Can perpetual learning explain the forward-premium puzzle?

Avik Chakraborty and George William Evans ()

Journal of Monetary Economics, 2008, vol. 55, issue 3, pages 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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Related works:
Working Paper: Can Perpetual Learning Explain the Forward Premium Puzzle? (2006)
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Persistent link: http://EconPapers.repec.org/RePEc:eee:moneco:v:55:y:2008:i:3:p:477-490

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