Fragmentation and Information in Trading Financial Assets: A Reinforcement Learning Approach

• Project/Area Number: 24K22624
• Research Category: Grant-in-Aid for Research Activity Start-up
• Allocation Type: Multi-year Fund
• Review Section: 0107:Economics, business administration, and related fields
• Research Institution: Ritsumeikan Asia Pacific University
• Principal Investigator: QU Chengcheng 立命館アジア太平洋大学, 国際経営学部, 助教 (11000802)
• Project Period (FY): 2024-07-31 – 2026-03-31
• Project Status: Granted (Fiscal Year 2024)
• Budget Amount: ¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000); Fiscal Year 2025: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000); Fiscal Year 2024: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
• Keywords: Financial trading / Reinforcement learning / Market fragmentation

Outline of Research at the Start

This project addresses how fragmentation affects traders' order splitting strategies and the market quality per consequence using a machine learning approach that handles the complexity of real-time market dynamics.