A proposal of a machine learning method combining enumeration and statistical learning

2015 Fiscal Year Final Research Report

• Project/Area Number: 25330266
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Intelligent informatics
• Research Institution: Keio University
• Principal Investigator: Sakurai Akito 慶應義塾大学, 理工学部, 教授 (00303339)
• Project Period (FY): 2013-04-01 – 2016-03-31
• Keywords: 金融時系列予測 / 機械学習

Outline of Final Research Achievements

Financial markets where foreign currency and stocks are exchanged are very efficient and short term time series of values of exchange rates, prices, and indexes are well approximated by stochastic processes with independent increments except for sudden changes caused by outer world events. But in reality, the changes remain and the increments are dependent on previous states/movements. In this research, so-called trends as human experts recognize are tried, and implicit non-linear representations are also tried, and used to describe and predict the time series. We showed that the former results in strong random sequences and does not contribute to improvements of prediction but the latter does.

Free Research Field

機械学習