NextFund: A Unified Performance Tracking Platform for Agentic Portfolio Management

2026-07-13

AI Summary

This work addresses the limitations of existing financial agent evaluation frameworks, which often rely on static benchmarks or focus solely on final returns, thereby lacking traceability of decision-making processes and hindering fine-grained, fair performance assessment in dynamic markets. To overcome these challenges, the authors propose a unified performance tracking platform for financial agents that, for the first time, enables persistent logging of the complete decision trajectory—from market observation to trade execution. By integrating a time-consistent market data interface, a multi-agent collaborative architecture, and an end-to-end logging system, the platform supports interactive, cross-market and cross-model attribution analysis. Deployed across Hong Kong, U.S., and A-share markets, the system—augmented with a visual Trading Arena interface—significantly enhances the transparency, interpretability, and diagnostic capability of agent evaluation.

Abstract

Large language models (LLMs) based agents are beginning to participate in portfolio construction and market analysis, where decisions must be justified under evolving information and risk constraints. Current assessment practice, however, remains poorly aligned with this setting: many studies rely on static examinations or report only terminal portfolio returns, while the intermediate evidence, analyst judgments, and execution steps that produced those returns stay largely invisible. We introduce NextFund, an evaluation platform that makes financial-agent behavior observable under live market conditions. The platform couples time-consistent market access, coordinated multi-agent analysis, and persistent logging of the full decision path from observation to trade. Through an interactive Trading Arena, users can compare models across markets, inspect equity curves, and drill from leaderboard outcomes down to individual justifications. We present NextFund on Hong Kong, U.S., and China A-share equities, illustrating how inspectable decision histories enable fairer benchmarking and more actionable diagnosis. Our demo is available at https://paradoox.cn/nextfund/.

Problem

• agentic portfolio management
• performance tracking
• financial-agent evaluation
• decision transparency
• LLM-based agents

Innovation

• Agentic Portfolio Management
• Decision Path Logging
• Time-Consistent Market Access
• Multi-Agent Financial Analysis
• Interpretable Benchmarking