Image Processing Tools for Financial Time Series Classification

Understand

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, i.e.