A HIDDEN MARKOV APPROACH TO THE FORWARD PREMIUM PUZZLE

Robert J. Elliott () and Bing Han
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Robert J. Elliott: Haskayne School of Business, University of Calgary, 2500 University Drive NW, Calgary, Alberta, T2N 1N4, Canada
Bing Han: Orfalea College of Business, California Polytechnic State University, San Luis Obispo, California, USA

International Journal of Theoretical and Applied Finance (IJTAF), 2006, vol. 09, issue 07, 1009-1020

Abstract: A Hidden Markov Chain (HMC) is applied to study the forward premium puzzle. The weekly quotient of the interest rate differential divided by the log exchange rate change is modeled as a Hidden Markov process. Compared with existing standard approaches, the Hidden Markov approach allows a detailed analysis of the puzzle on a day-to-day basis while taking into full account the presence of noise in the observations. Two and three state models are investigated. A three-state HMC model performs better than two-state models. Application of the three-state model reveals that the above quotient is mostly zero, and hence leads to the rejection of the uncovered interest rate parity hypothesis.

Keywords: Hidden Markov models; filtering; uncovered interest rate parity (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0219024906003949

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