Dynamic Forecasting Rules and the Complexity of Exchange Rate Dynamics

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dc.contributor.authorDewachter, Hans
dc.contributor.authorHoussa, Romain
dc.contributor.authorLyrio, Marco Túlio Pereira
dc.contributor.authorKaltwasser, Pablo Rovira
dc.coverage.cidadeSão Paulopt_BR
dc.coverage.paisBrasilpt_BR
dc.creatorDewachter, Hans
dc.creatorHoussa, Romain
dc.creatorLyrio, Marco Túlio Pereira
dc.creatorKaltwasser, Pablo Rovira
dc.date.accessioned2023-07-19T17:51:56Z
dc.date.available2023-07-19T17:51:56Z
dc.date.issued2011
dc.description.abstractThis paper investigates the exchange rate dynamics implied by a heterogeneous agent model proposed in De Grauwe and Grimaldi (2006). The two groups of agents, chartists and fundamentalists, use simple forecasting rules and the ex post relative profitability to decide whether to switch to the other group. We extend this model by introducing a simple evolutionary selection mechanism which allows agents not only to switch between groups but also to adapt the forecasting rule of each group over time. This selection process naturally leads agents to choose forecasting rules over time which results in the convergence of the exchange rate to its fundamental value. However, our learning rule is not robust to the introduction of shocks to the fundamental. In particular, once we allow for random variation in the fundamental, the model exhibits again all of the nonlinear features discussed in De Grauwe and Grimaldi (2006): the disconnect puzzle, volatility clustering and fat tails.
dc.description.otherThis paper investigates the exchange rate dynamics implied by a heterogeneous agent model proposed in De Grauwe and Grimaldi (2006). The two groups of agents, chartists and fundamentalists, use simple forecasting rules and the ex post relative profitability to decide whether to switch to the other group. We extend this model by introducing a simple evolutionary selection mechanism which allows agents not only to switch between groups but also to adapt the forecasting rule of each group over time. This selection process naturally leads agents to choose forecasting rules over time which results in the convergence of the exchange rate to its fundamental value. However, our learning rule is not robust to the introduction of shocks to the fundamental. In particular, once we allow for random variation in the fundamental, the model exhibits again all of the nonlinear features discussed in De Grauwe and Grimaldi (2006): the disconnect puzzle, volatility clustering and fat tails.pt_BR
dc.format.extent19 p.pt_BR
dc.format.mediumDigitalpt_BR
dc.identifier.issueBEWP 125/2011
dc.identifier.urihttps://repositorio.insper.edu.br/handle/11224/5872
dc.language.isoInglêspt_BR
dc.publisherInsperpt_BR
dc.publisherIBMEC São Paulopt_BR
dc.relation.ispartofseriesInsper Working Paperpt_BR
dc.rights.licenseO INSPER E ESTE REPOSITÓRIO NÃO DETÊM OS DIREITOS DE USO E REPRODUÇÃO DOS CONTEÚDOS AQUI REGISTRADOS. É RESPONSABILIDADE DO USUÁRIO VERIFICAR OS USOS PERMITIDOS NA FONTE ORIGINAL, RESPEITANDO-SE OS DIREITOS DE AUTOR OU EDITORpt_BR
dc.subject.keywordsBehavioral financept_BR
dc.subject.keywordsexchange ratept_BR
dc.titleDynamic Forecasting Rules and the Complexity of Exchange Rate Dynamicspt_BR
dc.typeworking paper
dspace.entity.typePublication
local.subject.cnpqCiências Sociais Aplicadaspt_BR
local.typeWorking Paperpt_BR
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