Research graph
References from Asymmetric financial risk factor identification via LoRA-enhanced large language models and risk-sensitive causal forests. Local targets link to admitted publications; unresolved targets remain external evidence.
Double/debiased machine learning for treatment and structural parameters
10.1111/ectj.12097 · 2018 · External reference
Generalized random forests
10.1214/18-aos1709 · 2019 · External reference
Measuring market volatility connectedness to media sentiment
10.1016/j.najef.2024.102091 · 2024 · External reference
Forecasting the Bitcoin price using the various machine learning: a systematic review in data-driven marketing
10.1016/j.sasc.2025.200209 · 2025 · External reference
Towards data and analytics driven B2B-banking for green finance: a cross-selling use case study
10.1016/j.techfore.2024.123542 · 2024 · External reference
Unraveling asset pricing with AI: a systematic literature review
10.1016/j.asoc.2025.112978 · 2025 · External reference
Predicting option prices: from the Black-scholes model to machine learning methods
2025 · External reference
Optimizing stock investment strategies with double deep Q-Networks: exploring the impact of oil and gold price signals
10.1016/j.asoc.2025.113264 · 2025 · External reference
Metalearners for estimating heterogeneous treatment effects using machine learning
10.1073/pnas.1804597116 · 2019 · External reference
A survey of large language models for data challenges in graphs
2026 · External reference
Fundamental characteristics, machine learning, and stock price crash risk
10.1016/j.finmar.2024.100908 · 2024 · External reference
Financial asset allocation strategies using statistical and Machine Learning models: evidence from comprehensive scenario testing
10.1016/j.asoc.2025.113193 · 2025 · External reference
AI Agents in finance and fintech: a scientific review of agent-based systems, applications, and future horizons
10.32604/cmc.2025.069678 · 2026 · External reference
Asset pricing via fused deep learning with visual clues
10.1016/j.inffus.2023.102049 · 2024 · External reference
A multi-layer machine learning approach for cryptocurrency trading utilizing technical indicators and sentiment index
10.1108/ijicc-03-2025-0128 · 2025 · External reference
Graph learning and its advancements on large language models: a holistic survey
10.1016/j.neucom.2025.132396 · 2026 · External reference
Deep-DFVAR: dynamic factor vector autoregression with deep learning for regional house price index forecasting
10.1016/j.neucom.2025.131103 · 2025 · External reference
A robust machine learning framework for stock market classification
10.1016/j.eswa.2025.128573 · 2025 · External reference
Global stock market forecasting: insights from series and parallel combination of machine learning models
10.1016/j.pacfin.2025.102905 · 2025 · External reference
Machine learning in the Chinese stock market
10.1016/j.jfineco.2021.08.017 · 2022 · External reference
Detecting stock market manipulation via machine learning: evidence from China Securities Regulatory Commission punishment cases
10.1016/j.irfa.2021.101887 · 2021 · External reference
Machine learning models to predict stock market spillovers
2025 · External reference
Supply bottlenecks and machine learning forecasting of international stock market volatility
10.1016/j.frl.2025.108931 · 2025 · External reference
International oil shocks and the volatility forecasting of Chinese stock market based on machine learning combination models
10.1016/j.najef.2023.102065 · 2024 · External reference
Enhancing stock return prediction in the Chinese market: a GAN-based approach
10.1016/j.ribaf.2025.102760 · 2025 · External reference
Ascertaining price formation in financial markets with machine learning: evidence from Chinese stocks
10.1016/j.pacfin.2025.103029 · 2026 · External reference
Novel delayed binary time-series pattern based machine learning techniques for stock market forecasting
10.1016/j.array.2025.100426 · 2025 · External reference
Stock market index enhancement via machine learning
10.1016/j.ememar.2025.101325 · 2025 · External reference
A hybrid causal-inference and neuro-fuzzy framework for advanced process monitoring
10.1016/j.jprocont.2026.103724 · 2026 · External reference
A hybrid DiGLPP-Kolmogorov-Arnold Network framework for robust fault detection in industrial chemical processes
10.1016/j.psep.2026.108854 · 2026 · External reference
A novel dynamic machine learning-based explainable fusion monitoring: application to industrial and chemical processes
10.1088/2632-2153/ada088 · 2025 · External reference
Advance industrial monitoring of physio-chemical processes using novel integrated machine learning approach
2024 · External reference
Intelligent machine learning-based multi-model fusion monitoring: application to industrial physio-chemical systems
10.1016/j.conengprac.2025.106361 · 2025 · External reference
Process monitoring and dynamic fusion of complex industrial systems: a reconstruction-based bayesian framework
10.1016/j.compchemeng.2025.109352 · 2025 · External reference
Hybrid fusion paradigm in advanced process monitoring: a panoramic review and future perspectives
10.1021/acs.iecr.5c02759 · 2025 · External reference
