Forecasting Crude Oil Prices Using Wavelet ARIMA Model Approach

This paper used complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) based hybrid model for the forecasting of world crude oil prices. For this purpose, the crude oil prices original time series are decomposed into sub small finite series called intrinsic mode functions (IMFs). Then ARIMA model was applied to each extracted IMF to estimate the parameters. Next, using these estimated parameters of each ARIMA model, the Kalman Filter was run for each IMF, so that these extracted IMFs can be predicted more accurately. Finally, all IMFs are combined to get the result. For testing and verification of the proposed method, two crude oil prices were used as a sample i.e. Brent and WTI (West Texas Intermediate) crude oil monthly prices series. The D-statistic values of the proposed model were 93.33% for Brent and 89.29% for WTI which reveals the importance of the CEEMDAN based hybrid model.

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Improving forecasting accuracy of crude oil prices using decomposition ensemble model with reconstruction of IMFs based on ARIMA model

Malaysian Journal of Fundamental and Applied Sciences ◽

10.11113/mjfas.v14n4.1013 ◽

2018 ◽

Vol 14 (4) ◽

pp. 471-483 ◽

Cited By ~ 3

Author(s):

Muhammad Aamir ◽

Ani Shabri ◽

Muhammad Ishaq

Keyword(s):

Crude Oil ◽

Moving Average ◽

Arima Model ◽

Oil Prices ◽

Autoregressive Moving Average ◽

Complex Data ◽

Ensemble Model ◽

Intrinsic Mode Functions ◽

Forecasting Accuracy ◽

Crude Oil Prices

The accuracy of crude oil price forecasting is more important especially for economic development and is considered a lifeblood of the industry. Hence, in this paper, a decomposition-ensemble model with the reconstruction of intrinsic mode functions (IMFs) is proposed for forecasting the crude oil prices based on the well-known autoregressive moving average (ARIMA) model. Essentially, the reconstruction of IMFs enhanced the forecasting accuracy of the existing decomposition ensemble models. The proposed methodology works in four steps: decomposition of the complex data into several IMFs using EEMD, reconstruction of IMFs based on order of ARIMA model, prediction of every reconstructed IMF, and finally ensemble the prediction of every IMF for the final output. A case study is carried out using two crude oil prices time series (i.e. Brent and West Texas Intermediate (WTI)). The empirical results exhibited that the reconstruction of IMFs based on order of ARIMA model was adequate and provided the best forecast. To check the correctness, robustness and generalizability simulations were also carried out.

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An Empirical Investigation of Factors Affecting Stock Prices in Vietnam

Journal of Economics and Development ◽

10.33301/2014.16.01.05 ◽

2014 ◽

pp. 74-89 ◽

Cited By ~ 1

Author(s):

Vinh Vo Xuan

Keyword(s):

Exchange Rates ◽

Crude Oil ◽

Foreign Exchange ◽

Stock Prices ◽

Global Financial Crisis ◽

Oil Prices ◽

Foreign Exchange Rates ◽

Factors Affecting ◽

Crude Oil Prices ◽

Before And After

This paper investigates factors affecting Vietnam’s stock prices including US stock prices, foreign exchange rates, gold prices and crude oil prices. Using the daily data from 2005 to 2012, the results indicate that Vietnam’s stock prices are influenced by crude oil prices. In addition, Vietnam’s stock prices are also affected significantly by US stock prices, and foreign exchange rates over the period before the 2008 Global Financial Crisis. There is evidence that Vietnam’s stock prices are highly correlated with US stock prices, foreign exchange rates and gold prices for the same period. Furthermore, Vietnam’s stock prices were cointegrated with US stock prices both before and after the crisis, and with foreign exchange rates, gold prices and crude oil prices only during and after the crisis.

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Determinants of Inflation in Vietnam: A VECM Approach

Journal of Asian Business and Economic Studies ◽

10.24311/jabes/2015.22.4.02 ◽

2015 ◽

Vol 22 (04) ◽

pp. 26-50

Author(s):

Ngoc Tran Thi Bich ◽

Huong Pham Hoang Cam

Keyword(s):

Interest Rate ◽

Crude Oil ◽

Error Correction ◽

Budget Deficit ◽

Oil Prices ◽

Crude Oil Prices ◽

Domestic Credit ◽

Short Run ◽

The Impact

This paper aims to examine the main determinants of inflation in Vietnam during the period from 2002Q1 to 2013Q2. The cointegration theory and the Vector Error Correction Model (VECM) approach are used to examine the impact of domestic credit, interest rate, budget deficit, and crude oil prices on inflation in both long and short terms. The results show that while there are long-term relations among inflation and the others, such factors as oil prices, domestic credit, and interest rate, in the short run, have no impact on fluctuations of inflation. Particularly, the budget deficit itself actually has a short-run impact, but its level is fundamentally weak. The cause of the current inflation is mainly due to public's expectations of the inflation in the last period. Although the error correction, from the long-run relationship, has affected inflation in the short run, the coefficient is small and insignificant. In other words, it means that the speed of the adjustment is very low or near zero. This also implies that once the relationship among inflation, domestic credit, interest rate, budget deficit, and crude oil prices deviate from the long-term trend, it will take the economy a lot of time to return to the equilibrium state.

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Dynamic Relationship between Crude Oil and Stock Prices in India: Before And After the Subprime Financial Crisis 2008

GIS Business ◽

10.26643/gis.v14i6.11683 ◽

2019 ◽

Vol 14 (6) ◽

pp. 96-104

Author(s):

P. Sakthivel ◽

S. Rajaswaminathan ◽

R. Renuka ◽

N. R.Vembu

Keyword(s):

Financial Crisis ◽

Crude Oil ◽

Stock Prices ◽

Oil Prices ◽

Energy Index ◽

Data Set ◽

Dynamic Relationship ◽

Crude Oil Prices ◽

Long Run ◽

Before And After

This paper empirically discovered the inter-linkages between stock and crude oil prices before and after the subprime financial crisis 2008 by using Johansan co-integration and Granger causality techniques to explore both long and short- run relationships. The whole data set of Nifty index, Nifty energy index, BSE Sensex, BSE energy index and oil prices are divided into two periods; before crisis (from February 15, 2005 to December31, 2007) and after crisis (from January 1, 2008 to December 31, 2018) are collected and analyzed. The results discovered that there is one-way causal relationship from crude oil prices to Nifty index, Nifty energy index, BSE Sensex and BSE energy index but not other way around in both periods. However, a bidirectional causality relationship between BSE Energy index and crude oil prices during post subprime financial crisis 2008. The co-integration results suggested that the absence of long run relationship between crude oil prices and market indices of BSE Sensex, BSE energy index, Nifty index and Nifty energy index before and after subprime financial crisis 2008.

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