Buch, Englisch, 436 Seiten, Format (B × H): 155 mm x 235 mm
Third CCF China Digital Finance Conference, CDFC 2026, Guangzhou, China, November 6–8, 2026, Revised Selected Papers
Buch, Englisch, 436 Seiten, Format (B × H): 155 mm x 235 mm
Reihe: Communications in Computer and Information Science
ISBN: 978-981-9279-21-0
Verlag: Springer
This book constitutes the refereed post-conference proceedings of the third CCF China Digital Finance Conference on Digital Finance, CDFC 2026, held in Guangzhou, China, during November 6–8, 2026.
The 19 full papers presented in this volume were carefully reviewed and selected from 54 submissions.They were focused in following topical sections : Time-Series Modeling and Forecasting; Intelligent Investment and Quantitative Trading; Financial Risk Assessment and Fraud Detection; Large Models, Big Data, and Digital Finance Applications.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
.- Time-Series Modeling and Forecasting.
.- Zero-Shot Time Series Understanding with Large Language Models.
.- Restoring Attention in Financial LLMs: Diagnosis and Reconstruction.
.- AMFA-LSTM: An Explainable Adaptive Multi-Physical Filtering Network for High-Noise Financial Time Series Forecasting.
.- An Interval-Based Multi-Channel LSTM Framework for Financial Time Series Prediction.
.- Intelligent Investment and Quantitative Trading.
.- Multi-Factor Deep Learning for Intraday Path Modeling of the Shanghai Composite Index.
.- MemTrade-Agent: A Memory-Enhanced LLM Multi-Agent Trading System with Similar-Decision Retrieval.
.- Impact of Training Labeling Strategies on Trading Model Performance.
.- Financial Risk Assessment and Fraud Detection.
.- Ensemble Learning for Stock Manipulation Risk Screening in China’s A-Share Market.
.- Multi-modal Residual-enhanced Graph Attention Networks for Forward-Looking Corporate Credit Risk Prediction.
.- Financial Risk Prediction Using MD&A Semantic Embeddings and Hybrid Deep Learning: Evidence from Chinese A-Share Listed Companies.
.- RAGD: Relation-Aware Graph Augmentation with Decoupled Dual-Granularity Contrastive Learning for Multi-Relational Graph Fraud Detection.
.- Rethinking Tabular Test-Time Adaptation with Coarse-Grained Statistical Prompts.
.- Extreme Risk Identification of the Shanghai Composite Index Based on a tsfresh–FSA–TW Framework.
.- Large Models, Big Data, and Digital Finance Applications.
.- Outcome Collapse in Financial Assessment with GRPO: Diagnosis and Correction via Distribution-Balanced Aggregation.
.- PANO-Bench: A Public Information-Grounded Benchmark for Annual Narrative Generation and Open-Ended Evaluation.
.- A Multimodal Multi-Agent Method for Financial Reimbursement Verification and Risk Identification.
.- Diagnosing LLM Non-Determinism in Multi-Agent Financial Systems: A Layer-wise Propagation Framework.
.- Scaling Before Gains: AI Adoption and Team Expansion in Digital Finance.
.- A Simple Yet Effective Technique for Improving Distribution Matching Distillation via Random Layer Skip.
