EDUCATION

The Wharton School, University of Pennsylvania
Ph.D. & M.A. in Finance, 2010 - 2015

KAIST (Korea Advanced Institute of Science and Technology)
B.S. in Management Engineering & Mathematics, 2003 - 2007

PUBLISHED AND ACCEPTED PAPERS

Do Rare Events Explain CDX Tranche Spreads?, with Jessica A. Wachter

• Journal of Finance 73 (5): 2343-2383, October 2018. Internet Appendix

• Awarded Marshall Blume Prize in Financial Research, honorable mention.
  
  

Option Prices in a Model with Stochastic Disaster Risk, with Jessica A. Wachter

• Management Science 65 (8): 3449-3469, August 2019.
  
  

Learning, Slowly Unfolding Disasters, and Asset Prices, with Mohammad Ghaderi and Mete Kilic

• Journal of Financial Economics 143 (1): 527-549, January 2022. Internet Appendix

• Previously circulated under the title "Slowly unfolding disasters"
  
  

Characterizing the Variance Risk Premium: The Role of the Leverage Effect, with Guanglian Hu and Kris Jacobs

• Review of Asset Pricing Studies 12 (2): 500-542, June 2022.
  
  

Synthetic Options and Implied Volatility for the Corporate Bond Market, with Steven Chen and Hitesh Doshi

• Journal of Financial and Quantitative Analysis 58 (3): 1295-1325, May 2023. Internet Appendix

• Previously circulated under the titles "Corporate Bond VIX" and "Ex Ante Risk in the Corporate Bond Market: Evidence from Synthetic Options"

• Data: Corporate Bond VIX time series
  
  

Why Do Rational Investors Like Variance at the Peak of a Crisis? A Learning-Based Explanation, with Mohammad Ghaderi and Mete Kilic

• Journal of Monetary Economics, 142, March 2024. Internet Appendix

WORKING PAPERS

The Risk and Return of Equity and Credit Index Options, with Hitesh Doshi, Jan Ericsson, and Mathieu Fournier

• R&R at the Journal of Financial Economics

Abstract: We develop a structural credit risk model, which allows us to price equity/credit indices and their options through the asset dynamics of index constituents. We estimate the model via MLE and find that equity and credit index option prices are well explained out-of-sample. Contrary to recent empirical findings, the two option markets are not inconsistently priced through the lens of our model. Returns on both options, while extreme, do not indicate any evidence of mispricing. Our analysis suggests that jointly addressing the pricing of various instruments requires a balance between three sources of systematic risk: asset, variance, and jump risks.

Is There a Macro-Announcement Premium?, with Mohammad Ghaderi

Abstract: The conditional return volatility barely drops at macro-announcements. This is at odds with the notion that high announcement returns are a manifestation of a large announcement premium. We show that models with an announcement premium cannot explain the joint patterns of return and volatility over announcement days. Surprisingly, traditional models, which do not feature such a premium, can. Our estimation results based on a statistical setup indicate that the average announcement return is mostly attributable to the monetary policy surprise and pure small-sample components, which do not average out in-sample; the announcement premium is estimated to be small, if any.

Options on Interbank Rates and Implied Disaster Risk, with Hitesh Doshi and Hyung Joo Kim

• R&R at the Journal of Financial and Quantitative Analysis

Abstract: The identification of disaster risk has remained a significant challenge due to the rarity of macroeconomic disasters. We show that the interbank market can help characterize the time variation in disaster risk. We propose a risk-based model in which macroeconomic disasters are likely to coincide with interbank market failure. Using interbank rates and their options, we estimate our model via MLE and filter out the short-run and long-run components of disaster risk. Our estimation results are independent of the stock market and serve as an external validity test of rare disaster models, which are typically calibrated to match stock moments.

CDS-Implied Risk of Economic Catastrophes

Abstract: I develop a tail risk measure that can pinpoint a portion of systematic risk that is catastrophic. Based on the observation that episodes of economic disasters coincide with severe defaults, I define my tail risk measure as the probability that many large firms collectively default. The measure is estimated using the time series, cross section, and term structures of CDS spreads based on a model of joint defaults. Using this, I show that high catastrophic tail risk robustly predicts high future excess returns for various assets. This risk is priced, generating substantial dispersion in the cross section of stock returns.

WORK IN PROGRESS

Do Peso Problems Explain Option Pricing Puzzles?, with Mohammad Ghaderi and Mete Kilic