.png){kind=icon}
Return
GLM-methods for volatility models
.png){kind=icon}
PRE
AI
DOI：10.1177/1471082x0800800303.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
We propose a multivariate volatility model for the behaviour of eight international equity indices. We show that many volatility models with heavy tails in financial work can be viewed as the GLM class of models with random effects in the dispersion. Hence, the h-likelihood approach, which provides efficient and simpler algorithms for GLM class, can be used as an estimation method for models used in finance. A comparison of the h-likelihood estimators with the ML estimators is made and its relative merits are discussed.
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
No journal information available
Organization
No organization information available
Cited Papers
No cited papers available