scholarly journals Forecasting the Direction of Short-Term Crude Oil Price Changes with Genetic-Fuzzy Information Distribution

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Xinyu Wang ◽  
Kegui Chen ◽  
Xueping Tan
Keyword(s):  
Crude Oil ◽  
Oil Price ◽  
Fuzzy Information ◽  
Information Distribution ◽  
Short Term ◽  
Distribution Method ◽  
Price Changes ◽  
Spot Prices ◽  
Price Series ◽  
Novel Approach

This paper proposes a novel approach to the directional forecasting problem of short-term oil price changes. In this approach, the short-term oil price series is associated with incomplete fuzzy information, and a new fused genetic-fuzzy information distribution method is developed to process such a fuzzy incomplete information set; then a feasible coding method of multidimensional information controlling points is adopted to fit genetic-fuzzy information distribution to time series forecasting. Using the crude oil spot prices of West Texas Intermediate (WTI) and Brent as sample data, the empirical analysis results demonstrate that the novel fused genetic-fuzzy information distribution method statistically outperforms the benchmark of logistic regression model in prediction accuracy. The results indicate that this new approach is effective in direction accuracy.

Crude oil price prediction based on LSTM network and GM (1,1) model

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tianxiang Yao ◽  
Zihan Wang
Keyword(s):  
Crude Oil ◽  
Oil Price ◽  
Crude Oil Price ◽  
Short Term ◽  
Content Type ◽  
Forecasting Models ◽  
Price Series ◽  
Mode Decomposition ◽  
Lstm Network

PurposeAccording to the problem of crude oil price forecasting, the purpose of this paper is to propose a multi-step prediction method based on the empirical mode decomposition, long short-term memory network and GM (1,1) model.Design/methodology/approachFirst, the empirical mode decomposition method is used to decompose the crude oil price series into several components with different frequencies. Then, each subsequence is classified and synthesized based on the specific periodicity and other properties to obtain several components with different significant characteristics. Finally, all components are substituted into a suitable prediction model for fitting. LSTM models with different parameters are constructed for predicting specific components, which approximately and respectively represent short-term market disturbance and long-term influences. Rolling GM (1,1) model is constructed to simulate a series representing the development trend of oil price. Eventually, all results obtained from forecasting models are summarized to evaluate the performance of the model.FindingsThe model is respectively applied to simulate daily, weekly and monthly WTI crude oil price sequences. The results show that the model has high accuracy on the prediction, especially in terms of series representing long-term influences with lower frequency. GM (1,1) model has excellent performance on fitting the trend of crude oil price.Originality/valueThis paper combines GM (1,1) model with LSTM network to forecast WTI crude oil price series. According to the different characteristics of different sequences, suitable forecasting models are constructed to simulate the components.

Impact of crude oil price on the socio-political environment of global countries

2019 ◽  
Vol 118 (3) ◽  
pp. 110-122
Author(s):  
Johnson Clement Madathil ◽  
Velmurugan P. S
Keyword(s):  
Crude Oil ◽  
Descriptive Analysis ◽  
Oil Price ◽  
Policy Framework ◽  
Political Environment ◽  
Policy Reforms ◽  
Crude Oil Price ◽  
Short Term ◽  
Political Impact ◽  
New Energy

Crude oil is known to have an impact on people’s life of both producers and consumers of crude oil countries. A producer country’s socio-political impact will be different from a consumer country’s socio-political impact. This paper aims to show that crude oil price has a socio-political impact on global countries through descriptive analysis. The study found that there were similarities in the movement of crude oil price and change in GDP of both India and United States and further Russia and Venezuela have had crude oil impact on their respective GDP’s, which has made them take policy reforms. The paper identifies changes in the policy framework due to influence of crude oil price and eventual changes in existing socio-political environment. Taking oil producing countries such as Russia and Venezuela as examples, this paper suggests that policy reforms are the key to having a stable socio-political environment. Russia shows us that having a flexible monetary policy can keep the budget dependence on crude oil reduced in the short term. On the other hand, for oil consuming countries, having a stable supply and moving to new energy sources is the key to tackle the influence of crude oil price on the socio-political environment of global countries.

Crude Oil Price and Food Security Related Variables in Malaysia

2016 ◽  
Vol 4 (2) ◽  
pp. 17-21
Author(s):  
Shri Dewi Applanaidu ◽  
Mukhriz Izraf Azman Aziz
Keyword(s):  
Food Security ◽  
Crude Oil ◽  
Price Index ◽  
Price Volatility ◽  
Food Price ◽  
Oil Price ◽  
Crude Oil Price ◽  
Price Changes ◽  
Oil Price Volatility ◽  
Crude Oil Prices

Objective - This study analyzes the dynamic relationship between crude oil price and food security related variables (crude palm oil price, exchange rate, food import, food price index, food production index, income per capita and government development expenditure) in Malaysia using a Vector Auto Regressive (VAR) model. Methodology/Technique - The data covered the period of 1980-2014. Impulse response functions (IRFs) was applied to examine what will be the results of crude oil price changes to the variables in the model. To explore the impact of variation in crude oil prices on the selected food security related variables forecast error variance decomposition (VDC) was employed. Findings - Findings from IRFs suggest there are positive effects of oil price changes on food import and food price index. The VDC analyses suggest that crude oil price changes have relatively largest impact on real crude palm oil price, food import and food price index. This study would suggest to revisiting the formulation of food price policy by including appropriate weight of crude oil price volatility. In terms of crude oil palm price determination, the volatility of crude oil prices should be taken into account. Overdependence on food imports also needs to be reduced. Novelty - As the largest response of crude oil price volatility on related food security variables food vouchers can be implemented. Food vouchers have advantages compared to direct cash transfers since it can be targeted and can be restricted to certain types of products and group of people. Hence, it can act as a better aid compared cash transfers. Type of Paper - Empirical Keywords: Crude oil price, Food security related variables, IRF, VAR, VDC

scholarly journals Impact of COVID-19 on Forecasting Stock Prices: An Integration of Stationary Wavelet Transform and Bidirectional Long Short-Term Memory

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Daniel Štifanić ◽  
Jelena Musulin ◽  
Adrijana Miočević ◽  
Sandi Baressi Šegota ◽  
Roman Šubić ◽  
...  
Keyword(s):  
Crude Oil ◽  
Stock Prices ◽  
Short Term Memory ◽  
Oil Price ◽  
Stationary Wavelet Transform ◽  
Crude Oil Price ◽  
Short Term ◽  
Term Memory ◽  
Long Short Term Memory ◽  
The Impact

COVID-19 is an infectious disease that mostly affects the respiratory system. At the time of this research being performed, there were more than 1.4 million cases of COVID-19, and one of the biggest anxieties is not just our health, but our livelihoods, too. In this research, authors investigate the impact of COVID-19 on the global economy, more specifically, the impact of COVID-19 on the financial movement of Crude Oil price and three US stock indexes: DJI, S&P 500, and NASDAQ Composite. The proposed system for predicting commodity and stock prices integrates the stationary wavelet transform (SWT) and bidirectional long short-term memory (BDLSTM) networks. Firstly, SWT is used to decompose the data into approximation and detail coefficients. After decomposition, data of Crude Oil price and stock market indexes along with COVID-19 confirmed cases were used as input variables for future price movement forecasting. As a result, the proposed system BDLSTM + WT-ADA achieved satisfactory results in terms of five-day Crude Oil price forecast.

Application of ARIMA Model in Short-Term Prediction of International Crude Oil Price

2013 ◽  
Vol 798-799 ◽  
pp. 979-982 ◽  
Author(s):  
Ying Xiang ◽  
Xiao Hong Zhuang
Keyword(s):  
Crude Oil ◽  
Arima Model ◽  
Oil Price ◽  
Good Prediction ◽  
Crude Oil Price ◽  
Short Term ◽  
Refined Oil ◽  
Price Data ◽  
Term Prediction ◽  
Short Term Prediction

International crude oil price is the referential scale of spot crude oil price and refined oil price. This paper made an analysis and prediction of Brent crude oil price by ARIMA model based on its price data from November 2012 to April 2013. It indicated that model ARIMA (1,1,1) possessed good prediction effect and can be used as short-term prediction of International crude oil price.

scholarly journals THE ISLAMIC CAPITAL MARKET VOLATILITY: A COMPARATIVE STUDY BETWEEN IN INDONESIA AND MALAYSIA

2013 ◽  
Vol 15 (4) ◽  
pp. 391-415
Author(s):  
Muhammad Syafii Antonio ◽  
Hafidhoh Hafidhoh ◽  
Hilman Fauzi
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Crude Oil ◽  
Capital Market ◽  
Oil Price ◽  
Crude Oil Price ◽  
Short Term ◽  
Macroeconomic Variables ◽  
Jones Index

This study attempts to examine the short-term and long-term relationship among selected global anddomestic macroeconomic variables fromeach country (Fed rate, crude oil price, Dow Jones Index, interest rate, exchange rate and inflation) for Indonesia and Malaysia Islamic capital market (Jakarta Islamic Index (JII) and FTSE Bursa Malaysia Hijrah Shariah Index (FHSI). The methodology used in this study is vector error correction model (VECM) for the monthly data starting from January 2006 to December 2010. The result shows that in the long-term, all selectedmacroeconomic variables except Dow Jones Index variable have significantly affect in both Islamic stock market FHSI and JII, while in the short-term there is no any selected macroeconomic variables that significantly affect FHSI and only inflation, exchange rate and crude oil price variables seem to significantly affect JII. Keywords : Islamic Stock Market, Jakarta Islamic Index, FTSE Hijrah Shariah Index, VAR/VECMJEL Classification: E52, E44

scholarly journals Impact of Crude Oil Price Changes on Household Consumption Expenditure in Oman (1990-2016)

2019 ◽  
Vol 4 (2) ◽  
pp. 97-104
Author(s):  
Abubakar El-Sidig A.A Mahdi
Keyword(s):  
Crude Oil ◽  
Household Consumption ◽  
Oil Price ◽  
Consumption Expenditure ◽  
Crude Oil Price ◽  
Price Changes ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Bound Test

Objective – The preceding three years (2014, 2015, and 2016) saw a drop in the price of oil which has impacted all parts of Omani macroeconomic life. This study aims to identify the association between oil price changes and aggregate household consumption expenditure in the Sultanate by analyzing the long term relationship between the variables of interest. Methodology/Technique – The (ARDL) Autoregressive Distributed Lag bound test of co-integration is used with 27 annual observations obtained between 1990 and 2016. Findings – The statistical results show that there is a long term, positive relationship between the two variables. Novelty – As Oman is heavily dependent on oil, any fluctuation in the price of oil will undoubtedly cause instability in the economy (macroeconomic variables) demonstrating the presence of a robust correlation between consumption and oil prices. The bound test of the ARDL approach demonstrates this relationship. This study is therefore useful for Muscat officials to identify ways to reduce the dependency on oil. Type of Paper: Empirical Keywords: Total Household Consumption Expenditure; Crude Oil Price; Autoregressive Distributed Lag (ARDL); Omani Economy. Reference to this paper should be made as follows: Abubakar El-Sidig A.A Mahdi. 2019. Impact of Crude Oil Price Changes on Household Consumption Expenditure in Oman (1990-2016), J. Bus. Econ. Review 4 (2): 97 – 104. https://doi.org/10.35609/jber.2019.4.2(4) JEL Classification: D1, D13, D19, E30.

scholarly journals Crude Oil Price Forecasting Using Long Short-Term Memory

2021 ◽  
Vol 7 (2) ◽  
pp. 286
Author(s):  
Muhamad Fariz Maulana ◽  
Siti Sa’adah ◽  
Prasti Eko Yunanto
Keyword(s):  
Crude Oil ◽  
Short Term Memory ◽  
Oil Price ◽  
Price Forecasting ◽  
Crude Oil Price ◽  
Short Term ◽  
Term Memory ◽  
Long Short Term Memory
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