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A dynamic leverage stochastic volatility model
Örebro University, Örebro University School of Business.ORCID iD: 0000-0002-0682-8584
Discipline of Business Analytics, The University of Sydney Business School and ACEMS, Sydney NSW, Australia.
Discipline of Business Analytics, The University of Sydney Business School and ACEMS, Sydney NSW, Australia.
2023 (English)In: Applied Economics Letters, ISSN 1350-4851, E-ISSN 1466-4291, Vol. 30, no 1, p. 97-102Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Routledge, 2023. Vol. 30, no 1, p. 97-102
Keywords [en]
Dynamic leverage, GAS, stochastic volatility (SV)
National Category
Economics
Identifiers
URN: urn:nbn:se:oru:diva-94900DOI: 10.1080/13504851.2021.1983127ISI: 000702714000001Scopus ID: 2-s2.0-85116319234OAI: oai:DiVA.org:oru-94900DiVA, id: diva2:1602705
Funder
The Jan Wallander and Tom Hedelius Foundation, BV18-0018Tore Browaldhs stiftelseSwedish National Infrastructure for Computing (SNIC), 2018-05973Available from: 2021-10-13 Created: 2021-10-13 Last updated: 2023-02-03Bibliographically approved

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Nguyen, Hoang

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