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.

THE DEMAND FOR LIQUID ASSETS: EVIDENCE FROM THE MINFLEX LAURENT DEMAND SYSTEM WITH CONDITIONALLY HETEROSKEDASTIC ERRORS

2018 ◽  
Vol 23 (07) ◽  
pp. 2941-2958
Author(s):  
Dongfeng Chang ◽  
Apostolos Serletis
Keyword(s):  
United States ◽  
Covariance Matrix ◽  
Financial Econometrics ◽  
The United States ◽  
Demand System ◽  
Demand Systems ◽  
Time Varying ◽  
Conditional Covariance ◽  
Demand For Money ◽  
Monetary Assets

We investigate the demand for money and the degree of substitutability among monetary assets in the United States using the generalized Leontief and the Minflex Laurent (ML) models as suggested by Serletis and Shahmoradi (2007). In doing so, we merge the demand systems literature with the recent financial econometrics literature, relaxing the homoskedasticity assumption and instead assuming that the covariance matrix of the errors of flexible demand systems is time-varying. We also pay explicit attention to theoretical regularity, treating the curvature property as a maintained hypothesis. Our findings indicate that only the curvature constrained ML model with a Baba, Engle, Kraft, and Kroner (BEKK) specification for the conditional covariance matrix is able to generate inference consistent with theoretical regularity.

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 High-Dimensional Conditional Covariance Matrices Estimation Using a Factor-GARCH Model

Symmetry ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 158
Author(s):  
Xiaoling Li ◽  
Xingfa Zhang ◽  
Yuan Li
Keyword(s):  
Covariance Matrix ◽  
Factor Model ◽  
Asymptotic Properties ◽  
Garch Model ◽  
Likelihood Estimation ◽  
Least Square ◽  
High Dimensional ◽  
Conditional Covariance ◽  
Financial Application ◽  
Quasi Maximum Likelihood

Estimation of a conditional covariance matrix is an interesting and important research topic in statistics and econometrics. However, modelling ultra-high dimensional dynamic (conditional) covariance structures is known to suffer from the curse of dimensionality or the problem of singularity. To partially solve this problem, this paper establishes a model by combining the ideas of a factor model and a symmetric GARCH model to describe the dynamics of a high-dimensional conditional covariance matrix. Quasi maximum likelihood estimation (QMLE) and least square estimation (LSE) methods are used to estimate the parameters in the model, and the plug-in method is introduced to obtain the estimation of conditional covariance matrix. Asymptotic properties are established for the proposed method, and simulation studies are given to demonstrate its performance. A financial application is presented to support the methodology.

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.

Portfolio selection: shrinking the time-varying inverse conditional covariance matrix

2018 ◽  
Vol 61 (6) ◽  
pp. 2583-2604 ◽  
Author(s):  
Ruili Sun ◽  
Tiefeng Ma ◽  
Shuangzhe Liu
Keyword(s):  
Covariance Matrix ◽  
Portfolio Selection ◽  
Time Varying ◽  
Conditional Covariance

scholarly journals A suggestion for constructing a large time-varying conditional covariance matrix

2017 ◽  
Vol 156 ◽  
pp. 110-113 ◽  
Author(s):  
Heather D. Gibson ◽  
Stephen G. Hall ◽  
George S. Tavlas
Keyword(s):  
Covariance Matrix ◽  
Large Time ◽  
Time Varying ◽  
Conditional Covariance
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