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Leopoldo Catania

A Stochastic Volatility Model with a General Leverage Specification

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A Stochastic Volatility Model with a General Leverage Specification. / Catania, Leopoldo.
In: Journal of Business and Economic Statistics, Vol. 40, No. 2, 2022, p. 678-689.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review

Harvard

Catania, L 2022, 'A Stochastic Volatility Model with a General Leverage Specification', Journal of Business and Economic Statistics, vol. 40, no. 2, pp. 678-689. https://doi.org/10.1080/07350015.2020.1855187

APA

Catania, L. (2022). A Stochastic Volatility Model with a General Leverage Specification. Journal of Business and Economic Statistics, 40(2), 678-689. Advance online publication. https://doi.org/10.1080/07350015.2020.1855187

CBE

Catania L. 2022. A Stochastic Volatility Model with a General Leverage Specification. Journal of Business and Economic Statistics. 40(2):678-689. https://doi.org/10.1080/07350015.2020.1855187

MLA

Catania, Leopoldo. "A Stochastic Volatility Model with a General Leverage Specification". Journal of Business and Economic Statistics. 2022, 40(2). 678-689. https://doi.org/10.1080/07350015.2020.1855187

Vancouver

Catania L. A Stochastic Volatility Model with a General Leverage Specification. Journal of Business and Economic Statistics. 2022;40(2):678-689. Epub 2020 Jan 1. doi: 10.1080/07350015.2020.1855187

Author

Catania, Leopoldo. / A Stochastic Volatility Model with a General Leverage Specification. In: Journal of Business and Economic Statistics. 2022 ; Vol. 40, No. 2. pp. 678-689.

Bibtex

@article{6972263dd5c149b2948d2ec92db60e2c,
title = "A Stochastic Volatility Model with a General Leverage Specification",
abstract = "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.",
keywords = "Asymmetric stochastic volatility, Leverage effect, Volatility prediction",
author = "Leopoldo Catania",
year = "2022",
doi = "10.1080/07350015.2020.1855187",
language = "English",
volume = "40",
pages = "678--689",
journal = "Journal of Business and Economic Statistics",
issn = "0735-0015",
publisher = "Taylor & Francis Inc.",
number = "2",

}

RIS

TY - JOUR

T1 - A Stochastic Volatility Model with a General Leverage Specification

AU - Catania, Leopoldo

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - Asymmetric stochastic volatility

KW - Leverage effect

KW - Volatility prediction

U2 - 10.1080/07350015.2020.1855187

DO - 10.1080/07350015.2020.1855187

M3 - Journal article

VL - 40

SP - 678

EP - 689

JO - Journal of Business and Economic Statistics

JF - Journal of Business and Economic Statistics

SN - 0735-0015

IS - 2

ER -