Multivariate time-varying \(G\)-\(H\) copula GARCH model and its application in the financial market risk measurement

DOI10.1155/2015/286014zbMath1395.62265OpenAlexW2101323243WikidataQ59117859 ScholiaQ59117859MaRDI QIDQ1665236

Dan Wang, Mingyong Pan, Qi'an Chen

Publication date: 27 August 2018

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2015/286014

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Statistical methods; risk measures (91G70) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Cites Work

• Estimating value at risk of portfolio by conditional copula-GARCH method
• The effects of prior outcomes on risky choice: evidence from the stock market
• Time-varying risk attitude and conditional skewness
• Some properties of the tukey g and h family of distributions
• An empirical analysis of multivariate copula models
• Value-at-Risk Prediction: A Comparison of Alternative Strategies
• The Quantitative Modeling of Operational Risk: Between G-and-H and EVT
• Unnamed Item
• Unnamed Item

This page was built for publication: Multivariate time-varying \(G\)-\(H\) copula GARCH model and its application in the financial market risk measurement