A Deep Learning Ensemble Method for Forecasting Daily Crude Oil Price Based on Snapshot Ensemble of Transformer Model

The oil industries are an important part of a country’s economy.The crude oil’s price is influenced by a wide range of variables.Therefore,how accurately can countries predict its behavior and what predictors to employ are two main questions.In this view,we propose utilizing deep learning and ensemble learning techniques to boost crude oil’s price forecasting performance.The suggested method is based on a deep learning snapshot ensemble method of the Transformer model.To examine the superiority of the proposed model,this paper compares the proposed deep learning ensemble model against different machine learning and statistical models for daily Organization of the Petroleum Exporting Countries(OPEC)oil price forecasting.Experimental results demonstrated the outperformance of the proposed method over statistical and machine learning methods.More precisely,the proposed snapshot ensemble of Transformer method achieved relative improvement in the forecasting performance compared to autoregressive integrated moving average ARIMA(1,1,1),ARIMA(0,1,1),autoregressive moving average(ARMA)(0,1),vector autoregression(VAR),random walk(RW),support vector machine(SVM),and random forests(RF)models by 99.94%,99.62%,99.87%,99.65%,7.55%,98.38%,and 99.35%,respectively,according to mean square error metric.

Analysis on the spatial pattern and evolution of China's petroleum trade under the dual effect of international oil price and “Belt and Road” Framework

“Belt and Road” is the important origin of oil import in China. Based on social network analysis and stochastic frontier gravity model, this paper studied the characteristic evolution and influence factor of oil import network between China and “Belt and Road” countries. Then by constructing a stochastic frontier gravity model including the crude oil future price and oil importing price, it found that the international crude oil future price, the oil importing price, the political situation, the trade agreements have the effects on the China's oil import from “Belt and Road” region. It provided suggestions for improving the spatial pattern of China's petroleum trade.

The relationship between international crude oil prices and China＇s refined oil prices based on a structural VAR model

With the frequent fluctuations of international crude oil prices and China＇s increasing dependence on foreign oil in recent years, the volatility of international oil prices has significantly influenced China domestic refined oil price. This paper aims to investigate the transmission and feedback mechanism between international crude oil prices and China＇s refined oil prices for the time span from January 2011 to November 2015 by using the Granger causality test, vector autoregression model, impulse response function and variance decomposition methods. It is demonstrated that variation of international crude oil prices can cause China domestic refined oil price to change with a weak feedback effect. Moreover, international crude oil prices and China domestic refined oil prices are affected by their lag terms in positive and negative directions in different degrees. Besides, an international crude oil price shock has a signif- icant positive impact on domestic refined oil prices while the impulse response of the international crude oil price variable to the domestic refined oil price shock is negatively insignificant. Furthermore, international crude oil prices and domestic refined oil prices have strong historical inheri- tance. According to the variance decomposition analysis, the international crude oil price is significantly affected by its own disturbance influence, and a domestic refined oil price shock has a slight impact on international crude oil price changes. The domestic refined oil price variance is mainly caused by international crude oil price disturbance, while the domestic refined oil price is slightly affected by its own disturbance. Generally, domestic refined oil prices do not immediately respond to an international crude oil price change, that is, there is a time lag.

Dynamics of oil price shocks and stock market behavior in Pakistan:evidence from the 2007 financial crisis period

Background:The aim of this study is to investigate the effect of the oil price and its volatility on the stock market of Pakistan before and after the 2007 financial crisis period.Methods:The analyses are carried out on daily data for the period from July 31,2000 to July 31,2014.This study uses several econometric techniques for the analyses,namely,the Johansen-Juselius cointegration test,generalized autoregressive conditional heteroskedasticity(GARCH)model,exponential generalized autoregressive conditional heteroskedasticity(EGARCH)model,variance decomposition method,and impulse response function.Results:The results of the cointegration method indicate a significant long-run association between stock market and oil prices in the pre-crisis period.The EGARCH model shows that oil price returns have a significant effect on stock market returns in both sub-periods,while the result for the GARCH model is significant only in the postcrisis period.We find a significant effect of oil price volatility on the stock market in both sub-periods from the GARCH model.Furthermore,the EGARCH model shows an asymmetric effect of oil price volatility on the stock market in the pre-crisis period.Variance decomposition shows that stock market variations are mostly explained by selfinnovation.Moreover,the impulse response function results show that oil price shocks affected the stock market adversely in the pre-crisis period but positively in the postcrisis period.Conclusions:This study suggests that economic policymakers and investors should consider the oil price as an important factor affecting stock market returns.

Inflationary effects of oil prices and domestic gasoline prices:Markov-switching-VAR analysis

The purpose of this study is to contribute to the literature by studying the effects of sudden changes both on crude oil import price and domestic gasoline price on inflation for Turkey, an emerging country. Since an inflation targeting regime is being carried out by the Central Bank of Turkey, determination of such effects is becoming more important. Therefore empirical evidence in this paper will serve as guidance for those countries, which have an in- flation targeting regime. Analyses have been done in the period of October 2005-December 2012 by Markovswitching vector autoregressive （MS-VAR） models which are successful in capturing the nonlinear properties of variables. Using MS-VAR analysis, it is found that there are 2 regimes in the analysis period. Furthermore, regime changes can be dated and the turning points of economic cycles can be determined. In addition, it is found that the effect of the changes in crude oil and domestic gasoline prices on consumer prices and core inflation is not the same under different regimes. Moreover, the sudden increase in gasoline price is more important for consumer price infla- tion than crude oil price shocks. Another finding is the presence of a pass-through effect from oil price and ga- soline price to core inflation.

Economics,fundamentals,technology,finance,speculation and geopolitics of crude oil prices:an econometric analysis and forecast based on data from 1990 to 2017

It is of real and direct significance for China to cope with oil price fluctuations and ensure oil security. This paper aims to quantitatively analyze the specific contribution ratios of the complex factors influencing international crude oil prices and to establish crude oil price models to forecast long-term international crude oil prices. Six explanatory influential variables, namely Dow Jones Indexes, the Organization for Economic Cooperation and Development oil stocks, US rotary rig count, US dollar index, total open interest, which is the total number of outstanding contracts that are held by market participants at the end of each day, and geopolitical instability are specified, and the samples, from January 1990 to August 2017, are divided into six sub-periods. Moreover, the co-integration relationship among variables shows that the contribution ratios of all the variables influencing Brent crude oil prices are in accordance with the corresponding qualitative analysis. Furthermore, from September 2017 to December 2022 outside of the sample, the Vector Autoregressive forecasts show that annually averaged Brent crude oil prices for 2017-2022 would be $53.0, $61.3, $74.4, $90.0, $105.5, and $120.7 per barrel, respectively. The Vector Error Correction forecasts show that annual average Brent crude oil prices for 2017-2022 would be $53.0, $56.5, $58.5, $60.7, $63.0 and $65.4 per barrel, respectively.

The time‑varying effects of oil prices on oil-gas stock returns of the fragile five countries

This study analyzes oil price exposure of the oil–gas sector stock returns for the fragile five countries based on a multi-factor asset pricing model using daily data from 29 May 1996 to 27 January 2020.The endogenous structural break test suggests the presence of serious parameter instabilities due to fluctuations in the oil and stock markets over the period under study.Moreover,the time-varying estimates indicate that the oil–gas sectors of these countries are riskier than the overall stock market.The results further suggest that,except for Indonesia,oil prices have a positive impact on the sectoral returns of all markets,whereas the impact of the exchange rates on the oil–gas sector returns varies across time and countries.

Accuracy comparison of short-term oil price forecasting models

A forecasting model of the monthly crude oil price is investigated using the data between 1988 and 2009 from U. S. Energy Information Administration. First generalized auto-regressive condi- tional beteroskedasticity （GARCH） is applied to a state space model, a hybrid model （SS-GARCH） is proposed. Afterwards by computing a special likelihood function with two weak assumptions, model parameters are estimated by means of a faster algorithm. Based on the SS-GARCH model with the identified parameters, oil prices of next three months are forecasted by applying a Kalman filter. Through comparing the results between the SS-GARCH model and an econometric structure model, the SS-GARCH method is shown that it improves the forecasting accuracy by decreasing the index of mean absolute error （ RMSE ） from 7. 09 to 2.99, and also decreasing the index of MAE from 3. 83 to 1.69. The results indicate that the SS-GARCH model can play a useful role in forecasting short-term crude oil prices.

Active and Passive Factors of Oil Prices

Price volatility analysis is a basic problem in the price modification,financial risk estimation and management process.Among the global commodities,oil plays an important role in the development of modern industry and economy.Hence the price of crude oil analysis is a hot topic.It is also a difficult topic since there are so many factors associating the price volatilities.And some factors give the different influences in the different periods.Based on data computing,people generally classify the factors into positive and negative ones.But some factors do not affect the price as the nominal effect.For instance,the output of OPEC gave the positive contributions to the oil price in the past long time.Hence,the investigation of the historic WTI oil price is well proposed and the factors are classified into active and passive ones.And then the better explanations are given using this type of classification.

Low cost development strategy for oilfields in China under low oil prices

By reviewing the challenges in the development of oilfields in China under low oil prices,this study analyzes the root causes of cost rising,put forwards the low cost oilfield development strategy and specific paths to realize the strategy,and predicts the development potential and prospect of oilfields in China.In addition to the low grade of the reservoir and high development maturation,the fundamental reasons of development full cost rising of oilfields in China are as follows:(1)Facing the problem of resources turning poorer in quality,we have built production capacity at a pace too fast before making enough technical and experimental preparation;(2)technical engineering service model leads to high service cost;(3)team of oil development expertise and matched engineering system cannot satisfy the technical requirements of stabilizing oil production,controlling water cut and fine development.To realize development at low cost,the core is to increase economic recoverable reserves.The concrete paths include:(1)to explore the"Daqing oilfield development culture",improve the ability of leaders in charge of development,and inspire potential of staff;(2)to improve the ability of reservoir dynamics control,and implement precise development by following scientific principles;(3)to speed up integration of water flooding and enhanced oil recovery(EOR)and technological upgrading in order to enhance oil recovery;(4)to innovate key techniques in gas flooding and accelerate the industrial popularization of gas flooding;(5)to break the related transaction barriers and create new management models;and(6)to collaboratively optimize strategic layout and cultivate key oil bases.Although oilfield development in China faces huge challenges in cost,the low-cost development strategy will succeed as long as strategic development of mature and new oil fields is well planned.The cores to lower cost are to control decline rate and enhance oil recovery in mature oil fields,and increase single well productivity through technical innovation and improve engineering service efficiency through management innovation in new oil fields.

Has COVID‑19 changed the stock return‑oil price predictability pattern?

In this paper,we examine if COVID-19 has impacted the relationship between oil prices and stock returns predictions using daily Japanese stock market data from 01/04/2020 to 03/17/2021.We make a novel contribution to the literature by testing whether the COVID-19 pandemic has changed this predictability relationship.Employing an empirical model that controls for seasonal effects,return-related control variables,heteroskedasticity,persistency,and endogeneity,we demonstrate that the influence of oil prices on stock returns declined by around 89.5%due to COVID-19.This implies that when COVID-19 reduced economic activity and destabilized financial markets,the influence of oil prices on stock returns declined.This finding could have implications for trading strategies that rely on oil prices.

Empirical Analysis of ARCH Family Models on Oil Price Fluctuations

This paper selects the daily data of national oil prices from January 2, 2014 to February 28, 2019, establishes an ARMA (2, 0) model, and tests its residuals for ARCH effects. Finally, the TARCH (1, 1) model is determined to quantitatively analyze the volatility of the crude oil market.

Strategy for China's Natural Gas Industry in the Low Oil Price Environment

In regard to the continuous decline of international oil prices in recent years, how should China's natural gas industry seize the opportunity brought by this round of energy price declines, and how should we meet the challenges posed to the development of the domestic natural gas industry caused by changes in the international energy pattern? These questions deserve serious consideration. Through analysis on the situation of the domestic and overseas oil and gas market, and in combination with China's 13 th Five-Year Plan for energy development, the article proposes the development strategy in response to the low oil prices, aiming to provide countermeasures and suggestions for the long-term stable development of China's natural gas industry.

Research on Innovation of Floating Production Storage and Offloading Unit’s Rent Mode under Low Oil Price

After many years of exploitation,onshore oil and gas resources are about to enter a recession period.Oil and gas will mainly come from oceans in the future.Generally speaking,the exploration and production(E&P)cost of oil from offshore is much higher than that of oil from onshore,so it is more sensitive to oil price.However,in recent years,oil price has been hovering at a low level for a long time,almost close to or even lower than the E&P cost of oil,which directly affects the development of oilfields.Besides the influence of oil price,some oilfields present the characteristics of marginal reserve scale,short peak production period and output rapidly declining.There leads to short economic life period and makes the economic benefit close to or lower than oilfield’s hurdle rate,which increases the difficulty of offshore oilfield development.As an important part of oilfield development,Floating Production Storage and Offloading unit,its investment mode and rent mode directly affect overall oilfield’s rate of return and the economic life.This paper chooses lease mode as the research object based on the analysis of investment mode,and further puts forward rent mode related with oil price through the analysis of traditional rent mode,and illustrates the advantages and disadvantages of various rent modes and their applicability so that the lessor chooses the right mode to achieve Win-Win with Oil Company and promotes the development of oilfields under low oil price.

CNOOC Reports Heavy Loss amid Low Oil Prices

CNOOC Limited,of which China National Offshore Oil Corporation(CNOOC)is the parent,recently posted its first-ever half-year loss as the plunge of crude oil prices destroy the profit at China’s biggest offshore oil and gas producer.The company swung to a 7.74 billion yuan(USD1.16billion)loss in the January-June period,compared to a

Profit Strategy of CNPC＇s Overseas Business in a Oil Price Downturn

In 2016,CNPC managed to achieve a profit even despite the fact that the international oil price was lingering at a decade low.This was the third year in a row for the group to gain profit.Moreover,2016 was a year that marked significant gains for both CNPC’s operational and non-operational business,and the company also did excellent work in terms of international trading。

Low Oil Prices Drive up China's Crude Oil Imports

China’s crude oil imports hit a record high in the first half of 2016 despite an economic slowdown,and analysts largely attributed the surge to low prices,not strategic maneuvering.The country imported 186.5 million tons of crude oil in the first half of the year,23.15 million