Cover Image

Modeling and Forecasting Stochastic Seasonality: Are Seasonal Autoregressive Integrated Moving Average Models Always the Best Choice?

Fuente: Wiley Open Access

Saved in:

Bibliographic Details
Main Authors:	Evangelos E. Ioannidis, Sofia‐Eirini Nikolakakou
Format:	Artículo Open Access
Published:	Wiley 2025
Subjects:	Journal of Forecasting
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Seasonal Decomposition‐Enhanced Deep Learning Architecture for Probabilistic Forecasting
by: Keyan Jin, et al.
Published: (2025)

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

Modeling and Forecasting the CBOE VIX With the TVP‐HAR Model
by: Wen Xu, et al.
Published: (2025)

Adaptive Model Integration for Stock Price Forecasting With CNN‐ATTN‐BiLSTM
by: Yi Xiao, et al.
Published: (2026)

Combined Effects of Fat‐Tail and Spread Forecasting on Pairs Trading: A Hybrid Model Based on Integrating VAR With GRU Models
by: Yuhee Kwon, et al.
Published: (2025)

Leveraging Structural Insights: Enhancing Inflation Forecasting With Dynamic Stochastic General Equilibrium‐Informed Long Short‐Term Memory Models
by: Langfeng Zhou, et al.
Published: (2026)

Forecasting and Modeling Macroeconomic Vulnerabilities in CESEE
by: Florian Huber, et al.
Published: (2025)

Trade and Economic Activity: Nonlinear Modeling and Forecasting
by: Alessandro Borin, et al.
Published: (2024)

Macroeconomic and Financial Forecasting in the Aftermath of the Covid Shock: Inflation Forecasting With Large Language Models
by: Nikolaos Giannellis, et al.
Published: (2026)

Modelling and Forecasting of Exchange Rate Pairs Using the Kalman Filter
by: Paresh Date, et al.
Published: (2024)

Enhancing Neural Network Volatility Forecasting: Decomposed Volatility Modeling
by: Xuzheng Ren, et al.
Published: (2026)

Forecasting With Dynamic Factor Models Estimated by Partial Least Squares
by: Samuel Rauhala
Published: (2026)

Forecasting the High‐Frequency Covariance Matrix Using the LSTM‐MF Model
by: Guangying Liu, et al.
Published: (2025)

A New Proposal for Forecasting Inflation in the Eurozone: A Global Model
by: Georgios Angelopoulos, et al.
Published: (2026)

Using a Wage–Price‐Setting Model to Forecast US Inflation
by: Nguyen Duc Do
Published: (2024)

Support Vector Machine to Forecast Reexamination Invalidation Decisions for Utility Model Patent
by: Mei‐Hsin Wang, et al.
Published: (2025)

Forecasting COVID‐19 Transmission: Insights From the Logistic Smooth Transition Model
by: Yeliz Uymaz, et al.
Published: (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
by: Noman Arshed, et al.
Published: (2026)

Forecasting Realized Volatility With Tree‐Based HAR‐Type Models Incorporating Macroeconomic Uncertainty
by: Wei Liu, et al.
Published: (2026)

The term structure of interest rates and economic activity: Evidence from the COVID‐19 pandemic
by: Evangelos Salachas, et al.
Published: (2024)

A Universal Multivariate Long‐Term Time‐Series Robust Forecasting Model With Distinguishable Variable Identifier
by: Xin‐ji Chen, et al.
Published: (2026)

Fiscal Forecasting Rationality Among Expert Forecasters
by: Belen Chocobar, et al.
Published: (2024)

Matrix Autoregressive Time Series With Reduced‐Rank and Sparse Structural Constraints
by: Xiaohang Wang, et al.
Published: (2025)

HyperVIX: A GWO‐Optimized ARIMA‐LSTM Hybrid Model for CBOE Volatility Index (VIX) Forecasting
by: Ran Wu, et al.
Published: (2025)

Whether Uncertainty Theory Can Enhance GDP Forecasting From Energy: A New Uncertain MIDAS Model
by: Yuxin Shi, et al.
Published: (2025)

A Hybrid Deep Learning Model for Coal Index Forecasting Based on Sentiment Analysis and Decomposition–Reconstruction Methods
by: Yi Xiao, et al.
Published: (2025)

Medium‐ to Long‐Term Demand Forecasting in Retail and Manufacturing Organizations: Integration of Machine Learning, Human Judgment, and Interval Variable
by: Sushil Punia
Published: (2025)

A Novel Approach to Forecasting After Large Forecast Errors
by: Jennifer L. Castle, et al.
Published: (2025)

A Comparative Forecasting Framework for Turkey–Germany Trade: Evidence From Time Series and Artificial Neural Networks Models
by: Seyma Nur Unal, et al.
Published: (2025)

A Multiscale Transformer Model for Long Time Series Forecasting Based on Discrete Wavelet Transform and Residual Learning Modules
by: Menghan Li, et al.
Published: (2025)

Integrating Google Mobility Indices for Forecasting Infectious Diseases Incidence: A Multi‐Country Study on COVID‐19 With LightGBM
by: Milton Soto‐Ferrari
Published: (2025)

Forecasting in turbulent times
by: Nikolaos Giannellis, et al.
Published: (2024)

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

Crossproduct Effect and Volatility Forecasting
by: Jiafu Xu, et al.
Published: (2024)

Coherent Forecasting of Realized Volatility
by: Marius Puke, et al.
Published: (2026)

Forecasting Natural Gas Futures Prices Using Hybrid Machine Learning Models During Turbulent Market Conditions: The Case of the Russian–Ukraine Crisis
by: Pavan Kumar Nagula, et al.
Published: (2025)

On Capturing Multi‐Scale Market Dynamics for High‐Frequency Stock Price Forecasting Using a Hybrid Attention‐Based Deep Learning Model
by: Runze Jiang, et al.
Published: (2026)

Mortality Forecasting Using Variational Inference
by: Patrik Andersson, et al.
Published: (2025)

Forecasting and Pricing in the Carbon Credits Market
by: Yiyang Chen, et al.
Published: (2026)

Nonstationary Functional Time Series Forecasting
by: Han Lin Shang, et al.
Published: (2024)