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1. Introduction . This article investigates international stock market integration in seven major, in terms of capitalization, international stock markets over the period June 1994 to June 2009. Investigate the evolution of integration overtime by estimating ICAPM in sub-periods and applying a ro
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2. 1. Introduction This article investigates international stock market integration in seven major, in terms of capitalization, international stock markets over the period June 1994 to June 2009.
Investigate the evolution of integration overtime by estimating ICAPM in sub-periods and applying a rolling estimation technique. In addition, we connect our results to the timing of world financial crises.
Estimate and test of a dynamic version of international CAPM (ICAPM) in the absence of purchasing power parity (PPP) using a parsimonious multivariate GARCH-in-Mean (MGARCH-M) approach (Diagonal BEKK).
3. 2. Describing and analyzing data Daily US-dollar denominated returns on stock indices for international markets are used in this study. The excess stock return is computed as
The seven stock market indices are from the following markets: the United States of America (USA), the United Kingdom (UK) Sweden (SWD), Japan (JAP), China (CHI), India (IND), EMU Datastream index (EMU), one Datastream world total market return index (WORLD). To proxy the currency risk we utilize the log first difference of the trade-weighted U.S. dollar price of the currencies of major industrialized countries (TWFX).
4. 3. The dynamic ICAPM
(1)
(2)
Assuming a fully integrated global financial market for which purchasing power parity holds
5. The dynamic ICAPM
In completely segmented markets and under the same assumptions as Eq. (1), (2) the conditionally expected excess return on the country ’s market index will only depend on its country-specific risk, and can be written as
(3)
Where:
is the time-invariant price of country-specific risk.
6. The dynamic ICAPM
The conditional version of this model can be written as:
(4)
7. The dynamic ICAPM
8. Dynamic ICAPM The dynamics of risk prices can be described as:
(10)
(11)
Where: = {CONSTANT, DUSTP, USDP, WORLD} is a vector of instruments observed at the end of time t-1 and ’s are time-invariant vectors of weights.
9. 4. Econometric methodology
Instead of using full BEKK specification, we use a parsimonious GARCH process proposed by Ding and Engle (2001) diagonal BEKK to parameterize the conditional variance–covariance structure of asset returns is used.
Finally, we used full information maximum likelihood estimation (FIML) to estimate Eq. (5), (6) and (7) and Marquardt algorithm for maximizing the log-likelihood.
10. F.I.M.L. estimation of dynamic I.C.A.P.M. for seven markets.
11. Diagnostic Tests for International dynamic I.C.A.P.M.
12. Time-Varying International Stock Market Integration
13. Time-Varying International Stock Market Integration
14. 5. Conclusion In this work we analyzed market integration of major international stock markets with world stock market indicating that international stock markets have become fully integrated over the last years.
Moreover it offers empirical evidence that support the view that international financial crises influence the overall degree of integration.
Such rising interdependence may thus require prudential supervisors and security market overseers that adopt a global view.
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