This document summarizes a study that analyzed volatility in Ghana's GDP growth rate using GARCH models. The study found that GDP volatility exhibited characteristics like clustering and leverage effects. A GARCH(1,1) model provided a reasonably good fit to quarterly GDP data. Volatility and leverage effects were found to have significantly increased. The best fitting models for GDP volatility were ARIMA(1,1,1)(0,0,1)12 and ARIMA(1,1,2)(0,0,1)12 models.
The document compares 11 time series models for fitting daily stock return data from the KLCI before and after the 1997 Asian financial crisis using two methods: 1) ranking models based on log likelihood, SBC, and AIC values, and 2) principal component analysis of these criteria. For the pre-crisis period, both methods identify GARCH(1,2) as the best fitting model and ARCH(1) as the worst, but disagree on intermediate models. PCA avoids information loss from ranking and better classifies models by performance level.
A Primer on Cointegration: Application to Nigerian Gross Domestic Product and...IOSR Journals
This document examines the relationship between gross domestic product (GDP) and exports (EXP) in Nigeria from 1970 to 2007 using cointegration analysis. Autocorrelation tests show that GDP and EXP are both non-stationary. Applying the Augmented Engle-Granger method reveals that regressing GDP on EXP produces a cointegrating relationship, not a spurious one. An error correction model indicates that while GDP and EXP have a long-term equilibrium relationship, GDP does not fully adjust to changes in EXP in the short run.
Nonlinear Extension of Asymmetric Garch Model within Neural Network Framework csandit
The importance of volatility for all market partici
pants has led to the development and
application of various econometric models. The most
popular models in modelling volatility are
GARCH type models because they can account excess k
urtosis and asymmetric effects of
financial time series. Since standard GARCH(1,1) mo
del usually indicate high persistence in the
conditional variance, the empirical researches turn
ed to GJR-GARCH model and reveal its
superiority in fitting the asymmetric heteroscedast
icity in the data. In order to capture both
asymmetry and nonlinearity in data, the goal of thi
s paper is to develop a parsimonious NN
model as an extension to GJR-GARCH model and to det
ermine if GJR-GARCH-NN outperforms
the GJR-GARCH model.
COMPARING NET PROFIT FORECASTS OF INDIAN BANKS USING OLS AND GARCH 1,1 FRAMEWORKSCHOLEDGE R&D CENTER
In the present paper the Bi-variate Ordinary Least Square (OLS) and Generalized autoregressive conditional heteroskedasicity (GARCH 1, 1) model are applied to gather the fitted Net –Profit series of Two nationalized banks viz, State Bank of India SBI (being a leader) and ING Vysya bank (not a leader) in the Indian Banking sector. It is evident that OLS is non-parameterized method while QMLE or QML is a parameterized technique of coefficients estimation. The robustness must therefore need to see with respect to the data in consideration. The whole approach is to measure how both the models provide Earning forecasts and to analyze the behavior of regression coefficients. Also, the second objective could be to see how “Leader” bank earnings estimation process differs from the non-leader bank in the Indian banking setup. The results are clearly explaining differences in two banks in terms of their coefficient values, residual state and R-squared values.
Analysis of Two-Echelon Inventory System with Two Suppliersinventionjournals
Inventories exist throughout the supply chain in various form for various reasons. Since carrying these inventories can cost anywhere from 20-40 % of their value a year, managing them in a scientific manner to maintain minimal levels makes economic sense. This paper presents a continuous review two echelon inventory system. The operating policy at the lower echelon is (s, S) that is whenever the inventory level traps to s on order for Q = (S-s) items is placed, the ordered items are received after a random time which is distributed as exponential. We assume that the demands accruing during the stock-out period are lost. The retailer replenishes their stock from the regular supplier which adopts (0,M) policy, M = n1Q. When the regular supplier stock is empty the replacement of retailer stock made by the outside supplier who adopts (0, N) policy N = n2Q. The joint probability disruption of the inventory levels of retailer, regular supplier and the outside supplier are obtained in the steady state case. Various system performance measures are derived and the long run total expected inventory cost rate is calculated. Several instances of a numerical examples, which provide insight into the behaviour of the system are presented.
Applications Residual Control Charts Based on Variable LimitsIJERA Editor
The main purpose of this paper is to verify the stability of a productive process in the presence of the effects of autocorrelation and volatility, in order to capture these characteristics by a joint forecast model which produces residuals that are evaluated by a control chart based on variable control limits. The methodology employed will be the joint estimation of the residuals by ARIMA – ARCH models and the conditional standard deviation from residuals to establish the chart control limits. The joint AR (1)-ARCH (1) model shows that an appropriate forecasting model brings a great contribution to the performance of residual control charts in monitoring the stability of industrial variables using just one chart to monitor mean and variance together.
The document compares 11 time series models for fitting daily stock return data from the KLCI before and after the 1997 Asian financial crisis using two methods: 1) ranking models based on log likelihood, SBC, and AIC values, and 2) principal component analysis of these criteria. For the pre-crisis period, both methods identify GARCH(1,2) as the best fitting model and ARCH(1) as the worst, but disagree on intermediate models. PCA avoids information loss from ranking and better classifies models by performance level.
A Primer on Cointegration: Application to Nigerian Gross Domestic Product and...IOSR Journals
This document examines the relationship between gross domestic product (GDP) and exports (EXP) in Nigeria from 1970 to 2007 using cointegration analysis. Autocorrelation tests show that GDP and EXP are both non-stationary. Applying the Augmented Engle-Granger method reveals that regressing GDP on EXP produces a cointegrating relationship, not a spurious one. An error correction model indicates that while GDP and EXP have a long-term equilibrium relationship, GDP does not fully adjust to changes in EXP in the short run.
Nonlinear Extension of Asymmetric Garch Model within Neural Network Framework csandit
The importance of volatility for all market partici
pants has led to the development and
application of various econometric models. The most
popular models in modelling volatility are
GARCH type models because they can account excess k
urtosis and asymmetric effects of
financial time series. Since standard GARCH(1,1) mo
del usually indicate high persistence in the
conditional variance, the empirical researches turn
ed to GJR-GARCH model and reveal its
superiority in fitting the asymmetric heteroscedast
icity in the data. In order to capture both
asymmetry and nonlinearity in data, the goal of thi
s paper is to develop a parsimonious NN
model as an extension to GJR-GARCH model and to det
ermine if GJR-GARCH-NN outperforms
the GJR-GARCH model.
COMPARING NET PROFIT FORECASTS OF INDIAN BANKS USING OLS AND GARCH 1,1 FRAMEWORKSCHOLEDGE R&D CENTER
In the present paper the Bi-variate Ordinary Least Square (OLS) and Generalized autoregressive conditional heteroskedasicity (GARCH 1, 1) model are applied to gather the fitted Net –Profit series of Two nationalized banks viz, State Bank of India SBI (being a leader) and ING Vysya bank (not a leader) in the Indian Banking sector. It is evident that OLS is non-parameterized method while QMLE or QML is a parameterized technique of coefficients estimation. The robustness must therefore need to see with respect to the data in consideration. The whole approach is to measure how both the models provide Earning forecasts and to analyze the behavior of regression coefficients. Also, the second objective could be to see how “Leader” bank earnings estimation process differs from the non-leader bank in the Indian banking setup. The results are clearly explaining differences in two banks in terms of their coefficient values, residual state and R-squared values.
Analysis of Two-Echelon Inventory System with Two Suppliersinventionjournals
Inventories exist throughout the supply chain in various form for various reasons. Since carrying these inventories can cost anywhere from 20-40 % of their value a year, managing them in a scientific manner to maintain minimal levels makes economic sense. This paper presents a continuous review two echelon inventory system. The operating policy at the lower echelon is (s, S) that is whenever the inventory level traps to s on order for Q = (S-s) items is placed, the ordered items are received after a random time which is distributed as exponential. We assume that the demands accruing during the stock-out period are lost. The retailer replenishes their stock from the regular supplier which adopts (0,M) policy, M = n1Q. When the regular supplier stock is empty the replacement of retailer stock made by the outside supplier who adopts (0, N) policy N = n2Q. The joint probability disruption of the inventory levels of retailer, regular supplier and the outside supplier are obtained in the steady state case. Various system performance measures are derived and the long run total expected inventory cost rate is calculated. Several instances of a numerical examples, which provide insight into the behaviour of the system are presented.
Applications Residual Control Charts Based on Variable LimitsIJERA Editor
The main purpose of this paper is to verify the stability of a productive process in the presence of the effects of autocorrelation and volatility, in order to capture these characteristics by a joint forecast model which produces residuals that are evaluated by a control chart based on variable control limits. The methodology employed will be the joint estimation of the residuals by ARIMA – ARCH models and the conditional standard deviation from residuals to establish the chart control limits. The joint AR (1)-ARCH (1) model shows that an appropriate forecasting model brings a great contribution to the performance of residual control charts in monitoring the stability of industrial variables using just one chart to monitor mean and variance together.
Modifying of li ni0.8co0.2o2 cathode material by chemical vapor deposition co...Alexander Decker
The document summarizes research on modifying the cathode material LiNi0.8Co0.2O2 by depositing thin ceramic oxide coatings via chemical vapor deposition to improve its thermal stability. Al2O3 and ZnO coatings were deposited. X-ray diffraction analysis showed the Al2O3 coating did not significantly change the material's structure, while the ZnO coating resulted in a new phase, likely a nickel-zinc compound. Electrochemical testing found the Al2O3-coated material had lower specific capacity in the first cycle but better capacity retention over subsequent cycles compared to the uncoated material. Differential scanning calorimetry also showed the Al2O3 coating reduced the exothermic reaction
This document summarizes an academic article that discusses the nature of interlanguage and research methods used in its study. It defines interlanguage as the linguistic system developed by second language learners between their native language and the target language. The article reviews Selinker's hypothesis of five psycholinguistic processes that shape interlanguage, including native language transfer and overgeneralization of target language rules. It also discusses Gregg's view of interlanguage variability and introduces common steps used in interlanguage data selection and analysis, such as operationalizing variables and categorizing data.
Measuring customer based brand equity in the iranian lubricants market case s...Alexander Decker
The document discusses measuring customer-based brand equity in the Iranian lubricants market for Sepahan oil company. It analyzes brand equity dimensions of brand loyalty, brand associations/awareness, and perceived quality based on a sample of 300 Sepahan oil company consumers. The findings conclude that brand loyalty and perceived quality are influential dimensions of brand equity, while weak support was found for the brand associations/awareness dimension.
Marketing for service quality in jordanian construction project organisationAlexander Decker
This document summarizes marketing concepts as applied to the construction industry in Jordan. It finds that most construction companies in Jordan do not have dedicated marketing departments or see marketing as a legitimate activity. Contracts are typically awarded based primarily on price. The document reviews key marketing concepts including the marketing mix, marketing orientation, segmentation, and positioning. It emphasizes the importance of understanding customer needs to improve quality and satisfaction.
Manpower training and development is positively related to productivity at Zenith Bank Plc. The study examined the relationship between manpower training costs and profitability at Zenith Bank Plc's Maitama branch in Abuja, Nigeria from 2001-2010. Data was collected through questionnaires and the bank's financial statements, and analyzed using chi-square tests and regression analysis. The results showed a significant positive relationship between the cost of manpower training and the bank's productivity and profitability. The study concluded that manpower training improves employee skills and performance, leading to higher productivity and profits for the bank.
Multivariate analysis of the impact of the commercial banks on the economic g...Alexander Decker
The document analyzes the impact of commercial banks on economic growth in Nigeria from 1970-2009 using multivariate analysis and the ordinary least squares method. It finds that commercial bank credits, deposit liabilities, and lending rates had a positive relationship with GDP, indicating they help achieve economic growth. However, the number of banks had a negative but insignificant relationship with GDP. The study concludes that policies aimed at increasing commercial bank capital bases should be pursued to increase loanable funds and sustainable economic growth and development.
Mathematical model of refrigerants boiling process in theAlexander Decker
The document presents a mathematical model of the boiling process of refrigerants in a partially closed volume. Key points:
1) The model considers heat transfer and fluid flow in a tube with outer fins that form a partially closed volume around the tube.
2) Bubbles form within this volume and grow until exiting through openings, with the liquid maintaining contact between the tube and fins.
3) Equations were developed to model the heat transfer between the boiling refrigerant and tube, mass transfer between the phases, and fluid dynamics within the partially closed volume.
4) Comparisons showed close agreement between the mathematical model and experimental data, demonstrating its ability to predict performance improvements over standard finned tubes.
Modeling and forecasting energy consumption in ghanaAlexander Decker
This document summarizes a study that models and forecasts energy consumption in Ghana using seasonal ARIMA models. The author obtained monthly energy consumption data from 2001-2011 from Ghana's Ministry of Energy. Various SARIMA models were identified and fitted to the data. The best fitting model was selected as SARIMA (1,1,1)(0,1,2) based on having the lowest Akaike Information Criterion and Schwartz Bayesian Criterion values. This model was used to accurately forecast energy consumption for 2013 based on validation with 2012 data. The study aims to provide a modeling tool for long-term energy planning in Ghana.
Meeting demands of vision 2030 and globalisation some reforms and innovations...Alexander Decker
The document discusses reforms needed in Kenya's curriculum to meet the demands of Vision 2030 and enable Kenya to compete globally. It notes that Kenya's current education system produces graduates lacking in skills like problem-solving, logical thinking and basic math. The curriculum is overly focused on exams and memorization. Reforms are needed to the curriculum, teaching methods, and teacher education to develop more innovative, creative thinking in students. Key reforms proposed include incorporating more inquiry-based, student-centered learning; focusing on skills like programming, problem-solving and statistics; and making teacher education more practical and grounded in teaching practice. The goal is for Kenya to produce graduates that can address societal issues and compete internationally.
Mathematical formulation of inverse scattering and korteweg de vries equationAlexander Decker
This document summarizes the mathematical formulation of inverse scattering and the Korteweg-de Vries (KdV) equation. It begins by defining inverse scattering as determining solutions to differential equations based on known asymptotic solutions, specifically by solving the Marchenko equation. It then discusses how the KdV equation describes shallow water waves and solitons, and how the inverse scattering transform method can be used to determine soliton solutions from arbitrary initial conditions. The document outlines the procedure, including deriving the scattering data from an initial potential function and using its time evolution to reconstruct solutions to the KdV equation at later times. It provides examples using reflectionless potentials, specifically obtaining the single-soliton solution from an initial sech^2
This document summarizes research on multilingualism in Iran, specifically focusing on the status of the Azeri language in East Azerbaijan Province. It introduces the concepts of language unity and pluralism in language planning, noting that Iran follows a unity approach with Persian as the sole official and national language. The researcher analyzes data on Azeri language use in local media and publications in East Azerbaijan and concludes that despite the emphasis on Persian, Azeri has maintained its status and is not being marginalized, showing that Iran's language policy has taken a balanced approach between unity and pluralism.
New type of multi-purpose standard radon chamber in south koreaAlexander Decker
This document summarizes the development of a new multi-purpose standard radon chamber in South Korea. The chamber was designed to evaluate radon emission rates from natural and artificial sources under different conditions, calibrate radon detectors, and assess the efficiency of radon mitigation systems. It has the ability to control temperature, humidity and air flow. Computational fluid dynamics modeling can also simulate radon movement within the chamber. The chamber fills an important need as existing chambers in South Korea are not widely used due to lack of demand. It will help advance radon research and regulation in the country.
Optimal generation scheduling of hydropower plant with pumped storage unitAlexander Decker
This document discusses optimal generation scheduling of a hydropower plant with a pumped storage unit. It proposes determining the optimum generation schedule based on analyzing hourly and annual generation costs. Power output is formulated as a linear function of hydraulic head and discharge rate. Hourly and annual costs are also linear functions of power output and energy generation, respectively. The optimum schedule is determined by minimizing total generation costs over time periods while considering constraints like water drawdown requirements. The strategy is demonstrated through a simulation of Thailand's Bhumibol hydropower plant.
This document contains contact information for Smile Effects, a business located at 6501 Dalrock Rd STE 108 in Rowlett, TX. Smile Effects can be reached by phone at 972-463-8338 and their website is smileeffects.net.
This document discusses approaches to measuring desertification. It reviews previous definitions of desertification and land degradation. It argues that desertification should be measured as a continuum over the long-term using indicators like Normalized Difference Vegetation Index (NDVI) that reflect changes in vegetation cover over time. Measuring desertification spatially at the pixel level and temporally over 15+ years can help account for climate variations and better identify localized degradation and causes. Efforts to combat desertification may be most effective at the local level where land use decisions are made.
Разработка схемотехнических решений на базе микроконтроллеров, испытательных стендов, а также алгоритмов и исследовательских, демонстрационных программ, предназначенных для совершенствования запатентованой технологии создания полиморфных микроджойстиков.
NONLINEAR EXTENSION OF ASYMMETRIC GARCH MODEL WITHIN NEURAL NETWORK FRAMEWORKcscpconf
The importance of volatility for all market participants has led to the development and
application of various econometric models. The most popular models in modelling volatility are
GARCH type models because they can account excess kurtosis and asymmetric effects of
financial time series. Since standard GARCH(1,1) model usually indicate high persistence in the
conditional variance, the empirical researches turned to GJR-GARCH model and reveal its
superiority in fitting the asymmetric heteroscedasticity in the data. In order to capture both
asymmetry and nonlinearity in data, the goal of this paper is to develop a parsimonious NN
model as an extension to GJR-GARCH model and to determine if GJR-GARCH-NN outperforms
the GJR-GARCH model.
This document summarizes a study that models crude oil prices using a Lévy process. The study finds that a MA(8) model best fits the time series properties of oil price returns. However, there is also evidence of GARCH effects. Therefore, the best overall model is a GARCH(1,1) with errors modeled by a Johnson SU distribution. This hybrid Lévy-GARCH process captures the temporal, spectral and distributional properties of the crude oil price data set.
Modifying of li ni0.8co0.2o2 cathode material by chemical vapor deposition co...Alexander Decker
The document summarizes research on modifying the cathode material LiNi0.8Co0.2O2 by depositing thin ceramic oxide coatings via chemical vapor deposition to improve its thermal stability. Al2O3 and ZnO coatings were deposited. X-ray diffraction analysis showed the Al2O3 coating did not significantly change the material's structure, while the ZnO coating resulted in a new phase, likely a nickel-zinc compound. Electrochemical testing found the Al2O3-coated material had lower specific capacity in the first cycle but better capacity retention over subsequent cycles compared to the uncoated material. Differential scanning calorimetry also showed the Al2O3 coating reduced the exothermic reaction
This document summarizes an academic article that discusses the nature of interlanguage and research methods used in its study. It defines interlanguage as the linguistic system developed by second language learners between their native language and the target language. The article reviews Selinker's hypothesis of five psycholinguistic processes that shape interlanguage, including native language transfer and overgeneralization of target language rules. It also discusses Gregg's view of interlanguage variability and introduces common steps used in interlanguage data selection and analysis, such as operationalizing variables and categorizing data.
Measuring customer based brand equity in the iranian lubricants market case s...Alexander Decker
The document discusses measuring customer-based brand equity in the Iranian lubricants market for Sepahan oil company. It analyzes brand equity dimensions of brand loyalty, brand associations/awareness, and perceived quality based on a sample of 300 Sepahan oil company consumers. The findings conclude that brand loyalty and perceived quality are influential dimensions of brand equity, while weak support was found for the brand associations/awareness dimension.
Marketing for service quality in jordanian construction project organisationAlexander Decker
This document summarizes marketing concepts as applied to the construction industry in Jordan. It finds that most construction companies in Jordan do not have dedicated marketing departments or see marketing as a legitimate activity. Contracts are typically awarded based primarily on price. The document reviews key marketing concepts including the marketing mix, marketing orientation, segmentation, and positioning. It emphasizes the importance of understanding customer needs to improve quality and satisfaction.
Manpower training and development is positively related to productivity at Zenith Bank Plc. The study examined the relationship between manpower training costs and profitability at Zenith Bank Plc's Maitama branch in Abuja, Nigeria from 2001-2010. Data was collected through questionnaires and the bank's financial statements, and analyzed using chi-square tests and regression analysis. The results showed a significant positive relationship between the cost of manpower training and the bank's productivity and profitability. The study concluded that manpower training improves employee skills and performance, leading to higher productivity and profits for the bank.
Multivariate analysis of the impact of the commercial banks on the economic g...Alexander Decker
The document analyzes the impact of commercial banks on economic growth in Nigeria from 1970-2009 using multivariate analysis and the ordinary least squares method. It finds that commercial bank credits, deposit liabilities, and lending rates had a positive relationship with GDP, indicating they help achieve economic growth. However, the number of banks had a negative but insignificant relationship with GDP. The study concludes that policies aimed at increasing commercial bank capital bases should be pursued to increase loanable funds and sustainable economic growth and development.
Mathematical model of refrigerants boiling process in theAlexander Decker
The document presents a mathematical model of the boiling process of refrigerants in a partially closed volume. Key points:
1) The model considers heat transfer and fluid flow in a tube with outer fins that form a partially closed volume around the tube.
2) Bubbles form within this volume and grow until exiting through openings, with the liquid maintaining contact between the tube and fins.
3) Equations were developed to model the heat transfer between the boiling refrigerant and tube, mass transfer between the phases, and fluid dynamics within the partially closed volume.
4) Comparisons showed close agreement between the mathematical model and experimental data, demonstrating its ability to predict performance improvements over standard finned tubes.
Modeling and forecasting energy consumption in ghanaAlexander Decker
This document summarizes a study that models and forecasts energy consumption in Ghana using seasonal ARIMA models. The author obtained monthly energy consumption data from 2001-2011 from Ghana's Ministry of Energy. Various SARIMA models were identified and fitted to the data. The best fitting model was selected as SARIMA (1,1,1)(0,1,2) based on having the lowest Akaike Information Criterion and Schwartz Bayesian Criterion values. This model was used to accurately forecast energy consumption for 2013 based on validation with 2012 data. The study aims to provide a modeling tool for long-term energy planning in Ghana.
Meeting demands of vision 2030 and globalisation some reforms and innovations...Alexander Decker
The document discusses reforms needed in Kenya's curriculum to meet the demands of Vision 2030 and enable Kenya to compete globally. It notes that Kenya's current education system produces graduates lacking in skills like problem-solving, logical thinking and basic math. The curriculum is overly focused on exams and memorization. Reforms are needed to the curriculum, teaching methods, and teacher education to develop more innovative, creative thinking in students. Key reforms proposed include incorporating more inquiry-based, student-centered learning; focusing on skills like programming, problem-solving and statistics; and making teacher education more practical and grounded in teaching practice. The goal is for Kenya to produce graduates that can address societal issues and compete internationally.
Mathematical formulation of inverse scattering and korteweg de vries equationAlexander Decker
This document summarizes the mathematical formulation of inverse scattering and the Korteweg-de Vries (KdV) equation. It begins by defining inverse scattering as determining solutions to differential equations based on known asymptotic solutions, specifically by solving the Marchenko equation. It then discusses how the KdV equation describes shallow water waves and solitons, and how the inverse scattering transform method can be used to determine soliton solutions from arbitrary initial conditions. The document outlines the procedure, including deriving the scattering data from an initial potential function and using its time evolution to reconstruct solutions to the KdV equation at later times. It provides examples using reflectionless potentials, specifically obtaining the single-soliton solution from an initial sech^2
This document summarizes research on multilingualism in Iran, specifically focusing on the status of the Azeri language in East Azerbaijan Province. It introduces the concepts of language unity and pluralism in language planning, noting that Iran follows a unity approach with Persian as the sole official and national language. The researcher analyzes data on Azeri language use in local media and publications in East Azerbaijan and concludes that despite the emphasis on Persian, Azeri has maintained its status and is not being marginalized, showing that Iran's language policy has taken a balanced approach between unity and pluralism.
New type of multi-purpose standard radon chamber in south koreaAlexander Decker
This document summarizes the development of a new multi-purpose standard radon chamber in South Korea. The chamber was designed to evaluate radon emission rates from natural and artificial sources under different conditions, calibrate radon detectors, and assess the efficiency of radon mitigation systems. It has the ability to control temperature, humidity and air flow. Computational fluid dynamics modeling can also simulate radon movement within the chamber. The chamber fills an important need as existing chambers in South Korea are not widely used due to lack of demand. It will help advance radon research and regulation in the country.
Optimal generation scheduling of hydropower plant with pumped storage unitAlexander Decker
This document discusses optimal generation scheduling of a hydropower plant with a pumped storage unit. It proposes determining the optimum generation schedule based on analyzing hourly and annual generation costs. Power output is formulated as a linear function of hydraulic head and discharge rate. Hourly and annual costs are also linear functions of power output and energy generation, respectively. The optimum schedule is determined by minimizing total generation costs over time periods while considering constraints like water drawdown requirements. The strategy is demonstrated through a simulation of Thailand's Bhumibol hydropower plant.
This document contains contact information for Smile Effects, a business located at 6501 Dalrock Rd STE 108 in Rowlett, TX. Smile Effects can be reached by phone at 972-463-8338 and their website is smileeffects.net.
This document discusses approaches to measuring desertification. It reviews previous definitions of desertification and land degradation. It argues that desertification should be measured as a continuum over the long-term using indicators like Normalized Difference Vegetation Index (NDVI) that reflect changes in vegetation cover over time. Measuring desertification spatially at the pixel level and temporally over 15+ years can help account for climate variations and better identify localized degradation and causes. Efforts to combat desertification may be most effective at the local level where land use decisions are made.
Разработка схемотехнических решений на базе микроконтроллеров, испытательных стендов, а также алгоритмов и исследовательских, демонстрационных программ, предназначенных для совершенствования запатентованой технологии создания полиморфных микроджойстиков.
NONLINEAR EXTENSION OF ASYMMETRIC GARCH MODEL WITHIN NEURAL NETWORK FRAMEWORKcscpconf
The importance of volatility for all market participants has led to the development and
application of various econometric models. The most popular models in modelling volatility are
GARCH type models because they can account excess kurtosis and asymmetric effects of
financial time series. Since standard GARCH(1,1) model usually indicate high persistence in the
conditional variance, the empirical researches turned to GJR-GARCH model and reveal its
superiority in fitting the asymmetric heteroscedasticity in the data. In order to capture both
asymmetry and nonlinearity in data, the goal of this paper is to develop a parsimonious NN
model as an extension to GJR-GARCH model and to determine if GJR-GARCH-NN outperforms
the GJR-GARCH model.
This document summarizes a study that models crude oil prices using a Lévy process. The study finds that a MA(8) model best fits the time series properties of oil price returns. However, there is also evidence of GARCH effects. Therefore, the best overall model is a GARCH(1,1) with errors modeled by a Johnson SU distribution. This hybrid Lévy-GARCH process captures the temporal, spectral and distributional properties of the crude oil price data set.
This document presents a time series model for the exchange rate between the Euro (EUR) and the Egyptian Pound (EGP) using a GARCH model. The author analyzes the time series data of the exchange rate for 2008 and finds that it exhibits volatility clustering where large changes tend to follow large changes. An ARCH or GARCH model is needed to capture the changing conditional variances over time. The author estimates several GARCH models and selects the GARCH(1,2) model based on statistical significance of coefficients and AIC values. Diagnostic tests show that the GARCH(1,2) model adequately captures the heteroskedasticity in the data. The fitted model is then used to predict future exchange rates
A predictive model for monthly currency in circulation in ghanaAlexander Decker
This document presents a predictive model for monthly currency in circulation in Ghana. The researchers used seasonal autoregressive integrated moving average (SARIMA) modeling to analyze secondary data on Ghana's monthly currency in circulation from 2000 to 2011. They found that an SARIMA (0,1,1)(0,1,1)12 model provided the best fit for the data based on having the lowest AIC, AICc, and BIC values. Diagnostic tests confirmed the model adequately represented the data and was free of autocorrelation and heteroscedasticity. Therefore, the researchers proposed this SARIMA model for predicting currency in circulation in Ghana in the future.
9. the efficiency of volatility financial model withikhwanecdc
This document summarizes a study that investigates the effectiveness of volatility financial models with the presence of additive outliers via Monte Carlo simulation. The study simulates data using an ARMA(1,0)-GARCH(1,2) model with different sample sizes of 500, 1000, and 1400, both with and without 10% additive outliers added. The effectiveness of the models is evaluated based on error metrics and information criteria. The results indicate that the effectiveness of the ARMA-GARCH model diminishes as sample size increases in the presence of additive outliers.
The International Journal of Engineering and Science (The IJES)theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability
The Use of ARCH and GARCH Models for Estimating and Forecasting Volatility-ru...Ismet Kale
This document discusses volatility modeling using ARCH and GARCH models. It first provides background on ARCH and GARCH models, noting they were developed to model characteristics of financial time series data like volatility clustering and fat tails. It then describes the specific ARCH and GARCH models that will be used in the study, including the ARCH, GARCH, EGARCH, GJR, APARCH, IGARCH, FIGARCH and FIAPARCH models. The document aims to apply these models to daily stock index data from the IMKB 100 to analyze and forecast volatility, and better understand risk in the Turkish market.
A Fuzzy Arithmetic Approach for Perishable Items in Discounted Entropic Order...Waqas Tariq
This paper uses fuzzy arithmetic approach to the system cost for perishable items with instant deterioration for the discounted entropic order quantity model. Traditional crisp system cost observes that some costs may belong to the uncertain factors. It is necessary to extend the system cost to treat also the vague costs. We introduce a new concept which we call entropy and show that the total payoff satisfies the optimization property. We show how special case of this problem reduce to perfect results, and how post deteriorated discounted entropic order quantity model is a generalization of optimization. It has been imperative to demonstrate this model by analysis, which reveals important characteristics of discounted structure. Further numerical experiments are conducted to evaluate the relative performance between the fuzzy and crisp cases in EnOQ and EOQ separately.
Application of Exponential Gamma Distribution in Modeling Queuing Dataijtsrd
There are many events in daily life where a queue is formed. Queuing theory is the study of waiting lines and it is very crucial in analyzing the procedure of queuing in daily life of human being. Queuing theory applies not only in day to day life but also in sequence of computer programming, networks, medical field, banking sectors etc. Researchers have applied many statistical distributions in analyzing a queuing data. In this study, we apply a new distribution named Exponential Gamma distribution in fitting a data on waiting time of bank customers before service is been rendered. We compared the adequacy and performance of the results with other existing statistical distributions. The result shows that the Exponential Gamma distribution is adequate and also performed better than the existing distributions. Ayeni Taiwo Michael | Ogunwale Olukunle Daniel | Adewusi Oluwasesan Adeoye ""Application of Exponential-Gamma Distribution in Modeling Queuing Data"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30097.pdf
Paper Url : https://www.ijtsrd.com/mathemetics/statistics/30097/application-of-exponential-gamma-distribution-in-modeling-queuing-data/ayeni-taiwo-michael
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VOLATILITY FORECASTING - A PERFORMANCE MEASURE OF GARCH TECHNIQUES WITH DIFFE...ijscmcj
Volatility Forecasting is an interesting challenging topic in current financial instruments as it is directly associated with profits. There are many risks and rewards directly associated with volatility. Hence forecasting volatility becomes most dispensable topic in finance. The GARCH distributions play an important role in the risk measurement and option pricing. The min motive of this paper is to measure the performance of GARCH techniques for forecasting volatility by using different distribution model. We have used 9 variations in distribution models that are used to forecast the volatility of a stock entity. The different GARCH distribution models observed in this paper are Std, Norm, SNorm, GED, SSTD, SGED, NIG, GHYP and JSU. Volatility is forecasted for 10 days in advance and values are compared with the actual values to find out the best distribution model for volatility forecast. From the results obtain it has been observed that GARCH with GED distribution models has outperformed all models.
The International Journal of Soft Computing, Mathematics and Control (IJSCMC) is a Quarterly peer-reviewed and refereed open access journal that publishes articles which contribute new results in all areas of Soft Computing, Pure, Applied and Numerical Mathematics and Control. The focus of this new journal is on all theoretical and numerical methods on soft computing, mathematics and control theory with applications in science and industry. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on latest topics of soft computing, pure, applied and numerical mathematics and control engineering, and establishing new collaborations in these areas.
Authors are solicited to contribute to this journal by submitting articles that illustrate new algorithms, theorems, modeling results, research results, projects, surveying works and industrial experiences that describe significant advances in Soft Computing, Mathematics and Control Engineering
VOLATILITY FORECASTING - A PERFORMANCE MEASURE OF GARCH TECHNIQUES WITH DIFFE...ijscmcj
Volatility Forecasting is an interesting challenging topic in current financial instruments as it is directly
associated with profits. There are many risks and rewards directly associated with volatility. Hence
forecasting volatility becomes most dispensable topic in finance. The GARCH distributions play an important
role in the risk measurement and option pricing. The min motive of this paper is to measure the performance
of GARCH techniques for forecasting volatility by using different distribution model. We have used 9
variations in distribution models that are used to forecast the volatility of a stock entity. The different GARCH
distribution models observed in this paper are Std, Norm, SNorm, GED, SSTD, SGED, NIG, GHYP and JSU.
Volatility is forecasted for 10 days in advance and values are compared with the actual values to find out the
best distribution model for volatility forecast. From the results obtain it has been observed that GARCH with
GED distribution models has outperformed all models.
Volatility Forecasting - A Performance Measure of Garch Techniques With Diffe...ijscmcj
Volatility Forecasting is an interesting challengingtopicin current financial instruments as it is directly associated with profits. There are many risks and rewards directly associated with volatility. Hence forecasting volatility becomes most dispensable topic in finance. The GARCH distributionsplay an import ant role in the risk measurement a nd option pricing. T heminmotiveof this paper is tomeasure the performance of GARCH techniques for forecasting volatility by using different distribution model. We have used 9 variations in distribution models that are used to forecast t he volatility of a stock entity. Thedifferent GARCH
distribution models observed in this paper are Std, Norm, SNorm,GED, SSTD, SGED, NIG, GHYP and JSU.Volatility is forecasted for 10 days in dvance andvalues are compared with the actual values to find out the best distribution model for volatility forecast. From the results obtain it has been observed that GARCH withGED distribution models has outperformed all models
Forecasting Bitcoin Risk Measures: A Robust Approach
TRUCIOS, CARLOS
Over the last few years, Bitcoin and other cryptocurrencies have attracted the interest of many investors, practitioners and researchers. However, little attention has been paid to the predictability of their risk measures. In this paper, we compare the predictability of the one-step-ahead volatility and Value-at-Risk of Bitcoin using several volatility models. We also include procedures that take into account the presence of outliers and estimate the volatility and Value-at-Risk in a robust fashion. Our results show that robust procedures outperform the non-robust ones when forecasting the volatility and estimating the Value-at-Risk. These results suggest that the presence of outliers play an important role in the modelling and forecasting of Bitcoin risk measures.
KEYWORDS: Cryptocurrency, GARCH, Model Confidence Set, Outliers, Realised Volatility, Value-at-Risk
MFBLP Method Forecast for Regional Load Demand SystemCSCJournals
Load forecast plays an important role in planning and operation of a power system. The accuracy of the forecast value is necessary for economically efficient operation and also for effective control. This paper describes a method of modified forward backward linear predictor (MFBLP) for solving the regional load demand of New South Wales (NSW), Australia. The method is designed and simulated based on the actual load data of New South Wales, Australia. The accuracy of discussed method is obtained and comparison with previous methods is also reported.
ANALYZING THE PROCESS CAPABILITY FOR AN AUTO MANUAL TRANSMISSION BASE PLATE M...ijmvsc
The industry today is working intensively on a goal-oriented way towards introducing regular studies in
manufacturing. The current study is part of a large overall spanning project aiming towards an increase in
productivity, i.e. more products produced per year with availability. In this paper we have analyze what
Process Capability is and how it is implemented on a current process. All the steps are listed out in an easy
to understand manner. In current scenario, specifications for products have been tightened due to
performance competition in market. Statistical tools like control charts, process capability analysis and
cause and effect diagram ensure that processes are fit for company specifications while reduce the process
variation and improve product quality characteristic. Process capability indices (PCIs) are used in the
manufacturing process to provide numerical measures on whether a process is capable of producing items
within the predetermined limits. For the analysis purpose MINITAB 16.0 is used and is found that the
process is placed exactly at the centre of the control limits. Analysis also shows that process is not
adequate. The cause and effect diagram is prepared to found out the root cause of variation in diameter of
work. In this study, a process-capability analysis was also carried out in a medium-sized company that
produces machine and spare parts.
Garch Models in Value-At-Risk Estimation for REITIJERDJOURNAL
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This document summarizes a study that empirically models the monthly Treasury bill rates in Ghana from 1998 to 2012. Specifically, it models the rates of the 91-day and 182-day Treasury bills using ARIMA models. For the 91-day bills, the ARIMA 3,1,1 model provided the best fit with a log likelihood value of -328.58. For the 182-day bills, the ARIMA 1,1,0 model fit best with a log likelihood value of -356.50. Residual tests on both models showed the residuals were free from heteroscedasticity and serial correlation. The study aims to determine appropriate time series models for predicting and forecasting future Treasury bill rates in
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3) Simulation studies and an application show that the adaptive approach gains better efficiency compared to other methods, especially when the innovation error is heavy-tailed.
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UiPath integration with generative AI
Speaker:
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Measuring the volatility in ghana’s gross domestic product (gdp) rate using the garch type models
1. European Journal of Business and Management
ISSN 2222-1905 (Paper) ISSN 2222-2839 (Online)
Vol.5, No.27, 2013
www.iiste.org
Measuring the Volatility in Ghana’s Gross Domestic
Product (GDP) Rate using the GARCH-type Models
Godfred Kwame Abledu(PhD)1* , Agbodah Kobina2
1.
School of Applied Science and Technology, Koforidua Polytechnic, PO Box 981, Koforidua, Ghana
2.
Statistics Department, Koforidua Polytechnic, PO Box 981, Koforidua, Ghana
* E-mail of the corresponding author: godfredabledu@gmail.com
Abstract
The objective of this paper was to empirically characterize the volatility in the growth rate of real Gross
Domestic Product (GDP) for Ghana in three sectors using data spanning from 2000 to 2012. The GARCH-type
models(GARCH, EGARCH and GJR-GARCH) were used for the analysis of data. The results of the study
present evidence that the symmetric GARCH(1, 1) structure applies reasonably well to GDP when quarterly
observations are used.. As expected from financial time series, the data for the study exhibit characteristics such
as leptokurtosis, clustering, asymmetric and leverage effects. It was found that there was a significant increase in
volatility and leverage effect.
1.
Introduction
The economy of Ghana has a diverse and rich resource base, and as such, has one of the highest GDP per capita
in Africa. Ghana is one of the top–ten fastest growing economies in the world, and the fastest growing economy
in Africa. Ghana remains somewhat dependent on international financial and technical assistance as well as the
activities of the extensive Ghanaian diaspora. Gold, timber, cocoa, diamond, bauxite, manganese, and many
other exports are major sources of foreign exchange. An oilfield which is reported to contain up to 3 billion
barrels (480×106 m3) of light oil was discovered in 2007. Oil exploration is ongoing and, the amount of oil
continues to increase.
Gross Domestic Product (GDP) is Ghana’s official measure of economic growth. There are three different
approaches that can be taken to calculate GDP; the production approach, the expenditure approach, and the
income approach. The approach used to calculate Ghana’s GDP on a quarterly basis is the production approach.
The Gross Domestic Product (GDP) in Ghana was worth 39.20 billion US dollars in 2011, according to a report
published by the World Bank. The GDP value of Ghana is roughly equivalent to 0.06 percent of the world
economy. Historically, from 1960 until 2011, Ghana’s GDP averaged 7.15 Billion USD reaching an all time high
of 39.20 Billion USD in December of 2011 and a record low of 1.20 Billion USD in December of 1960. The
gross domestic product (GDP) is a measure of national income and output for a given country's economy. The
gross domestic product (GDP) is equal to the total expenditures for all final goods and services produced within
the country in a stipulated period of time.
The reduction in the volatility of growth rates with country size is well known. Box and Jenkins(1976) uses size
measures to correct for possible heteroskedasticity in long run growth rates. Khan, et al.( 2011)calculate the
Spearman rank correlation coefficient of the volatility of GDP with total GDP across countries and argues that
the higher output variance of smaller countries is due to their greater openness and susceptibility to foreign
shocks. We argue that there is a highly structured relationship between aggregate output shocks and the size of
an economy and that microeconomic models should try to explain all of these empirical regularities.
2.
2.1.
Materials and Method
Procedure
The time series were first analysed to identify systematic patterns (frequency components or trends) which are
not salient in the time series. Autocorrelation and Crosscorrelation Functions (ACF, CCF) as well as Spectral
and Cross-Spectral densities were estimated for these purposes. All estimated correlation functions
(correlograms) were plotted with the 95% confidence intervals of consecutive lags in the specified range. The
sample autocorrelations had been used in the earlier part of the analysis to check the stationarity of the data set
and also to have a measure of the dependence considering the data as a time series.
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Seasonal dependency was proved by comparing the results of the Partial Autocorrelation Function (PACF),
which considerably reduces the dependence on the intermediate elements, within the lag, and the results of the
ordinary ACF (Box and Jenkins, 1976; Box and Pierce, 1970). The software routines applied validate the
significance of the correlation coefficients rk by comparing their values to the standard error of rk, under the
assumption that the series is a white noise process and that all autocorrelations are equal to zero.
The development of ARIMA models is based on the methodology described in the classical work of Box and
Jenkins (1976). The procedure is applied separately to the landings and SST time series, as a univariate time
series approach, taking into account only the mathematical properties of the data, without involving the
biological or the physical background of the system. This kind of analysis supposes that other 'external factors'
do not participate in the process development or that their contribution is stochastic.
For each developed ARIMA model the standard three-steps procedure has been followed, namely model
identification, parameter estimation and finally the diagnosis of the simulation and its verification (Brockwell
and Davis, 1996). As mentioned above, the input series for ARIMA needs to be differenced to achieve
stationarity. The order of differencing is reflected in the d parameter. The general model introduced by Box and
Jenkins (1976) can be summarized by the use of the following three types of parameters: the autoregressive
parameters (p), the number of differencing (d), and moving average parameters (q).
In the notation introduced by Box and Jenkins, a model described as (0, 1, 2) means that it contains 0 (zero)
autoregressive (p) parameters and 2 moving average (q) parameters which were computed for the series after it
was differenced once. Similarly the required parameters sp, sd and sq of the seasonal ARIMA process are
determined according to the results of the corresponding ACF and PACF. The approach used consequently was
to estimate the seasonal model first, then study the residuals of this model to get a clearer view of the nonseasonal model involved. If the identification of the seasonal model was correct, these residuals showed the nonseasonal portion of the model.
After the identification of the tentative model, its parameters were estimated applying maximum-likelihood
methods. The final results include: the parameter estimates, standard errors, estimate of residual variance,
standard error of the estimate, log likelihood, Akaike's information criterion (AIC), Schwartz's Bayesian criterion
(SBC). The minimizing of SBC and AIC were used, taking into account both how well the model fitted the
observed series, and the number of parameters used in the fit.
2.2.
The GARCH Models
GARCH models are used as a successful treatment to the financial data which often demonstrate timepersistence, volatility clustering and deviation from the normal distribution. Among the earliest models is Engel
(1982) linear ARCH model, which captures the time varying
features of the conditional variance. Bollerslev (1986) develops Generalized ARCH (GARCH)
model, allowing for persistency of the conditional variance and more efficient testing. Engle and
Bollerslev (1986) invent the Integrated GARCH (IGARCH) model that provides consistent estimation under the
unit root condition. Engle et. al. (1987) design the ARCH-in- Mean (ARCH-M) model to allow for time varying
conditional mean. Nelson’s (1990b) Exponential GARCH (EGARCH) model allows asymmetric effects and
negative coefficients in the conditional variance function. The leveraged GARCH (LGARCH) model
documented in Glosten et. al. (1993) take into account the asymmetric effects of shocks from different
directions.
Since their introduction by Engle (1982), Autoregressive Conditional Heteroskedastic (ARCH) models and their
extension by Bollerslev (1986) to generalised ARCH (GARCH) processes, GARCH models have been used
widely by practitioners. At a first glance, their structure may seem simple, but their mathematical treatment has
turned out to be quite complex. The aim of this article is to collect some probabilistic properties of GARCH
processes. Although the ARCH is simple, it often requires many parameters to adequately describe the volatility
process of an asset return some alternative models must be sought. Shrivastava, et al. (2010) and Hull(2006)
proposed a useful extension known as the generalized ARCH (GARCH) model. An important feature of
GARCH-type models is that the unconditional volatility σ depends on the entire sample, while the conditional
volatilities
Let
σt are determined by model parameters and recent return observations.
(ε t ) t ∈ℤ be
a sequence of independent and identically distributed (i.i.d.) random variables, and let
p ∈ ℕ = {1, 2, 3,..., ) and p ∈ ℕ o = ℕ ∪ {0} . Further, let α 0 > 0 , α1,..., α p −1 ≥ 0 , α p > 0 ,
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β1,..., βq −1 ≥ 0 and β q > 0
process is
(σ t ) t ∈ℤ
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be non-negative parameters. A GARCH(p, q) process
( X t ) t ∈ℤ
with volatility
is then a solution to the equations:
X t = σ tε t t ∈ℤ
(1)
,
p
q
σ t2 = α t + ∑α i X t2−1 + ∑ β jσ t2−1 t ∈ℤ
i =1
where the process
(σ t ) t ∈ℤ
(2)
,
j =1
is
non-negative. The sequence
(ε t ) t ∈ℤ
is referred to as the driving noise
sequence. GARCH (p, 0) processes are called ARCH (p) processes. The case of a GARCH (0, q) process is
excluded since in that case, the volatility equation (2) decouples from the observed process and the driving noise
sequence.
It is a desirable property that
σt
should depend only on the past innovations (ε t − h) h ∈ ℕ , that is, it is
measurable with respect to σ algebra generated by (ε t − h) h ∈ ℕ . If this condition holds, we shall call the
GARCH (p, q) process causal. Then
algebra σ (εt − h : h ∈ℕ0 ) ,
(εt + h)h∈ℕ0 , and Xt is independent
of σ (εt + h : h ∈ℕ ) , for fixed t. The requirement that all the coefficients α1,...,αp and β1 ,..., β q are non-
generated by
(εt −h)h∈ℕ0 .
( Xt ) is measurable with respect to σ
negative ensures that
Also,
σt
is
independent of
σ2 is non-negative, so that σt can indeed be defined as the square root of σ2 .
Equation(1) is the mean equation and is specified as an AR(p) process. Equation(2) is the
conditional variance equation and it is specified as the GARCH(1, 1) process. Conditional variance
models (Shrivastava, 2009), unlike the traditional or extreme value estimators, incorporate time varying
characteristics of second moment/volatility explicitly. By successively substituting for the lagged
conditional variance into equation(2), the following expression is obtained:
ht =
α0
∞
+ α1 ∑ i =1 β i −1ε t2−i
1− β
(3)
An ordinary sample variance would give each of the past squares an equal weight rather than
declining weights. Thus the GARCH variance is like a sample variance but it emphasizes the most
recent observations. Since ht is the one period ahead forecast variance based on past data, it is called
the conditional variance. The squared residual is given by:
vt = ε t2 − ht
(4)
Equation(4) is by definition unpredictable based on the past. Substituting equation(4) into
equation(2) yields an alternative expression as follows:
ε t2 = ω + (α1 + β )ε t2−1 + vt − β vt −1
(5)
It can immediately be seen that the squared errors followed an ARMA(1, 1) process. The
autoregressive root is the sum of α1 and β , and this is the rule which governs the persistence of
volatility shocks. The Autoregressive Moving Average (ARMA) Models have been used by many researcher
for forecasting(Shrivastava, et, al. , 2010; Abu and Behrooz, 2011) . Given a time series of data Z t , the ARMA
model is a tool for understanding and, perhaps, predicting future values in this series. The model consists of two
parts, an autoregressive (AR) part and “a” moving average (MA) part. The model is usually then referred to as
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the ARMA (a, b) model where a is the order of the autoregressive part and b is the order of the moving average
part. The notation ARMA (a, b) refers to the model with “a” autoregressive terms and “b” moving-average
terms. This model contains the AR(a) and MA(b) models. A time series Z t follows an ARMA (1, 1) model if it
satisfies
a
b
Z1 = k + ωt + ∑ β i Z t −i + ∑ α iωt −i
i −1
(6)
i =1
where { ω t } is a white noise series. The above equation implies that the forecasted value is depended on the
past value and previous shocks. The notation MA(b) which refers to the moving average model of order b is
written as
b
Z t = k + ωt + ∑ α iωt −i
(7)
i =1
and the notation AR(a) which refers to the autoregressive model of order a, is as
a
Z1 = k + ωt + ∑ β i Z t −i
(8)
i −1
α1 ,...,α b are the parameters of the model, µ is the expectation of Zt (often assumed to equal to 0),
and the ωt ,...,ωt −b are again, white noise error terms.
where the
2.3.
Model Estimation and Evaluation
The forecast error is the difference between the realization and the forecast. Thus
eς =
x
^
(T+
ς )...-
x
T +ς
(9)
.
Assuming the model is correct, then we have
^
eς = E[ X T +ς ] + ε ς − xς
(10)
We investigate the probability distribution of the error by computing its mean and variance. One desirable
characteristics of the forecast
⌢
X T +ς is that it is unbiased. For an unbiased estimate, the expected value of the
forecast is the same as the expected value of the time series. Because
εt
is assumed to have a mean of zero, an
unbiased forecast implies E[ε ς ] . The fact that the noise is independent from one period to the next period
means that the variance of the error is:
^
Var[ε t ] = Var{E[ X T +ς ] − x T +ς } + Var[ε T +ς ] and σ ε 2 (ς ) = σ E 2 (ς ) + σ 2 .
(11)
The conditional-sum-of-squares is used to find starting values of parameters, then the maximum likelihood
estimate for the proposed models. The procedure for choosing these models relies on choosing the model with
the minimum AIC, AICc and BIC. The models are presented in Table 1 with their corresponding values of AIC,
AICc and BIC. Among those possible models, comparing their AIC, AICc and BIC as shown in Table 1,
ARIMA (1,1,1)(0,0,1)12 and ARIMA (1,1,2)(0,0,1)12 were chosen as the appropriate model that fit the data well.
The basic volatility measure follows recent work by Comin and Mulani (2005, 2006) and Comin and Philippon
(2005), among others. The measure of volatility is given by:
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n Z
i , j +τ
γ −γ
σit = ∑
i , j+τ
it
t =i Pit
(
2.4.
1
2 2
)
(12)
Maximum Likelihood Method
As pointed out by Bera and Higgins (1993), the GARCH models are most often estimated
by maximum likelihood method. It is thus adopted in this study as well. The log likelihood function of the
GARCH model based on previous period’s information f t Ιψ t −1 ~ N (α 0 + α1 f t −1 , lt ) is given by
1 T
∑ li (θ )
T t −1
'
'
'
'
where θ = (ξ , γ ) with ξ and γ the conditional mean and conditional variance parameters respectively, and
l (θ ) =
1
ε2
lt (θ ) = const. − log( ht ) − t 2 The likelihood function provided above is maximized using Berndt, Hall,
2
2ht
Hall and Hausman (1974) numerical algorithm.
2.5.
Model Identification
This involves the determination of the order of the AR and MA for both seasonal and non-seasonal components.
This can be suggested by the sample ACF and PACF plots based on the Box-Jenkins approach. From Figures 1
and 2, the ACF plot tails of at lag 2 and the PACF plot spike at lag 1, suggesting that q= 2 and p=1 would be
needed to describe these data as coming from a non-seasonal moving average and autoregressive process
respectively.
Also looking at the seasonal lags, both ACF and PACF spikes at seasonal lag 12 and drop to zero for other
seasonal lags suggesting that Q= 1 and P= 1 would be needed to describe these data as coming from a seasonal
moving average and autoregressive process. Hence ARIMA (1,1,2)(1,0,1) could be a possible model for the
series.
3.
Results of the Study
3.1.
Data for the study
This study used data based on the quarterly real GDP in Ghana from three sectors(agriculture, industry and
services). The source is the Ghana Statistical Service’s Main Economic Indicators. The sample period is the first
quarter of 2000 through the fourth quarter of 2012. Each variable is seasonally adjusted. The quarterly growth is
calculated as (Yt − Yt −1 ) × 100 / Yt −1 , where Yt is the original data series (real GDP for agriculture, industry and
services) at time t. This statistical release contains independently compiled quarterly estimates of the gross
domestic product (GDP) for the period of first quarter of 1992 to second quarter of 2012. The estimates are
based on the 1993 System of National Accounts (SNA), International Standard Industrial Classification Revision
4 published by the United Nations and other international organizations and Quarterly National Accounts
Manual: Concepts, data sources, and compilation by International Monetary Fund (IMF). This means that the
methodology, concepts and classifications, are in accordance with the guidelines and recommendations of an
internationally agreed system of national accounts. The estimates of real GDP are expressed in terms of a 2006
base year.
Short-term indicators are used to estimate the quarterly GDP (ref Quarterly National Accounts Manual:
Concepts, Data sources, and Compilation - IMF) where Annual GDP estimates are calculated independently
from the quarterly estimates. Other than that, annual GDP estimates are derived as the sum of the GDP for the
four quarters. The quarterly value added and GDP estimates have been seasonally adjusted. Seasonal adjustment
is the process of estimating and removing seasonal effects from time series to reveal non-seasonal features. This
process is to provide a clearer view of short term movements and trends and also to allow earlier identification of
turning points
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3.2.
Empirical Results
The descriptive statistics for the GDP series are shown in Table 2. Generally, there is a large difference between
the maximum and the minimum return of the index. The standard deviation is also high with regards to the
number of observations including a high level of fluctuation of the yearly GDPs. The mean is close to zero and
positive as is expected for a time series of returns.
There is also negative skewness, indicating an asymmetric tail which exceeds more towards negative values. The
GDP series are leptokurtic, given their large kurtosis statistics as shown in Table 2. The kurtosis exceeds the
normal value of three indicating that the return distribution is flat-tailed. Jarque and Bera(1980) test for
normality confirms the results based on skewness and kurtosis and the series are non-normal according to Jarque
and Bera which rejects normality test at 1% level of significance.
Figure 3 shows the GDP series from 2000 to 2012. Virtual inspection shows that volatility change over the time
and it tends to cluster with the periods of low volatility and periods of high volatility. The volatility is relatively
consistent from 2003 to the year 2009 and seems to increase in the middle of 2008 till 2010.
Table 3 shows the results of ARCH- LM test. This was done to see if there is any ARCH effect in the residuals.
The ARCH- LM test for the series shows a significant presence of ARCH effect with low p-value of 0.000. The
null hypothesis of no ARCH effect is rejected and a strong presence of ARCH effect is detected as is expected
for most financial time series. The test is conducted at different numbers of lags. Values in parenthesis indicate
the p-values. The zero p-value at all lags indicates the presence of ARCH effect in the series. Obs*R-squared is
the number of observations multiplied by the R-squared value. The results in Table 3 confirm that the GARCHtype models can be applied to the GDP series. In most empirical implementations, the values, p ≤ 2 and q ≤ 2,
are sufficient to model the volatility which provides a sufficient tradeoff between flexibility and parsimony
(Knight and Satchell, 1998). The symmetric GARCH and nonlinear asymmetric EGARCH, and GJR-GARCH
models were examined at different lags for p ≤ 2 and q ≤ 2.
Table 4 shows the results of GARCH model estimation. The AR order for the mean equation is selected by the
Akaike Information Criterion (AIC) criterion and is found to be three for all the sectors. The AIC is a measure of
the relative goodness of fit of a statistical model. In the general case, the AIC is equal to 2 k − 2 In ( L ) ,
where k is the number of parameters in the statistical model, and L is the maximized value of the likelihood
function for the estimated model.
The GARCH(1, 1), EGARCH(1, 1) and GJR-GARCH(1, 1) were found to be the most successful models
according to AIC. As they have the smallest value while satisfying restriction such as non-negativity for
symmetric GARCH. The models were estimated for the series using Quasi-Maximum likelihood assuming the
Gaussian normal distribution.
Data in Table 5 clearly indicates that the ARCH and GARCH terms are both significant for the service
sector with coefficient of 0.8811 and 0.0901 respectively. Similar parameter estimates are obtained for both
coefficients in the agricultural sector, whereas the estimates are quite discrepant in the industrial sector, with
relatively large estimates for ARCH (0.3682) and a small estimate for GARCH(0.4539). Moreover, the sum of
α1 and β1 , a parameter that shows the persistence of volatility is relatively high in the service and agricultural
sectors, but relatively low in the industrial sector. It should be noted that AR order for the mean equation
selected by the AIC criteria is found to be three for all data sets. The number in parentheses below the parameter
estimates are standard errors obtained from the heteroskedasticity consistent covariance matrix of the
parameters.
Table 6 gives the residual diagnostics corresponding to the estimates in Table 5. The Ljung-Box test is
used to check the autocorrelation of the residuals (Ljung and Box, 1979) and the Jarque-Bara test is used to
check the normality of the residuals(Jarque and Bara, 1987). The enteries in Table 5 are the p-values and
LB2(12) values. The LB2(12) is the Ljung-Box test of order 12 using squared standardized residuals. As Table 6
indicates, the null hypothesis of no autocorrelation is not rejected for all three sectors at 1% significance level.
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The result of non-normality in residuals shows that the GARCH effect is insufficient to capture the
characteristics of the distribution.
The LB2 (12) is the Ljung-Box test of order 12 using squared standardized residuals and the normality test is
obtained from Jarque-Bera statistic. Entries represent corresponding p-values. P-values less than 0.05 imply the
hypothesis of remaining no ARCH effect is rejected and the hypothesis of normal distribution is rejected at the
5% level of significance.
The variance in the low volatility state is estimated at 0.4861 for the service sector, 0.4625 for the agricultural
sector, and 0.2534 for the industrial sector, and all these values are significant at the 5% significance level. The
variance in the high volatility state is estimated at 2.0811 for the service sector, 2.8925 for the agricultural sector,
and 1.2336 for the industrial sector, and all these values are significant at the 5% significance level. It is noted
that the variance in the high volatility state(St = 2) in the service, agricultural and industrial sectors are more than
four, six and eight times as great as the variances in the low volatility states respectively. It is then possible to
quantify the differences or the breaks in the variance of the GDP process reported in other studies(Kim, et.al.
2001; Bhar, et. al.2009)
4.
Conclusion
The ARCH and the GARCH models have been applied to a wide range of time series analysis but applications in
finance have been particularly successful and have been the focus of this paper. Recent studies have uncovered
evidence of a structural break in the variance of GDP process in many countries.
The paper used the GARCH – type models to characterize the volatility in the growth rate of real GDP in three
sectors. The main objects of interest were the unconditional volatility( σ )and conditional volatilities ( σt ). The
value that
σt
is set to can in some case make a large difference. For example, global volatility started picking
up with the advent of the 2007 crisis, peaking up in 2008. In such cases where there is a clear structural break in
volatility, the GARCH model experience difficulties since it is based on the assumption of average volatility
being constant.
Volatility models are estimated by maximum likelihood(ML)where parameter estimates are obtained by
numerically maximizing the likelihood function with an algorithm called the optimizer. Previous work has
documented the usefulness of a GARCH(1, 1) model without asymmetry in the innovation. In the absence of
market shocks GARCH variance will eventually settle to a steady state value. This is the value
2
t
σ 2 such that
2
σ = σ for all t.
References
Bera, A. and M. Higgins, (1993): ARCH models: properties, estimation and testing, Journal of Economic
Surveys, 7, 305-62.
Berndt, E., B. Hall, R. Hall and J. Hausman, 1974, Estimation and inference in nonlinear structural models,
Annals of Economic and Social Measurement, 4, 653-665.
Bollerslev, T., (1986): Combinationized autoregressive conditional heteroskedasticity. Journal of Econometrics,
31, 307-327.
Box, G. E. P. and Jenkins, G. M. (1976): Time series analysis: forecasting and control. Holden-Day, San
Francisco
Box, G. E. P. and Pierce, D. A. (1970): "Distribution of Residual Autocorrelations in Autoregressive-Integrated
Moving Average Time Series Models", Journal of the American Statistical Association, 65: 1509–1526.
Brockwell, P.J. and Davis, R.A. (1996): Time series: theory and methods(second edition) Springer-Verlag, New
York
Dhar, J. et. al. (2009): "Simulative approach to Constant Mean and Conditional Variance Heteroscedastic model
selection analysis using Likelihood Ratio Test for Indian Market Returns", Proc. IEEE Advance Computing
Conference 2009, Patiala.
71
8. European Journal of Business and Management
www.iiste.org
ISSN 2222-1905 (Paper) ISSN 2222-2839 (Online)
Vol.5, No.27, 2013
Engle, R., and V. Ng, (1993): Measuring and testing the impact of news on volatility, Journal of Finance 48,
1749-1778.
Engle, R., (1982): Autoregressive conditional heteroskedasticity with estimates of the variance of U.K. inflation,
Econometrica, 50, 987-1008.
Engle, R., and T. Bollerslev, (1986): Modelling the persistence of conditional variances, Econometric Reviews,
5, 1-50, 81-87.
Engle, R., D. Lilien and R. Robins, (1987): Estimating time varying risk premia in the term
structure: The ARCH-M model, Econometrica 55, 391-407.
Glosten, L., R. Jagannathan, and D. Runkle, (1993): On the relationship between the expected
value and the volatility of the nominal excess return on stocks, Journal of Finance 48, 17791802.
Georgakarakos, S. et, al,. (2002 ): Loliginid and Ommastrephid Stock Prediction in Greek
waters using time series analysis techniques
Khan, A. R. et al.( 2011): Inventories of SO2 and Particulate Matter Emissions from Fluid Catalytic Cracking
Units in Petroleum Refineries. Water, Air & Soil Pollution 214, no. 1-4 (2011): 287-295
Jarque, C. M. and
Bera, A. K. (1987). "A test for normality of observations and regression
residuals". International Statistical Review 55 (2): 163–172. .
Nelson, D., (1990a): Stationary and persistence in the GARCH (1,1) model, Econometric Theory
6, 318-334.
Nelson, D.,, (1990b): ARCH models as diffusion approximations, Journal of Econometrics 45, 7- 38.
Ljung G. M. and Box G. E. P. (1978). "On a Measure of a Lack of Fit in Time Series Models". Biometrika . Vol.
65 Issue 2, pp.297–303.
Shrivastava, et, al. , (2010): Regression Based Approach to Filter Conditional Mean and Variance Model
Forecast of Stock Market Returns. International Research Journal of Finance and Economics ISSN 1450-2887
Issue 5.
Toyoda,T., (1987): “Use of the Chow Test under heteroskedasticity”, Econometrica 42, 601-608.
Table 1: AIC and BIC for the Suggested ARIMA Model
Model
AIC
AICc
BIC
MA(1,1,1)(0,0,0)12
723.46
723.74
746.57
MA(1,1,1)(0,0,0) 12
723.54
723.86
751.24
MA(1,1,1)(0,0,0) 12
723.41
724.45
756.19
MA(1,1,1)(0,0,0) 12
723.75
724.82
761.21
MA(1,1,1)(0,0,0)12
723.85
735.39
753.02
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Table 2: Descriptive Statistics of GDP of the three Sectors (agriculture, industry and services)
Services
Mean
Agriculture
0.006429
Sectors
Industry
0.008126
0.002443
Standard Deviation
0.000013
0.000002
0.000027
Maximum
0.064365
0.057323
0.032394
minimum
-0.001265
-0.000213
-0.001219
Skewness
-0.544954
-0.646754
-0.564648
Kurtosos
10.142612
9.342675
11.242609
Jarque-Dera
2598.313
3546.325
32578.856
Probability
0.000000
0.000000
0.000000
Statistic
Table 3: ARCH LM test
1992 to 2012
Number of lags
1
F statistic
5
10
54.342
26.654
(0.000)
(0.000)
(0.000)
58.643
214.873
246.832
(0.000)
Obs*R-squared
69.987
(0.000)
(0.000)
Table 4: GARCH-type Models
GARCH-type Models
Coefficients
φ0
φ1
φ2
φ3
α0
α1
β1
GARCH
EGARCH
GJE-GARCH
0.00915
0.00718
0.02026
0.01417
0.07617
0.06121
0.06071
0.00341
0.09317
0.08691
0.08192
0.00231
0.00361
0.00622
0.03432
0.09017
0.08216
0.09541
0.02018
0.03421
0.06123
73
10. European Journal of Business and Management
www.iiste.org
ISSN 2222-1905 (Paper) ISSN 2222-2839 (Online)
Vol.5, No.27, 2013
Table 5: GARCH(1, 1) estimation of real growth rate in GDP
Model
SECTORS
Parameters
Service
Agriculture
Industry
φ0
0.2416*
0.5411*
0.4409*
(0.1013)
(0.1093)
(0.1342)
φ1
(0.0819)
0.3071*
0.2161
0.2112*
(0.0913)
(0.0801)
0.2596*
0.1387*
0.2596
(0.0786)
α0
0.1114*
(0.0718)
(0.0875)
φ3
0.1317
(0.0819)
φ2
0.1417**
(0.0236)
(0.0702)
0.0238
0.0332
0.0318
(0.0284)
(0.0185)
(0.0211)
0.0901*
0.0811**
0.0901*
(0.0385)
(0.0283)
(0.0475)
0.8901*
0.8721*
0.7803*
(0.0432)
(0.0337)
** significant at 5% level; * significant at 10% level
(0.0451)
α1
β1
Table 6: Diagnostic test using standardized residuals from GARCH(1, 1) model
SECTOR
Service
Agriculture
Industry
2
LB (12)
0.954
0.487
0.312
Normality test
0.000
0.000
0.000
Figure 1: ACF of First Order Difference Series
74
11. European Journal of Business and Management
www.iiste.org
ISSN 2222-1905 (Paper) ISSN 2222-2839 (Online)
Vol.5, No.27, 2013
Figure 2: PACF of First Order Difference Series
Figure 3: GDP series from 1992 to 2012
75
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