Nonlinear dynamics in foreign exchange excess returns: Tests of asymmetry

Riza Emekter, Benjamas Jirasakuldech and Sean M. Snaith

Journal of Multinational Financial Management, 2009, vol. 19, issue 3, 179-192

Abstract: This paper examines the nonlinear dynamic behaviors in foreign exchange excess returns of eight currencies. We applied the BDS test and two other nonlinear statistical techniques, the Markov chain, and time reversibility tests to characterize the exchange rate returns dynamics. The results from the BDS test provide strong evidence of nonlinear dependence on the British pound, the Singapore dollar, the South African rand, and the Swedish krone. The Markov chain test shows evidence of a non-random walk and positive serial dependence in all currencies except for the British pound, the Canadian dollar, and the Swiss franc. Lastly, evidence of time irreversible and asymmetric dynamic behavior is found in seven currencies with the exception of the Canadian dollar. The results indicate that the asymmetry in the Singapore dollar, the South African rand, and the Swiss franc is due to nonlinearity in the functional form as opposed to non-Gaussian innovations.

Keywords: Exchange; rate; Nonlinear; dynamics; Asymmetry (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1042-444X(08)00054-6
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:mulfin:v:19:y:2009:i:3:p:179-192

Access Statistics for this article

Journal of Multinational Financial Management is currently edited by I. Mathur and G. G. Booth

More articles in Journal of Multinational Financial Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().