Department of Economics and Business Economics

Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Standard

Realized Wishart-GARCH : A Score-driven Multi-Asset Volatility Model. / Gorgi, P; Hansen, Peter Reinhard; Janus, P; Koopman, S J.

In: Journal of Financial Econometrics, Vol. 17, No. 1, 2019, p. 1-32.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Harvard

Gorgi, P, Hansen, PR, Janus, P & Koopman, SJ 2019, 'Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model', Journal of Financial Econometrics, vol. 17, no. 1, pp. 1-32. https://doi.org/10.1093/jjfinec/nby007

APA

CBE

MLA

Gorgi, P et al. "Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model". Journal of Financial Econometrics. 2019, 17(1). 1-32. https://doi.org/10.1093/jjfinec/nby007

Vancouver

Author

Gorgi, P ; Hansen, Peter Reinhard ; Janus, P ; Koopman, S J. / Realized Wishart-GARCH : A Score-driven Multi-Asset Volatility Model. In: Journal of Financial Econometrics. 2019 ; Vol. 17, No. 1. pp. 1-32.

Bibtex

@article{0d3de8d0780f4775a48099eb410527fa,
title = "Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model",
abstract = "We propose a novel multivariate GARCH model that incorporates realized measures for the covariance matrix of returns. The joint formulation of a multivariate dynamic model for outer-products of returns, realized variances, and realized covariances leads to a feasible approach for analysis and forecasting. The updating of the covariance matrix relies on the score function of the joint likelihood function based on Gaussian and Wishart densities. The dynamic model is parsimonious while the analysis relies on straightforward computations. In a Monte Carlo study, we show that parameters are estimated accurately for different small sample sizes. We illustrate the model with an empirical in-sample and out-of-sample analysis for a portfolio of 15 U.S. financial assets.",
author = "P Gorgi and Hansen, {Peter Reinhard} and P Janus and Koopman, {S J}",
year = "2019",
doi = "10.1093/jjfinec/nby007",
language = "English",
volume = "17",
pages = "1--32",
journal = "Journal of Financial Econometrics",
issn = "1479-8409",
publisher = "Oxford University Press",
number = "1",

}

RIS

TY - JOUR

T1 - Realized Wishart-GARCH

T2 - A Score-driven Multi-Asset Volatility Model

AU - Gorgi, P

AU - Hansen, Peter Reinhard

AU - Janus, P

AU - Koopman, S J

PY - 2019

Y1 - 2019

N2 - We propose a novel multivariate GARCH model that incorporates realized measures for the covariance matrix of returns. The joint formulation of a multivariate dynamic model for outer-products of returns, realized variances, and realized covariances leads to a feasible approach for analysis and forecasting. The updating of the covariance matrix relies on the score function of the joint likelihood function based on Gaussian and Wishart densities. The dynamic model is parsimonious while the analysis relies on straightforward computations. In a Monte Carlo study, we show that parameters are estimated accurately for different small sample sizes. We illustrate the model with an empirical in-sample and out-of-sample analysis for a portfolio of 15 U.S. financial assets.

AB - We propose a novel multivariate GARCH model that incorporates realized measures for the covariance matrix of returns. The joint formulation of a multivariate dynamic model for outer-products of returns, realized variances, and realized covariances leads to a feasible approach for analysis and forecasting. The updating of the covariance matrix relies on the score function of the joint likelihood function based on Gaussian and Wishart densities. The dynamic model is parsimonious while the analysis relies on straightforward computations. In a Monte Carlo study, we show that parameters are estimated accurately for different small sample sizes. We illustrate the model with an empirical in-sample and out-of-sample analysis for a portfolio of 15 U.S. financial assets.

U2 - 10.1093/jjfinec/nby007

DO - 10.1093/jjfinec/nby007

M3 - Journal article

VL - 17

SP - 1

EP - 32

JO - Journal of Financial Econometrics

JF - Journal of Financial Econometrics

SN - 1479-8409

IS - 1

ER -