Collective Artificial Intelligence for Mechanical Technical Analysis
Because technical analysis uses only historical price data, it has affinity with machine learning approach and is often called modern technical analysis or mechanical technical analysis. In general, machine learning method is categorized as an artificial intelligence (AI), which is really a hot topic in the world since Google’s Al (AlphaGo) beat the world Go champion. Then, it has been called FinTech to apply Al for financial business intelligence.
In his presentation, Professor Suzuki introduces some ideas to develop Al algorithms for technical analysis, such as collective intelligence and abnormally detection. The collective intelligence can enhance the predictive power by integrating many neural networks and can select the most reliable stock by following their consensus. Then, the autoencoder is a new neural network used for the deep neural network, and he applies it to the abnormally detection of noisy financial markets. To confirm the validity of these ideas, Professor Suzuki performs investment simulations and statistical significance tests with real stock price data.
三和 裕美子氏
明治大学商学部 教授。大阪市立大学大学院経営学研究科後期博士課程単位取得退学後、明治大学商学部助手、同専任講師、同助教授、2005年より同教授、現在に至る。博士（商学）。ミシガン大学客員教授（2006年～2008年）主著書：『機関投資家の発展とコーポレート・ガバナンス』（日本評論社）、Corporate Governance in Japan(共著、シュプリンガフェアラーク東京)など。
Nobuyuki Hanaki is a professor of Economics at Université Côte d’Azur, France. After receiving Ph.D. in economics from Columbia University, he has taught at University of Tsukuba (Japan) and Aix-Marseille Université (France) before joining Université Côte d’Azur. His research has been published in such leading international journals as Economic Journal, Management Science, and American Economic Review.
IFTA大会（イタリア ミラノ）の講演内容：「What makes a good trader」
Experimental finance is an emerging fields of academic research that analyze data collected under controlled experimental setting and try to provide new quantitative insights to questions related to the field of finance. This approach takes paradoxes and biases in human judgment and decision making that have been demonstrated in the field of experimental economics and psychology. In recent years, there has been an increasing interest in involving professionals directly in these experiments. The aim is to reduce progressively the gap between stylized modelling or experimentation towards a contextually rich experimental scenario. This talk will focus mainly on this body of literature, highlighting recent findings. These are fresh ideas for practitioners to stimulate reflection about or even understand weaknesses or opportunities in their professional life.
