Leopoldo Catania, Aarhus University

"The Leverage Effect and Propagation in Stochastic Volatility Models"


The talk is based on two papers:

• Catania (2022, Journal of Business & Economic Statistics): “A Stochastic Volatility Model With a General Leverage Specification”
We introduce a new stochastic volatility model that postulates a general correlation structure between the shocks of the measurement and log volatility equations at different temporal lags. The resulting specification is able to better characterize the leverage effect and propagation in financial time series. Furthermore, it nests other asymmetric volatility models and can be used for testing and diagnostics. We derive the simulated maximum likelihood and quasi maximum likelihood estimators and investigate their finite sample performance in a simulation study. An empirical illustration shows that the postulated correlation structure improves the fit of the leverage propagation and leads to more precise volatility predictions.

• Catania (2022, working paper): “The Leverage Effect and Propagation”
This paper proposes a new way to measure the leverage effect and its propagation over time. We show that, with respect to the newly proposed measure, common volatility models like the GJR-GARCH, the Exponential GARCH, and the asymmetric SV can be inaccurate to correctly represent the leverage effect and its propagation for financial time series. We propose to modify the variance recursion of common volatility models by including an auxiliary leverage process which allows for a proper representation of the leverage effect and its propagation over time. Empirical results indicate that the inclusion of the auxiliary leverage process is required for both in sample and out of sample analyses.

Contact person: Rasmus Søndergaard Pedersen