Financial Market Prediction Using Recurrence Plot and Convolutional Neural Network

Tameru Hailesilassie

doi:10.20944/preprints201912.0252.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 17 December 2019 / Approved: 19 December 2019 / Online: 19 December 2019 (07:39:54 CET)

An application of deep convolutional neural network and recurrence plot for financial market movement prediction is presented. Though it is challenging and subjective to interpret its information, the pattern formed by a recurrence plot provide a useful insight into the dy- namical system. We used a recurrence plot of seven financial time series to train a deep neural network for financial market movement predic- tion. Our approach is tested on our dataset and achieved an average of 53.25% classification accuracy. The result suggests that a well trained deep convolutional neural network can learn a recurrence plot and pre- dict a financial market direction.

time series; deep learning; convolutional neural network; recurrence plot; financial market prediction

Computer Science and Mathematics, Computer Science

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Financial Market Prediction Using Recurrence Plot and Convolutional Neural Network

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