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A multivariate GARCH-jump mixture model

delete2023-09-11
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OA
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C
Chenxing Li *
J
John M. Maheu
DOI:10.1002/for.3019delete
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摘要

摘要

En 中文
This paper proposes a new parsimonious multivariate GARCH-jump (MGARCH-jump) mixture model with multivariate jumps that allows both jump sizes and jump arrivals to be correlated among assets. Dependent jumps impact the conditional moments of returns and beta dynamics of a stock. Applied to daily stock returns, the model identifies co-jumps well and shows that both jump arrivals and jump sizes are highly correlated. The jump model has better out-of-sample forecasts compared with a benchmark multivariate GARCH model.
Keyword:
beta dynamics
co-jump
jumps
multinomial
multivariate GARCH
value at risk

期刊

Journal of Forecasting 封面图
Journal of Forecasting
IF:
2.7
论文数:
2.3K
被引数:
3.0K

机构

H
hunan university
学者数:
4.5W
论文数: 3.3W
被引数: 70
M
McMaster University
学者数:
3.6W
论文数: 3.3W
被引数: 4.4W
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