Analyzing Tunisia’s exchange rate fluctuations: Fuzzy filter approach

 

Ali Chebbi* and Ramzi Knani

 

Research Article | Published April 2014

Journal of Economics and International Business Management, Vol. 2(2), pp. 15-26

 

Quantitative Methods and Economy Department, Head of the Laboratory of Macroeconomics and Quantitative Methods MACMA, University of Tunis.

 

*Corresponding author. E-mail: alicheb@yahoo.fr

 

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The standard approach analyzing the business cycle (RBC) is based on Hodrick-Prescott (HP) and Band-Pass (BP) filters to extract the cyclical component of the aggregate time series. By Monte Carlo experiments using Matlab program, we compared these traditional filters to a more recent Fuzzy Regression Filter. Our aim is to help the user to choose the appropriate filter in the appropriate time series. Through our application on the exchange rate (Dinar/U.S.$), the results show an improvement of the Fuzzy filter when the time series is non-stationary. In fact, through only the Fuzzy filter, (i) there no imposed restrictions on time series distribution; and (ii) the use of traditional filters lead to an evaluation bias of the exchange rate cyclical components. Additionally, when the implemented exchange policy is based on HP and/or BP filter, it then could be misled. Would it be necessary in a further research to review the stylized facts established by the standard RBC model by applying the Fuzzy filter as an alternative?

 

Keywords: Business cycle, Hodrick-Prescott and band-pass filters, fuzzy filter, FCM algorithm, Monte Carlo simulation, TDN/USD exchange rate.