Disputation: Anton Yurchenko-Tytarenko

Doctoral candidate Anton Yurchenko-Tytarenko at the Department of Mathematics will be defending the thesis Stochastic Volterra volatility models for the degree of Philosophiae Doctor.

picture of the candidate

Doctoral candidate Anton Yurchenko-Tytarenko

 

The PhD defence will be partially digital, in Abels Utsikt, 12th floor, Niels Henrik Abels hus and streamed directly using Zoom. The host of the session will moderate the technicalities while the chair of the defence will moderate the disputation.

Ex auditorio questions: the chair of the defence will invite the audience to ask questions ex auditorio at the end of the defence. If you would like to ask a question, click 'Raise hand' and wait to be unmuted.

Trial lecture

16th of December, time: 10:15 pm, Abels Utsikt, 12 etg. Niels Henrik Abels hus, and digitally on Zoom.

"Volatility models and volatility derivatives"
  • Join the trial lecture
    The webinar opens for participation just before the trial lecture starts, participants who join early will be put in a waiting room. 

Main research findings

Financial markets have extremely complex behavior that cannot be fully modeled using classical approaches. In particular, numerous empirical studies show that market volatility exhibits some form of long-range dependence and has time-varying Hölder regularity with prominent periods of “roughness” (i.e. of Hölder order ≈0.1). These two properties are far beyond the capabilities of classical Brownian diffusions and it is challenging to reproduce them simultaneously in one model. 

In the present thesis, we suggest a novel volatility modeling framework that grasps this unconventional behavior and solves a number of technical problems that are typical for classical stochastic volatility models. Namely, our model comprises the following properties:
- flexibility in the noise: the suggested model accepts various drivers – from fractional Brownian motions with different Hurst indices to general Hölder continuous processes – to account for different option pricing
phenomenons;
- control over the moments of the price: the model ensures the existence of moments of necessary orders for the corresponding price process;
- positivity: the volatility process is strictly positive and has inverse moments to ensure reasonable behavior of martingale densities.

We also present a variety of associated numerical methods and propose practically feasible algorithms for various applications, such as the pricing of contingent claims (including options with discontinuous payoffs) and mean-square hedging.

Adjudication committee

  • Associate Professor Elisa Alòs, Universitat Pompeu Fabra
  • Professor Saul D. Jacka, University of Warwick
  • Professor Tom Lindstrøm, University of Oslo

Supervisors

Chair of defence

Professor Nils Henrik Risebro

Host of the session

Professor Tom Lindstrøm

 

Organizer

Department of Mathematics
Published Dec. 2, 2022 1:39 PM - Last modified Dec. 15, 2022 2:16 PM