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Official PDF TranslationFrontiers of Information Technology & Electronic Engineering

QuantBench: benchmarking AI methods for quantitative investment from a full pipeline perspective

Authors: Saizhuo WANG; Hao KONG; Jiadong GUO; Fengrui HUA; Yiyan QI; Wanyun ZHOU; Jiahao ZHENG; Xinyu WANG; Lionel M. NI; Jian GUO

DOI: 10.1631/FITEE_2500280Status: Verified Translated Edition
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Key Findings in This Report

• QuantBench is an industrial-grade benchmark platform that standardizes AI evaluation for quantitative investment, addressing the lack of alignment with industry practices. • It provides flexibility for integrating various AI algorithms and full-pipeline coverage, encompassing standardized datasets, model implementations, and evaluations. • Empirical studies reveal critical research directions: continual learning for distribution shifts, improved relational financial data modeling, and robust overfitting mitigation in low signal-to-noise environments. • By open-sourcing on GitHub, QuantBench aims to accelerate AI research in quantitative investment, akin to benchmarks in computer vision and NLP.