Estimating time-varying conditional correlations between stock and foreign exchange markets

This study explores the dynamic interaction between stock market returns and changes in nominal exchange rates. Many financial variables are known to exhibit fat tails and autoregressive variance structure. It is well-known that unconditional covariance and correlation coefficients also vary signifi...

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Bibliographic Details
Published in:Physica A 2006-02, Vol.360 (2), p.445-458
Main Author: Tastan, Hüseyin
Format: Article
Language:English
Subjects:
Exchange rates
Multivariate GARCH
News impact surface
Stock prices
Time-varying conditional correlations
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Summary:This study explores the dynamic interaction between stock market returns and changes in nominal exchange rates. Many financial variables are known to exhibit fat tails and autoregressive variance structure. It is well-known that unconditional covariance and correlation coefficients also vary significantly over time and multivariate generalized autoregressive model (MGARCH) is able to capture the time-varying variance-covariance matrix for stock market returns and changes in exchange rates. The model is applied to daily Euro-Dollar exchange rates and two stock market indexes from the US economy: Dow-Jones Industrial Average Index and S&P500 Index. The news impact surfaces are also drawn based on the model estimates to see the effects of idiosyncratic shocks in respective markets.
ISSN:0378-4371
1873-2119
DOI:10.1016/j.physa.2005.06.062