RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction

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Journal of Soft Computing and Artificial Intelligence
Volume:1 Issue:2
RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction

RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction

Authors : Eren UNLU

Pages : 78-85

View : 23 | Download : 14

Publication Date : 2020-12-29

Article Type : Research Paper

Abstract :We present a novel intuitive graphical representation for daily stock prices, which we refer as RGBSticks, a variation of classical candle sticks. This representation allows the usage of complex deep learning based techniques, such as deep convolutional autoencoders and deep convolutional generative adversarial networks to produce insightful visualizations for market`s past and future states. We believe RGBStick representation has great potential to integrate human decision process and deep learning for stock market analysis and forecasting. The traders who are highly familiar with candlesticks are able to evaluate the results generated by deep learning algorithms by inspecting the varying color shades in a compact, instinctual and rapid fashion
Keywords : artificial intelligence, stock market, time series

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