scholarly journals Time-Varying Spot and Futures Oil Price Dynamics

2010 ◽  
Author(s):  
Guglielmo Maria Caporale ◽  
Davide Ciferri ◽  
Alessandro Girardi
Keyword(s):  
Oil Price ◽  
Price Dynamics ◽  
Time Varying

scholarly journals Time-Varying Spot and Futures Oil Price Dynamics

2010 ◽  
Author(s):  
Guglielmo Maria Caporale ◽  
Davide Ciferri ◽  
Alessandro Girardi
Keyword(s):  
Oil Price ◽  
Price Dynamics ◽  
Time Varying

scholarly journals Time-Varying Spot and Futures Oil Price Dynamics

2013 ◽  
Vol 61 (1) ◽  
pp. 78-97 ◽  
Author(s):  
Guglielmo Maria Caporale ◽  
Davide Ciferri ◽  
Alessandro Girardi
Keyword(s):  
Oil Price ◽  
Price Dynamics ◽  
Time Varying

Crude Oil Price Dynamics With Crash Risk Under Fundamental Shocks

2020 ◽  
Author(s):  
Cho-Hoi Hui ◽  
Chi-Fai Lo ◽  
Chi-Hin Cheung ◽  
Andrew Wong
Keyword(s):  
Crude Oil ◽  
Oil Price ◽  
Crash Risk ◽  
Price Dynamics ◽  
Crude Oil Price

scholarly journals Wavelet Entropy Based Analysis and Forecasting of Crude Oil Price Dynamics

Entropy ◽  
2015 ◽  
Vol 17 (12) ◽  
pp. 7167-7184 ◽  
Author(s):  
Yingchao Zou ◽  
Lean Yu ◽  
Kaijian He
Keyword(s):  
Crude Oil ◽  
Oil Price ◽  
Price Dynamics ◽  
Crude Oil Price ◽  
Wavelet Entropy

Oil price risk evaluation using a novel hybrid model based on time-varying long memory

2019 ◽  
Vol 81 ◽  
pp. 70-78 ◽  
Author(s):  
Lu-Tao Zhao ◽  
Kun Liu ◽  
Xin-Lei Duan ◽  
Ming-Fang Li
Keyword(s):  
Hybrid Model ◽  
Long Memory ◽  
Risk Evaluation ◽  
Oil Price ◽  
Price Risk ◽  
Time Varying ◽  
Model Based ◽  
Oil Price Risk

scholarly journals Oil Price Forecasting Using a Time-Varying Approach

Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1403
Author(s):  
Lu-Tao Zhao ◽  
Shun-Gang Wang ◽  
Zhi-Gang Zhang
Keyword(s):  
Crude Oil ◽  
Time Window ◽  
Oil Prices ◽  
Oil Price ◽  
Price Forecasting ◽  
Time Varying ◽  
Crude Oil Price ◽  
Trend Prediction ◽  
Oil Market ◽  
Polynomial Decomposition

The international crude oil market plays an important role in the global economy. This paper uses a variable time window and the polynomial decomposition method to define the trend term of time series and proposes a crude oil price forecasting method based on time-varying trend decomposition to describe the changes in trends over time and forecast crude oil prices. First, to characterize the time-varying characteristics of crude oil price trends, the basic concepts of post-position intervals, pre-position intervals and time-varying windows are defined. Second, a crude oil price series is decomposed with a time-varying window to determine the best fitting results. The parameter vector is used as a time-varying trend. Then, to quantitatively describe the continuation of the time-varying trend, the concept of the trend threshold is defined, and a corresponding algorithm for selecting the trend threshold is given. Finally, through the predicted trend thresholds, the historical reference data are selected, and the time-varying trend is combined to complete the crude oil price forecast. Through empirical research, it is found that the time-varying trend prediction model proposed in this paper achieves a better prediction than several common models. These results can provide suggestions and references for investors in the international crude oil market to understand the trends of oil prices and improve their investment decisions.

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