Predict Forex Trend via Convolutional Neural Networks

Yun-Cheng Tsai, Jun-Hao Chen and Jun-Jie Wang

Papers from arXiv.org

Abstract: Deep learning is an effective approach to solving image recognition problems. People draw intuitive conclusions from trading charts; this study uses the characteristics of deep learning to train computers in imitating this kind of intuition in the context of trading charts. The three steps involved are as follows: 1. Before training, we pre-process the input data from quantitative data to images. 2. We use a convolutional neural network (CNN), a type of deep learning, to train our trading model. 3. We evaluate the model's performance in terms of the accuracy of classification. A trading model is obtained with this approach to help devise trading strategies. The main application is designed to help clients automatically obtain personalized trading strategies.

Date: 2018-01
New Economics Papers: this item is included in nep-big, nep-cmp and nep-ets
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Citations: View citations in EconPapers (3)

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