- 追加された行はこの色です。
- 削除された行はこの色です。
[[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) &ref(SIG-FIN-019-09.pdf);