Can perpetual learning explain the forward-premium puzzle?

Avik Chakraborty, George W Evans

    Research output: Contribution to journalArticlepeer-review

    46 Citations (Scopus)

    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. (C) 2008 Elsevier B.V. All rights reserved.

    Original languageEnglish
    Pages (from-to)477-490
    Number of pages14
    JournalJournal of Monetary Economics
    Volume55
    Issue number3
    DOIs
    Publication statusPublished - Apr 2008

    Keywords

    • learning
    • exchange rates
    • forward premium
    • expectations
    • UNCOVERED INTEREST PARITY
    • EXCHANGE-RATE
    • EXCESS VOLATILITY
    • FINANCIAL-MARKETS
    • FOREIGN-EXCHANGE
    • MONETARY
    • POLICY
    • EXPECTATIONS
    • INFLATION
    • DEVIATIONS

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