scholarly journals Corrigendum to ‘Dynamic impacts of crude oil price on Chinese investor sentiment: Nonlinear causality and time-varying effect’ [International Review of Economics & Finance 66 (2020), 131–153]

2021 ◽  
Vol 72 ◽  
pp. 546
Author(s):  
Zhifang He
Keyword(s):  
Crude Oil ◽  
Investor Sentiment ◽  
Oil Price ◽  
Time Varying ◽  
International Review ◽  
Crude Oil Price ◽  
Dynamic Impacts

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 Finally, through the predicted trend thresholds, the historical reference data are selected, and the time-varying trend is combined to complete the crude oil price forecast.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.

Time-varying dependence measures: a comparative analysis through wavelet approach

2017 ◽  
Vol 11 (2) ◽  
pp. 350-364 ◽  
Author(s):  
Anyssa Trimech
Keyword(s):  
Energy Consumption ◽  
Crude Oil ◽  
Oil Price ◽  
Consumption Pattern ◽  
Time Varying ◽  
Crude Oil Price ◽  
Data Set ◽  
Content Type ◽  
Single Scale ◽  
Measure Of Dependence

Purpose This paper aims to investigate the pattern of dependence between crude oil price and energy consumption of the most important economic sectors in the USA, over different time periods, using monthly data set from January 1986 to July 2014 and a comparative study between linear correlation versus copula correlation as a measure of dependence over the single scale and the multiscale analysis. Design/methodology/approach The proposed method is based on the multiresolution analysis which gives more extensive and detailed description of the dependence price-consumption pattern over different periods of time. Findings The empirical results show that the dependence between variables is strongly sensitive to the time varying and generally increasing with time scale. In particular, the Pearson coefficients are less than the dependence copula measures. The single-scale analysis covers many time-varying dependences which are made clear, flexible and comprehensive by the description given by the multiscale approach. It explains better the structure of relationships between variables and helps understand the variations and improve forecasts of the crude oil price and energy consumption over different time scales. Originality/value The proposed methodology offers the opportunity to construct dynamic management strategies by taking into account the multiscale nature of crude oil price and consumption relationship. Moreover, the paper uses wavelets as a relatively new and powerful tool for statistical analysis in addition to the copula technique that allows a new understanding of variable correlation. The paper will be of interest not only for academics in the field of data dependencies analysis but also for fund managers and market investors.

scholarly journals Research on the Time-Varying Impact of Economic Policy Uncertainty on Crude Oil Price Fluctuation

2020 ◽  
Vol 12 (16) ◽  
pp. 6523 ◽  
Author(s):  
Yanhong Feng ◽  
Dilong Xu ◽  
Pierre Failler ◽  
Tinghui Li
Keyword(s):  
Economic Policy ◽  
Crude Oil ◽  
Price Volatility ◽  
Oil Price ◽  
Policy Uncertainty ◽  
Time Varying ◽  
Crude Oil Price ◽  
Price Fluctuation ◽  
Economic Policy Uncertainty ◽  
Oil Price Fluctuation

Due to multiple properties, the international crude oil price is influenced by various and complex interrelated factors from different determinants in different periods. However, the previous studies on crude oil price fluctuation with economic policy uncertainty (EPU) haven’t taken a wider range of volatility sources into their analysis frameworks. In this paper, the time-varying parameter factor-augmented vector autoregressive (TVP-FAVAR) model is introduced in order to avoid important information loss, as well as capture the time-varying impact on crude oil price fluctuation by EPU. Furthermore, the differences on crude oil fluctuations from net-oil exporting and net-oil importing country’s EPU are also elaborated. Here are three findings as follows. First, the impacts of global EPU on the crude oil price volatility show time-varying characteristics both in time duration and time-points. Second, the instantaneous impacts of global EPU on the price volatility of crude oil are directly relevant to major events, and the impacts are different in event types as well. Third, the time-varying characteristics depicting the impacts of EPU in countries who are net-oil exporter and net-oil importer on price volatility of crude oil show heterogeneity in fluctuation range, fluctuation intensity, and stage.

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