Extracting Global Stochastic Trend from Non-Synchronous Data

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

MoreLess

Year of publication:	2014
Authors:	Korhonen, Iikka
Other Persons:	Pereseckij, Anatolij A. (contributor)
Publisher:	[2014]: [S.l.] : SSRN
Subject:	Marktintegration \| Market integration \| Zustandsraummodell \| State space model \| Finanzmarkt \| Financial market \| Transformationsstaaten \| Transition countries \| Aktienmarkt \| Stock market

Extent:	1 Online-Ressource (22 p)
Series:	BOFIT Discussion Paper ; No. 15/2013
Type of publication:	Book / Working Paper
Language:	English
Notes:	Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments June 19, 2013 erstellt
Other identifiers:	10.2139/ssrn.2289790 [DOI]
Classification:	C49 - Econometric and Statistical Methods: Special Topics. Other ; c58 ; G10 - General Financial Markets. General ; G15 - International Financial Markets ; F36 - Financial Aspects of Economic Integration ; f65
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://ebvufind01.dmz1.zbw.eu/10013063552