Emergence from Emergence: Financial Market Simulation via Learning with Heterogeneous Preferences
Ryuji Hashimoto, Ryosuke Takata, Masahiro Suzuki, Yuki Tanaka, Kiyoshi Izumi

TL;DR
This paper introduces a multi-agent reinforcement learning model where agents with diverse preferences learn trading strategies, leading to realistic market phenomena like fat tails and volatility clustering, highlighting the importance of joint modeling of preferences and learning.
Contribution
It develops a unified framework combining heterogeneous preferences and learning, demonstrating their joint impact on emergent market behaviors in agent-based models.
Findings
Agents develop strategies aligned with their traits.
Differentiated interactions lead to realistic market dynamics.
Heterogeneous preferences and learning jointly enable two-stage emergence.
Abstract
Agent-based models help explain stock price dynamics as emergent phenomena driven by interacting investors. In this modeling tradition, investor behavior has typically been captured by two distinct mechanisms -- learning and heterogeneous preferences -- which have been explored as separate paradigms in prior studies. However, the impact of their joint modeling on the resulting collective dynamics remains largely unexplored. We develop a multi-agent reinforcement learning framework in which agents endowed with heterogeneous risk aversion, time discounting, and information access collectively learn trading strategies within a unified shared-policy framework. The experiment reveals that (i) learning with heterogeneous preferences drives agents to develop strategies aligned with their individual traits, fostering behavioral differentiation and niche specialization within the market, and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComplex Systems and Time Series Analysis · Stock Market Forecasting Methods · Financial Markets and Investment Strategies
