scholarly journals Volatility spillover and contagion effects between EURODOLLAR future and zero coupons markets: Evidence from Italy

2020 ◽  
Vol 17 (2) ◽  
pp. 67-88
Author(s):  
Konstantinos Tsiaras
Keyword(s):  
Futures Market ◽  
Time Varying ◽  
Volatility Spillover ◽  
Conditional Correlation ◽  
Dynamic Conditional Correlation ◽  
Contagion Effects ◽  
Eurodollar Futures ◽  
Bivariate Models ◽  
Investigation Period ◽  
Derivative Markets

This paper examines the time-varying conditional correlations between the Eurodollar futures market and the zero coupons of Banca Fideuram. We apply a bivariate dynamic conditional correlation (DCC) GARCH model in order to capture potential contagion effects between the markets for the period 2005-2017. Empirical results reveal contagion during the under-investigation period regarding the twenty-one bivariate models, showing that the Eurodollar futures market has a major impact on the zero coupons of Banca Fideuram. Findings have crucial implications for policymakers who provide regulations for the above-mentioned derivative markets.

scholarly journals Contagion in Futures FOREX Markets for the Post- Global Financial Crisis: A Multivariate FIGARCHcDCC Approach

2020 ◽  
Vol 4 (1) ◽  
pp. 1-1 ◽  
Author(s):  
Konstantinos Tsiaras
Keyword(s):  
Financial Crisis ◽  
Global Financial Crisis ◽  
Jel Classification ◽  
Time Varying ◽  
Conditional Correlation ◽  
Market Returns ◽  
Dynamic Conditional Correlation ◽  
Contagion Effects ◽  
Investigation Period ◽  
Conditional Correlations

This paper seeks to investigate the time-varying conditional correlations to the futures FOREX market returns. We employ a dynamic conditional correlation (DCC) Generalized ARCH (GARCH) model to find potential contagion effects among the markets. The under investigation period is 2014-2019. We focus on four major futures FOREX markets namely JPY/USD, KRW/USD, EUR/USD and INR/USD. The empirical results show an increase in conditional correlation or contagion for all the pairsof future FOREX markets. Based on the dynamic conditional correlations, KRW/USD seems to be the safest futures FOREX market. The results are of interest to policymakers who provide regulations for the futures FOREX markets. JEL Classification Codes: C58, C61, G11, G15

VOLATILITY SPILLOVER BETWEEN SPOT AND FUTURES MARKET OF HIGHLY TRADED COMMODITIES IN INDIA: The DCC-GARCH Approach

2018 ◽  
Vol 05 (09) ◽  
pp. 34-49
Author(s):  
Ruchika Kaura ◽  
Nawal Kishor ◽  
Namita Rajput
Keyword(s):  
Spillover Effect ◽  
Spillover Effects ◽  
Futures Market ◽  
Market Volatility ◽  
Multivariate Garch ◽  
Management Policy ◽  
Commodity Market ◽  
Time Varying ◽  
Volatility Spillover ◽  
Conditional Correlation

This study intends to examine the volatility spillover effects and measure the time-varying correlations between futures and spot prices of thirteen highly traded commodities traded on Multi Commodity Exchange (MCX) of India. The research uses Exponential GARCH proposed by Nelson (1991) to explore the direction and magnitude of spillover effects between futures and spot commodity market and employs Dynamic Conditional Correlation (DCC) GARCH proposed by Engle (2002) to demonstrate the time varying conditional correlation between heteroscedastic coefficients of the futures and spot markets. Empirical results show that significant and asymmetric bi-directional volatility spillover effects exist in case of most of the selected commodities, even though, the magnitude of volatility spillover is found larger in the direction from futures market to spot market. The dynamic correlation between the conditional variance of the spot and future markets is found to be significant in case of all the commodities except Silver and Copper. It proves that significant volatility spillover effect is present between spot and futures markets of selected commodities. Understanding of volatility transmission and interrelationship between spot and futures commodity market will help investors make right investment decisions, portfolio optimization and financial risk management. Policy makers and regulators can use this knowledge in planning and implementing appropriate regulatory framework. Much of the earlier research focuses on inter market volatility spillover taking into consideration two or more different financial markets. This study focuses on intra market volatility spillover by studying the interactions of spot-futures prices of commodities. Also, considering the time-varying nature of conditional correlations, this study employs EGARCH and multivariate GARCH (DCC) to capture the volatility spillover effects instead of univariate GARCH or standard linear VAR models.

scholarly journals The relationship between Google search interest for pulmonary symptoms and COVID-19 cases using dynamic conditional correlation analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Halit Cinarka ◽  
Mehmet Atilla Uysal ◽  
Atilla Cifter ◽  
Elif Yelda Niksarlioglu ◽  
Aslı Çarkoğlu
Keyword(s):  
Case Reports ◽  
Time Varying ◽  
Conditional Correlation ◽  
Web Based ◽  
Specific Symptom ◽  
Sliding Windows ◽  
Dynamic Conditional Correlation ◽  
The United Kingdom ◽  
Correlation Models ◽  
Google Search

AbstractThis study aims to evaluate the monitoring and predictive value of web-based symptoms (fever, cough, dyspnea) searches for COVID-19 spread. Daily search interests from Turkey, Italy, Spain, France, and the United Kingdom were obtained from Google Trends (GT) between January 1, 2020, and August 31, 2020. In addition to conventional correlational models, we studied the time-varying correlation between GT search and new case reports; we used dynamic conditional correlation (DCC) and sliding windows correlation models. We found time-varying correlations between pulmonary symptoms on GT and new cases to be significant. The DCC model proved more powerful than the sliding windows correlation model. This model also provided better at time-varying correlations (r ≥ 0.90) during the first wave of the pandemic. We used a root means square error (RMSE) approach to attain symptom-specific shift days and showed that pulmonary symptom searches on GT should be shifted separately. Web-based search interest for pulmonary symptoms of COVID-19 is a reliable predictor of later reported cases for the first wave of the COVID-19 pandemic. Illness-specific symptom search interest on GT can be used to alert the healthcare system to prepare and allocate resources needed ahead of time.

scholarly journals Empirical Evidence on Time-Varying Hedging Effectiveness of Emissions Allowances under Departures from the Cost-of-Carry Theory

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Kai Chang
Keyword(s):  
Futures Market ◽  
Time Varying ◽  
Conditional Volatility ◽  
Conditional Correlation ◽  
Spot Prices ◽  
Market Participants ◽  
Hedging Effectiveness ◽  
Hedge Ratios ◽  
Cost Of Carry ◽  
The Cost

Under departures from the cost-of-carry theory, traded spot prices and conditional volatility disturbed from futures market have significant impacts on futures price of emissions allowances, and then we propose time-varying hedge ratios and hedging effectiveness estimation using ECM-GARCH model. Our empirical results show that conditional variance, conditional covariance, and their correlation between between spot and futures prices exhibit time-varying trends. Conditional volatility of spot prices, conditional volatility disturbed from futures market, and conditional correlation of market noises implied from spot and futures markets have significant effects on time-varying hedge ratios and hedging effectiveness. In the immature emissions allowances market, market participants optimize portfolio sizes between spot and futures assets using historical market information and then achieve higher risk reduction of assets portfolio revenues; accordingly, we can obtain better hedging effectiveness through time-varying hedge ratios with departures from the cost-of-carry theory.

Dynamic Co-movement and Volatility Spillover Effect Between Sukuk and Conventional Bonds:A Comparison Study Between ASEAN and GCC

2021 ◽  
pp. 097215092110262
Author(s):  
Nevi Danila ◽  
Noor Azlinna Azizan ◽  
Eddy Suprihadi ◽  
Bunyamin Bunyamin
Keyword(s):  
Spillover Effect ◽  
Global Market ◽  
Bond Markets ◽  
Volatility Spillover ◽  
Conditional Correlation ◽  
Kingdom Of Saudi Arabia ◽  
Macroeconomic Factors ◽  
Dynamic Conditional Correlation ◽  
Dynamic Correlation ◽  
Volatility Spillovers

Sukuk and conventional bonds gain their popularity in the global market. Hence, an observation of the dynamic correlation and transmission of volatility between these two instruments is relevant. This article investigates the volatility spillover of sukuk and conventional bond markets by using GARCH-BEKK model. Then, we measure the dynamics of the co-movement of both markets by using GARCH-DCC model, and finally, we examine the macroeconomic factors that determine the dynamic conditional correlation between sukuk and conventional bonds in two Association of Southeast Asian Nations (ASEAN) markets (i.e., Indonesia and Malaysia) and four Gulf Cooperation Council (GCC) markets (i.e., Kingdom of Saudi Arabia, UAE, Qatar and Oman). The data reveal unidirectional and bidirectional volatility spillovers of sukuk and bond indices. The results also show strong evidence of dynamic conditional correlation for all markets. On the basis of the BEKK and dynamic conditional correlation (DCC) results, we infer that bonds and sukuk in ASEAN and GCC markets show the efficiency of the markets, which do not offer any diversification benefits to investors for having both instruments in their portfolios. As regards portfolio diversification strategies, investors must pay attention to the co-movements and spillover of both markets accordingly. Finally, only Oman market is influenced by all macroeconomic variables.

scholarly journals Volatility Spillover Effects among Securities Exchanges in East Africa

2019 ◽  
Vol 11 (10) ◽  
pp. 32
Author(s):  
Nelson Yunvirusaba ◽  
Jane Aduda ◽  
Ananda Kube
Keyword(s):  
East Africa ◽  
Spillover Effects ◽  
Dar Es Salaam ◽  
Volatility Spillover ◽  
Conditional Correlation ◽  
Vector Autoregressive ◽  
Dynamic Conditional Correlation ◽  
Long Run ◽  
Integration Test ◽  
Securities Exchanges

This paper aims at examining volatility spillover effects among the returns of three out of the four securities exchanges in East Africa. Vector autoregressive model was used to model return series evolution; and, Johansen co-integration test, was further applied to examine any possibilities of co-integration. Dynamic conditional correlation model was then employed to explore the dynamics of conditional variances. Daily closing all share indices data spanning the period 29 February 2008 to 28 February 2018 was used. The results of the study revealed that, there is bidirectional causality between Nairobi securities exchange and Dar es salaam securities exchange; unidirectional effect between Nairobi securities exchange and Uganda securities exchange; while between Dar es salaam securities exchange and Uganda securities exchange, there is a unidirectional effect. The study findings also indicate evidence of no co-integration, thus, no long-run relationship among the exchanges. The dynamic conditional correlation proved to be the most parsimonious model whose results indicated evidence of volatility spillover among the securities exchanges.

scholarly journals Volatility Spillover and Time-Varying Conditional Correlation Between DDGS, Corn, and Soybean Meal Markets

2017 ◽  
Vol 46 (3) ◽  
pp. 529-554 ◽  
Author(s):  
Xiaoli L. Etienne ◽  
Andrés Trujillo-Barrera ◽  
Linwood A. Hoffman
Keyword(s):  
Ethanol Production ◽  
Soybean Meal ◽  
Time Varying ◽  
Volatility Spillover ◽  
Conditional Correlation ◽  
Volatility Spillovers ◽  
Long Run ◽  
Conditional Correlations ◽  
The Impact

We find distiller's dried grains with solubles (DDGS) prices to be positively correlated with both corn and soybean meal prices in the long run. However, neither corn nor soybean meal prices respond to deviations from this long-run relationship. We also identify strong time-varying dynamic conditional correlations between the markets, with the correlation between DDGS and corn strengthened after the expansion of ethanol production. There also appear to exist significant volatility spillovers from both the corn and soybean meal markets to the DDGS market, with the impact from corn shocks much larger compared to soybean meal shocks.

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