Modeling exchange rates using wavelet decomposed genetic neural networks

DOI10.1016/j.stamet.2005.07.002zbMath1248.91077OpenAlexW1967880952MaRDI QIDQ713693

Amit Mitra, Sharmishtha Mitra

Publication date: 19 October 2012

Published in: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.stamet.2005.07.002

zbMATH Keywords

multiresolution analysisartificial intelligencegenetic algorithmwavelet decompositionexchange rate forecastingspot exchange rate

Mathematics Subject Classification ID

Economic time series analysis (91B84) Learning and adaptive systems in artificial intelligence (68T05) Numerical methods for wavelets (65T60) Application of orthogonal and other special functions (94A11)

Related Items (3)

Study of dynamic relationships between financial and real sectors of economies with wavelets ⋮ Using genetic algorithms grey theory to forecast high technology industrial output ⋮ A wavelet filtering based analysis of macroeconomic indicators: the Indian evidence

Cites Work

• ARCH modeling in finance. A review of the theory and empirical evidence
• A comparison between neural networks and chaotic models for exchange rate prediction.
• Much ado about nothing? Exchange rate forecasting: Neural networks vs. linear models using monthly and weekly data
• Conditional Heteroskedasticity in Asset Returns: A New Approach
• A theory for multiresolution signal decomposition: the wavelet representation
• Ten Lectures on Wavelets
• Multiresolution Approximations and Wavelet Orthonormal Bases of L 2 (R)
• Wavelet transforms versus Fourier transforms
• Wavelets in time-series analysis
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