Modeling co-movements among financial markets: applications of multivariate autoregressive conditional heteroscedasticity with smooth transitions in conditional correlations

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2013

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Öztek, Mehmet Fatih

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The main purpose of this thesis is to assess the potential of emerging stock markets and commodity markets in attracting the attention of international investors who utilize various portfolio diversification strategies to reduce the cumulative risk of their portfolio. A successful portfolio diversification strategy requires low correlation among financial markets. However, it is now well documented that the correlations among financial markets in developed countries are very high and hence the benefits of international portfolio diversification among these markets have been very limited. This fact suggests that investors should look for alternative markets whose correlations with developed markets are low (or even negative if possible) and which have high growth potentials. In this thesis, two emerging countries' stock markets and two commodity markets are considered as alternative markets. Among emerging countries, Turkey and China are chosen due to their promising growth performance since the mid-2000s. As commodity markets, agricultural commodity and precious metal markets are selected because of the outstanding performance of the former and the "safe harbor" property of the latter. The structures and properties of dependence between these markets and stock markets in developed countries are examined by modeling the conditional correlation in the dynamic conditional correlation framework. The results reveal that upward trend hypothesis is valid for almost all correlations among market pairs and market volatility plays significant role in time varying structures of correlations.

Subject Keywords

Capital market., Finance

URI

http://etd.lib.metu.edu.tr/upload/12615713/index.pdf
https://hdl.handle.net/11511/22575

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Graduate School of Social Sciences, Thesis

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Citation Formats

M. F. Öztek, “Modeling co-movements among financial markets: applications of multivariate autoregressive conditional heteroscedasticity with smooth transitions in conditional correlations,” Ph.D. - Doctoral Program, Middle East Technical University, 2013.