Reinforcement Learning in High-frequency Market Making
Y Zheng, Z Ding - arXiv preprint arXiv:2407.21025, 2024 - arxiv.org
This paper establishes a new and comprehensive theoretical analysis for the application of
reinforcement learning (RL) in high-frequency market making. We bridge the modern RL …
reinforcement learning (RL) in high-frequency market making. We bridge the modern RL …
Reinforcement Learning for Combining Search Methods in the Calibration of Economic ABMs
A Glielmo, M Favorito, D Chanda… - Proceedings of the Fourth …, 2023 - dl.acm.org
Calibrating agent-based models (ABMs) in economics and finance typically involves a
derivative-free search in a very large parameter space. In this work, we benchmark a …
derivative-free search in a very large parameter space. In this work, we benchmark a …
Multi-agent platform to support trading decisions in the FOREX market
Trading decisions often encounter risk and uncertainty complexities, significantly influencing
their overall performance. Recognizing the intricacies of this challenge, computational …
their overall performance. Recognizing the intricacies of this challenge, computational …
Simulating the economic impact of rationality through reinforcement learning and agent-based modelling
Agent-based models (ABMs) are simulation models used in economics to overcome some of
the limitations of traditional frameworks based on general equilibrium assumptions …
the limitations of traditional frameworks based on general equilibrium assumptions …
Calibration of Derivative Pricing Models: a Multi-Agent Reinforcement Learning Perspective
N Vadori - Proceedings of the Fourth ACM International …, 2023 - dl.acm.org
One of the most fundamental questions in quantitative finance is the existence of continuous-
time diffusion models that fit market prices of a given set of options. Traditionally, one …
time diffusion models that fit market prices of a given set of options. Traditionally, one …
Reinforcement Learning in Agent-Based Market Simulation: Unveiling Realistic Stylized Facts and Behavior
Z Yao, Z Li, M Thomas, I Florescu - arXiv preprint arXiv:2403.19781, 2024 - arxiv.org
Investors and regulators can greatly benefit from a realistic market simulator that enables
them to anticipate the consequences of their decisions in real markets. However, traditional …
them to anticipate the consequences of their decisions in real markets. However, traditional …
AI-driven prices for externalities and sustainability in production markets
Traditional competitive markets do not account for negative externalities; indirect costs that
some participants impose on others, such as the cost of over-appropriating a common-pool …
some participants impose on others, such as the cost of over-appropriating a common-pool …