Forecasting energy markets using support vector machines

No abstract is available for this paper.

• Publication year

  2014

• Venue

  Energy Economics

• Publication date

  2014-07-01

• Fields of study

  Engineering, Computer Science, Economics

• Identifiers
  DOI 10.1016/J.ENECO.2014.03.017
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• The Price and Trading Volume Dynamics Relationship in the EEX Power Market: A Wavelet Modeling

  2013cited by this paper
• Day-ahead electricity price forecasting using WT, CLSSVM and EGARCH model

  2013cited by this paper
• Classification of Future Electricity Market Prices

  2011cited by this paper
• A RBF neural network model with GARCH errors: Application to electricity price forecasting

  2011cited by this paper
• Causal modeling and inference for electricity markets

  2011cited by this paper
• HMM filtering and parameter estimation of an electricity spot price model

  2010cited by this paper
• On the market impact of wind energy forecasts

  2010cited by this paper
• Price formation in electricity forward markets and the relevance of systematic forecast errors

  2009cited by this paper
• Quantifying the supply-side benefits from forward contracting in wholesale electricity markets

  2007cited by this paper
• Day-ahead price forecasting of electricity markets by a new fuzzy neural network

  2006cited by this paper
• A Neural Network Approach to m-Daily-Ahead Electricity Price Prediction

  2006cited by this paper
• Stable modeling of different European power markets

  2005cited by this paper
• A GARCH forecasting model to predict day-ahead electricity prices

  2005cited by this paper
• Day-ahead electricity price forecasting using the wavelet transform and ARIMA models

  2005cited by this paper
• Forecasting electricity spot-prices using linear univariate time-series models

  2004cited by this paper
• Forecasting Next-Day Electricity Prices by Time Series Models

  2002cited by this paper
• ARIMA Models to Predict Next-Day Electricity Prices

  2002cited by this paper
• Support-Vector Networks

  1995cited by this paper

• Data Sharing, Privacy and Security Considerations in the Energy Sector: A Review from Technical Landscape to Regulatory Specifications

  2025cites this paper
• Forecasting Renewable Energy Consumption Using a Novel Fractional Grey Reverse Accumulation Model

  2025cites this paper
• Day-Ahead Electricity Price Forecasting Using the XGBoost Algorithm: An Application to the Turkish Electricity Market

  2025cites this paper
• Electricity Price Volatility and the Performance of Machine Learning Forecasting Models in European Energy Markets

  2025cites this paper
• Risk formulation mechanism among top global energy companies under large shocks

  2025cites this paper
• Crude oil Price forecasting: Leveraging machine learning for global economic stability

  2025cites this paper
• Day-ahead electricity price prediction in multi-price zones based on multi-view fusion spatio-temporal graph neural network

  2024cites this paper
• Predicting Electricity Market Price Using Machine Learning and Quantifying Dependency Beyond Renewable Energy

  2024cites this paper
• Forecasting crude oil price: A deep forest ensemble approach

  2024cites this paper
• Seasonality in deep learning forecasts of electricity imbalance prices

  2024cites this paper
• Unraveling the crystal ball: Machine learning models for crude oil and natural gas volatility forecasting

  2024cites this paper
• Forecasting Real Oil Returns Using a Deep Forest Ensemble Approach

  2024cites this paper
• A Scenario-Based Model Comparison for Short-Term Day-Ahead Electricity Prices in Times of Economic and Political Tension

  2023cites this paper
• Deep Learning-Based Imbalance Market Price Range Predictions in the Day-Ahead Horizon

  2023cites this paper
• TBDQN: A novel two-branch deep Q-network for crude oil and natural gas futures trading

  2023cites this paper
• Forecasting per Capita Energy Consumption in China Using a Spatial Discrete Grey Prediction Model

  2023cites this paper
• A DSO flexibility platform based on an optimal congestion management model for the European CoordiNet project

  2023cites this paper
• MFO Tunned SVR Models for Analyzing Dimensional Characteristics of Cracks Developed on Steam Generator Tubes

  2022cites this paper
• A novel metal futures forecasting system based on wavelet packet decomposition and stochastic deep learning model

  2022cites this paper
• Early warning system to predict energy prices: the role of artificial intelligence and machine learning

  2022cites this paper
• A multivariate grey prediction model based on energy logistic equation and its application in energy prediction in China

  2021cites this paper
• Machine Learning in Energy Forecasts with an Application to High Frequency Electricity Consumption Data

  2021cites this paper
• Scalable Smartification of Commercial Buildings HVAC Systems Using the Internet of Things and Machine Learning

  2021cites this paper
• Forecasting automobile gasoline demand in Australia using machine learning-based regression

  2021cites this paper
• Analysis and forecast of China's energy consumption structure

  2021cites this paper
• Identifying Consumer Preferences From User-Generated Content on Amazon.Com by Leveraging Machine Learning

  2021cites this paper
• Electric Water Heaters Management via Reinforcement Learning With Time-Delay in Isolated Microgrids

  2021cites this paper
• Forecasting the concentration of sulfur dioxide in Beijing using a novel grey interval model with oscillation sequence

  2021cites this paper
• A New Hybrid Forecasting Model Based on SW-LSTM and Wavelet Packet Decomposition: A Case Study of Oil Futures Prices

  2021cites this paper
• A machine learning-based surrogate model to approximate optimal building retrofit solutions

  2021cites this paper
• A Review of Machine Learning Applications in Electricity Market Studies

  2020cites this paper
• A granular deep learning approach for predicting energy consumption

  2020cites this paper
• Statistical learning and exchange rate forecasting

  2020cites this paper
• A novel hybrid forecasting scheme for electricity demand time series

  2020cites this paper
• Daily natural gas price forecasting by a weighted hybrid data-driven model

  2020cites this paper
• Forecasting Electricity Prices: A Machine Learning Approach

  2020cites this paper
• A novel hybrid approach to forecast crude oil futures using intraday data

  2020cites this paper
• Dynamic Residential Energy Management for Real-Time Pricing

  2020cites this paper
• A comparison of modern deep neural network architectures for energy spot price forecasting

  2020cites this paper
• The Impact of Renewable Energy Generation on the Spot Market Price in Germany: Ex-Post Analysis using Boosting Method

  2020cites this paper
• Energy futures and spots prices forecasting by hybrid SW-GRU with EMD and error evaluation

  2020cites this paper
• The role of the threshold effect for the dynamics of futures and spot prices of energy commodities

  2020cites this paper
• Utilization of Big Data in Energy Internet Infrastructure

  2020cites this paper
• The Impact of Renewable Energy Generation on the Spot Market Price in Germany: Ex-Post Analysis using Boosting Method

  2020cites this paper
• A Deep Learning CNN and AI-Tuned SVM for Electricity Consumption Forecasting: Multivariate Time Series Data

  2019cites this paper
• Impact of Influencing Factors on CO2 Emissions in the Yangtze River Delta during Urbanization

  2019cites this paper
• A Novel Optimized Nonlinear Grey Bernoulli Model for Forecasting China's GDP

  2019cites this paper
• A novel combined model based on hybrid optimization algorithm for electrical load forecasting

  2019cites this paper
• A comprehensive review on the application of artificial neural networks in building energy analysis

  2019cites this paper
• The VEC-NAR model for short-term forecasting of oil prices

  2019cites this paper
• Modeling Drying-Energy Consumption in Automotive Painting Line Based on ANN and MLR for Real-Time Prediction

  2019cites this paper
• Machine learning in energy economics and finance: A review

  2019cites this paper
• Research on Economic Recession Prediction Model From the Multiple Behavioral Features Perspective

  2019cites this paper
• Hybrid machine learning methods for demand forecasting: consecutive application of classification and regression methods for the forecasting of periodic and non-continuous demand

  2019cites this paper
• Carry Trade Returns with Support Vector Machines

  2019cites this paper
• The green behavioral effect of clean coal technology on China's power generation industry.

  2019cites this paper
• Modeling Drying-Energy Consumption in Automotive Painting Line Based on ANN and MLR for Real-Time Prediction

  2019cites this paper
• Forecasting and trading high frequency volatility on large indices

  2018cites this paper
• Coal overcapacity in China: Multiscale analysis and prediction

  2018cites this paper
• Support vector regression modelling and optimization of energy consumption in carbon fiber production line

  2018cites this paper
• Study of the impacts of upstream natural gas market reform in China on infrastructure deployment and social welfare using an SVM-based rolling horizon stochastic game analysis

  2018cites this paper
• Probabilistic Electricity Price Forecasting Models by Aggregation of Competitive Predictors

  2018cites this paper
• Forecasting Electricity Market Price for End Users in EU28 until 2020—Main Factors of Influence

  2018cites this paper
• Customer demand prediction of service-oriented manufacturing using the least square support vector machine optimized by particle swarm optimization algorithm

  2017cites this paper
• Forecasting stochastic neural network based on financial empirical mode decomposition

  2017cites this paper
• Power Demand Forecasting and Application based on SVR

  2017cites this paper
• Forecasting the total energy consumption in China using a new-structure grey system model

  2017cites this paper
• Customer demand prediction of service-oriented manufacturing incorporating customer satisfaction

  2016cites this paper
• Combining high frequency data with non-linear models for forecasting energy market volatility

  2016cites this paper
• Energy consumption control automation using Artificial Neural Networks and adaptive algorithms: Proposal of a new methodology and case study

  2016cites this paper
• Mid-Term Electricity Market Clearing Price Forecasting with Sparse Data: A Case in Newly-Reformed Yunnan Electricity Market

  2016cites this paper
• Still Crazy after All These Years: The Returns on Carry Trade

  2016cites this paper
• Factors affecting households' decisions in biogas technology adoption, the case of Ofla and Mecha Districts, northern Ethiopia

  2016cites this paper
• Implementación de algoritmos basados en máquinas de soporte vectorial (SVM) para sistemas eléctricos: revisión de tema

  2016cites this paper
• Forecasting the natural gas demand in China using a self-adapting intelligent grey model

  2016cites this paper
• A New Electricity Price and Load Uncertainty Prediction Method based on Optimal Neural Networks for Deregulated Electricity Power Markets

  2016cites this paper
• Future development of the air‐conditioning market in Europe: an outlook until 2020

  2016cites this paper
• Forecasting of a hydropower plant energy production

  2015cites this paper
• Genetic Optimal Regression of Relevance Vector Machines for Electricity Pricing Signal Forecasting in Smart Grids

  2015cites this paper
• Forecasting the U.S. Real House Price Index

  2015cites this paper
• Yield Curve Point Triplets in Recession Forecasting

  2015cites this paper
• Forecasting Electricity Prices Using Exogenous Predictors

  2015cites this paper
• Forecasting the Term Structure of Crude Oil Futures Prices with Neural Networks

  2015cites this paper
• Coupling High-Frequency Data with Nonlinear Models in Multiple-Step-Ahead Forecasting of Energy Markets' Volatility

  2014cites this paper
• Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction

  2014cites this paper