Exogenous shocks, dynamic correlations, and portfolio risk management for the Asian emerging and other global developed and emerging stock markets

ABSTRACT

This study examines the potential influence of exogenous shocks on time-varying correlations and portfolio strategies between the Asian emerging and other global stock markets including developed and other emerging markets. Using the ARMA-cDCC-FIEGARCH model with and without exogenous shocks, our results highlight the usefulness of including other global stock assets in the traditional portfolio for Asian emerging market investors. However, investors have limited opportunities to diversify their assets during the global financial crisis. Moreover, the shocks from the U.S. stock market have a greater influence on global stock markets compared to that from U.S. economic policy. Fortunately, the model with exogenous shocks improves its accuracy, which plays the same role of controlling structural breaks in the model. More importantly, incorporating exogenous shocks in our model also provides better value-at-risk performance results and hedging effectiveness. These results have several important implications for investors, researchers, and policymakers.

KEYWORDS:

• Stock markets
• exogenous shocks
• dynamic correlations
• portfolio strategy
• ARMA-cDCC-FIEGARCH

JEL CLASSIFICATION:

• C58
• F36
• G11
• G15

Highlights

• The influence of exogenous shocks on time-varying correlations and portfolio strategies is analysed.

• The ARMA-cDCC-FIEGARCH models with and without exogenous shocks are used.

• The diversified portfolios comprising of Asian emerging and other global stock assets reduce risk.

• The model with exogenous shocks improves the accuracy of the model, as does structural breaks in the model.

• Incorporating exogenous shocks in the model provides better portfolio strategies.

Acknowledgments

The authors appreciate the anonymous reviewers, as well as Professor Mark Taylor, Editor-in-Chief of ‘Applied Economics’, for their valuable comments and suggestions. The first author (X. Dong) is grateful for Research Project Supported by Shanxi Scholarship Council of China. The third author (S.-M. Yoon) is thankful for the financial support from the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2017S1A5B8057488).

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ The MSCI world index includes: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Hong Kong, Ireland, Israel, Italy, Japan, Netherlands, New Zealand, Norway, Portugal, Singapore, Spain, Sweden, Switzerland, United Kingdom, and the United States.

² The MSCI emerging markets ex Asia index includes: Brazil, Chile, Colombia, Czech Republic, Egypt, Greece, Hungary, Mexico, Peru, Poland, Russia, Qatar, South Africa, Turkey, and United Arab Emirates.

³ All daily VIX index is provided by the Chicago Board Options Exchange (www.cboe.com).

⁴ All U.S. daily EPU index is provided by Economic Policy Uncertainty (www.policyuncertainty.com).

⁵ Here, we choose the appropriate lag order of the ARMA and ARCH process in the return and variance equations to better capture the features of the cDCC-FIEGARCH model. Specifically, we select the ARMA(1,0)-cDCC-FIEGARCH(1,d,1) model for the Singapore market and the ARMA(1,1)-cDCC-FIEGARCH(1,d,2) model for the Malaysia market, and the ARMA(1,1)-cDCC-FIEGARCH(1,d,1) model for other remaining markets.

⁶ The results for the rest of the indices are similar to those for the three indices mentioned above. To save space, the results are not reported and are available on request.

Additional information

Funding

This work was supported by the National Research Foundation of Korea [NRF-2017S1A5B8057488];Shanxi Scholarship Council of China [No. 115640901004].