Can energy commodities affect energy blockchain-based cryptos?

2019 ◽  
Vol 36 (4) ◽  
pp. 682-699 ◽  
Author(s):  
Ikhlaas Gurrib
Keyword(s):  
Natural Gas ◽  
Crude Oil ◽  
Autoregressive Model ◽  
Structural Breaks ◽  
Price Index ◽  
Principal Component ◽  
Commodity Price ◽  
Var Model ◽  
Content Type ◽  
Heating Oil

Purpose The purpose of this paper is to shed fresh light into whether an energy commodity price index (ENFX) and energy blockchain-based crypto price index (ENCX) can be used to predict movements in the energy commodity and energy crypto market. Design/methodology/approach Using principal component analysis over daily data of crude oil, heating oil, natural gas and energy based cryptos, the ENFX and ENCX indices are constructed, where ENFX (ENCX) represents 94% (88%) of variability in energy commodity (energy crypto) prices. Findings Natural gas price movements were better explained by ENCX, and shared positive (negative) correlations with cryptos (crude oil and heating oil). Using a vector autoregressive model (VAR), while the 1-day lagged ENCX (ENFX) was significant in estimating current ENCX (ENFX) values, only lagged ENCX was significant in estimating current ENFX. Granger causality tests confirmed the two markets do not granger cause each other. One standard deviation shock in ENFX had a negative effect on ENCX. Weak forecasting results of the VAR model, support the two markets are not robust forecasters of each other. Robustness wise, the VAR model ranked lower than an autoregressive model, but higher than a random walk model. Research limitations/implications Significant structural breaks at distinct dates in the two markets reinforce that the two markets do not help to predict each other. The findings are limited by the existence of bubbles (December 2017-January 2018) which were witnessed in energy blockchain-based crypto markets and natural gas, but not in crude oil and heating oil. Originality/value As per the authors’ knowledge, this is the first paper to analyze the relationship between leading energy commodities and energy blockchain-based crypto markets.

Impact of fossil fuel prices on electricity prices in Mexico

2019 ◽  
Vol 46 (2) ◽  
pp. 356-371 ◽  
Author(s):  
Bruno Bernal ◽  
Juan Carlos Molero ◽  
Fernando Perez De Gracia
Keyword(s):  
Natural Gas ◽  
Crude Oil ◽  
Fossil Fuel ◽  
Positive Impact ◽  
Electricity Price ◽  
Electricity Prices ◽  
Content Type ◽  
Fuel Prices ◽  
Electricity Rates ◽  
Domestic Electricity

Purpose The purpose of this paper is to examine the impact of fossil fuel prices – crude oil, natural gas and coal – on different electricity prices in Mexico. The use of alternative variables for electricity price helps to increase the robustness of the analysis in comparison to previous empirical studies. Design/methodology/approach The authors use an unrestricted vector autoregressive model and the sample covers the period January 2006 to January 2016. Findings Empirical findings suggest that crude oil, natural gas and coal prices have a significant positive impact on electricity prices – domestic electricity rates – in Mexico in the short run. Furthermore, crude oil and natural gas prices have also a significant positive impact on electricity prices – commercial and industrial electricity rates. Originality/value Two are the main contributions. First, this paper explores the nexus among crude oil, natural gas, coal and electricity prices in Mexico, while previous studies focus on the US, UK and some European economies. Second, instead of using one electricity price as a reference of national or domestic electricity sector, the analysis considers alternative Mexican electricity prices.

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.

Kuwait energy sector expansion will hit obstacles

2015 ◽  
Keyword(s):  
Saudi Arabia ◽  
Natural Gas ◽  
Crude Oil ◽  
Production Capacity ◽  
Oil Prices ◽  
Energy Sector ◽  
Global Market ◽  
Oil Refinery ◽  
Content Type ◽  
Crude Oil Production

Subject Prospects for Kuwait's energy sector expansion Significance Despite falling revenue because of the slump in global oil prices Kuwait is embarking on two ambitious energy ventures: constructing what will be the region's largest new oil refinery and increasing crude oil production capacity by more than 1 million barrels per day (b/d) by 2020. Impacts Increased oil output capacity will bolster Kuwait' s effort to retain market share in an over-supplied global market. Kuwait is emulating Saudi Arabia in integrating its refining and petrochemical sectors, though diversification will lag. Kuwait will incur Saudi displeasure by developing closer ties with post-sanctions Iran, a possible supplier of new natural gas supplies.

Dynamic co-movements and directional spillovers among energy futures

2020 ◽  
Vol 37 (4) ◽  
pp. 673-696 ◽  
Author(s):  
Sercan Demiralay ◽  
Nikolaos Hourvouliades ◽  
Athanasios Fassas
Keyword(s):  
Crude Oil ◽  
Futures Markets ◽  
Spillover Effects ◽  
Time Varying ◽  
Content Type ◽  
Energy Futures ◽  
Risk Transfer ◽  
Volatility Transmission ◽  
Heating Oil ◽  
Practical Implications

Purpose This paper aims to examine dynamic equicorrelations (DECO) and directional volatility spillover effects among four energy futures markets, namely, West Texas Intermediate crude oil, heating oil, natural gas and reformulated blendstock for oxygenate blending gasoline, by using a multivariate fractionally integrated asymmetric power ARCH–DECO–generalized autoregressive conditional heteroskedasticity (GARCH) model and the spillover index technique. Design/methodology/approach The empirical analysis uses the dynamic equicorrelation model of Engle and Kelly (2012) to examine time-varying correlations at equilibrium. The authors further analyze dynamic volatility transmission among energy futures by using Diebold and Yilmaz (2012) dynamic spillover index based on generalized value-at-risk framework. Findings The empirical results provide evidence of heightened equicorrelations at times of financial turmoil. More specifically, the dynamic spillover analysis shows that volatility is transmitted predominantly from crude oil to the other markets and risk transfer among four markets exhibits asymmetries. Spillovers are found to be highly responsive to dramatic events such as the 9/11 terror attack, 2008–2009 global financial crisis and 2014–2016 oil glut. Practical implications The results of this study have important practical implications for investors, portfolio managers and energy policymakers as the presence of time-varying co-movements and spillovers suggests the need for dynamic trading strategies. There are also implications regarding risk management practices, as there is evidence of increased volatility transmission at times of financial turmoil and uncertainty. Finally, the results provide insights to policymakers in a better understanding of the spillover dynamics. Originality/value This paper investigates the DECOs and spillover effects among crude oil, natural gas, heating oil and gasoline futures markets. To the best of the knowledge, this is one of a few studies that examine co-movements and risk transfer in energy futures in a comprehensive framework.

Challenges facing the implementation of the national natural gas policy in Tanzania

2019 ◽  
Vol 13 (3) ◽  
pp. 500-517
Author(s):  
Obadia Kyetuza Bishoge ◽  
Lingling Zhang ◽  
Witness Gerald Mushi
Keyword(s):  
Natural Gas ◽  
Policy Implementation ◽  
Statistical Tests ◽  
Principal Component ◽  
Influential Factors ◽  
Demographic Information ◽  
Content Type ◽  
Implementation Challenges ◽  
The Relationship ◽  
Structured Questionnaire

Purpose This study aims to investigate the challenges facing the implementation of the natural gas policy in Tanzania. Design/methodology/approach A structured questionnaire was used to collect data, while the principal component analysis and statistical tests were used to explore the relationship between the opinions on the influential factors for the natural gas policy implementation and the demographic information. Findings The findings showed that over 50 per cent of the respondents regarded poor community participation and transparency and accountability as the major policy implementation challenges. Most of the demographic information showed the statistically significant effects of the policy implementation influential factors. Originality/value This paper provides the current challenges facing the implementation of the national natural gas policy in Tanzania.

Empirical differences between the overnight and day trading hour returns

2018 ◽  
Vol 8 (3) ◽  
pp. 315-331 ◽  
Author(s):  
Juan DU
Keyword(s):  
Principal Component ◽  
Futures Market ◽  
Commodity Futures ◽  
Var Model ◽  
Stable Model ◽  
Market Information ◽  
Market Returns ◽  
Content Type ◽  
Day Trading ◽  
Asymmetric Model

Purpose The purpose of this paper is to provide a stable model which covers market information of return to examine the empirical differences between the returns during night and day in Chinese commodity futures market. Design/methodology/approach Commodity indices are constructed using principal components analysis to represent the market returns for day and night trading in the Chinese commodity futures market. Then VAR models are employed to predict the commodity indices’ returns and squared returns. Findings The symmetric VAR model failed to model the market returns since the asymmetric effects of positive and negative returns are not taken into account. By allowing asymmetric behavior among positive and negative variables, asymmetric VAR model is utilized to trace the leading effect of overnight returns to daytime trading returns. However, the symmetric VAR model outperforms the asymmetric model when evaluating the predictive power of squared returns during night trading hours. Two major results based on asymmetric model for the return are: There is a 6-day leading effect of nighttime return to daytime return in Chinese commodity futures market. It is risky to hold day trading position overnight. Research limitations/implications Asymmetric VAR model provides a new approach to forecasting the direction of price movement. Practical implications Investment managers are able to create a stable portfolio contains major market information. Day and night traders are likely to gain some suggestions to discover arbitrage opportunities. Social implications Since there is no commodity futures index in China, the method for creating indices for Chinese commodity futures is provided to market regulators. Originality/value Combining principal component analysis and asymmetric VAR model provides a stable and predictable model to obtain market information.

scholarly journals Volatility Spillovers: Evidence On U.S. Oil Product Markets

2012 ◽  
Vol 28 (6) ◽  
pp. 1237 ◽  
Author(s):  
Bernard Ben Sita ◽  
Salah Abosedra
Keyword(s):  
Natural Gas ◽  
Crude Oil ◽  
Transmission Mechanism ◽  
Font Size ◽  
Product Markets ◽  
Volatility Spillovers ◽  
Oil And Natural Gas ◽  
Heating Oil ◽  
Energy Products ◽  
The Relationship

<span style="font-family: Times New Roman; font-size: small;"> </span><p style="margin: 0in 0.5in 0pt; text-align: justify; mso-pagination: none;" class="MsoNormal"><span lang="EN-CA" style="color: black; font-size: 10pt; mso-themecolor: text1; mso-ansi-language: EN-CA;"><span style="font-family: Times New Roman;">This paper provides evidence on the lead, the contemporaneous and the lagged transmission mechanism of extreme shocks across energy products. Our findings reveal a weak leadership of crude oil in guiding hedgers against risk that is specific to natural gas whose changes show a weak reliance on changes in crude oil. Moreover, our findings are consistent with the competitive use of energy products. It follows that substitutability characterizes the relationship between heating oil and natural gas when extreme standardized shocks are considered.<span style="mso-spacerun: yes;"> </span></span></span></p><span style="font-family: Times New Roman; font-size: small;"> </span>

scholarly journals Time-Varying Volatility Feedback of Energy Prices: Evidence from Crude Oil, Petroleum Products, and Natural Gas Using a TVP-SVM Model

2018 ◽  
Vol 10 (12) ◽  
pp. 4705 ◽  
Author(s):  
Yong Jiang ◽  
Chao-Qun Ma ◽  
Xiao-Guang Yang ◽  
Yi-Shuai Ren
Keyword(s):  
Natural Gas ◽  
Crude Oil ◽  
Structural Breaks ◽  
Price Volatility ◽  
Petroleum Products ◽  
Energy Price ◽  
Time Varying ◽  
Energy Prices ◽  
Svm Model ◽  
Volatility Feedback

: In this paper, the time-varying volatility feedback of nine series of energy prices is researched by employing the time-varying parameter stochastic volatility in mean (TVP-SVM) model. The major findings and conclusions can be grouped as follows: Significant differences exist in the time-varying volatility feedback among the nine major energy productions. Specifically, crude oil and diesel’s price volatility has a remarkable positive time-varying effect on their returns. Yet the returns, for natural gas and most petroleum products are negatively affected by their price volatility over time. Furthermore, obvious structural break features exist in the time-varying volatility feedback of energy prices, which coincide with the breakpoints in the energy volatility. This indicates that some factors such as major global economic and geopolitical events that cause the sudden structural breaks in the energy volatility may also affect the volatility feedback of the energy price. Moreover, the volatility feedback in energy price will become weak and even have no impact on energy returns in some special periods when the energy price volatility is extremely high.

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