Multivariate Hyper-Rotated GARCH-BEKK

2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Manabu Asai ◽  
Michael McAleer
Keyword(s):  
Moving Average ◽  
Garch Model ◽  
Multivariate Garch ◽  
Regularity Conditions ◽  
Finite Sample ◽  
Arch Models ◽  
Vector Autoregressive ◽  
Alternative Representation ◽  
Multivariate Garch Model ◽  
Coefficient Vector

Abstract For large multivariate models of generalized autoregressive conditional heteroskedasticity (GARCH), it is important to reduce the number of parameters to cope with the ‘curse of dimensionality’. Recently, Laurent, Rombouts and Violante (2014 “Multivariate Rotated ARCH Models” Journal of Econometrics 179: 16–30) developed the rotated multivariate GARCH model, which focuses on the parameters for standardized variables. This paper extends the rotated multivariate GARCH model by considering a hyper-rotation, which uses a more flexible structure for the rotation matrix. The paper shows an alternative representation based on a random coefficient vector autoregressive and moving-average (VARMA) process, and provides the regularity conditions for the consistency and asymptotic normality of the quasi-maximum likelihood (QML) estimator for VARMA with hyper-rotated multivariate GARCH. The paper investigates the finite sample properties of the QML estimator for the new model. Empirical results for four exchange rate returns show the new specifications works satisfactory for reducing the number of parameters.

A full-factor multivariate GARCH model

2003 ◽  
Vol 6 (2) ◽  
pp. 312-334 ◽  
Author(s):  
I. D. Vrontos ◽  
P. Dellaportas ◽  
D. N. Politis
Keyword(s):  
Garch Model ◽  
Multivariate Garch ◽  
Multivariate Garch Model

scholarly journals Probabilistic Assessment of Monthly River Flow Discharge Using Copula And OSVR Approaches

2021 ◽  
Author(s):  
Mohammad Nazeri Tahroudi ◽  
Rasoul Mirabbasi ◽  
Yousef Ramezani ◽  
Farshad Ahmadi
Keyword(s):  
River Flow ◽  
Garch Model ◽  
Support Vector ◽  
Monthly Precipitation ◽  
Arch Models ◽  
Vector Autoregressive ◽  
Flow Discharge ◽  
Simulation Results ◽  
Hydrometric Station ◽  
Hydrology And Water Resources

Abstract Simulation of flow discharge based on monthly precipitation values as inputs is one of the important issues in hydrology and water resources studies, especially in areas where data with the shorter time scales are not available. In this study, the applicability of support vector regression (SVR) model optimized by Ant colony and Copula-GARCH algorithms was investigated and compared to simulate the flow discharge based on total monthly rainfall in Talezang Basin, Iran. Entropy theory was used to select a suitable meteorological station corresponding to a hydrometric station. The vector autoregressive model was also used as the base model in Copula-GARCH simulations. The correlation results of the studied paired variable confirmed the possibility of using copula-based models. The simulation results were evaluated using R2, Nash-Sutcliffe Efficiency (NSE) and root mean square error (RMSE) statistics. According to the 99% confidence intervals of the simulations, the accuracy of both models was confirmed. The simulation results showed that the Copula-GARCH model was more accurate than the optimized SVR (OSVR) model. Considering the 90% efficiency (NSE = 0.90) of Copula-GARCH approach, the results show a 36% improvement of RMSE statistics by Copula-GARCH model compared to OSVR model in simulating the flow discharge on a monthly scale. The results also showed that by combining nonlinear ARCH models with the copula-based simulations, the reliability of the simulation results increases, which was also confirmed using the violin plot. The results also showed an increase in the accuracy of the Copula-GARCH model at the minimum and maximum values of the data.

scholarly journals Modeling Exchange Rate and Nigerian Deposit Money Market Dynamics Using Trivariate form of Multivariate GARCH Model

2019 ◽  
pp. 1-18
Author(s):  
Deebom, Zorle Dum ◽  
Tuaneh, Godwin Lebari
Keyword(s):  
Exchange Rate ◽  
Garch Model ◽  
Money Market ◽  
Multivariate Garch ◽  
Market Dynamics ◽  
Volatility Clustering ◽  
Volatility Spillovers ◽  
Multivariate Garch Model ◽  
The Difference ◽  
Student’S T

The risks associated with exchange rate and money market indicators have drawn the attentions of econometricians, researchers, statisticians, and even investors in deposit money banks in Nigeria. The study targeted at modeling exchange rate and Nigerian deposit banks money market dynamics using trivariate form of multivariate GARCH model. Data for the period spanning from 1991 to 2017 on exchange rate (Naira/Dollar) and money market indicators (Maximum and prime lending rate) were sourced for from the central bank of Nigeria (CBN) online statistical database. The study specifically investigated; the dynamics of the variance and covariance of volatility returns between exchange rate and money market indicators in Nigeria were examine whether there exist a linkage in terms of returns and volatility transmission between exchange rate and money market indicators in Nigeria and compared the difference in Multivariate BEKK GARCH considering restrictive indefinite under the assumption of normality and that of student’s –t error distribution.  Preliminary time series checks were done on the data and the results revealed the present of volatility clustering. Results reveal the estimate of the maximum lag for exchange rate and money market indicators were 4 respectively. Also, the results confirmed that there were two co-integrating equations in the relationship between the returns on exchange rate and money market indicators.  The results of the diagonal MGARCH –BEKK estimation  confirmed  that diagonal MGARCH –BEKK in students’-t was  the best fitted and an appropriate model for modeling exchange rate and Nigerian deposit money market dynamics using trivariate form of multivariate GARCH model. Also, the study confirmed presence of two directional volatility spillovers between the two sets of variables.

scholarly journals Detecting Shocks in The Economic Development Dynamics of Selected Countries

2014 ◽  
Vol 13 (2) ◽  
pp. 120-133
Author(s):  
Anna Janiga-Ćmiel
Keyword(s):  
Estimation Method ◽  
Garch Model ◽  
Positive Definite ◽  
Multivariate Garch ◽  
Contagion Effect ◽  
Multivariate Models ◽  
The United Kingdom ◽  
Multivariate Garch Model ◽  
Polish Economy ◽  
The Impact

Abstract The paper examines the development of the Polish economy as well as the economies of selected countries in the period from 2001 to 2012. For that purpose, models based on the GDP growth in particular countries were built. A comparative analysis of the development of economies in the countries concerned (the United Kingdom, Belgium, Denmark, France, Poland, the Netherlands), based on a specially built full-factor multivariate GARCH model, is presented. The theory of the construction of a full-factor multivariate GARCH model and its estimation method are discussed. In the paper, a multivariate GARCH model where the covariance matrix is always positive, definite and the number of parameters is relatively small compared to other multivariate models is proposed. The causality of the impact that economies exert on one another is examined and the occurrence of the contagion effect is verified by means of the Forbes and Rigobon test.

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