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Image Processing Tools for Financial Time Series Classification
[article]
2020
arXiv
pre-print
The application of deep learning to time series forecasting is one of the major challenges in present machine learning. We propose a novel methodology that combines machine learning and image processing methods to define and predict market states with intraday financial data. A wavelet transform is applied to the log-return of stock prices for both image extraction and denoising. A convolutional neural network then extracts patterns from denoised wavelet images to classify daily time series,
arXiv:2008.06042v2
fatcat:eadpzzd2ubgvrl73xmfm2zvapu