Publications:
7. Crowding of International Mutual Funds (2024), Journal of Banking and Finance 164 (July), with Tanja Artiga-Gonzalez, Justus Inhoffen, and Evert Wipplinger
Abstract: We study the relationship between crowding and performance in the active mutual fund industry. Using the equity holdings overlap of 17,364 global funds, we find that funds that crowd into the same stocks underperform passive benchmark funds by 1.4% per year. The negative returns to crowding can at least in part be explained by excess demand for liquidity and the associated discount for holding liquid stocks. We show that our measure of crowding contains novel information about performance that is not reflected in other variables that describe funds’ investment environment, such as fund size and style. Our findings suggest that crowding of investment opportunities is important for understanding diminishing returns.
6. Nonstandard Errors (2024), The Journal of Finance, 79 (June), 2339-2390, with many coauthors — the credit should rightfully go to the team of coordinators)
Abstract: In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
5. Better Kept in the Dark? Portfolio Disclosure and Agency Problems in Mutual Funds (2022), Journal of Financial and Quantitative Analysis 57 (June), 1529-1563 (with Jarrad Harford and Buhui Qiu)
Abstract: We study the agency implications of increased disclosure using a regulatory change in the mutual fund industry as an experimental setting. This quasi-natural experiment mandated more frequent portfolio disclosure, which we show imposes managerial skill re-assessment risks from investors on funds with high relative performance volatility. In turn, this risk translates into greater agency costs to investors. We show that high, relative to low, volatility funds responded to the increased skill re-assessment risk post-regulation with an increase in management fees and a decrease in risk taking. These actions get transmitted to fund investors in the form of inferior net performance.
4. Trade Less and Exit Overcrowded Markets: Lessons from International Mutual Funds (2020), Review of Finance, 24 (May), 677-731 (with Hao Jiang and Marno Verbeek)
Abstract: We study active investment skills in relation to returns to scale in the active mutual fund industry. Using a sample of 13,807 funds from sixteen domicile countries investing in forty-two equity markets from 2001 to 2014, we find that they achieve negative trading performance on average, driven mainly by particularly low returns to their trades in US equities. Exploring their investment environment, we find convincing evidence of decreasing returns to scale around the world, especially for the US market. Based on theory of optimal fund size, we estimate the optimal size of the active mutual fund industry. We find that the active mutual fund industry in USA has exceeded the optimal level, whereas in the international markets, there may still be room for further expansion. Consistent with this view, we find that mutual fund managers have been gradually reallocating their assets away from the USA and more into international equity markets.
3. Institutional Ownership and Future Stock Returns: An International Perspective (2020), International Review of Finance, 20 (March), 235-245 (with Evert Wipplinger)
Abstract: We investigate the risk‐adjusted performance of the aggregate equity holdings and trades of 13,807 active mutual funds located in 16 countries between 2001 and 2014. Using portfolio sorts, we find weak evidence that institutional holdings exhibit positive subsequent risk‐adjusted returns. However, any outperformance is unlikely to stem from short‐term informational advantage: stocks bought do not outperform stocks sold in the subsequent quarter. This finding is robust to regressions of subsequent stock returns on changes in institutional ownership and holds for different measurements of institutional trading.
2. Can Mutual Fund Investors Distinguish Good from Bad Managers? (2019), International Review of Finance, 19 (September), 505-540 (with Marno Verbeek)
Abstract: Mutual fund flows respond significantly to the return gap, which captures information about unobserved actions of mutual funds and predicts future performance. The sensitivity of fund flows to the return gap is: (i) strong and positive; (ii) increasing with investor sophistication; (iii) highly nonlinear; and (iv) decreasing with the informativeness of past fund returns. On average, the response of investors to the return gap enhances their performance. Our findings suggest there is a sophisticated mass of investors who can distinguish good from bad managers using information that may not be directly inferred from standard performance indicators.
1. Front-running of Mutual Fund Fire-sales (2013), Journal of Banking and Finance, 37 (December), 4931-4942 (with Marno Verbeek)
Abstract: We show that a real-time trading strategy which front-runs the anticipated forced sales by mutual funds experiencing extreme capital outflows generates an alpha of 0.5% per month during the 1990–2010 period. The abnormal return stems from selling pressure among stocks that are below the NYSE mean size and cannot be attributed to the arrival of public information. While the largest stocks also exhibit downward price pressure, their prices revert before the front-running strategy can detect it. The duration of the anticipated selling pressure has decreased from about a month in the 1990s to about two weeks in the most recent decade. Our results suggest that publicly available information of fund flows and holdings exposes mutual funds in distress to predatory trading.
Papers under Review:
2. Who is at the Center of the Global Supply Chain?, with Hao Jiang
Abstract: We study the network structure of the global supply chain, using trade in value-added data for 67 economies and 45 industries. We find that, in the global manufacturing network, a few hub economies such as China, US, Germany, Japan, and Russia drive the global and regional trade flows, but have low dependence on foreign sourcing. Building fine-grained global networks linking economy-industry pairs, we find that the structural importance of an economy-industry pair in the global supply chain drives its contribution to global economic and stock market fluctuations. These results provide fresh evidence supporting the network origins of global economic fluctuations.