Crude Oil Price Fluctuations Research Articles

The impact of crude oil price fluctuations on Economic Growth and Non-oil exports in the Kingdom of Saudi Arabia: An ARDL approach

Using annual data covering the period from 2000 to 2020 the effect of volatility was estimated on economic growth and crude oil prices on Saudi non-oil exports, each of the two sectors was chosen, Exports from manufacturing industries, agricultural exports, and high-tech exports to represent Non-oil export, also we Measuring the impact of oil price fluctuations on economic growth in the Kingdom of Saudi Arabia. The study followed the application of the ARDL model to study the equilibrium relationship between all of the volatility in oil prices, the three export sectors. The results indicated that the sector Exports of manufacturing industries is the sector most affected by the fluctuation in the price of oil, while the results did not indicate the existence of a long-term equilibrium relationship through which the sectors of agricultural exports and high-tech products are affected by the change in oil prices.The study recommends the need to increase investments for these twoSectors to secure a stable export proceeds that guarantee the stability of the Kingdom's economic growth rates.To reach the above, we have relied on measuring the impact of the relationship between oil prices and economic growth of the Kingdom of Saudi Arabia during the period 2000-2020, based on a model the Autoregressive Distributed Lag (ARDL).

Analysing the Risk Spillover of International Crude Oil Price and Exchange Rate Fluctuations Using a Pooled Empirical Modal Decomposition Approach

Analysing the Risk Spillover of International Crude Oil Price and Exchange Rate Fluctuations Using a Pooled Empirical Modal Decomposition Approach

A Study on the Correlation between International Crude Oil Price Fluctuation Cycle Measure and Economic Cycle Fluctuation

A Study on the Correlation between International Crude Oil Price Fluctuation Cycle Measure and Economic Cycle Fluctuation

Relationship Between Crude Oil Price Fluctuations, Economic Growth, Inflation, and Exchange Rate in Indonesia 1967-2019

<p>Economic fluctuations can be caused by demand shocks and supply shocks. One of the supply shocks is caused by changes in world crude oil prices. As a net importer of crude oil, any change in crude oil prices makes domestic economic activity vulnerable to these shocks. The purpose of this study is to determine the effect of fluctuations in world crude oil prices on economic variables in Indonesia in the form of economic growth, inflation, and exchange rates. In addition, this study also analyzes the causal relationship between these variables. The type of data used is secondary data sourced from the BP Statistical Review of World Energy and the Worldbank. This research uses the VAR/VECM method, the research period was carried out during the years 1967-2019. The results showed that during 1967-2019 fluctuations in world crude oil prices had a significant positive effect on economic growth and had a significant negative effect on inflation and the exchange rate in the long run. Meanwhile, in the short term, world crude oil price fluctuations do not significantly affect economic growth, inflation, and the exchange rate. The results of the Granger causality show that there is no two-way causality relationship between variables.</p><p><strong>Keywords:</strong> Fluctuation World Crude Oil Price, Economic Growth, Inflation, Exchange Rate, VAR/VECM, Granger Causality Test</p>

Composites of Vegetable Oil-Based Polymers and Carbon Nanomaterials

Owed to current environmental concerns and crude oil price fluctuations, the design of feasible substitutes to petroleum-based polymeric materials is a major challenge. A lot of effort has been focused on transforming natural vegetable oils (VOs), which are inexpensive, abundant, and sustainable, into polymeric materials. Different nanofillers have been combined with these bio-based polymer matrices to improve their thermal, mechanical, and antibacterial properties. The development of multifunctional nanocomposites materials facilitates their application in novel areas such as sensors, medical devices, coatings, paints, adhesives, food packaging, and other industrial appliances. In this work, a brief description of current literature on polymeric nanocomposites from vegetable oils reinforced with carbon nanomaterials is provided, in terms of preparation, and properties. Different strategies to improve the nanomaterial state of dispersion within the biopolymer matrix are discussed, and a correlation between structure and properties is given. In particular, the mechanical, thermal, and electrical properties of these natural polymers can be considerably enhanced through the addition of small quantities of single-walled carbon nanotubes (SWCNTs), multi-walled carbon nanotubes (MWCNTs), graphene (G), or its derivatives such as graphene oxide (GO) or fullerenes (C60). Finally, some current and potential future applications of these materials in diverse fields are briefly discussed.

Efficient separation and quantification of methyl palmitate and methyl oleate in biodiesel mixture using reverse-phase high performance liquid chromatography

ABSTRACT The excessive utilization of petroleum resources leads to global warming, crude oil price fluctuations, and fast depletion of petroleum reserves. Biodiesel (Fatty Acid Methyl Ester, FAME) has gained importance as a clean and renewable energy source over the last few years. It is produced by reacting vegetable oils and short-chain alcohols via transesterification/esterification reaction. The properties of biodiesel depend on the vegetable oils’ fatty acid composition due to the saturated and unsaturated fatty acid content variation. During the FAME quantification analysis, separation of methyl palmitate (MeP) and methyl oleate (MeO) are major challenges in the C18 column in High Performance Liquid Chromatography (HPLC). These components are difficult to quantify as they elute simultaneously by forming an overlapping peak. A new reverse-phase HPLC separation method with C18 column has been developed to efficiently separate and quantify FAMEs derived from palm oil. UV-VIS detector was used at 205 nm. The FAMEs separation was achieved using ternary mobile phase solvents acetonitrile, water, and acetone with the composition of 62%, 33%, and 5% in an isocratic flow with 2.20 mL/min flowrate and 45 °C column temperature. Methyl esters were analyzed with satisfactory linearity (r 2 >0.99), repeatability (relative standard deviation <2%), and sensitivity (limit of quantification).

Biodiesel Production Using Homogeneous, Heterogeneous, and Enzyme Catalysts via Transesterification and Esterification Reactions: a Critical Review.

The excessive utilization of petroleum resources leads to global warming, crude oil price fluctuations, and the fast depletion of petroleum reserves. Biodiesel has gained importance over the last few years as a clean, sustainable, and renewable energy source. This review provides knowledge of biodiesel production via transesterification/esterification using different catalysts, their prospects, and their challenges. The intensive research on homogeneous chemical catalysts points to the challenges in using high free fatty acids containing oils, such as waste cooking oils and animal fats. The problems faced are soap formation and the difficulty in product separation. On the other hand, heterogeneous catalysts are more preferable in biodiesel synthesis due to their ease of separation and reusability. However, in-depth studies show the limited activity and selectivity issues. Using biomass waste-based catalysts can reduce the biodiesel production cost as the materials are readily available and cheap. The use of an enzymatic approach has gained precedence in recent times. Additionally, immobilization of these enzymes has also improved the statistics because of their excellent functional properties like easy separation and reusability. However, free/liquid lipases are also growing faster due to better mass transfer with reactants. Biocatalysts are exceptional in good selectivity and mild operational conditions, but attractive features are veiled with the operational costs. Nanocatalysts play a vital role in heterogeneous catalysis and lipase immobilization due to their excellent selectivity, reactivity, faster reaction rates owing to their higher surface area, and easy recovery from the products and reuse for several cycles.

Fluctuations in Macroeconomic Variables on the Funding of Pension Funds in Iran (Combined Data Pattern Method with Different Frequency (Midas))

In the present study, the fluctuations of macroeconomic variables on the resilience of pension funds in Iran are investigated. For this purpose, using the combined data model method with different frequencies (Midas), the present issue was investigated for different seasonal and annual time periods. In the estimated model, the annual data of government debt, unemployment, and total expenditures of the Social Security Organization and quarterly data of oil price fluctuations, exchange rate jumps, money supply and consumer price index for the years 1370-1397 have been used. Data related to 1398 were not used in the initial estimation of the relationship in order to test the predictive power of the model outside the estimation range. Based on the results; Inflation rate, money supply, exchange rate jumps and crude oil price fluctuations have a statistically significant effect on the expenditures of the Social Security Organization. In other words, in terms of economic structure and according to the principles of economics, a steady increase in the exchange rate causes economic prosperity in society, but if this increase is temporary, economic prosperity can not be observed. A floating and managed exchange rate increase will cause relative stability in the foreign exchange market, which in turn will increase the total costs of the Social Security Administration in the long run. Exchange rate fluctuations lead to an increase in debt by companies and the government, and an increase in debt will lead to a general lack of liquidity, which in general, the lack of liquidity of enterprises has a negative effect on the situation of the Social Security Organization and increase the total costs of the organization. Has it. Also, by comparing the predicted values with the realized values, the prediction accuracy of the model is higher and is closer to the real values.

Do Crude Oil Price Levels Or Its Volatility Matter In Global Food Commodity Price Change?

This study investigates the effect of crude oil price fluctuations on wheat, sugar, corn, and fertilizers. Results of Markov switching dynamic regression support evidence of two states. State 1, pertains to the low volatility of crude oil prices, and state 2, refers to higher volatility of crude oil prices. At state 1 higher levels of oil prices lead to a decline in food commodity prices, whereas in state 2, higher oil prices cause an increase in food commodity prices. Results of Dynamic Conditional Correlation (DCC) GARCH estimates indicate the coefficients of oil price levels are significant and positively associated with the conditional volatility of the four commodity prices, implying that fluctuations in global food commodity prices are not due to oil price volatility but due to the oil price levels attained at the extreme points.

Crude oil price uncertainty and corporate carbon emissions.

Low-carbon transformation has become a key priority in China, as demonstrated in the implementation of the Carbon Peak, Carbon Neutralization policy, leading to increasing concern of environmental performance at the corporate level. This paper measures the carbon emission of 1,089 Chinese companies through the EIO-LCA-based approach. Then we examine the impacts of international crude oil price fluctuations and the corporate development level on carbon emissions of individual companies. Our results indicate that an increase in international crude oil price uncertainty could inhibit the company’s carbon emission. In parallel, we find that there might exist an environmental Kuznets curve (EKC) inverted U-shaped correlation between the company’s development level and its environmental performance. However, some exceptions to corporate carbon performance may emerge, resulting from specific corporate characteristics such as the state-owned nature and whether the firm is listed on the stock exchange. Our results could help companies optimize their internal carbon emission structure during the low-carbon transition process and contribute to effective policy regulations towards the target of carbon reduction.

Exploring relationship between crude oil price volatility and stock indices movement using wavelet analysis: evidence from India and China

Purpose This study aims to explore the linkage between fluctuations in the global crude oil price and equity market in fast emerging economies of India and China. Design/methodology/approach The present research uses wavelet decomposition and maximal overlap discrete wavelet transform (MODWT), which decompose the time series into various frequencies of short, medium and long-term nature. The paper further uses continuous and cross wavelet transform to analyze the variance among the variables and wavelet coherence analysis and wavelet-based Granger causality analysis to examine the direction of causality between the variables. Findings The continuous wavelet transform indicates strong variance in WTIR (return series of West Texas Instrument crude oil price) in short, medium and long run at various time periods. The variance in CNX Nifty is observed in the short and medium run at various time periods. The Chinese stock index, i.e. SCIR, experiences very little variance in short run and significant variance in the long and medium run. The causality between the changes in crude oil price and CNX Nifty is insignificant and there exists a bi-directional causality between global crude oil price fluctuations and the Chinese equity market. Originality/value To the best of the authors’ knowledge, very limited work has been done where the researchers have analyzed the linkage between the equity market and crude oil price fluctuations under the framework of discrete wavelet transform, which overlooks the bottleneck of non-stationarity nature of the time series. To bridge this gap, the present research uses wavelet decomposition and MODWT, which decompose the time series into various frequencies of short, medium and long-term nature.

US banks in the time of COVID-19: fresh insights from the wavelet approach

This study explores the impact of COVID-19, crude oil price, US economic policy uncertainty, baltic dry index, and the stock market volatility on the US bank indices. This study is conducted based on the daily data ranging from 21st January 2020 to 30th October 2020. The wavelet coherence analysis suggests that rising COVID-19 cases in the US have a strong impact on both bank indices. Also, global COVID-19 cases influence the bank indices, although it is not as strong as US COVID-19 cases. Additionally, we have found that the US economic policy uncertainty and stock market volatility imposed negative and strong effect on the bank indices in this pandemic situation. Moreover, continuous fluctuation of crude oil price makes the US banks volatile throughout the period.

Dynamics of Crude Oil Price Change and Global Food Commodity Prices

Purpose: This study investigates the effect of crude oil price fluctuations (price change as well as volatility) on wheat, sugar, corn, and fertilizers price changes. &#x0D; Methods: The study employs Markov switching dynamic regression, Dynamic Conditional Correlation (DCC), and Generalized Autoregressive Conditional Hetrosekadicity (GARCH) on monthly data covering the period from January 1988 to April 2018.&#x0D; Results: The findings of the research support evidence of two states. State 1, pertains to the low volatility of crude oil price, and state 2 belong to the case of the high volatility of crude oil prices. Our results indicated that at state 1, an increase in crude oil prices leads to a decline in food commodity prices, while in state 2, an increase in crude oil price levels causes an increase in food commodity prices. Results of Dynamic Conditional Correlation (DCC) GARCH estimates indicate the coefficients of oil price levels are significant and positively associated with the conditional volatility of the four commodity prices.&#x0D; Implications: The findings of the research imply that volatility in global food commodity prices is not due to oil price volatility but due to the oil price levels attained at extreme points.&#x0D; Originality: The paper investigates the impact of different volatility levels of crude oil prices on global food commodity prices.

Crude Oil Price Shock and the Nigerian Stock Market Performance in the Face of Covid-19 Pandemic Evidence from ARDL &amp; Granger Causality Approach

The study examined empirically the linear relationship between crude oil price shock and the Nigerian stock market performance, with the main objective of ascertaining the impact of the recent sharp decline in crude oil prices on stock market performance in the face of the global socio-economic challenge posed by COVID-19 pandemic. It used monthly time series data from the central bank of Nigeria (CBN) website (www.cbn.gov.ng) from 2017-2020 This period was chosen to capture the effects of changes in oil price on the performance of the Nigerian stock market within the context of the global economic challenges due to the COVID-19 pandemic. The auto-regressive distributed lag ARDL approach has been applied in the model specification and data analysis for the study. The results of the ARDL in both the short and long run revealed that the recent crude oil price shock has a significant impact on stock market performance in Nigeria. The results of the granger causality test also reveal a unidirectional causality from crude oil price to stock market performance with a piece of evidence from the current decline of global crude oil prices from December 2019 to April 2020. The study, therefore, suggests the need for the Nigerian capital market to continue to pursue with vigor the implementation of the capital market master plan in the hope that a more developed capital market should be able to absorb external shocks such as those arising from crude oil price fluctuations.

IMPACT OF CRUDE OIL PRICE ON COUNTRIES’ AND VIETNAM’S GDP GROWTH: VARIANCE DECOMPOSITION APPROACH

The crude oil price fluctuation investigation is to explore the impact of crude oil price shocks on the countries’ economic growth. The Vector Autoregressive Model (VAR) was applied and the variance decomposition is to analyze the impact of the GDP growth due to the shock of the crude oil price. Besides, nine countries' data were collected from 1990 to the third quarter of 2020. The countries' GDP growth was impacted by the crude oil price in 5 years respectively: 44.98%; 40.03%; 31.06%; 32.27%; 33.21%; 36.03%; 27.79%; 15.35%; 40.75% of the following countries are: China; America; Japan; Korea; Singapore; Thailand; Indonesia; Vietnam; Malaysia. This study identifies issues for countries to consider: have a comprehensive solution among macroeconomic policies, monetary policy, fiscal policy and other policies to control and stimulate growth.

THE INFLUENCE OF OIL PRICE FLUCTUATIONS ON STOCK MARKET OF DEVELOPING ECONOMIES: A FOCUS ON NIGERIA

The inconclusiveness of findings from various studies on Nigeria on the effect of crude oil price fluctuation on the stock market has led to an argument in literature, thus necessitating further exploration of the subject. This study examines the effect of variations in the price of crude oil on selected stock market performance variables in Nigeria using monthly frequency data covering January 1997 to December 2016. Variance decomposition, impulse response analysis, and VAR estimations were employed for the study. The results reveal that oil price variations are slowly transmitted in some stock market performance variables. The findings indicate that the effect of crude oil price fluctuations in the Nigerian stock market is greatly minimized and does not sufficiently account for market activities. Keywords: Emerging Economy, Nigeria, Oil Price Shocks, Stock Market, VAR. JEL Classifications: C25, Q47, F4 DOI: https://doi.org/10.32479/ijeep.10140

Protocol to Assess the Impact of Crude Oil Price Fluctuations on Future Asphalt Prices

It is clear for the transportation industry that asphalt prices are heavily affected by changes in the crude oil market. This occurs because asphalt is a byproduct of the process of refining crude oil. However, there is still a lack of research on assessing the economic implications of this relationship. This paper assesses those implications through an innovative statistical process designed to quantify the economic correlation between asphalt and crude oil price fluctuations in Alabama. The proposed statistical process is used in this paper to model the relationship between the Alabama Department of Transportation’s (ALDOT’s) monthly asphalt price index and a national crude oil index published by the US Energy Information Administration. The process quantifies the relationship between these two commodities in relation to two metrics: (1) the time gap between an observed change in the crude oil index and its corresponding impact on the asphalt price index and (2) the magnitude of that impact. It was found that the most likely time gap between crude oil and asphalt price fluctuations in Alabama is 3 months, with a change ratio of 0.58. This means that a 1% increase in the price of crude oil would most likely affect the Alabama asphalt market 3 months later with a price increase of about 0.58%. Recognizing that these are just average values, the paper also presents a risk assessment tool that provides ALDOT with the probability of occurrence of different scenarios taking into consideration the observed variability in time gaps and change ratios.

Forecasting crude oil price with a new hybrid approach and multi-source data

Faced with the growing research toward crude oil price fluctuations influential factors following the accelerated development of Internet technology, accessible data such as Google search volume index (GSVI) are increasingly quantified and incorporated into forecasting approaches. In this study, we apply multi-scale data that including both traditional economic data and GSVI data reflecting macro and micro mechanisms affecting crude oil price respectively, so as to reduce the forecasting deviation and improve the forecasting accuracy at source. In addition, a new hybrid approach: K-means＋KPCA＋KELM based on “divide and conquer” strategy is proposed for deeply exploring the information of above multi-data so that improve monthly crude oil price forecasting accuracy. Empirical results can be analyzed from data and method levels. At the data level, GSVI data perform better than economic data in level forecasting accuracy but with opposite performance in directional forecasting accuracy because of “Herd Behavior”, while hybrid data combined their advantages and obtain best forecasting performance in both level and directional accuracy. At the method level, the approaches with “divide and conquer” strategy gain a better forecasting performance, which demonstrates that “divide and conquer” strategy can effectively improve the forecasting performance.

THE IMPACT OF OIL PRICE ON STOCK MARKET:EMPIRICAL EVIDENCE FROM US

The analysis of this research focuses on the interactive relationship among the fluctuation of crude oil prices, the real GDP and the stock market of United State. This empirical investigation uses data is in between 1990 and 2018 with the Vector Auto-regression (VAR) analysis, and multiple regressions with its assumption were used in order to analyses data. &#x0D; Findings, oil price and economic growth are very important determinates of stock market in US because the p-value of this were less than the common alpha α =0.05. For instance, the crude oil price had positive impact on stock market because for each unit increasing of crude oil price, the stock market will increase by (0.276901) after holding all other variable constant. However, we find that GDP has negative impact on the participations of increasing the stock market.

Study on benefit evaluation of developed oil and gas fields

With the development of economy and the fluctuation of international crude oil price, people are more and more concerned about the economic benefits of oilfield development. At present, most of the domestic oil fields have entered the middle and late stage of development. With the increase of water cut and decline of production, the economic benefits vary greatly, and some single Wells and block incomes are not enough to make up for their production costs. How to carry out economic evaluation, provide basis for production and operation decision, and seek the best economic benefit is the first problem that must be studied and solved in the development of oilfield quality benefit. Single well and block benefit evaluation system is applied in this article, combined with the most oil field in recent years, the crude oil output, production cost, sales income, etc. comprehensive analysis and evaluation has been developed single well, block, formulate corresponding measures and countermeasures, to guide the oilfield production and operation, inefficient, invalid next block and single well comprehensive treatment has a positive meaning.