Short term prediction of market prices using tick data

Research Project

Project/Area Number	16K12492
Research Category	Grant-in-Aid for Challenging Exploratory Research
Allocation Type	Multi-year Fund
Research Field	Intelligent informatics
Research Institution	Keio University
Principal Investigator	Sakurai Akito 慶應義塾大学, 理工学部(矢上), 教授 (00303339)
Research Collaborator	Serjam Chanakya
Project Period (FY)	2016-04-01 – 2019-03-31
Project Status	Completed (Fiscal Year 2018)
Budget Amount *help	¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000) Fiscal Year 2018: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000) Fiscal Year 2017: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000) Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Keywords	外国為替証拠金取引 / 収益分布 / ティックデータ / 金融時系列 / リターン・リバーサル / 収益符号予測 / 機械学習 / 経済時系列予測
Outline of Final Research Achievements	The purpose of the research is to improve accuracy of short and medium horizon (minutes to hours) prediction of asset prices in financial markets, specifically focused on minutely and tick movement of exchange rates in foreign exchange markets (mainly EUR/USD and USD/JPY). (1) We successfully modeled 1 to 90 minutely returns of the rates and also showed that the long-term predictability of the model is based on the fractal-like property of return reversals. (2) We successfully built models to explain the return reversals and regress the distribution of the minutely and tick returns, which is supported by simulations for 2001 to 2015 data.
Academic Significance and Societal Importance of the Research Achievements	金融市場における資産価格変動の重要な例である外国為替市場におけるbid値の変動に関し、収益反転の存在を明確に示し、それを反映した、価格変化である収益の分布をこれまでにない精度で記述できるモデルが構築できたことは、為替変動のリスク評価の精緻化、他の資産の価格変動のモデル化の研究に、大きく寄与すると考えられる。