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Modelling the volatility transmission and conditional correlations between A and B shares in forecasting value-at-risk

✍ Scribed by Bernardo da Veiga; Felix Chan; Michael McAleer

Book ID
104042414
Publisher
Elsevier Science
Year
2008
Tongue
English
Weight
1018 KB
Volume
78
Category
Article
ISSN
0378-4754

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## Abstract Modelling of non‐stationary time series using regression methodology is challenging. The wavelet transforms can be used to model non‐stationary time series having volatility clustering. The traditional risk measure is variance and now a days Value at Risk (VaR) is widely used in finance