HUAIZHI CHEN
I am an Assistant Professor of Finance at the University of Notre Dame's Mendoza School of Business. Prior to this, I spent two years at Harvard Business School as a Post-Doc Fellow with the Behavioral Finance and Financial Stability Initiative. I completed my PhD in Finance at the London School of Economics.
I live in South Bend Indiana with my wife Dr. Anita Li, our daughter Victoria, and our cat Lami.
Working Papers
Last Update: November 2022. First Version: 2015
Presentations: London School of Economics Brown Bag (2015), University of Notre Dame (2016), Hong Kong University of Science and Technology (2016), The University of Hong Kong (2016), the Federal Reserve Board (2016), Tulane University (2016), the Wabash River Conference (2018), Arrowstreet Capital (2023), International Risk Management Conference (2023), and European Finance Association Meeting (2023)
(Formerly Risk Management and Price Pressure)
I demonstrate that the preference by asset managers to diversify stocks and follow certain investment mandates result in forecastable contrarian trading on their largest positions. Since large-cap stocks are held in similar positions across most asset managers, few equity portfolios are available to absorb this predictable source of demand. The large stock portfolios during the sample period (Q1 1990 to Q2 2021) exhibit a novel return-reversal pattern that is consistent with this demand channel. A variable that forecasts this source of demand for large stocks can explain return reversals in the momentum portfolios formed from the largest US companies.
Last Update: August 2023
With Richard B Evans and Yang Sun
Presentations: University of Notre Dame Brown Bag (2022), Brandeis Brown Bag (2022), Wabash River Conference (2023), Bristol Financial markets Conference (2023)
Revise and Resubmit at the Journal of Financial Economics
Using a panel of self-declared benchmarks, we examine the incidence of funds’ use of mismatched benchmarks over time. Consistent with the prior literature, it is high at the beginning of our sample (45% of TNA in 2008) but declines significantly over time (27% in 2020). This decline is driven primarily by the intensive margin: existing funds changing their benchmarks to match their style. In examining why funds “correct” their benchmarks, we find that benchmark corrections are associated with higher flows and market forces including increased investor sophistication, institutional investor governance, market competition, product differentiation and positioning all play a role.
Last Update: October 2022
With Lauren Cohen and Weiling Liu
Presentations: University of Notre Dame Brown Bag (2020), Virtual Municipal Finance Workshop (2020), Brookings Municipal Finance Conference (2021)
Accepted at Management Science
Almost 95% of long-term municipal bonds have callable features, and despite low interest rates, we find that a substantial fraction of local governments exercise these options with significant delays. Using data from 2001 to 2018, we estimate that US municipals lost over $31 billion from delayed refinancing, whereas US corporates lost only a comparative $1.4 billion. We present evidence that these delays are related to gaps in localized debt monitoring of issuers by their underwriters.
Last Update: February 2021
Presentations: University of Notre Dame Brown Bag (2020), Virtual Finance Seminar (University of Illinois at Chicago/ Michigan State University 2021), Virtual Finance Seminar (University of Bristol/ University of Exeter/ University of Lancaster/ University of Manchester 2021), Financial Markets and Corporate Governance Conference (2021)
I provide evidence that investor size matters in the market for short-term securities. Between January 2011 and November 2020, the largest asset management families obtained significantly higher promised returns from their money market securities than smaller families. Furthermore, I show that the enactment of Money Market Mutual Fund reforms on October 2016 decreased measures of competition in several categories of Money Market Mutual Funds. Consistent with improving market power, the largest fund families raised their lending rates (by 8 basis points) on their existing borrowers. These results highlight the trade-off in enacting macro-prudential policies and encouraging capital market efficiency.
Published Works
Latest Update: July 2022
Accepted at the Journal of Financial and Quantitative Analysis.
I show that cash distributions through cash-mergers, dividend payments, and stock buybacks are in principal similar to investor fund flows in generating demands for investable assets. Abnormal returns in certain assets can be forecasted because delegated investors predictably reinvest cash-returns toward certain holdings. Novel measures of stock level demand constructed using proportional reinvestments by mutual funds predict abnormal returns and issuances in non-cash paying stocks. These results highlight an alternative and substantial source of price fluctuations in the cross-section of equities.
April 9, 2021
With Lauren Cohen, and Umit Gurun.
Published at The Journal of Finance.
Winner of 2020 Consortium on Asset Management Best Paper Prize, FMA 2020 Best Paper in Investments
We provide evidence that bond fund managers misclassify their holdings, and that these misclassifications have a real and significant impact on investor capital flows. In particular, many funds report more investment grade assets than are actually held in their portfolios to important information intermediaries, making these funds appear significantly less risky. This results in pervasive misclassification across the universe of US fixed income mutual funds. The problem is widespread - resulting in up to 31.4% of funds being misclassified with safer profiles, when compared against their true, publicly reported holdings. “Misclassified funds” – i.e., those that hold risky bonds, but claim to hold safer bonds – appear to on-average outperform the low-risk funds in their peer groups. Within category groups, “Misclassified funds” moreover receive higher Morningstar Ratings (significantly more Morningstar Stars) and higher investor flows due to this perceived on-average outperformance. However, when we correctly classify them based on their actual risk, these funds are mediocre performers. These Misclassified funds also significantly underperform precisely when junk-bonds crash in returns. Misreporting is stronger following several quarters of large negative returns.
May 13, 2020
With Lauren Cohen, Dong Lou, Chris Malloy, and Umit Gurun.
Published in the Journal of Financial Economics.
Winner of Panagora A. Crowell Prize, and the IQ-KAP 2nd Best Place Prize
Using a novel database that tracks web traffic on the SEC’s EDGAR servers between 2003 and 2016, we show that mutual funds exert effort to reduce the dimensionality of their portfolio selection problem. Specifically, we show that mutual fund managers’ gather information on a very particular subset of firms and insiders, and their surveillance stays largely unchanged over time. This tracking has powerful implications for their portfolio choice, and its information content. An institution that downloaded an insider-trading filling by a given firm last quarter increases its likelihood of downloading an insider-trading filing on the same firm by more than 41.3 % this quarter, which is 8 times larger than the unconditional probability of an institution downloading at least one insider trading filing in a quarter from any firm in her existing portfolio (4.8%). Moreover, the average tracked stock that an institution sells generates 7.5% annualized DGTW- adjusted alpha, whereas the sale of an average non-tracked stock has close to zero DGTW adjusted alpha. The outperformance of tracked trades continues for a number of quarters following the tracked insider/institution sale and does not reverse within the sample period. Collectively, these results suggest that the information in tracked trades is important for fundamental firm value, and is only revealed following the information-rich dual trading by insiders and linked institutions.
April 17, 2016
With Lauren Cohen and Dong Lou.
Published in the Review of Financial Studies.
We explore a new mechanism by which investors take correlated shortcuts, and present evidence that managers undertake actions – in the form of sales management – to take advantage of these shortcuts. Specifically, we exploit a regulatory provision wherein a firm’s primary industry is determined by the highest sales segment. Exploiting this regulation, we provide evidence that investors classify operationally nearly identical firms vastly differently depending on their placement around this sales cut-off. Moreover, managers appear to exploit this by manipulating sales to be just over the cutoff in favorable industries. Further evidence suggests that managers then engage in activities to realize large, tangible benefits from this opportunistic action.