The paper reviews human behavior simulation research by behavior type, objective, and methodology, and identifies open problems such as multi-behavior joint simulation and LLM-driven agents.
CTMSTOU driven markets: simulated environment for regime-awareness in trading policies
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abstract
Market regimes is a popular topic in quantitative finance even though there is little consensus on the details of how they should be defined. They arise as a feature both in financial market prediction problems and financial market task performing problems. In this work we use discrete event time multi-agent market simulation to freely experiment in a reproducible and understandable environment where regimes can be explicitly switched and enforced. We introduce a novel stochastic process to model the fundamental value perceived by market participants: Continuous-Time Markov Switching Trending Ornstein-Uhlenbeck (CTMSTOU), which facilitates the study of trading policies in regime switching markets. We define the notion of regime-awareness for a trading agent as well and illustrate its importance through the study of different order placement strategies in the context of order execution problems.
fields
cs.HC 1years
2024 1verdicts
ACCEPT 1representative citing papers
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Human Behavior Simulation: Objectives, Methodologies, and Open Problems
The paper reviews human behavior simulation research by behavior type, objective, and methodology, and identifies open problems such as multi-behavior joint simulation and LLM-driven agents.