Structural Models of Volatility
Type
applied research project
Start Date
March 1, 2019
End Date
February 28, 2022
Status
completed
Keywords
MGARCH
structural identification
Description
As a weakness, multivariate GARCH modesl are rarely identified in a strict structural sense. This means that we only can derive statstical descriptions of the volatility transmission patterns with little insight regarding the underlying economics. The aim of this project is to propose new identification strategies and to empirically study their properities.
Leader contributor(s)
Member contributor(s)
Polivka, Jeannine
Partner(s)
Prof. Dr. Helmut Herwartz, Universität Göttingen
Funder
Range
HSG + other universities
Range (De)
HSG + andere
Eprints ID
247770
Funding code
176684
6 results
Filters
Settings
Now showing 1 - 6 of 6
- Some of the metrics are blocked by yourconsent settings
Item type:Publication, - Some of the metrics are blocked by yourconsent settings
Item type:Publication, - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Identifying structural shocks to volatility through a
proxy-MGARCH model - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Structural Volatility Impulse Response Analysis(2022-06-16); We make three contributions to the volatility impulse response function (VIRF) of Hafner and Herwartz (2006), the most widely applied impulse response function in the context of multivariate volatility models. Firstly, we derive its law in the BEKK model. Secondly, we present a structural embedding of the VIRF by relying on recent developments for identification in MGARCH models. This broadens the use case of the VIRF, to date limited to historical analyses, by allowing for counterfactual and out-of-sample scenario analyses of volatility responses. Thirdly, we show how to endow the VIRF with a causal interpretation. We illustrate the merits of a structural VIRF analysis by investigating the impacts of historical shock events as well as the consequences of well-defined future shock scenarios on the U.S. equity, government bond and foreign exchange market. Our findings suggest that it is vital to be able to assess the statistical significance of volatility impulse responses.Type:conference speech - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Structural Volatility Impulse Response Analysis(2025-01-31); We make three contributions to the volatility impulse response function (VIRF) developed by Hafner and Herwartz (2006). First, we derive its law for multivariate GARCH models of the BEKK type. Second, we present a structural embedding of the VIRF, leveraging recent advancements in the identification of multivariate generalized autoregressive conditional heteroskedasticity models. Third, we show how to endow the VIRF with a causal interpretation. We illustrate the merits of a structural VIRF analysis by investigating the impacts of historical and out-of-sample shock scenarios on the U.S. equity, government bond, and foreign exchange markets.Type:journal articleJournal:Journal of Financial EconometricsScopus© Citations 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Proxy-identification of a structural MGARCH model for asset returns(2024-10-17); We extend the multivariate GARCH (MGARCH) specification for volatility modeling by developing a structural MGARCH model that targets the identification of shocks and volatility spillovers in a speculative return system. Similarly to the proxy-SVAR framework, we leverage auxiliary proxy variables to identify the underlying shock system. The estimation of structural parameters, including an orthogonal matrix, is achieved through techniques derived from Riemannian optimization. Our analysis of daily S&P 500 returns, 10-year Treasury yields, and the U.S. Dollar Index, employing news-driven instrument variables, identifies an equity and a bond market shock.Type:working paperJournal:Swiss Finance Institute Research Paper Series
