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Proceedings of the AAAI Conference on Artificial Intelligence

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Controllable Financial Market Generation with Diffusion G...
Yu-Hao Huang · 2026-03-14 · via Proceedings of the AAAI Conference on Artificial Intelligence

Authors

  • Yu-Hao Huang Nanjing University
  • Chang Xu Microsoft Research Asia
  • Yang Liu Microsoft Research Asia
  • Weiqing Liu Microsoft Research Asia
  • Wu-Jun Li Nanjing University
  • Jiang Bian Microsoft Research Asia

DOI:

https://doi.org/10.1609/aaai.v40i1.37009

Abstract

Generative modeling has transformed many fields, such as language and visual modeling, while its application in financial markets remains under-explored. As the minimal unit within a financial market is an order, order-flow modeling represents a fundamental generative financial task. However, current approaches often yield unsatisfactory fidelity in generating order flow, and their generation lacks controllability, thereby limiting their practical applications. In this paper, we formulate the challenge of controllable financial market generation, and propose a Diffusion Guided Meta Agent (DigMA) model to address it. Specifically, we employ a conditional diffusion model to capture the dynamics of the market state represented by time-evolving distribution parameters of the mid-price return rate and the order arrival rate, and we define a meta agent with financial economic priors to generate orders from the corresponding distributions. Extensive experimental results show that DigMA achieves superior controllability and generation fidelity. Moreover, we validate its effectiveness as a generative environment for downstream high-frequency trading tasks and its computational efficiency.

How to Cite

Huang, Y.-H., Xu, C., Liu, Y., Liu, W., Li, W.-J., & Bian, J. (2026). Controllable Financial Market Generation with Diffusion Guided Meta Agent. Proceedings of the AAAI Conference on Artificial Intelligence, 40(1), 462–470. https://doi.org/10.1609/aaai.v40i1.37009

Issue

Section

AAAI Technical Track on Application Domains I

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