Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review
Realized Wishart-GARCH : A Score-driven Multi-Asset Volatility Model. / Gorgi, P; Hansen, Peter Reinhard; Janus, P et al.
In: Journal of Financial Econometrics, Vol. 17, No. 1, 2019, p. 1-32.Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review
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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.
KW - Wishart distribution
KW - high-frequency data
KW - multivariate GARCH
KW - multivariate volatility
KW - realized covariance
KW - score
UR - http://www.scopus.com/inward/record.url?scp=85054137869&partnerID=8YFLogxK
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 -