Financial Time Series Forecasting Using Empirical Mode Decomposition and Support Vector Regression

Risks- Switzerland

doi 10.3390/risks6010007

Full Text

Abstract

Available in

Date

Authors

Publisher

MDPI AG

Related search

A Forecasting Methodology Using Support Vector Regression and Dynamic Feature Selection

Journal of Information and Knowledge Management
Computer NetworksComputer Science ApplicationsInformation SciencesLibraryCommunications
2006English

A Comparison of Time Series Forecasting Using Support Vector Machine and Artificial Neural Network Model

Journal of Applied Sciences
2010English

Identification of Under-Detected Periodicity in Time-Series Microarray Data by Using Empirical Mode Decomposition

PLoS ONE
Multidisciplinary
2014English

Forecasting Grain Supply and Demand With Support Vector Regression

DEStech Transactions on Computer Science and Engineering
2017English

Support Vector Regression Based GARCH Model With Application to Forecasting Volatility of Financial Returns

SSRN Electronic Journal
2008English

Renewable Power Output Forecasting Using Least-Squares Support Vector Regression and Google Data

Sustainability
DevelopmentManagementMonitoringEnvironmental ScienceRenewable EnergyEnergy EngineeringLawSustainabilityPlanningPolicyPower Technologythe EnvironmentGeography
2019English

Short-Term Wind Power Forecasting Using Support Vector Regression and Harmony Search Algorithm

2016English

Parameters Optimization Using Genetic Algorithms in Support Vector Regression for Sales Volume Forecasting

Applied Mathematics
2012English

Single-Trial Classification of Bistable Perception by Integrating Empirical Mode Decomposition, Clustering, and Support Vector Machine

Eurasip Journal on Advances in Signal Processing
HardwareElectronic EngineeringSignal ProcessingElectricalArchitecture
2008English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2026 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy