scholarly journals Dynamic Characteristics of Oil Attributes and Their Market Effects

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3927
Author(s):  
Qingqing Hu ◽  
Tinghui Li ◽  
Xue Li ◽  
Hao Dong
Keyword(s):  
Crude Oil ◽  
Dynamic Characteristics ◽  
Market Returns ◽  
Policy Makers ◽  
Vector Autoregressive ◽  
Market Effects ◽  
Oil Market ◽  
Evolution Characteristics ◽  
Structural Vector Autoregressive Model ◽  
The Impact

The commercial and financial attributes of oil have significantly changed the evolution characteristics of prices and returns of the international crude oil market. Using monthly data from April 2003 to October 2020, this paper identifies dynamic characteristics of oil’s commercial and financial attributes based on the structural vector autoregressive model (SVAR) and further analyzes their market effects with different attributes. The result shows that there are situations of commercial and financial attributes dominating, and dual attributes co-dominating for oil. Furthermore, their durations account for 51%, 23%, and 26% respectively, of the full sample. Besides, the reactions of crude oil price or return to the different properties of oil are heterogeneous. Specifically, the dual attributes of oil play the most important role in the price evolution of the international crude oil market, which is 80.851. There are significant differences among the impact of different attributes of oil on the evolution of international crude oil market returns, which are 0.009, −0.008, and −0.004, respectively. Then, some relevant recommendations for policy-makers and investors based on the above research conclusions are also put forward.

Multivariate Markov-switching score-driven models: an application to the global crude oil market

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Szabolcs Blazsek ◽  
Alvaro Escribano ◽  
Adrian Licht
Keyword(s):  
Crude Oil ◽  
Moving Average ◽  
Local Level ◽  
Markov Switching ◽  
Impulse Response Functions ◽  
Common Trends ◽  
Vector Autoregressive ◽  
Oil Market ◽  
Long Run ◽  
Special Cases

Abstract A new class of multivariate nonlinear quasi-vector autoregressive (QVAR) models is introduced. It is a Markov switching score-driven model with stochastic seasonality for the multivariate t-distribution (MS-Seasonal-t-QVAR). As an extension, we allow for the possibility of having common-trends and nonlinear co-integration. Score-driven nonlinear updates of local level and seasonality are used, which are robust to outliers within each regime. We show that VAR integrated moving average (VARIMA) type filters are special cases of QVAR filters. Using exclusion, sign, and elasticity identification restrictions in MS-Seasonal-t-QVAR with common-trends, we provide short-run and long-run impulse response functions for the global crude oil market.

scholarly journals The impact of urbanization and financial development on electricity intensity in China: Evidence from panel VAR approach

2020 ◽  
Vol 194 ◽  
pp. 03010
Author(s):  
Ruijun Duan
Keyword(s):  
Financial Development ◽  
Negative Impact ◽  
Panel Var ◽  
Policy Makers ◽  
Vector Autoregressive ◽  
Development Policies ◽  
Impact Of Urbanization ◽  
Positive Shock ◽  
The Impact ◽  
Electricity Intensity

This paper aims at exploring the impact of urbanization and financial development on electricity intensity in China during the period 2004-2018. By employing a panel vector autoregressive (VAR) approach, the study finds that the electricity intensity response to one standard deviation shock on urbanization shows a negative impact, and a positive shock to financial development initially increases electricity intensity and eventually decreases electricity intensity. Our analysis is important for policy makers for improving electricity efficiency planning and sustainable economic development policies.

scholarly journals Detection of structural regimes and analyzing the impact of crude oil market on Canadian stock market: Markov regime-switching approach

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammadreza Mahmoudi ◽  
Hana Ghaneei
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Stock Return ◽  
Stock Exchange ◽  
Markov Switching ◽  
Stock Index ◽  
Var Model ◽  
Content Type ◽  
Oil Market ◽  
The Impact

Purpose This study aims to analyze the impact of the crude oil market on the Toronto Stock Exchange Index (TSX). Design/methodology/approach The focus is on detecting nonlinear relationship based on monthly data from 1970 to 2021 using Markov-switching vector auto regression (VAR) model. Findings The results indicate that TSX return contains two regimes: positive return (Regime 1), when growth rate of stock index is positive; and negative return (Regime 2), when growth rate of stock index is negative. Moreover, Regime 1 is more volatile than Regime 2. The findings also show the crude oil market has a negative effect on the stock market in Regime 1, while it has a positive effect on the stock market in Regime 2. In addition, the authors can see this effect in Regime 1 more significantly in comparison to Regime 2. Furthermore, two-period lag of oil price decreases stock return in Regime 1, while it increases stock return in Regime 2. Originality/value This study aims to address the effect of oil market fluctuation on TSX index using Markov-switching approach and capture the nonlinearities between them. To the best of the author’s knowledge, this is the first study to assess the effect of the oil market on TSX in different regimes using Markov-switching VAR model. Because Canada is the sixth-largest producer and exporter of oil in the world as well as the TSX as the Canada’s main stock exchange is the tenth-largest stock exchange in the world by market capitalization, this paper’s framework to analyze a nonlinear relationship between oil market and the stock market of Canada helps stock market players like policymakers, institutional investors and private investors to get a better understanding of the real world.

scholarly journals Tail Dependence between Crude Oil Volatility Index and WTI Oil Price Movements during the COVID-19 Pandemic

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4147
Author(s):  
Krzysztof Echaust ◽  
Małgorzata Just
Keyword(s):  
At Risk ◽  
Crude Oil ◽  
Value At Risk ◽  
Tail Dependence ◽  
Oil Price ◽  
Health Crisis ◽  
Oil Market ◽  
Volatility Index ◽  
Conditional Copula ◽  
The Impact

This study investigates the dependence between extreme returns of West Texas Intermediate (WTI) crude oil prices and the Crude Oil Volatility Index (OVX) changes as well as the predictive power of OVX to generate accurate Value at Risk (VaR) forecasts for crude oil. We focus on the COVID-19 pandemic period as the most violate in the history of the oil market. The static and dynamic conditional copula methodology is used to measure the tail dependence coefficient (TDC) between the variables. We found a strong relationship in the tail dependence between negative returns on crude oil and OVX changes and the tail independence for positive returns. The time-varying copula discloses the strongest tail dependence of negative oil price shocks and the index changes during the COVID-19 health crisis. The findings indicate the ability of the OVX index to be a fear gauge with respect to the oil market. However, we cannot confirm the ability of OVX to improve one day-ahead forecasts of the Value at Risk. The impact of investors’ expectations embedded in OVX on VaR forecasts seems to be negligible.

scholarly journals Measuring the impact of COVID-19 surveillance variables over the international oil market

2022 ◽  
Vol 9 (1) ◽  
pp. 27-33
Author(s):  
Alshdadi et al. ◽  
Keyword(s):  
Saudi Arabia ◽  
Crude Oil ◽  
Global Economy ◽  
Oil Prices ◽  
Oil Reserves ◽  
Oil Market ◽  
Crude Oil Prices ◽  
Oil Markets ◽  
Long Term Impact ◽  
The Impact

Coronavirus (COVID-19) has turned to be an alarm for the whole world both in terms of health and economics. It is striking the global economy and increasing the unpredictability of the financial market in several ways. Significantly, the pandemic spread stimulated the social distancing which led to the lockdown of the countries’ businesses, financial markets, and daily life events. International oil markets have accommodated the crude oil prices during the early COVID-19 period. However, after the first 50 days, Saudi Arabia has surged the market with oil, which caused a certain decrease in crude oil prices, internationally. Saudi Arabia is one of the biggest oil reserves in the world. International trade is based on oil reservoirs which in turn, have been significantly dislodged by the pandemic. Therefore, it is crucial to study the impact of COVID-19 on the international oil market. The purpose of this study is to investigate the short-term and long-term impact of COVID-19 on the international oil market. The daily crude oil price data is used to analyze the impact of daily price fluctuation over COVID-19 surveillance variables. The correlation between surveillance variables and international crude oil prices is calculated and analyzed. Consequently, the project will help in stabilizing the expected world economic crises and particularly will provide the implications for the policymakers in the oil market.

scholarly journals The impact of energy derivatives on the crude oil market

1999 ◽  
Vol 21 (2) ◽  
pp. 135-167 ◽  
Author(s):  
Jeff Fleming ◽  
Barbara Ostdiek
Keyword(s):  
Crude Oil ◽  
Energy Derivatives ◽  
Oil Market ◽  
The Impact

scholarly journals POPULATION GROWTH INDUCED AND HOUSEHOLDS FINANCIAL VULNERABILITY IN NIGERIA

2021 ◽  
Vol 5 (2) ◽  
Author(s):  
Chidinma C. Mbah ◽  
Chike K. Okoli ◽  
Chinecherem M. Uzonwanne
Keyword(s):  
Population Growth ◽  
World Bank ◽  
Secondary Data ◽  
Rapid Population Growth ◽  
Financial Vulnerability ◽  
Vector Autoregressive ◽  
Long Run ◽  
Structural Vector Autoregressive Model ◽  
The Impact ◽  
Structural Vector

Nigeria has been recording a rapid increase in its population over the years. This reality has posed a serious concern for the welfare of households especially as the increase in population growth puts households at the risk of financial vulnerability. Based on this, this study is on the move to examined the impact population growth induced has on household in Nigeria. The study made use of secondary data obtained from World Bank and the Central Bank statistical bulletine spanning from 1981 to 2020 to analyze the impact of population growth induced and its financial vulnerability on household using a structural vector autoregressive model (SVAR). After the analysis, the study found out that in the long run, an increase in financial vulnerability, due to an increase in population growth decreases household welfare in Nigeria. Hence, this study recommends that the Nigerian legislature should formulate a law against rapid population growth induced to ensure that the increase in population does not outscore the means of subsistence. JEL: H10; H31 <p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0789/a.php" alt="Hit counter" /></p>

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