摘要：AbstractIn this paper we utilize a Long Short-Term Memory Neural Network to learn from and improve upon traditional trading algorithms used in technical analysis. The rationale behind our study is that the network can learn market behavior and be able to predict when a given strategy is more likely to succeed. We implemented our algorithm in Python pursuing Google's TensorFlow. We show that our strategy, based on a combination of neural network prediction, and traditional technical analysis, performs better than the latter alone.
