[Teppei Ogihara] Machine learning theory in functional space and its application to high-frequency financial data analysis

Research Director

Teppei Ogihara

Teppei Ogihara

School of Statistical Thinking, Research Organization of Information and Systems The Institute of Statistical Mathematics
Assistant Professor
website

Outline

Recently, it is getting easier to obtain high-frequency financial data, that is, all trade records in intra-day security markets. Studying such data is a challenging issue because of its complicated structure in addition to enormous information content. In this study, we will establish a new statistical approach that enables us to study high-frequency financial data, by combining machine learning theory and the theory of stochastic processes.

Quick Access

Quick Access

 News

arrow On-going

arrow Completed

Program

  • CREST
  • PRESTO
  • ACT-I
  • ERATO
  • ACT-C
  • ACCEL
  • ALCA
  • RISTEX
Finish programs
  • Pamphlet
  • ProjectDB
  • GlobalActivity
  • Diversity-EN
  • OS_Policy-EN
  • Question-E