CANSSI National Seminar Series – Maciej Augustyniak, Nov. 26, 2020

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Seminar: 1:00-2:30pm EST
Student Session: 3:00-4:00 EST

Multifractal Discrete Stochastic Volatility


Regime-switching processes are popular tools to interpret, model and forecast financial data. The Markov-switching multifractal (MSM) model has proved to be a strong competitor to the GARCH class of models for modeling the volatility of returns. In this model, volatility dynamics are driven by a latent high-dimensional Markov chain constructed by multiplying independent two-state Markov chains. We propose the multifractal discrete stochastic volatility (MDSV) model as a generalization of the MSM process. Our model is intended to jointly model financial returns and realized volatilities, and therefore also extends existing high-dimensional Markov-switching processes to the joint setting. We also show that the MDSV process can be interpreted as a multi-component stochastic volatility model. An empirical study on a variety of financial time series shows that the MDSV model can improve upon the realized EGARCH and the realized Markov switching models in terms of fitting and forecasting performance.


Maciej Augustyniak joined the faculty of the Department of Mathematics and Statistics of the Université de Montréal in December 2013 and is now an Associate Professor. He holds a PhD in Statistics and is a former Society of Actuaries Hickman Scholar. His research interests relate to actuarial science, econometrics and quantitative finance, and his current research program aims to develop new models and methods for quantifying and managing long-term risks in actuarial and financial applications.


Student Session

The student session after the talk will allow students to ask Maciej questions about his research, the talk, the recommended paper or career opportunities. If you’re a student, make sure to register for this session.

Journal Club

The use of regime-switching models in economics and finance was popularized in the 1980s by econometrician James D. Hamilton. The emphasis early on in the literature has been on models with a relatively low number of states—between two and four. The paper by Calvet and Fisher (2004) exposes that regime-switching processes with a high-dimensional state space have the ability to generate a higher degree of volatility persistence, as is necessary to model financial data. Therefore, this paper proposes a new approach to regime-switching for financial applications. In Maciej’s talk, he will tell us more about this model and propose a generalization of it.

• Laurent E. Calvet, Adlai J. Fisher, How to Forecast Long-Run Volatility: Regime Switching and the Estimation of Multifractal Processes, Journal of Financial Econometrics, Volume 2, Issue 1, January 2004, Pages 49–83, https://doi.org/10.1093/jjfinec/nbh003

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