Tekle Bobo (11 results)
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- Softcover
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- Softcover
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Literature Review from the year 2020 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, , language: English, abstract: This paper is a review to the GARCH family's models. Since the seminal paper of Engle from 1982…, much advancement has been made in understanding GARCH models and their multivariate extensions. In MGARCH models parsimonious models should be used to overcome the difficulty of estimating the VEC model ensuring MGARCH modeling is to provide a realistic and parsimonious specification of the variance matrix ensuring its positivity.BEKK models are flexible but require too many parameters for multiple time series of more than four elements. BEKK models are much more parsimonious but very restrictive for the cross-dynamics. They are not suitable if volatility transmission is the object of interest, but they usually do a good job in representing the dynamics of variances and covariance. DCC models allow for different persistence between variances and correlations, but impose common persistence in the latter (although this may be relaxed) Student's t distribution assumption is more proper under negative skewness and high kurtosis of return series.Understanding and predicting the temporal dependence in the second-order moments of asset returns is important for many issues in financial econometrics. It is now widely accepted that financial volatilities move together over time across assets and markets. Recognizing this feature through a multivariate modeling framework leads to more relevant empirical models than working with separate univariate models. From a financial point of view, it opens the door to better decision tools in various areas, such as asset pricing, portfolio selection, option pricing, and hedging and risk management. Indeed, unlike at the beginning of the 1990s, several institutions have now developed the necessary skills to use the econometric theory in a financial perspective.
- Softcover
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Taschenbuch. Condition: Neu. Multivariate GARCH models. The time varying variance-covariance for the exchange rate | Tekle Bobo | Taschenbuch | Englisch | 2021 | GRIN Verlag | EAN 9783346288912 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: p…reigu.
- Softcover
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Master's Thesis from the year 2020 in the subject Economics - Statistics and Methods, grade: 24, Haramaya University, language: English, abstract: Application of GARCH type model is a key for modeling and forecasting volatility for high frequency d…ata such as daily commodity price. Following the same framework, the objective of the present study is to apply the multiplicative GARCH-MIDAS model for daily exported coffee price as proxy of daily total coffee price of Ethiopia over the period of 1-1-2008 to 7-17-2018 with the purpose of fitting and forecasting coffee price returns volatility. The GARCH-MIDAS model decomposes the conditional variance as short-term component of GARCH (1,1) process, and long-term component, with monthly frequencies of macroeconomic variables. In this study exchange rate (nominal exchange rate), inflation rate (general inflation), interest rate (lending interest rate), fuel oil price (price of imported petroleum and petroleum production), total consumption and money supply (broad money) macroeconomic variables were employed through MIDAS specification using beta-weighting scheme to analyze impact of the variables on the long-term volatility component. For fitted ARMA (1,1) of coffee price return ARCH effect test on the residual from the mean model revealed the existence of time varying conditional variance for the selected mean model. A conditional variance model GARCH (1,1) was selected and used to model the conditional variance of coffee price return with Quasi Maximum Likelihood along with Bayesian estimation methods and both estimation procedures indicated the persistence of conditional variance observed even for small sample under Bayesian estimation framework. Asymmetry test show the insignificance of the asymmetric term, while Lundbergh and Terasvirta Lagrange Multiplier and the Li-Mak portmanteau test for the residual of GARCH model show the existence of time varying unconditional variance and made call for GARCH-MIDAS model. From the result of estimated GARCH-MIDAS model exchange rate and inflation rate were found to be the best drivers of coffee price volatility in Ethiopia and used for in and out of sample forecast. Finally, the Mean Absolute Error Root Mean Square Error and Diebold Mariano test were used for evaluating and comparing the forecasting ability of GARCH-MIDAS component model against standard GARCH (1,1) model which indicated that, including exchange rate and inflation rate make efficient forecasting of coffee price volatility in Ethiopia.
- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: Neu. Macroeconomic Determinants of the Coffee Price Volatility in Ethiopia. Application of the Garch-Midas Model | Tekle Bobo (u. a.) | Taschenbuch | Englisch | 2020 | GRIN Verlag | EAN 9783346277275 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[…at]preigu[dot]de | Anbieter: preigu.
- Softcover
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Literature Review from the year 2020 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, , language: English, abstract: This paper is a review to the GARCH family's models. Since the seminal paper of… Engle from 1982, much advancement has been made in understanding GARCH models and their multivariate extensions. In MGARCH models parsimonious models should be used to overcome the difficulty of estimating the VEC model ensuring MGARCH modeling is to provide a realistic and parsimonious specification of the variance matrix ensuring its positivity.BEKK models are flexible but require too many parameters for multiple time series of more than four elements. BEKK models are much more parsimonious but very restrictive for the cross-dynamics. They are not suitable if volatility transmission is the object of interest, but they usually do a good job in representing the dynamics of variances and covariance. DCC models allow for different persistence between variances and correlations, but impose common persistence in the latter (although this may be relaxed) Student's t distribution assumption is more proper under negative skewness and high kurtosis of return series.Understanding and predicting the temporal dependence in the second-order moments of asset returns is important for many issues in financial econometrics. It is now widely accepted that financial volatilities move together over time across assets and markets. Recognizing this feature through a multivariate modeling framework leads to more relevant empirical models than working with separate univariate models. From a financial point of view, it opens the door to better decision tools in various areas, such as asset pricing, portfolio selection, option pricing, and hedging and risk management. Indeed, unlike at the beginning of the 1990s, several institutions have now developed the necessary skills to use the econometric theory in a financial perspective. 36 pp. Englisch.
- Softcover
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Master's Thesis from the year 2020 in the subject Economics - Statistics and Methods, grade: 24, Haramaya University, language: English, abstract: Application of GARCH type model is a key for modeling and forecasting volatility for…high frequency data such as daily commodity price. Following the same framework, the objective of the present study is to apply the multiplicative GARCH-MIDAS model for daily exported coffee price as proxy of daily total coffee price of Ethiopia over the period of 1-1-2008 to 7-17-2018 with the purpose of fitting and forecasting coffee price returns volatility. The GARCH-MIDAS model decomposes the conditional variance as short-term component of GARCH (1,1) process, and long-term component, with monthly frequencies of macroeconomic variables. In this study exchange rate (nominal exchange rate), inflation rate (general inflation), interest rate (lending interest rate), fuel oil price (price of imported petroleum and petroleum production), total consumption and money supply (broad money) macroeconomic variables were employed through MIDAS specification using beta-weighting scheme to analyze impact of the variables on the long-term volatility component. For fitted ARMA (1,1) of coffee price return ARCH effect test on the residual from the mean model revealed the existence of time varying conditional variance for the selected mean model. A conditional variance model GARCH (1,1) was selected and used to model the conditional variance of coffee price return with Quasi Maximum Likelihood along with Bayesian estimation methods and both estimation procedures indicated the persistence of conditional variance observed even for small sample under Bayesian estimation framework. Asymmetry test show the insignificance of the asymmetric term, while Lundbergh and Terasvirta Lagrange Multiplier and the Li-Mak portmanteau test for the residual of GARCH model show the existence of time varying unconditional variance and made call for GARCH-MIDAS model. From the result of estimated GARCH-MIDAS model exchange rate and inflation rate were found to be the best drivers of coffee price volatility in Ethiopia and used for in and out of sample forecast. Finally, the Mean Absolute Error Root Mean Square Error and Diebold Mariano test were used for evaluating and comparing the forecasting ability of GARCH-MIDAS component model against standard GARCH (1,1) model which indicated that, including exchange rate and inflation rate make efficient forecasting of coffee price volatility in Ethiopia. 100 pp. Englisch.
- Softcover
- Print on Demand
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Literature Review from the year 2020 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, , language: English, abstract: This paper is a review to the GARCH family¿s models. Since the seminal paper of Eng…le from 1982, much advancement has been made in understanding GARCH models and their multivariate extensions. In MGARCH models parsimonious models should be used to overcome the difficulty of estimating the VEC model ensuring MGARCH modeling is to provide a realistic and parsimonious specification of the variance matrix ensuring its positivity. BEKK models are flexible but require too many parameters for multiple time series of more than four elements. BEKK models are much more parsimonious but very restrictive for the cross-dynamics. They are not suitable if volatility transmission is the object of interest, but they usually do a good job in representing the dynamics of variances and covariance. DCC models allow for different persistence between variances and correlations, but impose common persistence in the latter (although this may be relaxed) Student¿s t distribution assumption is more proper under negative skewness and high kurtosis of return series. Understanding and predicting the temporal dependence in the second-order moments of asset returns is important for many issues in financial econometrics. It is now widely accepted that financial volatilities move together over time across assets and markets. Recognizing this feature through a multivariate modeling framework leads to more relevant empirical models than working with separate univariate models. From a financial point of view, it opens the door to better decision tools in various areas, such as asset pricing, portfolio selection, option pricing, and hedging and risk management. Indeed, unlike at the beginning of the 1990s, several institutions have now developed the necessary skills to use the econometric theory in a financial perspective. 36 pp. Englisch.
- Softcover
- Print on Demand
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
Contact seller5-star sellerCondition: New
US$ 56.40
US$ 68.52 shippingShips from Germany to U.S.A.Quantity: 1 available
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Master's Thesis from the year 2020 in the subject Economics - Statistics and Methods, grade: 24, Haramaya University, language: English, abstract: Application of GARCH type model is a key for modeling and forecasting volatility for high… frequency data such as daily commodity price. Following the same framework, the objective of the present study is to apply the multiplicative GARCH-MIDAS model for daily exported coffee price as proxy of daily total coffee price of Ethiopia over the period of 1-1-2008 to 7-17-2018 with the purpose of fitting and forecasting coffee price returns volatility. The GARCH-MIDAS model decomposes the conditional variance as short-term component of GARCH (1,1) process, and long-term component, with monthly frequencies of macroeconomic variables. In this study exchange rate (nominal exchange rate), inflation rate (general inflation), interest rate (lending interest rate), fuel oil price (price of imported petroleum and petroleum production), total consumption and money supply (broad money) macroeconomic variables were employed through MIDAS specification using beta-weighting scheme to analyze impact of the variables on the long-term volatility component. For fitted ARMA (1,1) of coffee price return ARCH effect test on the residual from the mean model revealed the existence of time varying conditional variance for the selected mean model. A conditional variance model GARCH (1,1) was selected and used to model the conditional variance of coffee price return with Quasi Maximum Likelihood along with Bayesian estimation methods and both estimation procedures indicated the persistence of conditional variance observed even for small sample under Bayesian estimation framework. Asymmetry test show the insignificance of the asymmetric term, while Lundbergh and Terasvirta Lagrange Multiplier and the Li-Mak portmanteau test for the residual of GARCH model show the existence of time varying unconditional variance and made call for GARCH-MIDAS model. From the result of estimated GARCH-MIDAS model exchange rate and inflation rate were found to be the best drivers of coffee price volatility in Ethiopia and used for in and out of sample forecast. Finally, the Mean Absolute Error Root Mean Square Error and Diebold Mariano test were used for evaluating and comparing the forecasting ability of GARCH-MIDAS component model against standard GARCH (1,1) model which indicated that, including exchange rate and inflation rate make efficient forecasting of coffee price volatility in Ethiopia. 100 pp. Englisch.
