English, Article edition: A HIDDEN MARKOV APPROACH TO THE FORWARD PREMIUM PUZZLE ROBERT J. ELLIOTT; BING HAN

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Physical Description
  • article
Language
  • English

Edition details

Title
  • A HIDDEN MARKOV APPROACH TO THE FORWARD PREMIUM PUZZLE
Author
  • ROBERT J. ELLIOTT
  • BING HAN
Physical Description
  • article
Notes
  • 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.
  • Hidden Markov models, filtering, uncovered interest rate parity
  • RePEc:wsi:ijtafx:v:09:y:2006:i:07:p:1009-1020
Language
  • English
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