FORESIGHT-9: Prospective and Process-Aware Evaluation of Adaptive Trading Agents

Trading-agent evaluation can fail at three successive levels: a ranking on realized history may not transfer reliably to alternative future paths, prospective returns may not exceed simple non-learning controls, and a favorable terminal outcome may persist after adaptation itself has stopped. We introduce FORESIGHT-9, a prospective and process-aware benchmark with nine auditable counterfactual worldlines branching from a common July 2026 information boundary. A com- mon contract fixes the market panel, cadence, constraints, costs, and account writes while preserving framework-specific research and proposal mechanisms. Across 36 long-horizon runs from two frameworks and two model backbones, Native-Policy Retrospective Replay yields a historical ranking whose median Spearman correlation with prospective rankings is −0.8; its winner remains first in only 1/9 worldlines. Prospectively, periodic equal weighting and a causal inverse- volatility rule each outperform 31 of 36 agent–worldline runs, showing that pos- itive agent returns need not establish incremental value from online adaptation. Finally, in a high-return WL8 run the live research library collapses while the declared ensemble persists and executed holdings converge toward equal weight: the run keeps earning after meaningful self-evolution has ceased. FORESIGHT- 9 therefore evaluates future robustness, incremental value over simple controls, and whether the intended adaptive mechanism remains functional. We release the worldlines, trajectories, audit traces, and deterministic regeneration scripts.