Accepted Papers

Financial institutions face increasing complexity in assessing borrower default, market risk and operational risk. This paper proposes a unified machine-learning framework that combines gradient-boosted tree ensembles (XGBoost, LightGBM), a stacked meta-learner, and a SHAP-based …

We extend the dynamic-conditional-correlation GARCH framework with a transformer encoder to model time-varying volatility transmission across six Asian equity indices. The hybrid model captures both short-term shocks and longer-range dependencies that conventional MV-GARCH specif…

Optimal trade execution in the Chinese A-share market is complicated by T+1 settlement, daily price limits, and pronounced order-book imbalance dynamics. We present a deep deterministic policy gradient (DDPG) agent that ingests micro-second-level Level-2 order book snapshots and …

Traditional credit-scoring models treat firms as independent observations, ignoring contagion effects propagating through supply-chain and ownership networks. We construct a heterogeneous corporate graph for ~5,800 Chinese listed firms, integrating supplier-customer linkages, equ…

We benchmark four Chinese-capable language models — ChatGLM-3, Qwen-2, BERT-wwm-Chinese, and FinBERT-CN — for sentence-level sentiment extraction on a hand-labelled corpus of 14,000 earnings-call transcripts from Shanghai and Shenzhen-listed firms (2018-2024). Qwen-2 with chain-o…

Mobile-payment ecosystems generate billions of micro-transactions with extreme class imbalance (suspicious-to-normal ratio ~1:100,000). We propose a two-tier stacking ensemble combining gradient-boosted trees, an autoencoder reconstruction-error detector, and a graph-based commun…