Research

Disclaimer: The views in these papers do not necessarily reflect the views of the Office of the Comptroller of the Currency, the US Department of the Treasury, or any federal agency and do not establish supervisory policy, requirements, or expectations.

Publications

The Informational Role of Forex Option Volume

(with Kun Bao, Chen Gu, Erlina Papakroni, Raluca Stan, and Muhan Wang), International Review of Financial Analysis, 100 (2025), 1057-5219.

This paper investigates the effect of foreign exchange (FX) option trading volume on the underlying EUR/USD futures market. Our in-sample and out-of-sample tests show that the FX put-call volume ratio can predict future exchange rate changes. Greater put-call volume ratios predict a depreciation of the Euro relative to the US dollar. The predictability is prevalent in times of high uncertainty in the FX market, and is stronger during crisis than non-crisis periods. We use a predictive regression forecast model based on the put-call ratio to propose a trading strategy that performs better than the simple strategy of buying and holding Euros, or than the strategy of trading based on the prevailing mean forecast method. Overall, trading volume in the FX option market seems to facilitate information flow into the underlying FX futures market.

Estimation of Discrete Choice Network Models with Missing Outcome Data

(with Hua Kiefer and Xiaodong Liu), Regional Science and Urban Economics, 97 (2022), 103835.

This paper studies the problem of missing observations on the outcome variable in a discrete choice network model. The research question is motivated by an empirical study of the spillover effect of home mortgage delinquencies, where mortgage repayment decisions can only be observed for a sample of all the borrowers in the study region. We show that the nested pseudo-likelihood (NPL) algorithm can be readily modified to address this missing data problem. Monte Carlo simulations indicate that the proposed estimator works well in finite samples and ignoring this issue leads to a severe downward bias in the estimated spillover effect. We apply the proposed estimation procedure using data on single-family residential mortgage delinquencies in Clark County of Nevada in 2010, and find strong evidence of the spillover effect. We also conduct some counterfactual experiments to illustrate the importance of consistently estimating the spillover effect in policy evaluation.

It is not just What you say, but How you say it: Why Tonality Matters in Central Bank Communication 

(with Chen Gu, Raluca Stan, and Aizhong Shen), Journal of Empirical Finance, 68 (2022), 216-231.

This paper investigates the stock market reaction to the tone of central bank communication. We use textual analysis techniques to measure the tonality of the FOMC minutes’ text and show that a more optimistic tonality has a positive impact on stock returns. This positive effect is prevalent during times of high monetary policy uncertainty and comes mainly from the effect tonality has on risk premium and growth expectations. Our results show that the FOMC minutes are an effective central bank communication tool, particularly during times of high policy uncertainty.

Resolution of Financial Market Uncertainty around the release of Unemployment Rate Announcements 

(with Chen Gu and Raluca Stan), International Review of Economics and Finance, 80 (2022), 586-596. 

We provide evidence that the release of the unemployment rate announcement unconditionally leads to financial market uncertainty resolution in the stock, treasury, commodity, and foreign currency markets. The finding is economically valuable. A simple daily strategy of selling the 10-year Treasury Note Volatility Index futures before the unemployment rate announcement and closing the position after the announcement generates an annualized Sharpe ratio of 3.79, while a similar intraday strategy using VIX futures generates an annualized Sharpe ratio of 3.98. Although this resolution is not conditional of the value of the unemployment rate surprise, we also find that larger (lower) than expected unemployment can weaken (strengthen) the uncertainty resolution process.

The Role of Investor Sentiment and Market Reaction to Macroeconomic News 

(with Chen Gu and Raluca Stan), Journal of Futures Markets, 41 (2021), 1412-1426. 

We provide evidence that the stock market response to macroeconomic news weakens in times of high investor sentiment. The reaction to macroeconomic information is 50% weaker in times of elevated bullish investor sentiment, relative to periods of low sentiment. This dampening effect holds for both good and bad macroeconomic news. Investor sentiment seems to hinder the incorporation of public information into asset prices. Our findings shed new light on how investor sentiment affects the link between fundamentals and security prices.

Risk Aversion Decomposition and the Impact of Monetary Policy Surprises on Aggregate Tail Risk Aversion 

Journal of Risk Finance, 19 (2018), 564-590.

This paper extends the jump-diffusion model to extract the fear component towards rare events from traditional representative agent’s risk aversion. The model implicates that investor’s fear of tail jumps in the financial market impacts equity risk premium. It also provides empirical findings that both positive stock market and monetary policy shocks decrease investor’s fear. It can be attributed that a bullish stock market and an increase in interest rate reflects expanding economy, and it leads to a decrease in overall risk aversion. The results also show that a surprise decline in the expected short-term rate has a positive effect on stock prices and mixed impact on tail risk aversion. A plausible explanation is that investors believe a surprise drop in expected short-term rate reflects a fast deteriorating economic outlook during unconventional monetary policy period.

Post-Accident Stock Returns of Aircraft Manufacturers Based on Potential Fault 

(with Kevin Krieger), Journal of Air Transport Management, 43 (2015), 20-28. 

The literature has considered the market's response to the stocks of commercial airline carriers after their flights are involved in accidents. The aircraft manufacturer stock price, in the wake of a crash, has received considerably less attention in the literature. We analyze this response over a modern sample period and determine that a quick downturn of nearly 50 basis points of negative abnormal return accompanies the typical accident. Careful consideration of the cause of the accident, however, reveals a striking difference in market reaction based on the potential fault of the manufacturer. Market reactions are initially significantly negative when the manufacturer is judged to have potential fault in the incident but are otherwise insignificant. The market makes this determination even though there is often some ambiguity surrounding an accident's circumstances. We also find that manufacturer stock prices continue to drift significantly downward in the weeks following accidents that are deemed to potentially involve manufacturer fault. However, prices rebound significantly from the smaller initial downward reaction when no fault is linked to the manufacturer and actually demonstrate positive abnormal returns weeks after an accident.

VIX Changes and Derivative Returns on FOMC Meeting Days 

(with Kevin Krieger and Nathan Mauck), Financial Markets and Portfolio Management, 26 (2012), 315-331. 

We examine the link between scheduled Federal Open Market Committee (FOMC) meetings and the VIX measure. Our results indicate that VIX declines significantly on scheduled meeting dates. Unlike prior studies suggesting that the drop in VIX is mechanical, we attribute the decline to the resolution of uncertainty regarding future interest rates provided by the meetings. We examine returns to investable positions on VIX. Though a decline in the VIX level commonly occurs on FOMC meeting dates, we find that significant returns may still be garnered from taking short-VIX positions in derivative markets, even after accounting for the bid-ask spread.

Working papers

Does Social Media Attention Foretell Stock Trading Activities? Evidence from Twitter Attention 

(with Chen Gu, Raluca Stan, and Jing Lu)

This paper investigates the impact of Twitter attention, measured by abnormal number of tweets on stock trading activities. We find that Twitter attention has predictive power for future stock volatility and trading volume. A heightened number of tweets is followed by high volatility and trading volume over the next trading day. This finding is robust when focusing on international markets and controlling for other attention measures. We also find that high Twitter attention strengthens stock price adjustment to recommendation changes whereas it alleviates post-announcement price drift. These findings suggest that market underreaction to new information is related to limited investor attention from social media.