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The Nonlinear Dynamic Relationship of Exchange Rates: Parametric and Nonparametric Causality testing

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  • Bekiros, S.
  • Diks, C.G.H.

    () (Universiteit van Amsterdam)

Abstract

The present study investigates the long-term linear and nonlinear causal linkages among six currencies, namely EUR/USD, GBP/USD, USD/JPY, USD/CHF, AUD/USD and USD/CAD. The prime motivation for choosing these exchange rates comes from the fact that they are the most liquid and widely traded, covering about 90% of total FX trading worldwide. The data spans two periods (PI: 3/20/1991 \u2013 3/20/1997, PII: 3/20/2003 \u2013 3/20/2007) before and after the structural break of the Asian financial crisis, which set a platform for departure for causality testing. We apply a new nonparametric test for Granger non-causality by Diks and Panchenko (2005, 2006) as well as the conventional linear Granger test on the return time series. To ensure that any causality is strictly nonlinear in nature, we also examine the nonlinear causal relationships of pairwise VAR filtered residuals as well as in a six-variate formulation. We find remaining significant bi- and uni-directional causal nonlinear relationships in the return series. Finally, we investigate the hypothesis of nonlinear non-causality after controlling for conditional heteroskedasticity in the data using a GARCH-BEKK model. Our approach allows the entire variance-covariance structure of the currency interrelationship to be incorporated in order to explicitly capture the volatility spillover mechanism. Whilst the nonparametric test statistics are smaller in some cases, significant nonlinear causal linkages persisted even after GARCH filtering during both the pre- and post-Asian crisis period. This indicates that currency returns may exhibit asymmetries and statistically significant higher-order moments.

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  • Bekiros, S. & Diks, C.G.H., 2007. "The Nonlinear Dynamic Relationship of Exchange Rates: Parametric and Nonparametric Causality testing," CeNDEF Working Papers 07-08, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  • Handle: RePEc:ams:ndfwpp:07-08
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    Cited by:

    1. Jan G. De Gooijer & Cees G. H. Diks & Łukasz T. Gątarek, 2012. "Information Flows Around the Globe: Predicting Opening Gaps from Overnight Foreign Stock Price Patterns," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 4(1), pages 23-44, March.
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    4. Grigoryev, Ruslan & Jaffry, Shabbar & Marchenko, German, 2012. "Investigation of the consequences of ignoring daily data non-synchronism in cross-market linkages: BRIC and developed countries," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 26(2), pages 92-112.
    5. Syed Hassan & Sarosh Shabi & Taufiq Choudhry, 2018. "US Economic Uncertainty, EU Business Cycles and the Global Financial Crisis," Working Papers 2018-05, Swansea University, School of Management.
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    8. Andreasson, Pierre & Bekiros, Stelios & Nguyen, Duc Khuong & Uddin, Gazi Salah, 2016. "Impact of speculation and economic uncertainty on commodity markets," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 115-127.
    9. Mikhail Stolbov, 2014. "How Are Interbank and Sovereign Debt Markets Linked? Evidence from 14 OECD Countries, the Euro Area and Russia," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 61(3), pages 331-348, June.
    10. De Vita, Glauco & Trachanas, Emmanouil, 2016. "‘Nonlinear causality between crude oil price and exchange rate: A comparative study of China and India’ — A failed replication (negative Type 1 and Type 2)," Energy Economics, Elsevier, vol. 56(C), pages 150-160.
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    12. Dajcman, Silvio & Festic, Mejra, 2012. "The Interdependence of the Stock Markets of Slovenia, The Czech Republic and Hungary with Some Developed European Stock Markets – The Effects of Joining the European Union and the Global Financial Cri," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 163-180, December.

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