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.

Dynamic and frequency connectedness across Islamic stock indexes, bonds, crude oil and gold

2019 ◽  
Vol 12 (3) ◽  
pp. 306-321 ◽  
Author(s):  
Nader Trabelsi
Keyword(s):  
Crude Oil ◽  
The United States ◽  
Asia Pacific ◽  
Volatility Spillover ◽  
Content Type ◽  
Time Frequency ◽  
Volatility Spillovers ◽  
Long Run ◽  
Portfolio Managers ◽  
Stock Indexes

Purpose This paper aims to investigate the connectedness of Islamic Stock Markets in five regional financial systems, namely, the United States, the United Kingdom, Europe (EU), GCC (Gulf Cooperation Council) and APAC (Asia-Pacific Countries), and across different asset classes (i.e. bonds, gold and crude oil). Design/methodology/approach This methodology is inspired by Diebold and Yilmaz (2012) and Barunlik and Krehlik (2017) for performing dynamic variance decomposition network and for studying time–frequency dynamics of connectedness at different frequencies. Findings Results show that the nature of connectedness over the past decade is time–frequency dynamics. The decomposition of the total volatility spillovers is mostly dominated by the long-run component. Furthermore, dominant regions are the largest contributors of spillover index, with the lowest contribution in the system coming from the GCC market. Results also reveal a slightly higher volatility spillover index of Islamic than conventional equity indexes. Finally, the system that encompasses commodities and Islamic finance instruments, generates the much lower volatility spillover. Originality/value The findings have significant implications for portfolio managers who are interested in being able to predict asset returns, as well as for policymakers who are concerned with market stability.

The Impact of Structural Breaks on Volatility Linkages between Asian Stock and Oil Futures Markets

2016 ◽  
Vol 24 (1) ◽  
pp. 31-64
Author(s):  
Sang Hoon Kang ◽  
Seong-Min Yoon
Keyword(s):  
Futures Markets ◽  
Structural Breaks ◽  
Global Financial Crisis ◽  
Garch Model ◽  
Time Varying ◽  
Oil Futures ◽  
Volatility Spillovers ◽  
Icss Algorithm ◽  
The Global Financial Crisis ◽  
The Impact

This paper investigates the impact of structural breaks on volatility spillovers between Asian stock markets (China, Hong Kong, India, Indonesia, Japan, Korea, Singapore, and Taiwan) and the oil futures market. To this end, we apply the bivariate DCC-GARCH model to weekly spot indices during the period 1998-2015. The results reveal significant volatility transmission for the pairs between the Asian stock and oil futures markets. Moreover, we find a significant variability in the time-varying conditional correlations between the considered markets during both bullish and bearish markets, particularly from early 2007 to the summer of 2008. Using the modified ICSS algorithm, we find several sudden changes in these markets with a common break date centred on September 15, 2008. This date corresponds to the collapse of Lehman Brothers which is considered as our breakpoint to define the global financial crisis. Also, we analyse the optimal portfolio weights and time-varying hedge ratios based on the estimates of the multivariate DCC-GARCH model. The results emphasize the importance of overweighting optimal portfolios between Asian stock and the oil futures markets.

scholarly journals NEGATIVE VOLATILITY SPILLOVERS IN THE UNRESTRICTED ECCC-GARCH MODEL

2009 ◽  
Vol 26 (3) ◽  
pp. 838-862 ◽  
Author(s):  
Christian Conrad ◽  
Menelaos Karanasos
Keyword(s):  
Covariance Matrix ◽  
Garch Model ◽  
Positive Definiteness ◽  
Time Varying ◽  
Conditional Covariance ◽  
Conditional Correlation ◽  
Economic Theories ◽  
Model Builder ◽  
Volatility Spillovers ◽  
Volatility Feedback

This paper considers a formulation of the extended constant or time-varying conditional correlation GARCH model that allows for volatility feedback of either the positive or negative sign. In the previous literature, negative volatility spillovers were ruled out by the assumption that all the parameters of the model are nonnegative, which is a sufficient condition for ensuring the positive definiteness of the conditional covariance matrix. In order to allow for negative feedback, we show that the positive definiteness of the conditional covariance matrix can be guaranteed even if some of the parameters are negative. Thus, we extend the results of Nelson and Cao (1992) and Tsai and Chan (2008) to a multivariate setting. For the bivariate case of order one, we look into the consequences of adopting these less severe restrictions and find that the flexibility of the process is substantially increased. Our results are helpful for the model-builder, who can consider the unrestricted formulation as a tool for testing various economic theories.

scholarly journals Estimating Time-Varying Long-Run Growth Rate of Russian GDP in the ARX Model with Oil Prices

2020 ◽  
Vol 15 (1) ◽  
pp. 40-63 ◽  
Keyword(s):  
Growth Rate ◽  
Growth Rates ◽  
Oil Prices ◽  
Likelihood Method ◽  
Time Varying ◽  
Arx Model ◽  
Long Run ◽  
Unobserved Components Model ◽  
The Impact ◽  
Trend Growth

The paper estimates the path of trend growth rates for Russian GDP based on an autoregressive model with exogenous variables and with a time-varying parameter of trend growth, which, by assumption, is described by a random walk process. In conditions of a high dependence of the Russian economy on commodity exports, terms of trade are used as a control exogenous variable for GDP dynamics. For the purpose of econometric estimation, the ARX model is presented as an unobserved components model and estimated using the maximum likelihood method with the Kalman filter applied. It is shown that in the first half of the 2000s the trend growth rate was at 4%, which can be interpreted as recovery growth after a transformational recession. The higher growth rates actually achieved during this period are explained by the intensive growth of world oil prices. Later, the potential for recovery growth was exhausted, and after the crisis of 2008 the rates of trend growth were remaining at the level of 2% per year for a long period of time. However, following the 2014 crisis, trend growth rates began to decline steadily, and had reached about 1% per year by the beginning of 2019, which can be interpreted as the impact of sanctions and geopolitical uncertainty on the economic development of the Russian Federation. The results of an econometric analysis of the model on household consumption and investment data also suggest that the trend growth rate is approximately 1% per year at present.

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 Testing the conditional correlations and volatility spillovers between US and ASEAN Islamic stock markets: A Multivariate GARCH Analysis

2015 ◽  
Vol 2 (1) ◽  
pp. 029
Author(s):  
Muhammad Rizky Prima Sakti
Keyword(s):  
Stock Markets ◽  
Multivariate Garch ◽  
Garch Models ◽  
Time Varying ◽  
Foreign Investors ◽  
Volatility Spillovers ◽  
The Us ◽  
Conditional Correlations ◽  
Multivariate Garch Models ◽  
Empirical Design

This study examines the conditional correlations and volatility spillovers between the US and ASEAN Islamic stock markets. The empirical design uses MSCI (Morgan Stanley Capital International) Islamic indexes as it adopted stringent restriction to include companies in sharia list. By using a three multivariate GARCH models (BEKK, diagonal VECH, and CCC model), we find evidence of returns and volatility spillovers from the US to the ASEAN Islamic stock markets. However, as the estimated time-varying conditional correlations and volatilities indicate there is still a room for diversification benefits, particularly in the single markets. The Islamic MSCI of Thailand, Indonesia, and Singapore are less correlate to the US MSCI Islamic index. The implication is that foreign investors may benefit from the reduction of risk by adding the Islamic stocks in those countries.

scholarly journals Modelling time varying volatility spillovers and conditional correlations across commodity metal futures

2018 ◽  
Vol 57 ◽  
pp. 246-256 ◽  
Author(s):  
Menelaos Karanasos ◽  
Faek Menla Ali ◽  
Zannis Margaronis ◽  
Rajat Nath
Keyword(s):  
Time Varying ◽  
Volatility Spillovers ◽  
Conditional Correlations

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.

Sign in / Sign up

Export Citation Format

Share Document