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Wei-Jian Huang

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Conference Aug 2026

A Deep Learning Framework for Fraud Detection on Multimodal Financial Report Data

Financial statement fraud (FSF) poses severe threats to investor confidence and capital market stability, yet most existing detection models rely solely on a single modality, such as either financial ratios extracted from tables or textual disclosures in management discussion. Such single-view models fail to capture th...

Jia-Wen Li, Zuo-Cheng Hu, Ming Qiang et al. · 0 citations
Open access Jul 2026

Reshaping Alpha with Conditional Probability: A Low-Cost Improvement Path for Index Timing

 Direct linear regression prediction of index returns has long been recognized as a challenging task in industry time-series timing research. Constrained by the extremely low signal-to-noise ratio and pervasive nonlinear characteristics of financial data, ordinary least squares (OLS) regression suffers from poor out-of...

Wei-Jian Huang, Yuanqi Huang, Xianpeng Jiang · 0 citations
Open access Jul 2026

Research on Machine Learning High-Frequency Trading Strategies Under Transaction Cost

There is a significant disconnect between model prediction accuracy and actual net returns; marginal improvements in prediction brought by complex models cannot offset profit losses caused by transaction frictions in high-frequency trading.

Wei-Jian Huang, Zhanwei Wang, Wenchang Jiang · 0 citations
Open access Jul 2026

Research on Machine Learning High-Frequency Trading Strategy of Cryptocurrency Based on Transaction Cost-Aware Filtering

The empirical results verify that the core bottleneck of high-frequency quantitative trading is not model prediction accuracy but the cost adaptation mechanism of signal transformation, and a simple and efficient transaction cost filtering strategy is far more valuable than blindly iterating complex time-series models.

Wei-Jian Huang, Zhanwei Wang, Xianpeng Jiang · 0 citations

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