Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/212770 
Year of Publication: 
2013
Series/Report no.: 
BOFIT Discussion Papers No. 15/2013
Publisher: 
Bank of Finland, Institute for Economies in Transition (BOFIT), Helsinki
Abstract: 
We use a Kalman filter type model of financial markets to extract a global stochastic trend from the discrete non-synchronous data on daily stock market index returns of different stock exchanges. The model is tested for robustness. In addition, we derive "most important" hours of world financial market and estimate the relative importance of local versus global news for different stock markets. The model generates results that are consistent with intuition.
Subjects: 
emerging stock markets
transition economies
financial market integration
stock market returns
global stochastic trend
state space model
Kalman filter
non-synchronous data
JEL: 
C49
C58
G10
G15
F36
F65
Persistent Identifier of the first edition: 
ISBN: 
978-952-6699-18-9
Document Type: 
Working Paper

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