- 著者
-
上田 翼
東出 卓朗
- 出版者
- 一般社団法人 人工知能学会
- 雑誌
- 人工知能学会第二種研究会資料 (ISSN:24365556)
- 巻号頁・発行日
- vol.2017, no.FIN-018, pp.12, 2017-03-10 (Released:2023-01-06)
Central bank's monetary policy is one of the major interests for market participants. In this paper, we clarified Reserve Bank of Australia's monetary policy reaction function, predicted its policy change,and applied them to investment strategy. First of all, assuming perfect foresight by the central bank, we estimated an extended Taylor rule using bidirectional Recurrent Neural Network. Next, we combined it with distributed representation of Monetary Policy Committee minutes to develop a classifier of interest rate decision. Both the extended Taylor rule and the classifier showed improved performance. Finally, we formulated profitable Foreign Exchange strategy based on the classifier's prediction and market economists' forecasts.