公式化Alpha语言中的调整锚依赖:一个可验证语法与重锚审计
Adjustment-Anchor Dependence in Formulaic Alpha Languages: A Certified Grammar and a Re-Anchoring Audit
Zhengkai Tu, Xinyue Xiang, Jimmy Huang
AI 速读 基于摘要
该论文形式化了公式化Alpha挖掘中价格调整锚依赖问题,提出可验证锚不变性的类型系统,并通过重锚审计揭示已发表方法挖掘的池在存储表示上IC偏高。
cs.SI
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Several public scripts for formulaic alpha mining store prices adjusted to the snapshot's last day, so a past day's stored price changes with every later split or dividend and formulas that do not cancel the adjustment factor depend on future corporate actions. We formalise a change of adjustment anchor as a per-stock group action and give a two-sorted type system that soundly certifies anchor invariance from a formula's syntax, under a declared field-adjustment contract and idealised operator semantics; its second sort admits log-returns, and a linear-time checker plugs into any miner. In a re-anchoring audit on Chinese A-shares, pools that five published methods mined in our benchmark pipeline score a mean information coefficient (IC) 0.005 higher on the stored representation than on a cutoff-anchored one, about 14% of their IC. The mean signed change for certified pools is about -0.001, and pools mined on past-anchored data stay sensitive. On the Chinese development folds, certification shows no detectable predictive cost or gain; the estimated minimum detectable difference is about 0.017 IC across cells on pool ICs of 0.03-0.04. We also trace an erroneous index-membership entry to public Qlib data snapshots and show that re-mining exposes the effect of such data defects, which re-evaluating fixed pools understates.