reward-listwise-rank-correlation-exact-numeric-forecasts TEC-0184 · proposedReward listwise rank correlation, not exact numeric forecast
Train the model with GRPO using a Spearman rank-correlation reward between its generated asset ordering and realized future returns, with a fixed penalty for malformed or hallucinated asset lists, then feed the ranking into Entropy Pooling
Proposed. Filed by the drafting stage because a paper introduces or tests it. Nobody has vouched for it. The claim drafted from that paper is its first evidence, and what the paper used to validate it is in that claim’s source note. Say whether it held up for you, below.
Train the model with GRPO using a Spearman rank-correlation reward between its generated asset ordering and realized future returns, with a fixed penalty for malformed or hallucinated asset lists, then feed the ranking into Entropy Pooling Filed by the drafting stage from FinRankGRPO: Optimizing LLMs for Listwise Financial Asset Ranking via Group Relative Policy Optimization (2609.24175) with status proposed: the paper introduces or tests it, and the claim drafted from the paper is its first evidence. The paper validated it by: Compared against equal weight, mean-variance, momentum, three commercial LLMs, and same-checkpoint SFT/standard-GRPO/NDCG@3/Kendall reward variants on Spearman, Kendall, NDCG@k, annualized return, Sharpe (0.636 best), and max drawdown, averaged over 5 trials; plus news-removal ablation (Sharpe 0.636 to 0.045) and a sentiment-inversion faithfulness check.. Nobody has vouched for it; add support or contest it on this page.
Does it work?
nothing measured0 supporting · 0 contesting sources
Efficacy claims — what this technique actually moves, under which conditions, and whether that has been contested.
No efficacy claim filed yet. The technique is catalogued; whether it moves the capability, and when, is a separate assertion that needs its own sources.
No search recorded either, so this says nothing about the literature — only that nobody has looked here yet.
Code
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Sources
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