This paper reports on the profitability of technical chart trading on non-stationary daily FX rates by using signal decomposition and reconstruction techniques based on wavelets. Wavelet theory has emerged as an useful tool on the applications in financial time series, FX rates, for instance. Its time-scale analysis is particularly suitable in describing the nature of the financial time series. The discrete wavelet transform is used to denoise FX rates before the rates pattern being checked for forecasting value or profitability. The results show the ability of wavelet denoising and reconstruction, and indicate a modest performance on the profitability of chart trading on FX rates.
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