019-09

第19回研究会

LSTM-RNNを用いたイベント考慮・時系列予測の試み†

著者†

南正太郎(あすかアセットマネジメント株式会社)

概要†

The forecasting the stock price of a particular has been a difficult task for many of analysts and researchers. In fact, investors are highly interested in the research area of stock price prediction. However, to improve the accuracy of forecasting a single stock price is a really challenging task, therefore in this paper, I propose a sequential learning model for prediction of a single stock price with corporate action event information and Macro-Economic indices using LTSM-RNN method. The results show the proposed model is expected to be a promising method in the stock price prediction of a single stock with variables like corporate action and corporate publishings.

キーワード†

LSTM, Long short term memory, Recurrent　Neuralnet, Prediction of Single Stock Price

論文†

SIG-FIN-019-09.pdf