Xiao Xiao

Xiao Xiao 肖晓

SSRN CV

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

7. Common Factors in Equity Option Returns

with Aurelio Vasquez and Alex Horenstein

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.

5. Why Does Volatility Uncertainty Predict Equity Option Returns?

with Jay Cao, Aurelio Vasquez and Xintong Zhan

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.

4. Implied Volatility Changes and Corporate Bond Returns

with Jay Cao, Amit Goyal and Xintong Zhan

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.

3. Equity Tail Risk and Currency Risk Premia

with Juan M. Londono and Zhenzhen Fan

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.

2. Moment Risk Premia and Stock Return Predictability

with Hao Zhou and Zhenzhen Fan

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.

The Decomposition of Jump Risks in Individual Stock Returns, with Chen Zhou

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

8. From Index Trackers to Risk Managers: The Expanding Role of Derivatives in ETFs, with Aneel Keswani and Yue Zhang, 2025

Presented at Oxford-Man Institute Machine Leaning in Quantitative Finance Conference (2025), Alliance Manchester Business School (2025), 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 regulatory data from the SEC’s N-PORT filings, we provide the first systematic study of derivative use by exchange-traded funds (ETFs). Nearly 60% of ETFs use derivatives, with greater derivative weight and exposure than mutual funds. Derivative use varies across ETF types: passive ETFs primarily use futures and forwards to reduce costs, while active ETFs rely on options strategies to improve risk profiles. Despite charging higher fees, active derivative-using ETFs attract more flows and exhibit reduced fee sensitivity. We show that these flows appear to be driven by superior downside protection, suggesting that investors value this benefit. Moreover, the extent of derivative reliance predicts both improved risk profiles and higher fees. Overall, our study highlights the strategic role of derivatives in ETF market competition.

9. Signed Option Trading and Stock Market Anomalies, 2024

with Yufeng Han and Dayong Huang

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

10. Factor Selection in the Cross-section, with Chuanping Sun

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.

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