A dynamic leverage stochastic volatility model

ABSTRACT

Stock returns are considered as a convolution of two random processes that are the return innovation and volatility innovation. The correlation of these two processes tends to be negative, which is the so-called leverage effect. In this study, we propose a dynamic leverage stochastic volatility (DLSV) model where the correlation structure between the return innovation and the volatility innovation is assumed to follow a generalized autoregressive score (GAS) process. We find that the leverage effect is reinforced in the market downturn period and weakened in the market upturn period.

KEYWORDS:

• Dynamic leverage
• GAS
• stochastic volatility (SV)

JEL CLASSIFICATION:

• C59
• C11

Acknowledgments

The computations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at HPC2N, partially funded by the Swedish Research Council through grant agreement no. 2018-05973. Financial support from Jan Wallanders and Tom Hedelius Foundation (grants number BV18-0018) is gratefully acknowledged.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

This work was supported by the Jan Wallanders och Tom Hedelius Stiftelse samt Tore Browaldhs Stiftelse [BV18-0018]; Swedish National Infrastructure for Computing [2018-05973].