Research
Research Interests: Empirical Asset Pricing, Derivatives/Risk Management, Credit Risk, Fixed Income
Working Papers:
(1) "Accounting Transparency and the Implied Volatility Smile "
with Hitesh Doshi, Jan Ericsson, and Fan Yu
Presentations: EasternFA 2024, AFFI 2023, FMA Europe 2023, F&A Annual Research Symposium 2023, MFA 2023, SWFA 2023, FMA 2022, World Finance 2022, BI Norwegian School of Business, Acadia University
Stock price jump risk is known to be important for explaining the option-implied volatility skew generated by the Black-Scholes model. Financial leverage (distress) has an important impact on the shape of the implied volatility skew, however, we find that the impact of leverage on the implied volatility skew depends on the quality of the firm's accounting transparency. In this paper, we propose a model where incomplete accounting information and the risk of financial distress together act as important drivers of jump rates and sizes for individual stocks. Consistent with our model, empirical tests using individual stock option data indicate that the impact of leverage on the skew is weaker for firms with lower accounting transparency and stronger for firms with higher accounting transparency.
(2) "Does News, Order Flow, or Illiquidity drive stock jumps? In the day or in the night?"
with Yoontae Jeon, and Tom McCurdy
Presentations: FMA 2023, AFFI 2023, FMA Europe 2023, EFMA 2023, NHH Finance Brownbag, Oxford Man Institute of Quantitative Finance, TMU Seminar, BI Norwegian School of Business
**EFMA 2023 Capital Markets Best Paper Award Winner**
We investigate how firm-level news, stock illiquidity, and order imbalances are reflected in stock return jumps and idiosyncratic jump risk. We analyze these relationships for the entire day as well as for the daytime and overnight trading periods. Our results show that information flows and trading frictions are significantly related to non-parametric measures of jump intensity and jump-size distributions and reveal variations over the trading day and across individual firms. Our analyses could enrich the economic content of models for stock return dynamics which typically have treated the sources of jumps as latent, and also help identify jumps due to information arrival as opposed to liquidity or strategic trading based on private information.
(3) "Weather Derivatives Variance Risk Premia"
with Joon Woo Bae (Case Western Reserve), Yoontae Jeon (McMaster), Virgilio Zurita (Baylor)
Presentations: WFA 2024 , AEFIN 2024, FutFinInfo 2024 (Poster), 4th Frontiers of Factor Investing Lancaster 2024 Conference (Poster), EasternFA 2024, Queen Mary University, Oxford Man Institute of Quantitative Finance, Case Western University, BI Norwegian School of Business, Conference on Climate and Energy Finance (Leibniz Hannover), McMaster University
We analyze the information content of a variance risk premia extracted from the weather derivatives contracts written on the local temperature of individual U.S. cities. We term this the Weather Variance Risk Premia (WVRP). By constructing the WVRP measure from the CME’s weather futures and options contracts, we examine the role of weather variance risk on bond credit spreads of local corporations and municipalities. Our results indicate informativeness of weather derivatives market as a local risk factor priced in the bond returns of local corporations and municipalities. Our result is robust to controlling state level economic uncertainty measures.
(4) "Blame it on the weather: Market Implied Weather Volatility and Firm Performance"
with Joon Woo Bae (Case Western Reserve), Yoontae Jeon (McMaster), Virgilio Zurita (Baylor)
Presentations: EEA 2024, CEMA 2024, AEFIN 2024, NEOMA Sustainable Finance Conference 2024, 2nd Structured Retail Derivatives Conference 2024, 4th Frontiers of Factor Investing Lancaster 2024 Conference , MFA 2024, Queen Mary University, Oxford Man Institute of Quantitative Finance, Case Western University, Southern Illinois University, Rochester Institute of Technology, McMaster University, BI Norwegian School of Business
We introduce a novel measure of weather risk implied from weather options' contracts. WIVOL captures risks of future temperature oscillations, increasing with climate uncertainty about physical events and regulatory policies. We find that shocks to weather volatility increase the likelihood of unexpected costs: a one-standard deviation change in WIVOL increases quarterly operating costs by 2%, suggesting that firms, on average, do not fully hedge exposures to weather risks. We estimate returns' exposure to WIVOL innovations and show that more negatively exposed firms are valued at a discount, with investors demanding higher compensations to hold these stocks. Firms' exposure to local but not foreign WIVOL predicts returns, which confirms the geographic nature of weather risks shocks.
(5) "Do asset pricing factors really price corporate bond returns?"
Presentations: BI Norwegian School of Business, University of Sherbrooke, LSE, ITAM, University of Freiberg, Western University (Ivey), UQAM, University of Massachusetts at Boston, Toulouse School of Economics PhD Student Seminar (2020), McGill Finance Brownbag (2020)
A recent literature has emerged in finance that calls for a higher hurdle in determining whether characteristics and factors predict the cross-section of stocks returns. I observe a growing Factor Zoo of discovered characteristics and factors that predict the cross-section of corporate bond returns. Once accounting for a higher benchmark in discovered characteristics and factors, many are no longer significant. In cross-sectional regressions and portfolio sorts of hundreds of characteristics and factors, on average 2.4% predict the cross- section of corporate bond returns when adjusting for higher benchmarks. A horse-race finds a higher number of corporate bond, rather than stock, characteristics and factors that predict the cross-section of corporate bond returns when adjusting for higher benchmarks. In addition to the lower number of corporate bond characteristics and factors that predict the cross-section of stock returns, my results suggest that the stock and corporate bond markets are more segmented segmented than previously documented.
(6) "Do Option-Based Measures of Stock Mispricing Find Investment Opportunities or Market Frictions? "
with Martijn Cremers, Ruslan Goyenko, and Paul Schultz
Presentations: Long Tail Alpha Hedge Fund (2021), CUHK Derivatives and Quant Investing Conference (2019), SUNY Buffalo Finance Seminar (2019), Notre Dame University Finance Brownbag (2019), McGill Finance Seminar (2018)
This paper considers a plethora of option-based measures of stock mispricing introduced by previous literature. These measures are based on differences between implied and actual stock prices, differences in implied volatilities across options, and on option trading volume. We show that stocks that these measures indicate are mispriced are small and/or hard to borrow. When small and hard-to-borrow stocks are omitted, returns to short selling are insignificant for some of the measures and greatly diminished for others. Three of the nine measures, however, predict positive abnormal stock returns for value-weighted portfolios without obvious market frictions, suggesting that they constitute investment opportunities.
Select Work in Progress:
(1) "CDO Pricing with Stochastic Asset Volatility"
with Hitesh Doshi and Jan Ericsson
Pre-PhD Research:
(1) "Leverage and Closed End Bond Funds"
with Phelim Boyle
Journal of Fixed Income. 2015, 24 (4) 47-59
Presentations: University of Waterloo (2014), Oxford University (2013)
The performance of a closed end bond fund is based on the returns of an underlying portfolio of bonds. This paper uses a structural model to assess the impact of leverage on the expected return and riskiness of a closed end bond fund. We use the model to explore the role of leverage during the financial crisis. Our model indicates that during the worst extremes of the financial crisis the debt of closed end bond funds had virtually no default risk and that the funding problems stemmed from a defective funding vehicle.