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A multivariate GARCH-jump mixture model
DOI:10.1002/for.3019.png)
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
IF:
2.7
论文数:
2.3K
被引数:
3.0K
机构
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