Paul De Grauwe (KULeuven) Agnieszka Markiewicz (KULeuven)
Abstract
In this paper, we investigate the behavior of the exchange rate within the framework of an asset pricing model. We assume boundedly rational agents who use simple rules to forecast the future exchange rate. They test these rules continuously using two learning mechanisms. The first one, the fitness method, assumes that agents evaluate forecasts by computing their past profitability. In the second mechanism, agents learn to improve these rules using statistical methods. First, we find that both learning mechanisms reveal the fundamental value of the exchange rate in the steady state. Second, both mechanisms mimic regularities observed in the foreign exchange markets, namely exchange rate disconnect and excess volatility. Fitness learning rule generates the disconnection at different frequencies, while the statistical method has this ability only at the high frequencies. Statistical learning can produce excess volatility of magnitude closer to reality than fitness learning but can also lead to explosive solutions
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Find related papers by JEL classification: F31 - International Economics - - International Finance - - - Foreign Exchange F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
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Zwart, G.J. de & Markwat, T.D. & Swinkels, L. & Dijk, D.J.C. van, 2007.
"The Economic Value of Fundamental and Technical Information in Emerging Currency Markets,"
Research Paper
ERS-2007-096-F&A Revision, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni.
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