scholarly journals VOLATILITY SPILLOVER AND DYNAMIC CORRELATION BETWEEN THE CARBON MARKET AND ENERGY MARKETS

2019 ◽  
Vol 20 (5) ◽  
pp. 979-999 ◽  
Author(s):  
Yufeng Chen ◽  
Fang Qu ◽  
Wenqi Li ◽  
Minghui Chen
Keyword(s):  
Natural Gas ◽  
Global Financial Crisis ◽  
Energy Markets ◽  
Volatility Spillover ◽  
Energy Prices ◽  
Eu Ets ◽  
Dynamic Correlation ◽  
Demand Reduction ◽  
The Global Financial Crisis ◽  
Multi Phase

This paper studies the volatility spillover and dynamic correlation between EU emission allowance (EUA) prices and energy prices by considering three energy commodities, including oil, gas, and coal. The asymmetric BEKK model is employed for multi-phase analysis of EU ETS, yet only a little empirical evidence backing up the existence of volatility spillover between EU ETS and energy markets, i.e., the establishments of the EU ETS may not effectively limitation and influence energy markets. The time-varying conditional correlation between EUA and each of energy prices is analyzed. The dynamic correlation shows there is a relatively stable, positive correlation between the EUA and Brent oil, natural gas. However, modeling the dynamics correlation also suggests that the correlation between the EUA and the natural gas, coal became weaker and more volatile since second and third phases, especially after the Global Financial Crisis in 2008, which may indicate that the demand reduction in emission allowances caused by the economic slowdown far exceeds the reduction in the annual restraint of EU ETS.

scholarly journals Information Linkage between Carbon and Energy Markets: Multiplex Recurrence Network Approach

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12 ◽  
Author(s):  
Hua Xu ◽  
Minggang Wang ◽  
Weiguo Yang
Keyword(s):  
Time Delay ◽  
Natural Gas ◽  
Carbon Price ◽  
Energy Markets ◽  
Carbon Markets ◽  
Energy Prices ◽  
The European Union ◽  
Linkage Relationship ◽  
Leading Role ◽  
Carbon Prices

In this paper, a multilayer recurrence network is introduced to examine the information linkage between carbon and energy markets. We first construct a multilayer recurrence network of energy and carbon markets, and we define the information linkage coefficient to measure the linkage relationship between the network layers based on the network microstructure. To measure the mutual leading relationship between carbon and energy markets, we construct a time-delay multilayer recurrence network and introduce the time-delay information linkage coefficient to measure the intersystem interaction. The carbon and energy prices, including West Texas Intermediate crude oil, coal, natural gas, and gasoline, from February 22, 2011, to April 1, 2019, are selected as sample data for empirical analysis. The results show that the linkage relationship between oil, coal, natural gas, and carbon prices presents a U-shaped trend in the second, transitional, and third phases of the European Union carbon market, while the linkage trend of gasoline and carbon prices continues to rise. The mutual leading relationship between energy and carbon prices changes in different stages, and carbon price plays a leading role at the present stage.

scholarly journals Dynamic Interrelationship and Volatility Spillover among Sustainability Stock Markets, Major European Conventional Indices, and International Crude Oil

2020 ◽  
Vol 12 (9) ◽  
pp. 3908 ◽  
Author(s):  
Basel Maraqa ◽  
Murad Bein
Keyword(s):  
Crude Oil ◽  
Stock Returns ◽  
Global Financial Crisis ◽  
Oil Prices ◽  
Volatility Spillover ◽  
Socially Responsible ◽  
Crude Oil Prices ◽  
Daily Data ◽  
Oil Markets ◽  
The Global Financial Crisis

This study examines the dynamic interrelationship and volatility spillover among stainability stock indices (SSIs), international crude oil prices and major stock returns of European oil-importing countries (UK, Germany, France, Italy, Switzerland and The Netherlands) and oil-exporting countries (Norway and Russia). We employ the DCC-MGARCH model and use daily data for the sample period from 28 September 2001 to 10 January 2020. We find that the dynamic interrelationship between SSIs, stock returns of European oil importing/exporting countries and oil markets is different. There is higher correlation between SSIs and oil-importing countries, while oil-exporting countries have higher correlation with the oil market. Notably, the correlation between oil and stock returns became higher during and after the global financial crisis. This study also reveals the existence of significant volatility spillover between sustainability stock returns, international oil prices and the major indices of oil importing/exporting countries. These results have important implications for investors who are seeking to hedge and diversify their assets and for socially responsible investors.

Volatility spillover between the US, Chinese and Australian stock markets

2017 ◽  
Vol 43 (2) ◽  
pp. 263-285 ◽  
Author(s):  
Emawtee Bissoondoyal-Bheenick ◽  
Robert Brooks ◽  
Wei Chi ◽  
Hung Xuan Do
Keyword(s):  
United States ◽  
Financial Services ◽  
Stock Markets ◽  
Global Financial Crisis ◽  
The United States ◽  
Jel Classification ◽  
Volatility Spillover ◽  
Stock Market Volatility ◽  
Index Level ◽  
The Global Financial Crisis

We assess the stock market volatility spillover between three closely related countries, the United States, China and Australia. This study considers industry data and hence provides a clear idea of the channels through which volatility is transmitted across these countries. We find that there is significant bilateral causality between the countries at the market index level and across most of the industries for the full sample period from July 2007 to May 2016. There is one-way volatility spillover from the United States to China in the financial services, industrials, consumer discretionary and utilities industry. There is insignificant volatility spillover from the Australian to Chinese stock markets in financial services, telecommunications and energy industries. Once we remove the effect of the global financial crisis (GFC), we find significant bilateral relationship across all of the industries across the three countries. JEL Classification: G15

scholarly journals Comparing The South African Stock Markets Response To Two Periods Of Distinct Instability The 1997-98 East Asian And Russian Crisis And The Recent Global Financial Crisis

2014 ◽  
Vol 13 (3) ◽  
pp. 427 ◽  
Author(s):  
Anmar Pretorius ◽  
Jesse De Beer
Keyword(s):  
Financial Crisis ◽  
South African ◽  
Stock Markets ◽  
Global Financial Crisis ◽  
East Asian ◽  
Volatility Spillover ◽  
The South ◽  
Share Prices ◽  
Export Destination ◽  
The Global Financial Crisis

This paper compares the South African stock markets response to two periods of distinct instability, namely the East Asian and Russian crisis of 1997-98 and the global financial crisis of 2007-09. Considering share prices, the Johannesburg Securities Exchange (JSE) was more severely affected by the earlier crisis, when the domestic fundamentals were weaker. The low levels of foreign reserves were the main cause of concern. The paper further empirically investigates volatility spillover between the JSE and various developed and emerging stock markets during the two crisis periods, employing twelve separate bi-variate GARCH models. The main contributors to volatility spillover during the East Asian and Russian crisis were Mexico, Thailand, Brazil, and Germany predominantly emerging markets. During the second crisis period, Germany, US, Brazil, and UK played the dominant parts predominantly developed markets. The importance of Germany in both periods can be attributed to the countrys role as main export destination of South African goods in Europe.

scholarly journals How Does the Spillover among Natural Gas, Crude Oil, and Electricity Utility Stocks Change over Time? Evidence from North America and Europe

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 727 ◽  
Author(s):  
Wenting Zhang ◽  
Xie He ◽  
Tadahiro Nakajima ◽  
Shigeyuki Hamori
Keyword(s):  
North America ◽  
Natural Gas ◽  
Crude Oil ◽  
Extreme Events ◽  
Global Financial Crisis ◽  
Spillover Effects ◽  
Volatility Spillover ◽  
Stock Indices ◽  
Current Events ◽  
Electricity Utility

Our study analyzes the return and volatility spillover among the natural gas, crude oil, and electricity utility stock indices in North America and Europe from 4 August 2009 to 16 August 2019. First, in time domain, both total return and volatility spillover are stronger in Europe than in North America. Furthermore, compared to natural gas, crude oil has a greater volatility spillover on the electricity utility stock indices in North America and Europe. Second, in frequency domain, most of the return spillover occurs in the short-term, while most of the volatility spillover occurs over a longer period. Third, the rolling analyses indicate that the return and volatility from 2009 to late 2013 remained stable in North America and Europe, which may be a result of the 2008 global financial crisis, and started to fluctuate after late 2013 due to some extreme events, indicating that extreme events can significantly influence spillover effects. Moreover, investors should monitor current events to diversify their portfolios properly and hedge their risks.

scholarly journals Volatility Spillovers in Capesize Forward Freight Agreement Markets

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Xiaoxing Gong ◽  
Jing Lu
Keyword(s):  
Goodness Of Fit ◽  
Global Financial Crisis ◽  
Deviance Information Criterion ◽  
Information Criterion ◽  
Spillover Effects ◽  
Volatility Spillover ◽  
Research Subjects ◽  
Volatility Spillovers ◽  
Before And After ◽  
The Global Financial Crisis

This paper is to investigate spillovers in the Capesize forward freight agreements (FFAs) markets before and after the global financial crisis. The paper chooses four Capesize voyage routes FFAs (C3, C4, C5, and C7), two time-charter routes FFAs (BCIT/C average, BPI T/C average), and spot rates as research subjects, covering the periods 3 January 2006 to 24 December 2015. This paper applies Volatility Spillover Multivariate Stochastic Volatility (VS-MSV) model to analyze volatility spillover effects and estimates the parameters via software of Bayesian inference using Gibbs Sampling (BUGS), the deviance information criterion (DIC) used for goodness-of-fit model. The results suggest that there are volatility spillover effects in certain Capesize FFAs routes, and the effects from spot rates to FFAs take place before crisis, yet they are bilateral after crisis. With the development of shipping markets, the correlations between FFAs and spot rate are enhanced, and it seems that the effects depend on market information and traders’ behavior. So practitioners could make decisions according to the spillovers.

scholarly journals Investigating Spillover Effects between Foreign Exchange Rate Volatility and Commodity Price Volatility in Uganda

Economies ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 1 ◽  
Author(s):  
Lorna Katusiime
Keyword(s):  
Financial Crisis ◽  
Global Financial Crisis ◽  
Exchange Rate Volatility ◽  
Price Volatility ◽  
Spillover Effects ◽  
Commodity Price ◽  
Volatility Spillover ◽  
Conditional Correlation ◽  
Volatility Spillovers ◽  
The Global Financial Crisis

This study investigates the impact of commodity price volatility spillovers on financial sector stability. Specifically, the study investigates the spillover effects between oil and food price volatility and the volatility of a key macroeconomic indicator of importance to financial stability: the nominal Uganda shilling per United States dollar (UGX/USD) exchange rate. Volatility spillover is examined using the Generalized Vector Autoregressive (GVAR) approach and Multivariate Generalized Autoregressive Conditional Heteroskedasticity (MGARCH) techniques, namely the dynamic conditional correlation (DCC), constant conditional correlation (CCC), and varying conditional correlation (VCC) models. Overall, the results of both the GVAR and MGARCH techniques indicate low levels of volatility spillover and market interconnectedness except during crisis periods, at which point cross-market volatility spillovers and market interconnectedness sharply and markedly increased. Specifically, the results of the MGARCH analysis show that the DCC model produces the best results. The obtained results point to an amplification of dynamic conditional correlations during and after the global financial crisis (GFC), suggesting an increase in volatility spillovers and interdependence between these markets following the global financial crisis. This is also confirmed by the results of the total spillover index based on the GVAR analysis, which shows low but time-varying volatility spillover that intensified during periods of high uncertainty and market crises, particularly during the global financial crisis and sovereign debt crisis periods.

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