Xiao Xiao 肖晓
Welcome to my website. Since January 2025, I am an Associate Professor in Finance at Cambridge Judge Business School, University of Cambridge. I was a Reader in finance at Bayes Business School, City University of London (2022-2024), and an Assistant Professor in Finance at Amsterdam Business School, University of Amsterdam (2020-2022).
Address: Judge Business School, Trumpington Street, Cambridge, UK, CB2 1AG
Email: xiaox@jbs.cam.ac.uk
Publications
Accepted at Review of Financial Studies.
We explore the factor structure in delta-hedged equity option returns. A sparse latent factor model generates a correlation of 0.90 or higher between average and predicted option returns. A comparable performance is achieved with a characteristic-based model containing four factors. Traditional stock return factors cannot explain these option factors.
6. Default Risk and Option Returns with Aurelio Vasquez
Management Science, 70.4 (2024): 2144-2167.
Delta-hedged option returns have a negative relation with default risk measured by credit ratings or default probability. The results are consistent with a stylized capital structure model where the negative relation is driven by firm leverage and asset volatility.
Quarterly Journal of Finance (2023), 13.1: 2350005
Uncertainty of volatilities amplifies the model risk, leading to a higher option premium charged by dealers. Volatility of volatility-increases, rather than that of volatility-decreases, contributes to the effect of implied volatility uncertainty, supporting the gambling-preference channel.
Management Science (2023), 69.3: 1375-1397
Option implied volatility change has significant cross-sectional predictive power for the underlying firms’ bond returns. The sign of predictability is different for bond returns and stock returns, consistent with Merton's capital structure model.
Journal of Financial Economics (2022), 143.1: 484-503
A portfolio that buys currencies with high equity tail beta and shorts those with low beta extracts the global component in the tail factor. The global tail factor is priced in currency carry and momentum portfolios, among other asset classes.
Journal of Financial and Quantitative Analysis (2022), 57.1: 1-27
Combining the higher moment risk premia with the second moment risk premium improves the stock market predictability over multiple horizons, both in-sample and out-of-sample.
Journal of Empirical Finance (2018), 47, 207-228
Idiosyncratic risk premium contributes to more than half of the expected return by estimating a GARCH-jump mixed model.
Working Papers
Presented at Cancun Derivatives and Asset Pricing Conference (2025), Bristol University (2025), Católica Porto Business School (2024), Hong Kong Baptist University (2024), and Vienna Graduate School of Finance (2024)
Using SEC's N-PORT filings, we provide the first systematic study of derivative use by exchange-traded funds (ETFs). We document that nearly 60% of ETFs use derivatives with greater derivative weight and exposure than mutual funds. Different ETF segments have distinct preferences for derivative use: passive ETFs rely on futures and forwards, active ETFs focus on option strategies, and leveraged ETFs primarily use swaps. Our evidence shows that derivative use shapes market competition: passive derivative users compete on cost by offering lower fees, while some active derivative users compete on quality by delivering downside protection for investors. Active derivative users exhibit reduced flow sensitivity to fees and attract more flows, even though they charge higher fees than nonusers. Our study demonstrates that the strategic use of derivatives plays an important role in ETF market competition.
This paper examines how options traders trade daily stock market mispricing measured by short-term past return and put-call option volatility spread. Anomaly return is 7.31 basis points per day when customer option traders trade along with the anomaly signal and is insignificant when they trade against it. We find that delta-hedging activities by option market makers contribute to the correction of mispricing in the stock market. In addition, institutional investors copycat customer options trades, facilitating the price discovery of mispriced stocks.
Work in Progress
We examine a new approach to selecting asset pricing factors in the factor zoo. Our novel method can: (1) identify a set of factors that have incremental information for explaining the cross-section of asset returns; (2) establish a hierarchical order to explain the importance of factors; (3) quantify unique contributions of each factor; and (4) address which factors can be subsumed by others and to what extent. In a simulation study with multiple settings for factor structures, we demonstrate that our method outperforms both stepwise regression (i.e., forward selection and backward selection) and LASSO regression. Empirically, we find that selected factors are dense instead of sparse in the stock market, corporate bond market, and options market.