Applied Mathematics & Information Sciences

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This work concentrates on computational approach for predicting the interval (number of trading days), a significant feature of stock market analysis using Haar Wavelet. A distinct model is proposed for predicting the high value of returns. The prime objective is to understand the trends using Haar wavelet and use this information to determine the interval for future direction. This model used 85 securities closing price and validated 4355 trading days. The results reported at 200 recent trading days with an average accuracy of 45.88% on 85 securities over a period of 15 years.

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