Multivariate GARCH Modeling of Sector Volatility Transmission: A DCC Model Approach

2011 ◽  
Author(s):  
Marcelo Brutti Righi ◽  
Paulo Sergio Ceretta
Keyword(s):  
Multivariate Garch ◽  
Volatility Transmission ◽  
Garch Modeling ◽  
Model Approach

Multivariate GARCH modeling of sector volatility transmission

2007 ◽  
Vol 47 (3) ◽  
pp. 470-480 ◽  
Author(s):  
Syed Aun Hassan ◽  
Farooq Malik
Keyword(s):  
Multivariate Garch ◽  
Volatility Transmission ◽  
Garch Modeling

Price and volatility transmission in, and between, skimmed milk powder, livestock feed and oil markets

2017 ◽  
Vol 46 (4) ◽  
pp. 248-257 ◽  
Author(s):  
Dennis Bergmann ◽  
Declan O’Connor ◽  
Andreas Thümmel
Keyword(s):  
Crude Oil ◽  
Milk Powder ◽  
Multivariate Garch ◽  
Volatility Transmission ◽  
Crude Oil Prices ◽  
Multivariate Garch Model ◽  
Oil Markets ◽  
Skimmed Milk ◽  
Derivative Markets ◽  
Skimmed Milk Powder

Price and volatility transmission effects between European Union (EU) and World skimmed milk powder (SMP) prices, as well as those between both SMP series, soybeans and crude oil prices from 2004 to 2014 were analysed using a vector error correction model combined with a multivariate GARCH model. The results show significant transmission effects between EU and World SMP prices, but no significant transmission effects from soybeans or crude oil to either of the SMP prices. For policymakers and modellers, these results indicate the need to consider World SMP prices when considering EU prices. On the other hand, the finding of no transmission effects from soybean to SMP prices reduces the opportunity for a successful cross-hedging for dairy commodities using well-established soybean derivative markets.

scholarly journals Islamic equities and COVID-19 pandemic: measuring Islamic stock indices correlation and volatility in period of crisis

2021 ◽  
Vol 29 (1) ◽  
pp. 50-66
Author(s):  
Shafiu Ibrahim Abdullahi
Keyword(s):  
Stock Market ◽  
Generalized Method Of Moments ◽  
Multivariate Garch ◽  
Content Type ◽  
Volatility Transmission ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Stock Indices ◽  
Cointegration Tests ◽  
Normal Correlation

PurposeThe purpose of the study is to measure cross-country stock market correlation and volatility transmission during the global coronavirus disease 2019 (COVID-19) pandemic. The paper traces trajectory of Islamic equity investments in order to get insights on the behavior of the markets during the crisis.Design/methodology/approachThe paper uses generalized method of moments (GMM), autoregressive distributed lag (ARDL) and multivariate GARCH (MGARCH) models for analysis of dynamic causality, stock market cointegration, correlation and volatility transmission between Islamic stock indices.FindingsThe result of normal correlation analysis on the share indices show the markets move together. The result of ARDL cointegration test shows the markets returns are cointegrated as a group. To further make sense of the data; the indices were grouped into four different categories, then cointegration tests were conducted. The results of the analysis show that the subgroups are cointegrated except the low COVID-19 subgroup. Based on MGARCH findings, the possibility of volatility transmission between markets during the crisis is high. The market returns indices show the usual herd mentality common during the period of crisis.Originality/valueUnlike other works in this area, this paper attempt to trace the trajectory of Islamic equity investment in order to get relevant insights and arrives at appropriate ways of responding to the crisis.

scholarly journals Bayesian semiparametric multivariate GARCH modeling

2013 ◽  
Vol 176 (1) ◽  
pp. 3-17 ◽  
Author(s):  
Mark J. Jensen ◽  
John M. Maheu
Keyword(s):  
Multivariate Garch ◽  
Bayesian Semiparametric ◽  
Garch Modeling

Volatility Transmission in U.K. Housing: A Multivariate GARCH Approach

2010 ◽  
Vol 16 (3) ◽  
pp. 241-248 ◽  
Author(s):  
William Miles
Keyword(s):  
Multivariate Garch ◽  
Volatility Transmission

Simultaneous Volatility Transmission and Spillover Effects

2010 ◽  
Vol 13 (01) ◽  
pp. 127-156 ◽  
Author(s):  
Gerard L. Gannon
Keyword(s):  
Futures Markets ◽  
Spillover Effects ◽  
The United States ◽  
Market Volatility ◽  
Multivariate Garch ◽  
Index Futures ◽  
Volatility Transmission ◽  
Volatility Models ◽  
Volatility Model ◽  
Intraday Data

Simultaneous volatility models are developed and shown to be separate from multivariate GARCH estimators. An example is provided that allows for simultaneous and unidirectional volatility and volume of trade effects. These effects are tested using intraday data from the Australian cash index and index futures markets. Overnight volatility spillover effects from the United States S&P500 index futures markets are tested using alternative estimates of this US market volatility. The simultaneous volatility model proves to be robust to alternative specifications of returns equations and to misspecification of the direction of volatility causality.

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