Buchumschlag

How Does Cyber Risk Impact Systemic Stability?

Fuente: Wiley Open Access

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Kung‐Cheng Ho, Shih‐Cheng Lee, Zikui Pan, Andreas karathanasopoulos
Format:	Artículo Open Access
Veröffentlicht:	Wiley 2025
Schlagworte:	Journal of Forecasting
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Stock movement prediction: A multi‐input LSTM approach
von: Pan Tang, et al.
Veröffentlicht: (2024)

US Climate Shocks: The Double Risk for the Global Financial Stability
von: Brahim Gaies, et al.
Veröffentlicht: (2026)

GDP Nowcasting With Artificial Neural Networks: How Much Does Long‐Term Memory Matter?
von: Kristóf Németh, et al.
Veröffentlicht: (2025)

Harnessing volatility cascades with ensemble learning
von: Mingmian Cheng
Veröffentlicht: (2024)

Measuring the Impact of Transition Risk on Financial Markets: A Joint VaR‐ES Approach
von: Laura Garcia‐Jorcano, et al.
Veröffentlicht: (2025)

Point and Risk estImation Using an enSemble of Models for Nowcasting: PRISM‐Now
von: Beomseok Seo, et al.
Veröffentlicht: (2026)

Forecasting the realized volatility of agricultural commodity prices: Does sentiment matter?
von: Matteo Bonato, et al.
Veröffentlicht: (2024)

Risk Spillover Network in Commodity Markets Under Climate Transition Risk
von: Zhihong Niu, et al.
Veröffentlicht: (2025)

Measuring the Default Risk of Small Business Loans: Improved Credit Risk Prediction Using Deep Learning
von: Yiannis Dendramis, et al.
Veröffentlicht: (2025)

The effects of governance quality on renewable and nonrenewable energy consumption: An explainable decision frame
von: Futian Weng, et al.
Veröffentlicht: (2024)

Common Shocks and Climate Risk in European Equities
von: Andrea Cipollini, et al.
Veröffentlicht: (2025)

Fire Prediction and Risk Identification With Interpretable Machine Learning
von: Shan Dai, et al.
Veröffentlicht: (2025)

Lost in Translation? Risk‐Adjusting RMSE for Economic Forecast Performance
von: Lukas Salcher, et al.
Veröffentlicht: (2026)

Global Risk Aversion: Driving Force of Future Real Economic Activity
von: Jinhwan Kim, et al.
Veröffentlicht: (2024)

Machine Learning Forecasts of Tail‐Risk Spillovers in Carbon and Energy Markets
von: Shengnan Liu, et al.
Veröffentlicht: (2026)

A Two‐Stage Interpretable Model to Explain Classifier in Credit Risk Prediction
von: Lu Wang, et al.
Veröffentlicht: (2025)

Forecasting Corporate Default Risk Across Multiple Horizons With Interpretable Machine Learning
von: Qingli Dong, et al.
Veröffentlicht: (2026)

Parametric Quantile Autoregressive Conditional Duration Models With Application to Intraday Value‐at‐Risk Forecasting
von: Helton Saulo, et al.
Veröffentlicht: (2024)

Estimation of Constrained Factor Models for High‐Dimensional Time Series
von: Yitian Liu, et al.
Veröffentlicht: (2025)

Enhancing Financial Tail Risk Forecasting: A Blending Ensemble Framework for Nonlinear Expectile Regression
von: Yaolan Ma, et al.
Veröffentlicht: (2026)

Information Illusion: Different Amounts of Information and Stock Price Estimates
von: Andreas Oehler, et al.
Veröffentlicht: (2025)

Climate Change Risk and Financial Market Response: An International Evidence From Performance Forecasts by Financial Analysts
von: Cyrine Khiari, et al.
Veröffentlicht: (2025)

Forecasting Energy Efficiency in Manufacturing: Impact of Technological Progress in Productive Service and Commodity Trades
von: Zixiang Wei, et al.
Veröffentlicht: (2025)

Forecasting Gold Volatility in an Uncertain Environment: The Roles of Large and Small Shock Sizes
von: Li Zhang, et al.
Veröffentlicht: (2025)

Probabilistic electricity price forecasting based on penalized temporal fusion transformer
von: He Jiang, et al.
Veröffentlicht: (2024)

The Impact of News Sentiment on the Bitcoin Price via Machine Learning and Deep Learning‐Based NLP Models
von: Yunus Emre Gür, et al.
Veröffentlicht: (2025)

Visualizing Uncertainty in Time Series Forecasts: The Impact of Uncertainty Visualization on Users' Confidence, Algorithmic Advice Utilization, and Forecasting Performance
von: Dirk Leffrang, et al.
Veröffentlicht: (2024)

Forecasting Life Cycle Costs of Weapon Systems: An Open Source Approach With Artificial Intelligence
von: Martín Díaz Cuesta, et al.
Veröffentlicht: (2026)

Long‐term forecasting of maritime economics index using time‐series decomposition and two‐stage attention
von: Dohee Kim, et al.
Veröffentlicht: (2024)

A multi‐objective optimization metaheuristic hybrid technique for forecasting the electricity consumption of the UAE: A grey wolf approach
von: Andreas Karathanasopoulos, et al.
Veröffentlicht: (2024)

Optimized Internet of Things‐Based Intelligent Energy Management System for Enhanced Renewable Generation through Advanced Forecasting and Load Strategies
von: X. Mercilin Raajini, et al.
Veröffentlicht: (2026)

Forecasting European Union Electronic Trading Systems Phase 4 Spot Prices Using Data‐Driven Hybrid Deep Learning Models: Integrating Energy and Market Activity as Controls
von: Noman Arshed, et al.
Veröffentlicht: (2026)

Deciphering Long‐Term Economic Growth: An Exploration With Leading Machine Learning Techniques
von: Zin Mar Oo, et al.
Veröffentlicht: (2025)

Forecasting Volatility of Australian Stock Market Applying WTC‐DCA‐Informer Framework
von: Hongjun Zeng, et al.
Veröffentlicht: (2025)

On the Optimal Selection of Time‐Lag Embedding Dimension for Deep Learning Approaches in Financial Forecasting With Big Data
von: Mohammadreza Ghadimpour, et al.
Veröffentlicht: (2025)

A Novel Multiclass Imbalance Classification Framework With Dynamic Evidential Fusion for Credit Rating
von: Wen‐hui Hou, et al.
Veröffentlicht: (2025)

A Dynamic Fuzzy Modeling Method for Interval Time Series and Applications in Range‐Based Volatility Prediction
von: Leandro Maciel, et al.
Veröffentlicht: (2025)

Modeling Volatility Dynamics in Emerging Markets: Novel Evidence From Large Set of Predictors
von: Maria Ghani, et al.
Veröffentlicht: (2025)

Scaling‐Aware Rating of Poisson‐Limited Demand Forecasts
von: Malte C. Tichy, et al.
Veröffentlicht: (2025)

Innovative Techniques to Predict Churn in the French Insurance Industry: Integration of Machine Learning With the Grabit Model
von: Christophe Schalck, et al.
Veröffentlicht: (2025)