ETFs may deviate from their benchmarks to leverage informational advantages (which leads to a surprising stock-selection ability) and to help affiliated OEFs through cross-trading. These effects are more prevalent in ETFs domiciled in Europe. Moreover, ETF flows seem to respond to additional risk. These results have important normative implications for consumer protection and financial stability.

“Mutual Funds and Mispriced Stocks”, with Doron Avramov and Allaudeen Hameed, Management Science, forthcoming.

Abstract: We propose a new measure of fund investment skill, active fund overpricing (AFO), encapsulating the fund’s active share of investments, the direction of fund active bets with regard to mispriced stocks, and the dispersion of mispriced stocks in the fund’s investment opportunity set. We find that fund activeness is not sufficient for outperformance: high (low) AFO funds taking active bets on the wrong (right) side of stock mispricing achieve inferior (superior) fund performance. However, high AFO funds receive higher flows during periods of high investor sentiment, when the performance-flow relation becomes weaker.