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Stock Forecasting using M-Band Wavelet-Based SVR and RNN-LSTMs Models
[article]
2019
arXiv
pre-print
The task of predicting future stock values has always been one that is heavily desired albeit very difficult. This difficulty arises from stocks with non-stationary behavior, and without any explicit form. Hence, predictions are best made through analysis of financial stock data. To handle big data sets, current convention involves the use of the Moving Average. However, by utilizing the Wavelet Transform in place of the Moving Average to denoise stock signals, financial data can be smoothened
arXiv:1904.08459v1
fatcat:u3qnsq7dwrdnnbv2xpvi2brcli