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Do Euro exchange rates follow a martingale? Some out-of-sample evidence

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  • Yang, Jian
  • Su, Xiaojing
  • Kolari, James W.

Abstract

Traditional autocorrelation and variance ratio tests are based on serial uncorrelatedness rather than martingale difference. As such, they do not capture potential nonlinearity-in-mean, which could lead to misleading inferences in favor of the martingale hypothesis. This paper employs various parametric and nonparametric nonlinear models as well as several model comparison criteria to examine the potential martingale behavior of Euro exchange rates in the context of out-of-sample forecasts. The overall evidence indicates that, while martingale behavior cannot be rejected for Euro exchange rates with major currencies such as the Japanese yen, British pound, and US dollar, there is nonlinear predictability in terms of economic criteria with respect to several smaller currencies.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Banking & Finance.

Volume (Year): 32 (2008)
Issue (Month): 5 (May)
Pages: 729-740

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Handle: RePEc:eee:jbfina:v:32:y:2008:i:5:p:729-740

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Cited by:
  1. Zsolt Darvas, 2008. "Leveraged carry trade portfolios," Working Papers 0802, Department of Mathematical Economics and Economic Analysis, Corvinus University of Budapest, revised 18 Jun 2008.
  2. Wang, Tao & Yang, Jian, 2010. "Nonlinearity and intraday efficiency tests on energy futures markets," Energy Economics, Elsevier, vol. 32(2), pages 496-503, March.
  3. Chuluun, Tuugi & Eun, Cheol S. & KiliƧ, Rehim, 2011. "Investment intensity of currencies and the random walk hypothesis: Cross-currency evidence," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 372-387, February.
  4. Chortareas, Georgios & Jiang, Ying & Nankervis, John C., 2011. "The random-walk behavior of the Euro exchange rate," Finance Research Letters, Elsevier, vol. 8(3), pages 158-162, September.
  5. Fong, Wai Mun, 2010. "A stochastic dominance analysis of yen carry trades," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1237-1246, June.
  6. Kocenda, Evzen & Poghosyan, Tigran, 2009. "Macroeconomic sources of foreign exchange risk in new EU members," Journal of Banking & Finance, Elsevier, vol. 33(11), pages 2164-2173, November.
  7. Jesus Crespo Cuaresma & Mauro Costantini & Jaroslava Hlouskova, 2014. "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Department of Economics Working Papers wuwp176, Vienna University of Economics, Department of Economics.
  8. Kellard, Neil & Dunis, Christian & Sarantis, Nicholas, 2010. "Foreign exchange, fractional cointegration and the implied-realized volatility relation," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 882-891, April.
  9. Sermpinis, Georgios & Theofilatos, Konstantinos & Karathanasopoulos, Andreas & Georgopoulos, Efstratios F. & Dunis, Christian, 2013. "Forecasting foreign exchange rates with adaptive neural networks using radial-basis functions and Particle Swarm Optimization," European Journal of Operational Research, Elsevier, vol. 225(3), pages 528-540.
  10. Adrian Wai-Kong Cheung & Jen-Je Su & Astrophel Kim Choo, 2011. "Are Euro exchange rates markets efficient? New evidence from a large panel," Discussion Papers in Finance finance:201109, Griffith University, Department of Accounting, Finance and Economics.

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