Learning, the Forward Premium Puzzle and Market Efficiency
AbstractThe Forward Premium Puzzle is one of the most prominent empirical anomalies in international finance. The forward premium predicts exchange rate depreciation but typically with the opposite sign and smaller magnitude than specified by rational expectations, a result also considered to indicate inefficiency in the foreign exchange market. This paper proposes a resolution of the puzzle based on recursive least squares learning applied to a simple model of exchange rate determination. The key assumption is that risk neutral agents are not blessed with rational expectations and do not have perfect knowledge about the market. Agents learn about the parameters underlying the stochastic process generating the exchange rate using constant gain recursive least squares. When exchange rate data are generated from the model and the empirical tests are performed, for plausible parameter values the results replicate the anomaly along with other observed empirical features of the forward and spot exchange rate data.
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Bibliographic InfoPaper provided by University of Oregon Economics Department in its series University of Oregon Economics Department Working Papers with number 2005-4.
Date of creation: 01 Oct 2004
Date of revision: 01 Oct 2004
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Spot Exchange Rate; Forward Rate; Constant-gain Recursive Least Squares Learning.;
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Blog mentionsAs found by EconAcademics.org, the blog aggregator for Economics research:
- In praise of belief in efficient markets
by chris dillow in Stumbling and Mumbling on 2009-02-13 11:14:47
- Brian Lucey & Grace Loring, . "Forward Exchange Rate Biasedness across Developed and Developing Country Currencies - Do Observed Patterns Persist Out of Sample?Abstract:," The Institute for International Integration Studies Discussion Paper Series iiisdp404, IIIS.
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