Large shocks and the September 11th terrorist attacks on international stock markets

Charles, Amélie; Darné, Olivier

doi:10.1016/j.econmod.2006.03.008

Cited by 118 publications

(64 citation statements)

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“…Firstly, many authors argue that the GARCH(1,1) specification model is the most appropriate for predicting volatility given the existence of ARCH effect in returns series (Ramlall, 2010;Nikkinen et al 2008;Charles and Darne, 2006;Bollerslev et al, 1994). Second, the choice of the GARCH model is made after a comparison with a non-linear EGARCH specification.…”

Section: Results Of Conditional Volatility Modelmentioning

confidence: 99%

Financial market interdependencies: A quantile regression analysis of volatility spillover

Rejeb

Arfaoui

2016

Research in International Business and Finance

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This paper investigates the degree and structure of interdependence between emerging (Asian and Latin American) and developed (USA and Japan) stock markets through the study of volatility spillovers for the period spanning from January 1, 1993 to October 13, 2010. Using both standard GARCH model and quantile regression approach, we find the evidence of significant interdependence between financial markets which may give evidence of volatility transmission existence. The volatility transmission is closely associated with geographical proximity as well as with crisis periods which confirm the presence of contagion. The analysis of upper and lower quantiles allows observing that the interdependence increases during bullish markets while decreases during bearish markets. Accordingly, the structure of interdependence is asymmetric for both Asian and Latin American emerging markets. These findings open up new insights for government policy makers and for managerial purposes.

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Section: Results Of Conditional Volatility Modelmentioning

confidence: 99%

Financial market interdependencies: A quantile regression analysis of volatility spillover

Rejeb

Arfaoui

2016

Research in International Business and Finance

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“…One possible explanation is that the QML-t estimator seems to estimate better the marginal variance. We tend to think that good parameter estimates lead to good volatility estimates; see Charles and Darné (2006). However, this might not be true due to non-linearities.…”

Section: Robust Estimation Of the Volatilitymentioning

confidence: 99%

Estimating GARCH volatility in the presence of outliers

2012

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“…van Dijk, Franses, and Lucas (1999) demonstrate that neglecting additive outliers frequently leads to a rejection of the null hypothesis of homoskedasticity, when it is in fact true. Tolvi (2001) and Charles and Darné (2006), however, show another possibility. That is, outliers can hide the ARCH tests of the series.…”

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confidence: 98%

Modeling the volatility of real GDP growth: The case of Japan revisited

Fang

Miller

2009

Japan and the World Economy

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Previous studies (e.g., Hamori, 2000;Ho and Tsui, 2003;Fountas et al., 2004) find high volatility persistence of economic growth rates using generalized autoregressive conditional heteroskedasticity (GARCH) specifications. This paper reexamines the Japanese case, using the same approach and showing that this finding of high volatility persistence reflects the Great Moderation, which features a sharp decline in the variance as well as two falls in the mean of the growth rates identified by Perrons (1998, 2003) multiple structural change test. Our empirical results provide new evidence. First, excess kurtosis drops substantially or disappears in the GARCH or exponential GARCH model that corrects for an additive outlier. Second, using the outlier-corrected data, the integrated GARCH effect or high volatility persistence remains in the specification once we introduce intercept-shift dummies into the mean equation. Third, the time-varying variance falls sharply, only when we incorporate the break in the variance equation. Fourth, the ARCH in mean model finds no effects of our more correct measure of output volatility on output growth or of output growth on its volatility. Journal of Economic Literature Classification: C32, E32, O40

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Large shocks and the September 11th terrorist attacks on international stock markets

Cited by 118 publications

References 50 publications

Financial market interdependencies: A quantile regression analysis of volatility spillover

Financial market interdependencies: A quantile regression analysis of volatility spillover

Estimating GARCH volatility in the presence of outliers

Modeling the volatility of real GDP growth: The case of Japan revisited

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