A structurally motivated stochastic volatility model for equity returns

Activity: Talk or presentationOral presentation

Description

Several researchers have proposed multiplicatively decomposing volatility into slow-moving and transient components. A recent vein in the literature has used a structural model of the firm to identify the slow-moving component as potentially stemming from the amount of financial leverage that the firm under consideration has taken on. Consequently, the transient component is interpreted as a volatility model in asset- rather than equity returns, and the slow-moving component is called a "leverage multiplier". This captures the well-known notion that leverage makes equity more risky. I use this backdrop to propose an extension of a seminal model in this literature. I argue that an autoregressive stochastic volatility model may be a better model for asset returns than its GARCH counterpart, and that the choice between the two may have non-trivial consequences in applications. I suggest a new parameterization and detail how it can be estimated. I carry out a short empirical study that demonstrates that the new model can reduce the negative correlation between returns and volatility.
Period18.12.2022
Event title16th International Conference on Computational and Financial Econometrics (CFE)
Event typeConference
LocationLondon, United KingdomShow on map
Degree of RecognitionInternational