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A Novel Multivariate Decomposition Ensemble Model with News Text for Crude Oil Price Forecasting

https://doi.org/10.2139/ssrn.4186710
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.apenergy.2018.12.034openalex-extracted
Designing a multi-stage multivariate empirical mode decomposition coupled with ant colony optimization and random forest model to forecast monthly solar radiation
inferredcites →https://doi.org/10.1016/j.apenergy.2019.114033openalex-extracted
A multi-scale method for forecasting oil price with multi-factor search engine data
inferredcites →https://doi.org/10.1016/j.apenergy.2020.115035openalex-extracted
A novel hybrid model for forecasting crude oil price based on time series decomposition
inferredcites →https://doi.org/10.1016/j.asoc.2020.106161openalex-extracted
A new secondary decomposition-ensemble approach with cuckoo search optimization for air cargo forecasting
inferredcites →https://doi.org/10.1016/j.asoc.2022.108941openalex-extracted
A multivariate EMD-LSTM model aided with Time Dependent Intrinsic Cross-Correlation for monthly rainfall prediction
inferredcites →https://doi.org/10.1016/j.dsm.2021.10.002openalex-extracted
Tourism demand forecasting and tourists’ search behavior: evidence from segmented Baidu search volume
inferredcites →https://doi.org/10.1016/j.dsm.2022.05.002openalex-extracted
New developments in wind energy forecasting with artificial intelligence and big data: a scientometric insight
inferredcites →https://doi.org/10.1016/j.econmod.2015.12.014openalex-extracted
Oil price forecasting using gene expression programming and artificial neural networks
inferredcites →https://doi.org/10.1016/j.eneco.2007.02.012openalex-extracted
A new approach for crude oil price analysis based on Empirical Mode Decomposition
inferredcites →https://doi.org/10.1016/j.eneco.2008.05.003openalex-extracted
Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm
inferredcites →https://doi.org/10.1016/j.eneco.2010.04.009openalex-extracted
International evidence on crude oil price dynamics: Applications of ARIMA-GARCH models
inferredcites →https://doi.org/10.1016/j.eneco.2011.07.018openalex-extracted
Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling
inferredcites →https://doi.org/10.1016/j.eneco.2013.07.028openalex-extracted
Beyond one-step-ahead forecasting: Evaluation of alternative multi-step-ahead forecasting models for crude oil prices
inferredcites →https://doi.org/10.1016/j.eneco.2014.09.019openalex-extracted
A compressed sensing based AI learning paradigm for crude oil price forecasting
inferredcites →https://doi.org/10.1016/j.eneco.2015.02.018openalex-extracted
A novel hybrid method for crude oil price forecasting
inferredcites →https://doi.org/10.1016/j.eneco.2015.09.003openalex-extracted
Forecasting the real prices of crude oil under economic and statistical constraints
inferredcites →https://doi.org/10.1016/j.eneco.2017.05.023openalex-extracted
A deep learning ensemble approach for crude oil price forecasting
inferredcites →https://doi.org/10.1016/j.eneco.2017.09.010openalex-extracted
Influential factors in crude oil price forecasting
inferredcites →https://doi.org/10.1016/j.eneco.2017.10.035openalex-extracted
Investor sentiment and the price of oil
inferredcites →https://doi.org/10.1016/j.eneco.2019.07.009openalex-extracted
Monthly crude oil spot price forecasting using variational mode decomposition
inferredcites →https://doi.org/10.1016/j.energy.2021.120403openalex-extracted
Forecasting the U.S. oil markets based on social media information during the COVID-19 pandemic
inferredcites →https://doi.org/10.1016/j.engappai.2021.104217openalex-extracted
Forecasting crude oil price with a new hybrid approach and multi-source data
inferredcites →https://doi.org/10.1016/j.ijforecast.2018.07.006openalex-extracted
Text-based crude oil price forecasting: A deep learning approach
inferredcites →https://doi.org/10.1016/j.ijforecast.2021.06.006openalex-extracted
Crude oil price forecasting incorporating news text
inferredcites →https://doi.org/10.1016/j.resourpol.2017.08.006openalex-extracted
Price forecasting in the precious metal market: A multivariate EMD denoising approach
inferredcites →https://doi.org/10.1016/j.resourpol.2022.102737openalex-extracted
Multi-Perspective Crude Oil Price Forecasting with a New Decomposition-Ensemble Framework
inferredcites →https://doi.org/10.1080/07350015.2011.648859openalex-extracted
Real-Time Forecasts of the Real Price of Oil
inferredcites →https://doi.org/10.1098/rspa.2003.1123openalex-extracted
A confidence limit for the empirical mode decomposition and Hilbert spectral analysis
inferredcites →https://doi.org/10.1109/lsp.2007.904710openalex-extracted
Bivariate Empirical Mode Decomposition
inferredcites →https://doi.org/10.1109/tsp.2009.2033730openalex-extracted
Empirical Mode Decomposition for Trivariate Signals
inferredcites →https://doi.org/10.1109/tste.2019.2963270openalex-extracted
A Hybrid Ensemble Model for Interval Prediction of Solar Power Output in Ship Onboard Power Systems
inferredcites →https://doi.org/10.1145/1462198.1462204openalex-extracted
Textual analysis of stock market prediction using breaking financial news
inferredcites →https://doi.org/10.1162/089976698300017467openalex-extracted
Nonlinear Component Analysis as a Kernel Eigenvalue Problem
inferredcites →https://doi.org/10.1162/neco.1997.9.8.1735openalex-extracted
Long Short-Term Memory
inferredcites →https://doi.org/10.1198/073500102753410444openalex-extracted
Comparing Predictive Accuracy
inferredcites →https://doi.org/10.2139/ssrn.3992383openalex-extracted

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.31315/telematika.v20i2.8104openalex-snapshot
Forecasting Performance of Double Exponential Smoothing Model and ETS Model for Predicting Crude Oil Prices
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