scholarly journals Forecasting crude oil spot price using OECD petroleum inventory levels

2002 ◽  
Vol 8 (4) ◽  
pp. 324-333 ◽  
Author(s):  
Michael Ye ◽  
John Zyren ◽  
Joanne Shore
Keyword(s):  
Crude Oil ◽  
Spot Price ◽  
Petroleum Inventory

FORECASTING THE CRUDE OIL SPOT PRICE BY WAVELET NEURAL NETWORKS USING OECD PETROLEUM INVENTORY LEVELS

2011 ◽  
Vol 07 (02) ◽  
pp. 281-297 ◽  
Author(s):  
YE PANG ◽  
WEI XU ◽  
LEAN YU ◽  
JIAN MA ◽  
KIN KEUNG LAI ◽  
...  
Keyword(s):  
Neural Network ◽  
Crude Oil ◽  
Linear Models ◽  
Wavelet Neural Network ◽  
Spot Price ◽  
Inventory Level ◽  
Forecasting Model ◽  
Nonlinear Relationship ◽  
Forecast Horizon ◽  
Petroleum Inventory

In this study, a novel forecasting model based on the Wavelet Neural Network (WNN) is proposed to predict the monthly crude oil spot price. In the proposed model, the OECD industrial petroleum inventory level is used as an independent variable, and the Wavelet Neural Network (WNN) is used to explore the nonlinear relationship between inventories and the price. For verification purposes, the West Texas Intermediate (WTI) crude oil spot price is used for the tested target. Experimental results reveal that the WNN can model the nonlinear relationship between inventories and the price very well. Furthermore, the in-sample and out-of-sample prediction performance also demonstrates that the WNN-based forecasting model can produce more accurate prediction results than other nonlinear and linear models, even when the lengths of the forecast horizon are relatively short or long.

The Co-Movements Between Crude Oil Price and Internet Concerns: Causality Analysis in the Frequency Domain

2020 ◽  
Vol 8 (3) ◽  
pp. 224-239
Author(s):  
Jingjing Li ◽  
Ling Tang ◽  
Ling Li
Keyword(s):  
Crude Oil ◽  
Test Method ◽  
Oil Price ◽  
Spot Price ◽  
Causality Analysis ◽  
Crude Oil Price ◽  
Causality Test ◽  
Low Frequencies ◽  
Oil Market

AbstractWith the boom of web technology, Internet concerns (IC) have become emerging drivers of crude oil price. This paper makes the first attempt to measure the frequency-varying co-movements between crude oil price and IC in five domains (i.e., fundamentals, supply-demand, crisis, war and weather) by using the frequency causality test method. Based on the monthly Brent spot price and search volumes (SVs) captured by Google Trends from January 2004 to September 2019, new and complementary insights regarding the co-movements between crude oil price and IC are obtained. 1) The co-movements between crude oil price and the IC of supply-demand, war, and weather support a neutral hypothesis at all frequencies due to the characteristics (low value or volatility) of these IC data. 2) There is a unidirectional causal relationship between crude oil price and the IC of fundamentals, running from the latter to the former at low frequencies (long-term). 3) There is a feedback relationship between crude oil price and the IC of crisis, with the IC of crisis driving crude oil price at medium and low frequencies (mid- and long-term) and crude oil price causing the IC of crisis to change permanently. The conclusions of this paper provide important implications for both oil market economists and investors.

scholarly journals Crude Oil Spot Price Forecasting Based on Multiple Crude Oil Markets and Timeframes

Energies ◽  
2014 ◽  
Vol 7 (5) ◽  
pp. 2761-2779 ◽  
Author(s):  
Shangkun Deng ◽  
Akito Sakurai
Keyword(s):  
Crude Oil ◽  
Spot Price ◽  
Price Forecasting ◽  
Oil Markets

Volatility and efficiency of the world crude oil market

2015 ◽  
Vol 31 (1) ◽  
pp. 20-29
Author(s):  
Fawzan Abdul Aziz Al Fawzan
Keyword(s):  
Random Walk ◽  
Crude Oil ◽  
Weak Form ◽  
Efficient Market Hypothesis ◽  
Spot Price ◽  
Conditional Heteroskedasticity ◽  
Efficient Market ◽  
Content Type ◽  
Oil Market ◽  
Autoregressive Conditional Heteroskedasticity

Purpose – The purpose of this paper is to examine volatility and the weak-form efficient market hypothesis (random walk) of world spot crude oil market. Design/methodology/approach – The study uses the generalized autoregressive conditional heteroskedasticity (GARCH-M), exponential generalized autoregressive conditional heteroskedasticity (EGARCH), and threshold GARCH (TGARCH) models. The data are selected from three markets: Dubai Vetch (DV), West Texas Intermediate, and Europe Brent Spot Price. Findings – The weak-form efficient market (random walk) hypothesis was rejected for all estimated GARCH-M, EGARCH, and TGARCH models, indicating that these markets are inefficient and predictable. For daily data, the empirical results showed the presence of asymmetric effects, and the conditional variance process was found to be highly persistent. Originality/value – This study is unique in its nature as it examines three markets on three continents. In addition, one of these markets (DV) was not carried out by the previous study. This work takes into account the market location.

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