019-09

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[[第19回研究会>019]]

*LSTM-RNNを用いたイベント考慮・時系列予測の試み [#kecb5010]

**著者 [#a8b44581]
南正太郎(あすかアセットマネジメント株式会社)

**概要 [#r6c0b734]
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 [#e7f4988f]
LSTM, Long short term memory, Recurrent　Neuralnet, Prediction of Single Stock Price

**論文 [#d24f1b06]

//(10月11日以降に公表いたします)
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