National and sectoral integration of Chinese and Russian stock markets with world markets jAN BABECKý , LUBOš KOMáREK AND

Keyword(s):  
2002 ◽  
Vol 5 (3) ◽  
pp. 526-548
Author(s):  
Elna Moolman ◽  
Suzanne McCoskey

It seems as if national stock markets within certain groups of countries, for example within Europe and Asia, are interdependent. But to what extent are stock markets between these groups interdependent? Is it still possible to diversify among these groups, or have globalization tied world markets together to such an extent that diversification is no longer feasible? In this study we use time series techniques to analyze the interdependence among four of the most important groups of economies, namely Europe, Latin America, Asia and the US. This will show whether it is still possible to diversify between the stock markets of these groups of economies, since stock markets within these groups seem to be interdependent to such an extent that diversification within these groups is no longer possible. On a methodological level, we compare the results of the OLS-VAR with an FM-VAR model, which is a more robust estimation procedure in the presence of non-stationary or cointegrated series.


2005 ◽  
Vol 2005 (2) ◽  
pp. 111-117
Author(s):  
Juan R. Sánchez

The multiscale behavior of a recently reported model for stock markets is presented. It has been shown that indexes of real-world markets display absolute returns with memory properties on a long-time range, a phenomenon known as cluster volatility. The multiscale characteristics of an index are studied by analyzing the power-law scaling of the volatility correlations which display nonunique scaling exponents. Here such analysis is done on an artificial time series produced by a simple model for stock markets. After comparison, excellent agreements with the multiscale behavior of real-time series are found.


1919 ◽  
Vol 120 (20) ◽  
pp. 514-515
Author(s):  
Lynn W. Meekins
Keyword(s):  

1918 ◽  
Vol 119 (21) ◽  
pp. 414-414
Author(s):  
Lynn W. Meekins
Keyword(s):  

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