Xiaomeng Lu is an Associate Professor of Finance (untenured) at the Fudan International School of Finance (FISF), Fudan University. Prior to joining FISF in 2021, she was an Assistant Professor of finance at Shanghai Advanced Institute of Finance (SAIF), Shanghai Jiao Tong University. She received her Ph.D. in Economics from Cornell University. She has a B.A. degree in Economics and a B.S. degree in Statistics from Peking University. Her research fields include empirical asset pricing, behavioral finance, FinTech, and household finance. She is also interested in topics related to the Chinese financial market.
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Publications
Financial Inclusion via FinTech: From Digital Payments to Platform Investments, with Claire Yurong Hong and Jun Pan, 2025, Management Science, online.
Abstract: We study household finance in the age of FinTech, where consumption, payments, and investments take place via all-in-one super-apps. We hypothesize that FinTech adoption can improve household risk-taking by breaking down the traditional physical and psychological barriers and enhance financial inclusion. Taking advantage of an individual-level FinTech dataset, we find that higher FinTech adoption, both at the individual-level and the county-level instrumented by distance-from-Hangzhou, results in higher participation and more risk-taking in mutual-fund investments. Moreover, individuals who are otherwise more constrained, those with higher risk tolerance or living in under-banked counties, stand to benefit more from the advent of FinTech.
FinTech Platforms and Mutual Fund Distribution, with Claire Yurong Hong and Jun Pan, 2025, Management Science 71, no. 1: 488-517.
Abstract: We document a novel platform effect caused by the emergence of FinTech platforms in the intermediation of financial products. In China, platform distributions of mutual funds emerged in 2012 and grew quickly into a formidable presence. Utilizing the staggered entrance of funds onto platforms, we find a marked increase of performance-chasing, driven by the centralized information flow unique to FinTech platforms. This pattern is further confirmed using proprietary data from a top platform. Examining the platform impact on fund managers, we find that, incentivized by the amplified performance-chasing, fund managers increase risk taking to enhance their probability of getting onto the top ranking.
Disagreement Beta, with George Gao, Zhaogang Song, and Hongjun Yan, 2019, Journal of Monetary Economics, 107, pp.96-113.
Abstract: When two investors agree to disagree on market prospects and bet against each other, both expect to profit from their trades. Hence, an increase in disagreement leads to higher perceived trading profits and lower marginal utilities for both investors, so disagreement betas can affect cross-sectional asset returns. We construct a disagreement measure us- ing professional forecasts of U.S. macroeconomic fundamentals. Betas with respect to this disagreement factor positively explain cross-sectional returns of stocks, corporate bonds, mortgage-backed securities, and government securities. Further tests using portfolio-based test assets confirm the significant pricing power of the disagreement factor on top of in- fluential benchmark factors.
Tail Risk Concerns Everywhere, with George Gao and Zhaogang Song, 2019, Management Science, 65(7), pp.3111-3130.
Abstract: We showthat the beta with respect to an index of global ex ante tail risk concerns (GRIX), whichwe construct using out-of-the-money options on multiple global assets, negatively drives cross-sectional return variations across asset classes, including international equity indices, foreign currencies, and government bond futures. The pricing power of GRIX becomes stronger when more asset-class-level tail risk concerns are incorporated in the index construction. GRIX also dominates asset-class-level tail risk concerns in pricing assets within each asset class. These evidences imply that the pricing effect of tail risk concerns works predominantly as a global channel. The GRIX pricing effect is distinct from that of tail risk factors based on historical realizations, consistent with the interpretation that tail risk concerns likely reflect investors' ex ante subjective belief about tail risk.
Working papers
Inflation, Default, and Corporate Bond Returns, with Yoshio Nozawa, and Zhaogang Song, 2025, R&R at Review of Financial Studies.
Abstract: We document key facts about the inflation risk exposure of corporate bonds from 2004–2022. Inflation betas of standard bond excess returns (relative to T-bills) are generally negative, whereas those of credit excess returns (relative to duration-matched Treasurys) are positive across most bonds. Cross-sectional variation in inflation betas is mainly driven by credit excess returns, with higher-default-risk bonds showing stronger positive exposure. Inflation beta affects future bond returns in the cross-section through credit excess returns, and firms with higher bond inflation betas exhibit higher stock inflation betas. Analyses using pre-2004 data and alternative inflation measures further illuminate underlying economic channels.
Some Capital Gains are Consumed More Equally than Others, with Guodong Chen, Yiqing Lu, and Michaela Pagel, 2026, working paper.
Abstract: Using linked mutual-fund and consumption records for 180,000 investors on the world's largest mobile payment platform, we test whether investors consume more out of capital gains from funds that are more highly ranked in their online portfolios. Quasi-exogenous variation from a same-company grouping rule shows that mechanically elevating funds significantly increases next-month redemptions and spending. Effects are strongest at the top of the portfolio interface, for gains rather than losses, and among investors holding more funds. Finally, we show that fund-level attention effects aggregate to persistent portfolio-level consumption differences across investors with varying exposure to salient holdings.
Understanding Corporate Bond Excess Returns, with Liyuan Cui and Zhaogang Song, 2026, working paper.
Abstract: This paper provides a comprehensive analysis of excess returns specific to corporate bonds. We construct a measure of excess returns that uses synthetic Treasury securities with identical cash flows as benchmarks, thereby fully removing interest-rate effects and isolating the component of returns specific to corporate bonds. Using a monthly sample from 2002 to 2024, we find that corporate-bond-specific excess returns differ significantly from standard, T-bill-based excess returns, both on average and in the cross section. We further examine the effects of a broad set of bond-level characteristics and systematic risk factors on corporate-bond-specific excess returns. In addition, we decompose interest-rate effects into duration and higher-order components. Together, these findings provide a foundational bench-mark for future research on corporate bond returns.
Stock Market Attacks: Evidence from China, with Ziyang Geng, 2024, working paper.
Abstract: In existing behavioral finance literature on stock mispricing, rational investors largely play a passive role in tolerating mispricing due to limits to arbitrage. In this paper, we show that rational speculators sometimes proactively and intentionally create mispricing by driving up stock prices away from their fundamental values through synchronized attacks with explosive trading volumes. The inflated stock price is subsequently supported by new rounds of irrational buyers who are subject to extrapolation bias and by existing stockholders who are reluctant to sell due to the disposition effect. This paper develops a simple model to illustrate how bubble-creating attacks can succeed in equilibrium under certain limits-to-arbitrage conditions, and provides consistent empirical evidence in the Chinese stock market using investors' trading data from a large brokerage company in China.
Anomalies Abroad: Beyond Data Mining, 2018, with Robert F. Stambaugh and Yu Yuan, working paper.
Abstract: A pre-specified set of nine prominent U.S. equity return anomalies produce significant alphas in Canada, France, Germany, Japan, and the U.K. All of the anomalies are consistently significant across these five countries, whose developed stock markets afford the most extensive data. The anomalies remain significant even in a test that assumes their true alphas equal zero in the U.S. Consistent with the view that anomalies reflect mispricing, idiosyncratic volatility exhibits a strong negative relation to return among stocks that the anomalies collectively identify as overpriced, similar to results in the U.S.
Work-in-progress
Improving Investor Trading Habit via Digital Companion, with Jun Qian, Shang-Jin Wei, and Xingjian Zheng.
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