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Can Perpetual Learning Explain the Forward Premium Puzzle?

Author

Listed:
  • George W. Evans

  • Avik Chakraborty

    (Department of Economics, University of Tennessee)

Abstract

Under rational expectations and risk neutrality the linear projection of exchange rate change on the forward premium has a unit coefficient. However, empirical estimates of this coefficient are significantly less than one (and often negative). We investigate whether replacing rational expectations by discounted least squares (or "perpetual") learning can explain the result. We calculate the asymptotic bias under perpetual learning and show that there is a negative bias that becomes strongest when the fundamentals are strongly persistent, i.e. close to a random walk. Simulations confirm that adaptive learning is potentially able to explain the forward premium puzzle.

Suggested Citation

  • George W. Evans & Avik Chakraborty, 2006. "Can Perpetual Learning Explain the Forward Premium Puzzle?," University of Oregon Economics Department Working Papers 2006-8, University of Oregon Economics Department, revised 20 Aug 2006.
    • Handle: RePEc:ore:uoecwp:2006-8
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    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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