DescriptionSeveral 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.
|Event title||16th International Conference on Computational and Financial Econometrics (CFE)|
|Location||London, United Kingdom|
|Degree of Recognition||International|