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The nonlinear relationships between stock indexes and exchange rates

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  • Ho, Liang-Chun
  • Huang, Chia-Hsing

Abstract

The Lagrange multiplier (LM) principle is used to study the causality in variance and the relationships between the stock indexes and exchange rates of Brazil, Russia, India, and China (BRIC). Weekly closing prices from February 2002 to December 2013 are used for the analysis. The full study period is divided into two sub-periods after the Chow breakpoint test and Quandt–Andrews unknown breakpoint test. The causality is from exchange rate to stock in the first sub-period and no causality relationship between stock index and exchange rate in the second sub-period for Brazil. The causality is from stock index to exchange rate in both the first sub-period and the second sub-period for Russia. The causality is from exchange rate to stock index in both the first sub-period and the second sub-period for India. There is no causality relationship between stock index and exchange rate in the first sub-period, and from exchange rate to stock index in the second sub-period for China. The study results support the argument that volatility can be transmitted between stock index and exchange rate even when the returns of these two variables are either statistically uncorrelated or exhibit no causality in means.

Suggested Citation

  • Ho, Liang-Chun & Huang, Chia-Hsing, 2015. "The nonlinear relationships between stock indexes and exchange rates," Japan and the World Economy, Elsevier, vol. 33(C), pages 20-27.
    • Handle: RePEc:eee:japwor:v:33:y:2015:i:c:p:20-27
    DOI: 10.1016/j.japwor.2015.02.002
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    2. Andrew Phiri, 2020. "Structural changes in exchange rate-stock returns dynamics in South Africa: examining the role of crisis and new trading platform," Economic Change and Restructuring, Springer, vol. 53(1), pages 171-193, February.
    3. Ruipeng Liu & Riza Demirer & Rangan Gupta & Mark E. Wohar, 2017. "Do Bivariate Multifractal Models Improve Volatility Forecasting in Financial Time Series? An Application to Foreign Exchange and Stock Markets," Working Papers 201728, University of Pretoria, Department of Economics.
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    7. Xiyong Dong & Seong‐Min Yoon, 2018. "Structural breaks, dynamic correlations, and hedge and safe havens for stock and foreign exchange markets in Greater China," The World Economy, Wiley Blackwell, vol. 41(10), pages 2783-2803, October.
    8. Kocaarslan, Baris & Sari, Ramazan & Gormus, Alper & Soytas, Ugur, 2017. "Dynamic correlations between BRIC and U.S. stock markets: The asymmetric impact of volatility expectations in oil, gold and financial markets," Journal of Commodity Markets, Elsevier, vol. 7(C), pages 41-56.
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    12. Kanda, Patrick & Burke, Michael & Gupta, Rangan, 2018. "Time-varying causality between equity and currency returns in the United Kingdom: Evidence from over two centuries of data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 1060-1080.
    13. Naresh, G. & Vasudevan, Gopala & Mahalakshmi, S. & Thiyagarajan, S., 2018. "Spillover effect of US dollar on the stock indices of BRICS," Research in International Business and Finance, Elsevier, vol. 44(C), pages 359-368.
    14. Meng, Xiangcai & Huang, Chia-Hsing, 2016. "Nonlinear models for the sources of real effective exchange rate fluctuations: Evidence from the Republic of Korea," Japan and the World Economy, Elsevier, vol. 40(C), pages 21-30.
    15. Saadati, Alireza & Honarmandi, Zahra & Zarei, Samira, 2020. "Real Exchange Rate Shocks and Export-Oriented Businesses in Iran: An Empirical Analysis Using NARDL Model," MPRA Paper 101554, University Library of Munich, Germany, revised 30 Jun 2020.
    16. Mutiu A. Oyinlola & Tirimisyu F. Oloko, 2018. "Exchange rate dynamics and stock market performance in Nigeria: Evidence from a Nonlinear ARDL Approach," Working Papers 059, Centre for Econometric and Allied Research, University of Ibadan.

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    More about this item

    Keywords

    Stock index; Exchange rate; Causality in variance;
    All these keywords.

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • F01 - International Economics - - General - - - Global Outlook
    • F30 - International Economics - - International Finance - - - General
    • E00 - Macroeconomics and Monetary Economics - - General - - - General

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