IFTA2020: How to Build Investment Strategies with AI and Machine Learning

Recent advances in AI and machine learning are finding practical applications across many industries, not least the finance industry. In particular, research into the use of AI and machine learning as a new tool for stock investment has been very active.

 I’ll show how AI and machine learning can be applied to the problem of discovering and implementing stock investment strategies.

As an example, I’ll introduce an example of developing machine learning based forecasting methods while focusing on the perspective  of price fluctuation patterns, which is the philosophy of technical analysis.

Dr. Nakagawa is a quantitative analyst in Innovation Lab at Nomura Asset Management Co Ltd. from 2018.
He engages in the R&D of cutting-edge technologies such as AI, machine learning, and FinTech and their application to the asset management business.
He received a B.A., in Economics from Kyoto University in 2012, an MBA from the University of Tsukuba in 2015, and a Ph.D. in Business Administration in 2020 from the University of Tsukuba.
From 2012, He was a risk manager and quantitative investment strategy fund manager.
He managed quantitative funds investing in Japanese Long-Short Equity, Global Equity, and REIT. He developed a lot of quantitative equity and multi-asset allocation models.
Not only does he have work experience as a quant, but he also has many academic presentations and papers on artificial intelligence, machine learning, and financial engineering including top-tier AI academic conferences.
His research interest lies in improving the method of finance by machine learning and, on the contrary, developing machine learning by the method of finance.
He teaches at Tokyo Institute of Technology, the University of Tsukuba, and Waseda University.

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