Learning to Forecast the Exchange Rate: Two Competing Approaches
AbstractIn 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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Bibliographic InfoPaper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 1717.
Date of creation: 2006
Date of revision:
Other versions of this item:
- De Grauwe, Paul & Markiewicz, Agnieszka, 2013. "Learning to forecast the exchange rate: Two competing approaches," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 42-76.
- Paul De Grauwe & Agnieszka Markiewicz, 2006. "Learning to Forecast the Exchange Rate: Two Competing Approaches," Computing in Economics and Finance 2006 367, Society for Computational Economics.
- F31 - International Economics - - International Finance - - - Foreign Exchange
- F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-06-03 (All new papers)
- NEP-CBA-2006-06-03 (Central Banking)
- NEP-FMK-2006-06-03 (Financial Markets)
- NEP-FOR-2006-06-03 (Forecasting)
- NEP-IFN-2006-06-03 (International Finance)
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