Can perpetual learning explain the forward-premium puzzle? |
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Authors: | Avik Chakraborty |
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Institution: | a University of Tennessee, USA b Department of Economics, University of Oregon, Eugene, OR 97403-1285, USA |
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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. |
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Keywords: | D83 D84 F31 G12 G15 |
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