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Test for Theory of Portfolio Diversification
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 Title & Authors
Test for Theory of Portfolio Diversification
Kim, Tae-Ho; Won, Youn-Jo;
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 Abstract
This study investigates the dynamic structure of interdependence on the domestic and related major stock markets by employing a statistical framework. Finance theory predicts potential gains by international portfolio diversification if returns from investment in different national stock markets are not perfectly correlated or not cointegrated. The benefit of international diversification is limited when national stock markets are cointegrated because of the limited amount of independent variation by the presence of common factors. The statistical tests suggest that international diversification appears to be favorable after the period of the comovement of the stock prices caused by 1997 Asian financial crisis. The result reflects the increase in overseas investment and purchase of overseas funds after the early 2000`s.
 Keywords
Diversification;common stochastic trend;forecasting error;
 Language
Korean
 Cited by
1.
Variable Selection in Clustering by Recursive Fit of Normal Distribution-based Salient Mixture Model, Korean Journal of Applied Statistics, 2013, 26, 5, 821  crossref(new windwow)
2.
Statistical testings for common stochastic trends in markets under recession, Korean Journal of Applied Statistics, 2016, 29, 4, 559  crossref(new windwow)
 References
1.
김찬웅, 문규현, 홍정효 (2003). 나스닥시장의 코스닥 및 자스닥시장에 대한 정보이전 효과에 관한 연구, <재무관리연구>, 20, 163–190.

2.
지청, 조담, 양채열 (2001). 우리나라 주가변동에 대한 미국 주가의 영향, <증권학회지>, 28, 1-19.

3.
Bahmani-Oskooee, M. and Brooks, T. J. (1999). Cointegration approach to estimating bilateral trade elasticities between U.S. and her trading partners, International Economic Journal, 13, 119-128. crossref(new window)

4.
Baillie, R. T. and Bollerslev, T. (1989). The message in daily exchange rates : A conditional variance tale, Journal of Business and Economic Statistics, 7, 297–305. crossref(new window)

5.
Bessler, D. A. and Yang, J. (2003). The structure of interdependence in international stock markets, Journal of International Money and Finance, 22, 261–287.

6.
Ericsson, N. R., Hendry, D. F. and Mizon, G. E. (1998). Exogeneity, cointegration and economic policy analysis, Journal of Business and Economic Statistics, 16, 370–387.

7.
Ghosh, A., Saidi, R. and Johnson, K. H. (1999). Who moves the Asia-Pacific stock markets-US or Japan? empirical evidence based on the theory of cointegration, The Financial Review, 34, 159-170.

8.
Granger, C. (1981). Some properties of time series data and their use in econometric model specification,Journal of Econometrics, 16, 121–130.

9.
Granger, C. W. J. and Hallman, J. J. (1991). Long memory series with attractors, Oxford Bulletin of Eco-nomics and Statistics, 53, 11–26.

10.
Hall, S. G. (1989). Maximum likelihood estimation of cointegration vectors : An example of the Johansen procedure, Oxford Bulletin of Economics and Statistics, 52, 213–218.

11.
Malliaropulos, D. and Priestley, R. (1999). Mean reversion in Southeast Asian stock markets, Journal of Empirical Finance, 6, 355–384.

12.
Pantula, S. G., Gonzalo-Farias, G. and Fuller, W. A.(1994). A comparison of unit-root test criteria, Journal of Business and Economic Statistics, 12, 449–459.

13.
Pearl, J. (1995). Causal diagram for empirical research, Biometrika, 82, 669-710. crossref(new window)

14.
Phillips, P. (1998). Impulse response and forecast error variance asymptotics in nonstationary VARs, Journal of Econometrics, 83, 21–56.

15.
Swanson, N. R. and Granger, C. W. J. (1997). Impulse response functions based on a causal approach to residual orthogonalization in vector autoregressions, Journal of the American Statistical Association, 92, 357–367.

16.
Zeileis, A., Kleiker, C., Kramer, W. and Hornik, K. (2003). Testing and dating of structural changes in practice, Computational Statistics and Data Analysis, 44, 1–38.