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Forecasting Crude Oil Price with an Autoregressive Integrated Moving Average (ARIMA) Model · Study

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ChapterForecasting Crude Oil Price with an Autoregressive Integrated Moving Average (ARIMA) Model

Chunlan Zhao2013

Chapter2013

Forecasting Crude Oil Price with an Autoregressive Integrated Moving Average (ARIMA) Model

Chunlan Zhao · Bing Wang

32 citations·0/0 files stored·Advances in intelligent systems and computing

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Forecasting Techniques and Applications Market Dynamics and Volatility Stock Market Forecasting Methods

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References

2008Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm 2001A semiparametric approach to short-term oil price forecasting 2005Modeling and forecasting cointegrated relationships among heavy oil and product prices 2005A monthly crude oil spot price forecasting model using relative inventories 2004A COMPARISON OF VAR AND NEURAL NETWORKS WITH GENETIC ALGORITHM IN FORECASTING PRICE OF OIL 2005Forecasting short-run crude oil price using high- and low-inventory variables 1998Efficiency in the crude oil futures market 1994Oil Price Forecasting in the 1980s: What Went Wrong?*

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2023Crude Oil Price Time Series Forecasting: A Novel Approach Based on Variational Mode Decomposition, Time-Series Imaging, and Deep Learning

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Year2013

Typechapter

Published2013-11-26

VenueAdvances in intelligent systems and computing

ISSN-L2194-5357

Languageen

Citations32

Files0 public / 0

ShelfForecasting Techniques and Applications

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doi10.1007/978-3-642-38667-1_27

openalex_workW78997746

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