Paper: arXiv 2610.41689

Authors: Yichong Bai, Kaigui Bian

Abstract

Formulaic alpha miners increasingly differ in how they generate candidates, yet each system typically couples its own representation, evaluator, and selector into a bespoke pipeline whose results are difficult to reproduce or compare. We present QBX, a compiler that defines a well-formed, auditable space of alpha programs. A finite, versioned block registry and whole-strategy port-DAG language define the candidate space; the compiler either rejects a proposal with structured diagnostics or emits an evidence-carrying IR with types, time-availability effects, executable linkage, and Merkle-style content identities. Compiler-closed actions keep search inside the admitted space, node identities support incremental evaluation, and context-bound root identities govern program deduplication and trial provenance. The availability-effect system rejects contract-visible look-ahead while admitting legal point-in-time forecasts. On Chinese A-share panels, evaluation-valid proposals increase from 26.8% for free strings and 36.4% for a grammar-only control to 97.7% for typed programs. Incremental evaluation replays search lineages 7.5 times faster with numerical parity, while the availability checker admits zero registered-contract violations across 23,342 candidates. Under matched LLM-call budgets, compiler-closed search reaches the pool-specific diagnostic frontier with substantially fewer calls. These results concern validity, reuse, and search efficiency within the registered vocabulary, not an increase in the information available from the market panel.

Complexity vs Empirical Score

  • Math Complexity: 6.5/10
  • Empirical Rigor: 8.0/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: This paper introduces a novel compiler-based approach to address critical issues in alpha program generation, including validity, reproducibility, and look-ahead bias. The empirical evaluation on Chinese A-share panels demonstrates significant improvements in proposal validity and search efficiency, showcasing strong practical relevance and rigorous testing. The methodology, while dense, presents a sophisticated solution to a pervasive problem in quant finance research.

Research Flowchart

  flowchart TD
    A[Research Goal: Define Well-Formed, Auditable Alpha Programs] --> B(Methodology: Design QBX Compiler & Language);
    B --> C{Inputs: Block Registry, Port-DAG Language, Chinese A-share Panels};
    C --> D[Computational Process: QBX Compilation, Type & Availability Checking, Incremental Evaluation];
    D --> E{Outcomes: Valid Programs, Reproductibility, Search Efficiency};
    E --> F[Key Findings: 97.7% Valid Programs; 7.5x Faster Incremental Eval; Zero Look-ahead Violations; Efficient LLM Search];