ShiJianBench - Investor Outcome: leaderboard

ShiJianBench (2026) places an LLM investment advisor in conversation with 27 simulated investors, a multi-agent simulator calibrated on 7,199 real users, while Chinese public-fund history from 2021 to 2026 replays, and scores each advisor against a matched rollout without advice. This component scores the uplift in returns and drawdown control of the advised investors over the full horizon, on a 0-100 scale; higher is better.

Metric: Investment score (0-100): 0.6 x return-uplift + 0.4 x drawdown-reduction scores of the advised investors against the matched no-advisor rollout, full horizon, over five matched runs of 27 simulated investors (risk profile x financial literacy x asset tier, weighted by 7,199 real users) in an LLM investor simulator replaying Chinese public-fund market traces, with GPT-4o judging advisor messages. Source: arxiv.org. Saturation forecast: Estimated already saturated. 5 models tracked.

Top models

#ModelScoreOverall rank
1GPT-564.1#167
2DeepSeek V4 Flash64.09#258
3Claude Sonnet 4.664.08#161

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=shijianbench-investor-outcome · How It Works · Data refreshed daily, snapshot 2026-11-13.