Dynamic Currency Linkages and Their Determinants: An Empirical Study for East Asian Economic Community Region

References

• Aggarwal, R., and M. Mougoue. 1996. Cointegration among Asian currencies: Evidence of the increasing influence of the Japanese yen. Japan and the World Economy 8 (3):291–308. doi:10.1016/0922-1425(96)88806-2.
   Web of Science ®Google Scholar
• Ahmad, W., S. Sehgal, and N. Bhanumurthy. 2015. Regime dependent dynamics and European stock markets: Is asset allocation really possible? Empirica 42 (1):77–107. doi:10.1007/s10663-014-9248-0.
   Web of Science ®Google Scholar
• Albulescu, C. T., C. Aubin, D. Goyeau, and A. K. Tiwari. In press. Extreme co-movements and dependencies among major international exchange rates: A copula approach. Quarterly Review of Economics and Finance.
   Google Scholar
• Aloui, R., S. Hammoudeh, and D. K. Nguyen. 2013. A time-varying copula to oil and stock market dependence: The case of transition economies. Energy Economics 39:208–21. doi:10.1016/j.eneco.2013.04.012.
   Web of Science ®Google Scholar
• Ang, A., and G. Bekaert. 2002. International asset allocation with regime shifts. Review of Financial Studies 15:1137–87. doi:10.1093/rfs/15.4.1137.
   Web of Science ®Google Scholar
• Angelini, P., A. Nobili, and C. Picillo. 2011. The interbank market after August 2007: What has changed, and why? Journal of Money, Credit and Banking 43 (5):923–58. doi:10.1111/jmcb.2011.43.issue-5.
   Web of Science ®Google Scholar
• Antonakakis, N. 2012. Exchange return co-movements and volatility spillovers before and after the introduction of euro. Journal of International Financial Markets, Institutions and Money 22 (5):1091–109. doi:10.1016/j.intfin.2012.05.009.
   Web of Science ®Google Scholar
• Arellano, M., and S. Bond. 1991. Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The Review of Economic Studies 58 (2):277–97. doi:10.2307/2297968.
   Web of Science ®Google Scholar
• Arellano, M., and O. Bover. 1995. Another look at the instrumental variable estimation of error-components models. Journal of Econometrics 68 (1):29–51. doi:10.1016/0304-4076(94)01642-D.
   Web of Science ®Google Scholar
• Arfaoui, M., and E. Abaoub. 2010. On the determinants of international financial integration in the global business area. Journal of Applied Economic Sciences 5 (3):153–72.
   Google Scholar
• AuYong, H. H., C. Gan, and S. Treepongkaruna. 2004. Cointegration and causality in the Asian and emerging foreign exchange markets: Evidence from the 1990s financial crises. International Review of Financial Analysis 13 (4):479–515. doi:10.1016/j.irfa.2004.02.024.
   Google Scholar
• Azali, M., and L. Chin. 2008. Asian financial integration during the pre- and post-crisis periods. Journal of International Economic Review 2:103–12.
   Google Scholar
• Baig, T. 2001. Characterizing exchange rate regimes in post-crisis East Asia. IMF Working Paper 01/125. doi:10.5089/9781451857092.001.
   Google Scholar
• Baltagi, B. H. 2008. Econometric Analysis of Panel Data, 4th ed. Chichester, UK: John Wiley and Sons Ltd.
   Google Scholar
• Bank of International Settlements (BIS). 2013. Triennial Central Bank Survey Foreign exchange turnover in April 2013: Preliminary global results. Basel, Switzerland: Bank of International Settlements.
   Google Scholar
• Bank of International Settlements (BIS). 2016. Triennial Central Bank Survey of foreign exchange and OTC derivatives markets. Basel, Switzerland: Bank of International Settlements.
   Google Scholar
• Basher, S. A., N. Salem, and Z. Hui. 2014. Dependence patterns across Gulf Arab stock markets: A copula approach. Journal of Multinational Financial Management 25–26:30–50. doi:10.1016/j.mulfin.2014.06.008.
   Google Scholar
• Bekiros, S., and M. Marcellino. 2013. The multiscale causal dynamics of foreign exchange markets. Journal of International Money and Finance 33 (March):282–305. doi:10.1016/j.jimonfin.2012.11.016.
   Web of Science ®Google Scholar
• Blundell, R., and S. Bond. 1998. Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics 87 (1):115–43. doi:10.1016/S0304-4076(98)00009-8.
   Web of Science ®Google Scholar
• Boero, G., P. Silvapulle, and A. Tursunalieva. 2011. Modelling the bivariate dependence structure of exchange rates before and after the introduction of the euro: A semi-parametric approach. International Journal of Finance & Economics 16 (4):357–74. doi:10.1002/ijfe.434.
   Web of Science ®Google Scholar
• Bollerslev, T. 1987. A conditionally heteroskedastic time series model for speculative prices and rates of return. Review of Economics and Statistics 69:542–47. doi:10.2307/1925546.
   Web of Science ®Google Scholar
• Bound, J., D. Jaeger, and R. Baker. 1995. Problems with instrumental variables estimation when the correlation between the instruments and the endogenous explanatory variables is weak. Journal of American Statistical Association 90(430):443–50.
   Web of Science ®Google Scholar
• Bowsher, C. G. 2002. On testing overidentifying restrictions in dynamic panel data models. Economics Letters 77 (2):211–20. doi:10.1016/S0165-1765(02)00130-1.
   Web of Science ®Google Scholar
• Brock, W. A., W. D. Dechert, B. LeBaron, and J. A. Scheinkman. 1996. A test for independence based on the correlation dimension. EconometricReviews 15:197–235.
   Google Scholar
• Brunnermeier, M. K., S. Nagel, and L. H. Pedersen. 2008. Carry trades and currency crashes. NBER Macroeconomics Annual 23:313–47. doi:10.1086/593088.
   Google Scholar
• Büttner, D., and B. Hayo. 2011. Determinants of European stock market integration. Economic Systems 35 (4):574–85. doi:10.1016/j.ecosys.2010.10.004.
   Web of Science ®Google Scholar
• Calvo, G., L. Leiderman, and C. Reinhart. 1993. Capital inflows and real exchange rate appreciation in Latin America: The role of external factors. IMF Staff Papers 40 (1):108–51. doi:10.2307/3867379.
   Google Scholar
• Calvo, S., and C. Reinhart. 1996. Capital flows to Latin America: Is there evidence of contagion effects?. In Private capital flows to emerging markets after the Mexican crisis, eds. G. Calvo, M. Goldstein, and E. Hochreiter. Washington, DC: Institute for International Economics.
   Google Scholar
• Cappiello, L., R. Engle, and K. Sheppard. 2006. Asymmetric dynamics in the correlations of global equity and bond returns. Journal of Financial Econometrics 4:537–72. doi:10.1093/jjfinec/nbl005.
   Google Scholar
• Chan, K. C., L. T. Cheng, and M. S. Pan. 1997. Market efficiency and cointegration: Some evidence in Pacific-basin black exchange markets. Journal of Economics and Finance 21 (1):25–31. doi:10.1007/BF02929019.
   Google Scholar
• Chinn, M. D., and H. Ito. 2006. What matters for financial development? capital controls, institutions, and interactions. Journal of Development Economics 81 (1):163–92. doi:10.1016/j.jdeveco.2005.05.010.
   Web of Science ®Google Scholar
• Ciner, C. 2011. Information transmission across currency futures market: Evidence from frequency domain tests. International Review of Financial Analysis 20:134–39. doi:10.1016/j.irfa.2011.02.010.
   Web of Science ®Google Scholar
• Clayton, D. G. 1978. A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence. Biometrika 65:141–52. doi:10.1093/biomet/65.1.141.
   Web of Science ®Google Scholar
• Combes, J., T. Kinda, and P. Plane. 2012. Capital flows, exchange rate flexibility, and the real exchange rate. IMF Working Paper 11/9. Washington, DC: International Monetary Fund.
   Google Scholar
• Crowder, W. J. 1994. Foreign exchange market efficiency and common stochastic trends. Journal of International Money and Finance 13 (5):551–64. doi:10.1016/0261-5606(94)90004-3.
   Web of Science ®Google Scholar
• Da Silva Filho, O. C., F. A. Ziegelmann, and M. J. Dueker. 2012. Modeling dependence dynamics through copulas with regime switching. Insurance: Mathematics and Economics 50:346–56.
   Web of Science ®Google Scholar
• Dias, A., and P. Embrechts. 2010. Modeling exchange rate dependence dynamics at different time horizons. Journal of International Money and Finance 29 (8):1687–705. doi:10.1016/j.jimonfin.2010.06.004.
   Web of Science ®Google Scholar
• Edwards, S., J. Biscarri, and F. Perez De Gracia. 2003. Stock market cycles, financial liberalization and volatility. Journal of International Money and Finance 22 (7):925–55. doi:10.1016/j.jimonfin.2003.09.011.
   Web of Science ®Google Scholar
• Engel, C., and J. D. Hamilton. 1990. Long swings in the dollar: Are they in the data and do markets know it? American Economic Review 80:689—713.
   Web of Science ®Google Scholar
• Engel, C., N. Mark, and K. West. 2012. Factor model forecasts of exchange rates. Unpublished working paper, University of Wisconsin and University of Notre Dame
   Google Scholar
• Engle, R. 2002. Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics 20:339–50. doi:10.1198/073500102288618487.
   Web of Science ®Google Scholar
• Faruqee, H. 1995. Long-run determinants of the real exchange rate: A stock-flow perspective. IMF Staff Papers 42:80–107.
   Google Scholar
• Fernandez, V. 2008. Copula-based measures of dependence structure in assets returns. Physica A: Statistical Mechanics and Its Applications 387 (14):3615–28. doi:10.1016/j.physa.2008.02.055.
   Web of Science ®Google Scholar
• Fratzscher, M. 2009. What explains global exchange rate movements during the financial crisis. Journal of International Money and Finance 28:1390–407. doi:10.1016/j.jimonfin.2009.08.008.
   Web of Science ®Google Scholar
• Genest, C., B. Rémillard, and D. Beaudoin. 2009. Goodness-of-fit tests for copulas: A review and a power study. Insurance. Mathematics and Economics 44:199–213. doi:10.1016/j.insmatheco.2007.10.005.
   Web of Science ®Google Scholar
• Gharleghi, B., N. Shafighi, and B. Fah. 2015. Financial integration and common CurrencyArea in ASEAN. Journal of Economics, Business and Management 3 (1):111–14. doi:10.7763/JOEBM.2015.V3.164.
   Google Scholar
• Gill, I., N. Sugawara, and J. Zalduendo. 2014. The center still holds: Financial integration in the Euro area. Comparative Economic Studies 56:351. doi:10.1057/ces.2014.15.
   Google Scholar
• Gjika, D., and R. Horvath. 2013. Stock market comovements in Central Europe: Evidence from asymmetric DCC model. Economic Modelling 33:55–64. doi:10.1016/j.econmod.2013.03.015.
   Web of Science ®Google Scholar
• Guesmi, K., D.-K. Nguyen, and F. Teulon. 2013. Further evidence on the determinants of regional stock markets integration in Latin America. European Journal of Comparative Economics 34 (1):397–413.
   Google Scholar
• Gumbel, E. J. 1960. Bivariate exponential distributions. Journal of the American Statistical Association 55:698–707. doi:10.1080/01621459.1960.10483368.
   Web of Science ®Google Scholar
• Hall, S. G., and M. Ahmad. 2014. Revisiting the institutions-growth Nexus in developing countries: The new evidence. New Zealand Economic Papers 48 (3):301–12. doi:10.1080/00779954.2013.867795.
   Google Scholar
• Hamilton, J. D. 1994. Time series analysis New Jersey. USA: Princeton University Press.
   Google Scholar
• Hansen, L. P. 1982. Large sample properties of generalized method of moments estimators. Econometrica: Journal of the Econometric Society 1029–54. doi:10.2307/1912775.
   Web of Science ®Google Scholar
• Huoy, C. W., and K. L. Goh. 2007. The determinants of stock market integration: A panel data investigation. 15th Annual Conference on Pacific Basin Finance, Economics, Accounting and Management, Ho Chi. Minh City, Vietnam, July 20 & 21.
   Google Scholar
• Ito, T., P. Isard, and S. Symansky. 1997. Economic growth and real exchange rate: An overview of the Balassa-Samuelson hypothesis in Asia. In Changes in exchange rates in rapidly developing countries: Theory, practice, and policy issues (NBER-EASE volume 7), eds. T. Ito and A. O. Krueger, 109–32. Chicago: University of Chicago Press.
   Google Scholar
• Jeon, B. N., and E. Lee. 2002. Foreign exchange market efficiency, cointegration, and policy coordination. Applied Economics Letters 9 (1):61–68. doi:10.1080/13504850110049351.
   Web of Science ®Google Scholar
• Jondeau, E., and M. Rockinger. 2006. The copula–GARCH model of conditional dependencies: An international stock-marketapplication. Journal of International Money and Finance 25 (5):827–53. doi:10.1016/j.jimonfin.2006.04.007.
   Web of Science ®Google Scholar
• Kim, B. H., S. E. Jeong, and H. G. Min. 2010. Export similarity, FDI and Yen-synchronization of East Asian currencies: Regime switching regression model and microstructural analysis. Working paper. Available at SSRN: https://ssrn.com/abstract=1588368 or http://dx.doi.org/10.2139/ssrn.1588368.
   Google Scholar
• Kim, B. H., H. Kim, and H. G. Min. 2013. Reassessing the link between the Japanese yen and emerging Asian currencies. Journal of International Money and Finance 33:306–26. doi:10.1016/j.jimonfin.2012.11.021.
   Web of Science ®Google Scholar
• Kim, M. S., and S. Wang. 2006. On the application of stochastic volatility models. Comput.Stat.Data Anal. 51 (4):2210–17. doi:10.1016/j.csda.2006.08.002.
   Web of Science ®Google Scholar
• Kojadinovic, I., and J. Yan. 2011. A goodness-of-fit test for multivariate multiparameter copulas based on multiplier central limit theorems. Statistics and Computing 21 (1):17–30. doi:10.1007/s11222-009-9142-y.
   Web of Science ®Google Scholar
• Komarkova, Z., and L. Komarek. 2007. Integration of the foreign exchange markets of theselected EU new member states. Politickáekonomie 55 (3):315–33.
   Google Scholar
• Kumar, N., ed. (2004). Towards and Asian economic community: Vision of a New Asia, New Delhi & Singapore. RIS and ISEAS 91–108.
   Google Scholar
• Lane, P. R., and G. M. Milesi-Ferretti. 2004. The transfer problem revisited: Net foreign assets and real exchange rates. Review of Economics and Statistics. doi:10.1162/0034653043125185.
   Web of Science ®Google Scholar
• Lartey, E. K., F. S. Mandelman, and P. A. Acosta. 2012. Remittances, exchange rate regimes and the Dutch disease: A panel data analysis. Review of International Economics 20 (2):377–95. doi:10.1111/j.1467-9396.2012.01028.x.
   Web of Science ®Google Scholar
• Longin, F., and B. Solnik. 2001. Extreme correlation of international equity market. Journal of Finance 56:649−676. doi:10.1111/0022-1082.00340.
   Web of Science ®Google Scholar
• Maheu, J., T. McCurdy, and Y. Song. 2010. Components of bull and bear markets, bull corrections and bear rallies. Working Paper, University of Toronto.
   Google Scholar
• Malevergne, Y., and D. Sornette. 2003. Testing the Gaussian copula hypothesis for financial assets dependences. Quantitative Finance 3:231–50. doi:10.1088/1469-7688/3/4/301.
   Web of Science ®Google Scholar
• Mandelbrot, B. B. 1963. The variation of certain speculative prices. Journal of Business XXXVI (1963):392–417.
   Google Scholar
• Nelson, D. B. 1991. Conditional heteroskedasticity in asset returns: A new approach. Econometrica 59:347–70. doi:10.2307/2938260.
   Web of Science ®Google Scholar
• Ng, L., B. Solnik, E. Wu, and B. Zhang. 2013. Characterizing global financial and economic integration using cash flow expectations. Working paper of University of Wisconsin- Milwaukee.
   Google Scholar
• Nickell, S. 1981. Biases in dynamic models with fixed effects. Econometrica: Journal of the Econometric Society 1417–26. doi:10.2307/1911408.
   Web of Science ®Google Scholar
• Ning, C. 2010. Dependence structure between the equity market and the foreign exchange market–A copula approach. Journal of International Money and Finance 29:743–59. doi:10.1016/j.jimonfin.2009.12.002.
   Web of Science ®Google Scholar
• O’Connell Paul, G. J. 1998. The overvaluation of purchasing power parity. Journal of International Economics 44:1–19. doi:10.1016/S0022-1996(97)00017-2.
   Web of Science ®Google Scholar
• Patton, A. J. 2006a. Modelling asymmetric exchange rate dependence. International Economic Review 47 (2):527–56. doi:10.1111/iere.2006.47.issue-2.
   Web of Science ®Google Scholar
• Patton, A. J. 2006b. Estimation of multivariate models for time series of possibly different lengths. Journal of Applied Econometrics 21 (2):147–73. doi:10.1002/(ISSN)1099-1255.
   Web of Science ®Google Scholar
• Peng, Y., and W. Ng. 2012. Analysing financial contagion and asymmetric market dependence with volatility indices via copulas. Annals of Finance 8:49–74.
   Google Scholar
• Poon, S.-H., M. Rockinger, and J. Tawn. 2004. Extreme value dependence in financial markets: Diagnostics, models, and financial implications. The Review of Financial Studies 17 (2):581–610. doi:10.1093/rfs/hhg058.
   Web of Science ®Google Scholar
• Rapp, T. A., and S. C. Sharma. 1999. Exchange rate market efficiency: Across and within countries. Journal of Economics and Business 51 (5):423–39. doi:10.1016/S0148-6195(99)00017-X.
   Google Scholar
• Reboredo, J. C. 2011. How do crude oil prices co-move? A copula approach. Energy Economics 33:948–55. doi:10.1016/j.eneco.2011.04.006.
   Web of Science ®Google Scholar
• Roch, O., and A. Alegre. 2006. Testing the bivariate distribution of daily equity returns using copulas: An application to the Spanish stock market. Computational Statistics & Data Analysis 51 (2):1312–29. doi:10.1016/j.csda.2005.11.007.
   Web of Science ®Google Scholar
• Rodriguez, J. C. 2007. Measuring financial contagion: A copula approach. Journal of Empirical Finance 14 (3):401–23. doi:10.1016/j.jempfin.2006.07.002.
   Google Scholar
• Sehgal, S., P. Gupta, and F. Deisting. 2017. Assessing time-varying stock market integration in economic and Monetary union for normal and crisis periods. European Journal of Finance 23:1025–58.
   Web of Science ®Google Scholar
• Sehgal, S., P. Pandey, and F. Deisting. In press. Stock market integration dynamics and its determinants in the East Asian economic community region. Journal of Quantitative Economics. doi:10.1007/s40953-017-0090-7.
   Google Scholar
• Sklar, A. 1959. Fonctions de répartition à n dimensions etleursmarges. Publications De l’Institut De Statistique De Paris 8:229–31.
   Google Scholar
• Sriputtangkul, P., P. Tarsakoo, and R. Komonrat. (2015).Comovement of ASEAN Currency: A cointegration analysis. International Journal of Economic Research 12 (3):633–647.
   Google Scholar
• Tamakoshi, G., and S. Hamori. 2014. Co-movements among major European exchange rates: A multivariate time-varying asymmetric approach. International Review of Economics and Finance 31:105–13. doi:10.1016/j.iref.2014.01.016.
   Web of Science ®Google Scholar
• Teixeira, A. A., and A. S. Queirós. 2016. Economic growth, human capital and structural change: A dynamic panel data analysis. Research Policy 45 (8):1636–48. doi:10.1016/j.respol.2016.04.006.
   Web of Science ®Google Scholar
• Trichet, J.-C. 2010. State of the Union: The financial crisis and the ECB’s response between 2007 and 2009. Journal of Common Market Studies 48 (1):7–19. doi:10.1111/j.1468-5965.2010.02091.x.
   Google Scholar
• Tse, Y. K., and L. K. Ng. 1997. The cointegration of Asian currencies revisited. Japan and the World Economy 9 (1):109–14. doi:10.1016/S0922-1425(96)00239-3.
   Web of Science ®Google Scholar
• Vo, X. V., and K. J. Daly. 2007. The determinants of international financial integration. Global Finance Journal 18 (2):228–50.
   Google Scholar
• Wang, G. J., and C. Xie. 2013. Cross-correlations between Renminbi and four majorcurrencies in the Renminbi currency basket. Physica A: Statistical Mechanics and Its Applications 392 (6):1418–28. doi:10.1016/j.physa.2012.11.035.
   Web of Science ®Google Scholar
• Windmeijer, F. 2005. A finite sample correction for the variance of linear efficient Two-step GMM estimators. Journal of Econometrics 126 (1):25–51. doi:10.1016/j.jeconom.2004.02.005.
   Web of Science ®Google Scholar
• Yang, L., X. J. Cai, M. Li, and S. Hamori. 2015. Modeling dependence structures among international stock markets: Evidencefrom hierarchical Archimedean copulas. Economic Modelling 51:308–14. doi:10.1016/j.econmod.2015.08.017.
   Web of Science ®Google Scholar