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Overview of FinMMEval 2026 Task 3: Live Financial Decision-Making Agents

Author

Listed:
  • Zhuohan Xie

    (MBZUAI - Mohamed bin Zayed University of Artificial Intelligence)

  • Lingfei Qian

    (The Fin AI)

  • Georgi Georgiev

    (Faculty of Mathematics and Informatics [Sofia] - Sofia University Saint Kliment Ohridski - Софийски университет „Свети Климент Охридски)

  • Dimitar Dimitrov

    (Faculty of Mathematics and Informatics [Sofia] - Sofia University Saint Kliment Ohridski - Софийски университет „Свети Климент Охридски)

  • Yuyang Dai

    (INSAIT - Institute for Computer Science, Artificial Intelligence and Technology)

  • Rania Elbadry

    (MBZUAI - Mohamed bin Zayed University of Artificial Intelligence)

  • Vanshikaa Jani

    (University of Arizona)

  • Xueqing Peng

    (The Fin AI)

  • Fan Zhang

    (UTokyo - The University of Tokyo)

  • Jimin Huang

    (The Fin AI)

  • Jiahui Geng

    (LIU - Linköpings Universitet = Linköping University)

  • Yankai Chen

    (MBZUAI - Mohamed bin Zayed University of Artificial Intelligence, McGill University = Université McGill [Montréal])

  • Ye Yuan

    (McGill University = Université McGill [Montréal], Mila - Institut québécois d’intelligence artificielle = Quebec Artificial Intelligence Institute)

  • Haolun Wu

    (McGill University = Université McGill [Montréal], Mila - Institut québécois d’intelligence artificielle = Quebec Artificial Intelligence Institute)

  • Yuxia Wang

    (INSAIT - Institute for Computer Science, Artificial Intelligence and Technology)

  • Ivan Koychev

    (Faculty of Mathematics and Informatics [Sofia] - Sofia University Saint Kliment Ohridski - Софийски университет „Свети Климент Охридски)

  • Veselin Stoyanov

    (MBZUAI - Mohamed bin Zayed University of Artificial Intelligence)

  • Mingzi Song

    (Meiji Gakuin University)

  • Yu Chen

    (UTokyo - The University of Tokyo)

  • Xue Liu

    (MBZUAI - Mohamed bin Zayed University of Artificial Intelligence, McGill University = Université McGill [Montréal], Mila - Institut québécois d’intelligence artificielle = Quebec Artificial Intelligence Institute)

  • Preslav Nakov

    (MBZUAI - Mohamed bin Zayed University of Artificial Intelligence)

Abstract

FinMMEval 2026 Task 3 evaluates financial decision-making agents in a live endpoint-based setting. Participating teams deployed public HTTP endpoints that received daily market payloads and returned BUY, HOLD, or SELL decisions for BTC and TSLA. Unlike static question-answering benchmarks, this task evaluates trading decisions produced by complete agent services under repeated daily calls; endpoint reachability and response validity are deployment constraints of the protocol. For each accepted endpoint, the official ranking averages the BTC and TSLA cumulative returns, each computed from a long/flat/short portfolio simulation with an initial balance of 100,000. Within the official scoring window, simulated returns differed sharply by asset: Infraglyph led the cross-asset mean CR, Fin-Analyst achieved the highest TSLA return, and NLP-DE achieved the highest BTC return. This divergence shows why a multi-asset evaluation should report both aggregate and asset-level results.

Suggested Citation

  • Zhuohan Xie & Lingfei Qian & Georgi Georgiev & Dimitar Dimitrov & Yuyang Dai & Rania Elbadry & Vanshikaa Jani & Xueqing Peng & Fan Zhang & Jimin Huang & Jiahui Geng & Yankai Chen & Ye Yuan & Haolun Wu, 2026. "Overview of FinMMEval 2026 Task 3: Live Financial Decision-Making Agents," Post-Print hal-05726648, HAL.
    • Handle: RePEc:hal:journl:hal-05726648
    Note: View the original document on HAL open archive server: https://hal.science/hal-05726648v1
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