Can perpetual learning explain the forward-premium puzzle?
Avik Chakraborty and
George Evans
Journal of Monetary Economics, 2008, vol. 55, issue 3, 477-490
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 show that replacing rational expectations by discounted least-squares (or "perpetual") learning generates a negative bias that becomes strongest when the fundamentals are strongly persistent, i.e. close to a random walk. Perpetual learning can explain the forward-premium puzzle while simultaneously replicating other features of the data, including positive serial correlation of the forward premium and disappearance of the anomaly in other forms of the test.
Date: 2008
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Working Paper: Can Perpetual Learning Explain the Forward Premium Puzzle? (2006) 
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Persistent link: https://EconPapers.repec.org/RePEc:eee:moneco:v:55:y:2008:i:3:p:477-490
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