A data envelopment analysis-based framework for the relative performance evaluation of competing crude oil prices' volatility forecasting models

2012 ◽  
Vol 34 (2) ◽  
pp. 576-583 ◽  
Author(s):  
Bing Xu ◽  
Jamal Ouenniche
Keyword(s):  
Performance Evaluation ◽  
Data Envelopment Analysis ◽  
Crude Oil ◽  
Oil Prices ◽  
Relative Performance ◽  
Data Envelopment ◽  
Relative Performance Evaluation ◽  
Volatility Forecasting ◽  
Forecasting Models ◽  
Crude Oil Prices

scholarly journals Further Study of the DEA-Based Framework for Performance Evaluation of Competing Crude Oil Prices’ Volatility Forecasting Models

Mathematics ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 827 ◽  
Author(s):  
Zhongbao Zhou ◽  
Qianying Jin ◽  
Jian Peng ◽  
Helu Xiao ◽  
Shijian Wu
Keyword(s):  
Crude Oil ◽  
Oil Prices ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Volatility Forecasting ◽  
Analysis Model ◽  
Super Efficiency ◽  
Forecasting Models ◽  
Crude Oil Prices ◽  
Efficiency Data

The super-efficiency data envelopment analysis model is innovative in evaluating the performance of crude oil prices’ volatility forecasting models. This multidimensional ranking, which takes account of multiple criteria, gives rise to a unified decision as to which model performs best. However, the rankings are unreliable because some efficiency scores are infeasible solutions in nature. What’s more, the desirability of indexes is worth discussing so as to avoid incorrect rankings. Hence, herein we introduce four models, which address the issue of undesirable characteristics of indexes and infeasibility of the super efficiency models. The empirical results reveal that the new rankings are more robust and quite different from the existing results.

scholarly journals A Review of Crude Oil Prices Forecasting using Hybrid Method

2018 ◽  
Vol 11 (3) ◽  
pp. 1114
Author(s):  
Nurull Qurraisya Nadiyya Md-Khair ◽  
Ruhaidah Samsudin
Keyword(s):  
Crude Oil ◽  
Review Paper ◽  
Oil Prices ◽  
Economic Activities ◽  
Data Decomposition ◽  
Forecasting Models ◽  
Forecasting Methods ◽  
Crude Oil Prices ◽  
Forecasting Method ◽  
Hybrid Forecasting

Crude oil is considered as a crucial energy source in modern days. Consequently, the fluctuation of crude oil prices can cause a significant impact on economic activities. Researchers have proposed many hybrid forecasting models on top of single forecasting methods which are utilized to predict crude oil prices movement more accurately. Nevertheless, many limitations still existed in hybrid forecasting models and models that can predict crude oil prices as accurate as possible is required. The motivations of this review paper are to identify and assess the mostly used crude oil prices forecasting methods and to analyse their current limitations. 12 studies that used “decomposition-and-ensemble” framework was selected for review. Wavelet transform is identified as the mostly used data decomposition method while some limitations have been recognized. Future researches should include more studies to further elucidate the limitations in existing forecasting method so that subsequent forecasting methods can be improved.

scholarly journals Forecasting Models Evaluation Using A Slacks-Based Context-Dependent DEA Framework

2014 ◽  
Vol 30 (5) ◽  
pp. 1477 ◽  
Author(s):  
Jamal Ouenniche ◽  
Bing Xu ◽  
Kaoru Tone
Keyword(s):  
Data Envelopment Analysis ◽  
Methodological Issue ◽  
Oil Prices ◽  
Performance Measure ◽  
Data Envelopment ◽  
Super Efficiency ◽  
Forecasting Models ◽  
Ranking Models ◽  
Context Dependent ◽  
Efficiency Data

Xu and Ouenniche (2012a) proposed an input-oriented radial super-efficiency Data Envelopment Analysis (DEA) based model to address a common methodological issue in the evaluation of competing forecasting models; namely, ranking models based on a single performance measure at a time, which typically leads to conflicting ranks. However, their approach suffers from a number of issues. In this paper, we overcome these issues by proposing a slacks-based context-dependent DEA framework and use it to rank forecasting models of oil prices volatility.

An Empirical Investigation of Factors Affecting Stock Prices in Vietnam

2014 ◽  
pp. 74-89 ◽  
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.

Determinants of Inflation in Vietnam: A VECM Approach

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.

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

GIS Business ◽  
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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