The Cross Section of Monetary Policy Announcement Premium (with Hengjie Ai, Xuhui Pan and Lai Xu), 2022, Journal of Financial Economics, 143(1), 247-276. [Online Appendix] [Readme] [Data] [Model Codes][Slides]
Abstract: Using the expected option-implied variance reduction to measure the sensitivity of stock returns to monetary policy announcement surprises, this paper shows monetary policy announcements require significant risk compensation in the cross section of equity returns. We develop a parsimonious equilibrium model in which FOMC announcements reveal the Federal Reserve’s private information about its interest-rate target, which affects the private sector’s expectation about the long-run growth-rate of the economy. Our model accounts for the dynamics of implied variances and the cross section of the monetary policy announcement premium realized around FOMC announcement days.
Abstract: Using the expected option-implied variance reduction to measure the sensitivity of stock returns to monetary policy announcement surprises, this paper shows monetary policy announcements require significant risk compensation in the cross section of equity returns. We develop a parsimonious equilibrium model in which FOMC announcements reveal the Federal Reserve’s private information about its interest-rate target, which affects the private sector’s expectation about the long-run growth-rate of the economy. Our model accounts for the dynamics of implied variances and the cross section of the monetary policy announcement premium realized around FOMC announcement days.
Ambiguity, Information Processing, and Financial Intermediation (with Kenneth Kasa and Yulei Luo), 2024, Journal of Economic Theory, 222, 105922. [Data and Model Codes]
Abstract: This paper incorporates ambiguity and information processing constraints into the He and Krishnamurthy (2012) model of intermediary asset pricing. Financial intermediaries possess greater information processing capacity than households. In response, households optimally choose to delegate their investment decisions. The contractual relationship between households and intermediaries is subject to a moral hazard friction, which results in a financial constraint. We show that ambiguity aversion not only amplifies households' incentives to delegate but also tightens the financial constraint. The calibrated model can quantitatively explain both the unconditional and time-varying moments of observed asset prices, while endogenously generating an empirically consistent crisis frequency.
Abstract: This paper incorporates ambiguity and information processing constraints into the He and Krishnamurthy (2012) model of intermediary asset pricing. Financial intermediaries possess greater information processing capacity than households. In response, households optimally choose to delegate their investment decisions. The contractual relationship between households and intermediaries is subject to a moral hazard friction, which results in a financial constraint. We show that ambiguity aversion not only amplifies households' incentives to delegate but also tightens the financial constraint. The calibrated model can quantitatively explain both the unconditional and time-varying moments of observed asset prices, while endogenously generating an empirically consistent crisis frequency.
Announcements, Expectations, and Stock Returns with Asymmetric Information, 2025, Journal of Monetary Economics, 103751. [Appendix] [Data Codes] [Model Codes] [Slides]
Awards: 2021 Northern Finance Association Meetings Best Ph.D Student Paper Award
2020 WFA Cubist Systematic Strategic Ph.D Candidate Award for Outstanding Research
Abstract: Revisions of consensus macroeconomic and earnings forecasts positively predict announcement-day forecast errors, whereas stock market returns during forecast revision periods negatively predict announcement-day returns. A dynamic noisy rational expectations model with periodic announcements quantitatively accounts for these findings. Under asymmetric information, informed investors' forecast revisions positively predict forecast errors of the uninformed, causing average beliefs to underreact to new information and positively predict belief errors. Additionally, stock prices are partially driven by noise. Noise impact accumulates into stock prices during revision periods but gets corrected upon announcements. Therefore, revision period price changes negatively predict announcement-day returns.
Awards: 2021 Northern Finance Association Meetings Best Ph.D Student Paper Award
2020 WFA Cubist Systematic Strategic Ph.D Candidate Award for Outstanding Research
Abstract: Revisions of consensus macroeconomic and earnings forecasts positively predict announcement-day forecast errors, whereas stock market returns during forecast revision periods negatively predict announcement-day returns. A dynamic noisy rational expectations model with periodic announcements quantitatively accounts for these findings. Under asymmetric information, informed investors' forecast revisions positively predict forecast errors of the uninformed, causing average beliefs to underreact to new information and positively predict belief errors. Additionally, stock prices are partially driven by noise. Noise impact accumulates into stock prices during revision periods but gets corrected upon announcements. Therefore, revision period price changes negatively predict announcement-day returns.
Information-Driven Volatility (with Hengjie Ai and Lai Xu) [Slides] Revise & Resubmit at The Journal of Finance
Abstract: Standard asset pricing models with stochastic volatility predict a robust positive correlation between past realized volatility and future expected returns. Empirical work typically finds this relationship to be negative. We develop an asset pricing model where stock market volatility dynamics are driven by information. We show that under strong generalized risk sensitivity of preferences, information-driven volatility induces a negative correlation between past realized volatility and future expected returns. Using FOMC announcements and news-related stock market jump days to identify information events, we provide empirical evidence for the unique implications of the information-driven volatility channel.
Abstract: Standard asset pricing models with stochastic volatility predict a robust positive correlation between past realized volatility and future expected returns. Empirical work typically finds this relationship to be negative. We develop an asset pricing model where stock market volatility dynamics are driven by information. We show that under strong generalized risk sensitivity of preferences, information-driven volatility induces a negative correlation between past realized volatility and future expected returns. Using FOMC announcements and news-related stock market jump days to identify information events, we provide empirical evidence for the unique implications of the information-driven volatility channel.
Macroeconomic Announcements and the Repricing of Earnings Risk (with Ella Patelli) [Slides] Revise & Resubmit at The Review of Financial Studies
Abstract: Macroeconomic announcements trigger the repricing of previous firm-specific earnings news, generating cross-sectional heterogeneity in risk compensation. At earnings announcements, investors form joint beliefs about firm-specific fundamentals and aggregate conditions. Subsequent macroeconomic announcements reveal the aggregate state, leading investors to reassess the firm-specific component of prior earnings news. We quantify this repricing channel in a dynamic equilibrium model with learning across earnings and macroeconomic announcements. Empirical evidence supports the model's predictions: on macroeconomic announcement days, firms with recent earnings news earn lower risk premia than those without, and this effect is stronger when their earnings are more informative about aggregate conditions.
Abstract: Macroeconomic announcements trigger the repricing of previous firm-specific earnings news, generating cross-sectional heterogeneity in risk compensation. At earnings announcements, investors form joint beliefs about firm-specific fundamentals and aggregate conditions. Subsequent macroeconomic announcements reveal the aggregate state, leading investors to reassess the firm-specific component of prior earnings news. We quantify this repricing channel in a dynamic equilibrium model with learning across earnings and macroeconomic announcements. Empirical evidence supports the model's predictions: on macroeconomic announcement days, firms with recent earnings news earn lower risk premia than those without, and this effect is stronger when their earnings are more informative about aggregate conditions.
Information Acquisition and the Pre-Announcement Drift (with Hengjie Ai and Ravi Bansal) [Slides]
Abstract: We present a dynamic Grossman-Stiglitz model with endogenous information acquisition to explain the pre-FOMC announcement drift. Because FOMC announcements reveal substantial information about the economy, investors' incentives to acquire information are particularly strong days ahead of the announcements. Information acquisition partially resolves the uncertainty for uninformed traders. Under generalized risk sensitive preferences (Ai and Bansal, 2018), resolution of uncertainty is associated with realizations of risk premium, generating a pre-FOMC announcement drift. Because our theory does not rely on leakage of information, it can simultaneously explain the high average return and the low realized volatility during the pre-FOMC announcement period.
Abstract: We present a dynamic Grossman-Stiglitz model with endogenous information acquisition to explain the pre-FOMC announcement drift. Because FOMC announcements reveal substantial information about the economy, investors' incentives to acquire information are particularly strong days ahead of the announcements. Information acquisition partially resolves the uncertainty for uninformed traders. Under generalized risk sensitive preferences (Ai and Bansal, 2018), resolution of uncertainty is associated with realizations of risk premium, generating a pre-FOMC announcement drift. Because our theory does not rely on leakage of information, it can simultaneously explain the high average return and the low realized volatility during the pre-FOMC announcement period.
Monetary Policy and Anomalies (with Xi Dong and Yushui Shi) [Slides]
Abstract: Stocks that anomaly signals classify as overpriced earn higher returns than underpriced stocks on FOMC announcement days but lower returns on earnings announcement days. The CAPM explains neither. FOMC announcements amplify mispricing; earnings announcements correct it. A dynamic model jointly and quantitatively explains both. Mispricing—the gap between price and fundamental value—arises from biased cash-flow expectations. Overpriced stocks have higher cash-flow expectations and longer duration than underpriced stocks, hence higher premia for FOMC discount-rate risk. Prices rise more than fundamental values for overpriced but less for underpriced stocks, widening the gap. Earnings announcements reveal cash-flow news, narrowing the gap.
Abstract: Stocks that anomaly signals classify as overpriced earn higher returns than underpriced stocks on FOMC announcement days but lower returns on earnings announcement days. The CAPM explains neither. FOMC announcements amplify mispricing; earnings announcements correct it. A dynamic model jointly and quantitatively explains both. Mispricing—the gap between price and fundamental value—arises from biased cash-flow expectations. Overpriced stocks have higher cash-flow expectations and longer duration than underpriced stocks, hence higher premia for FOMC discount-rate risk. Prices rise more than fundamental values for overpriced but less for underpriced stocks, widening the gap. Earnings announcements reveal cash-flow news, narrowing the gap.
Uncertainty and Incentives: Theory and Evidence on Mutual Funds (with Erica Jiang, Laura Starks and Sophia Sun)
Abstract: We demonstrate that economic uncertainty influences investment decisions in the mutual fund industry through incentives. Empirically, we show that during periods of high uncertainty, the flow-performance sensitivity decreases, and fund managers engage in less active portfolio management. The evidence aligns with our optimal contracting model with moral hazard, where increased uncertainty leads investors to reduce fund flows based on performance, effectively reducing the risk borne by risk-averse managers. Moreover, increased uncertainty also diminishes the informativeness of performance, resulting in less effort in active management by fund managers. Our results imply that heightened uncertainty reduces welfare and investment efficiency not only through the traditional real options channel but also because it results in less effective incentive provisions in asset management.
Abstract: We demonstrate that economic uncertainty influences investment decisions in the mutual fund industry through incentives. Empirically, we show that during periods of high uncertainty, the flow-performance sensitivity decreases, and fund managers engage in less active portfolio management. The evidence aligns with our optimal contracting model with moral hazard, where increased uncertainty leads investors to reduce fund flows based on performance, effectively reducing the risk borne by risk-averse managers. Moreover, increased uncertainty also diminishes the informativeness of performance, resulting in less effort in active management by fund managers. Our results imply that heightened uncertainty reduces welfare and investment efficiency not only through the traditional real options channel but also because it results in less effective incentive provisions in asset management.