Artificial Neural Networks Approach to the Forecast of Stock Market Price Movements

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Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019, methodology): “[179] S&P500, EUR/USD 1950-2016 Price data 30d, 30d*min 1d, 1min Wavelet+CNN Accuracy, logloss Keras”
Stock market's price movement prediction with LSTM neural networks (2017, methodology): “[18] compares the performance of LSTM and MLP to their own proposed method based on a combination of wavelets and Convolutional Neural Networks, which outperforms both but has very close results to the LSTM network.”
Replicating a Trading Strategy by Means of LSTM for Financial Industry Applications (2018, background): “Persio and Honchar [11] investigate different artificial neural network (ANN) architectures, namely Multilayer Perceptron (MLP), Convolutional Neural Network (CNN) and LSTM, to stock price movement forecasting, where the prediction of future trend movements are based on past returns.”
Evolving Recurrent Neural Networks for Time Series Data Prediction of Coal Plant Parameters (2019, methodology): “Regarding time series prediction, for example, LSTM RNNs have been used for stock market forecasting [11] and forex market forecasting [12].”