Tag Archives: option-implied

Brooklyn Quant Experience Lecture Series: Viktor Todorov

Brooklyn Quant Experience Lecture Series, NYU Tandon

Viktor Todorov, Professor of Risk Management and Professor of Finance at the Kellogg School of Management, Northwestern University, will give the following talk on Thursday, March 18th at 9:30 AM EST. 
*Kindly note that we have changed the time to 9:30 AM on Thursdays. The new time change allows our invited international guests to join these important virtual talks.

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Meeting ID: 979 5163 8107
Password: FREBQEVT

Title

Option-Implied Semimartingale Characteristics

Abstract

We propose nonparametric methods for the recovery of the spot semimartingale characteristics of an asset price from noisy short-dated option data. The estimation is based on forming portfolios of options with different strikes that replicate the (risk-neutral) conditional characteristic function of the underlying price in a model-free way. The recovery of spot volatility is done by making use of the dominant role of the volatility in the conditional characteristic function over short time intervals and for large values of the characteristic exponent. The estimation of the tail jump variation measures, on the other hand, is based on their representation as integrals of the Laplace transforms of the jump compensator. The latter are in turn recovered from the second derivative of the option-implied characteristic function estimate, de-biased by its value at high frequencies to account for the diffusive volatility. We apply the estimation techniques to real data and illustrate the use of the extracted option-implied semimartingale characteristics in asset pricing applications.

Bio

Viktor Todorov is Harold H. Hines Jr. Professor of Risk Management and Professor of Finance at the Kellogg School of Management, Northwestern University. Professor Todorov is a Fellow of the Society for Financial Econometrics and the Journal of Econometrics. His research interests are in the areas of theoretical and empirical asset pricing, econometrics, and applied probability. He has published extensively in these fields.

His recent work focuses on the robust estimation of asset pricing models using high-frequency financial data as well as the development and application of parametric and nonparametric methods of inference for studying risks and risk premia using derivatives markets data. He currently serves as a Co-Editor for Econometric Theory and is on the editorial board of a number of leading academic journals, including Econometrica and the Journal of Econometrics. He received his Ph.D. in Economics from Duke University in 2007.