ITEM METADATA RECORD
Title: Learning to forecast the exchange rate: two competing approaches
Authors: De Grauwe, Paul ×
Markiewicz, Agnieszka #
Issue Date: 2012
Series Title: Journal of International Money and Finance vol:32 pages:42-76
Abstract: This paper compares two competing approaches to model foreign exchange market participants’ behavior: statistical learning and fitness learning. These learning mechanisms are applied to a set of predictors: chartist and fundamentalist rules. We examine which of the learning approaches is best in terms of replicating the exchange rate dynamics within the framework of a standard asset
pricing model. We find that both learning methods reveal the
fundamental value of the exchange rate in the equilibrium but only fitness learning creates the disconnection phenomenon and only statistical learning replicates volatility clustering. None of the mechanisms is able to produce a unit root process but both of them generate non-normally distributed returns.
ISSN: 0261-5606
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Research Center of International Economics @ Leuven
× corresponding author
# (joint) last author

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