scholarly journals High Frequency Newswire Textual Sentiment: Evidence from International Stock Markets During the European Financial Crisis

2015 ◽  
Author(s):  
Andreas S. Chouliaras
Keyword(s):  
Financial Crisis ◽  
Stock Markets ◽  
High Frequency ◽  
International Stock Markets

scholarly journals FINANCIAL CRISIS AND STOCK MARKET LINKAGES

2015 ◽  
Vol 23 (4) ◽  
Author(s):  
VICTOR MANUEL DE SOUSA GABRIEL ◽  
JOSE RAMOS PIRES MANSO
Keyword(s):  
Financial Crisis ◽  
Stock Markets ◽  
Global Financial Crisis ◽  
Impulse Response Functions ◽  
Vector Autoregressive ◽  
International Stock Markets ◽  
Short Run ◽  
The Global Financial Crisis ◽  
European Markets ◽  
Dot Com

This paper investigates interdependencies and linkages between international stock markets in the short-run. Thus, twelve European and non-European markets were selected, and the period from 4. October 1999 to 30 June 2011 was chosen, which includes the Dot-Com crisis and the recent Global Financial Crisis. To investigate interdependence and dynamic linkages between stock markets, a vector autoregressive model, the concept of Granger causality and impulse-response functions were considered. We concluded that the global financial crisis contributes to the intensification of the interdependence between stock markets. 

scholarly journals Predicting Contagion from the US Financial Crisis to International Stock Markets Using Dynamic Copula with Google Trends

Mathematics ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 1032 ◽  
Author(s):  
Maneejuk ◽  
Yamaka
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Stock Markets ◽  
Google Trends ◽  
Time Varying ◽  
International Stock Markets ◽  
Leading Indicator ◽  
Dynamic Copula ◽  
The Us ◽  
Us Financial Crisis

The accuracy of contagion prediction has been one of the most widely investigated and challenging problems in economic research. Much effort has been devoted to investigating the key determinant of contagion and enhancing more powerful prediction models. In this study, we aim to improve the prediction of the contagion effect from the US stock market to the international stock markets by utilizing Google Trends as a new leading indicator for predicting contagion. To improve this contagion prediction, the dynamic copula models are used to investigate the structure of dependence between international markets and the US market, before, during, and after the occurrence of the US financial crisis in 2008. We also incorporate the Google Trends data as the exogenous variables in the time-varying copula equation. Thus, the ARMAX process is introduced. To investigate the predictive power of Google Trends, we employ the likelihood ratio test. Our empirical findings support that Google Trends is a significant leading indicator for predicting contagion in seven out of 10 cases: SP-FTSE, SP-TSX, SP-DAX, SP-Nikkei, SP-BVSP, SP-SSEC, and SP-BSESN pairs. Our Google-based models seem to predict particularly well the effect of the US crisis in 2008. In addition, we find that the contribution of Google Trends to contagion prediction varies among the different stock market pairs. This finding leads to our observation that the more volatile the market time-varying correlation, the more useful Google Trends.

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