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jeasiq-1824
Applying some hybrid models for modeling bivariate time series assuming different distributions for random error with a practical application
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Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous variables (GARCHX) are applied to analyze and capture the volatility that occurs in the conditional variance of a linear model. Since time series observations rarely have linear or nonlinear components in nature or usually included together. Therefore, the main purpose of this paper is to employ the hybrid model technique according to Zhang methodology for hybrid models to combine the linear forecasts of the best linear model of ARMAX models and the nonlinear forecasts of the best nonlinear models of (ARCH, GARCH & GARCHX) models and thus increase the efficiency and accuracy of performance forecasting future values of the time series.

This paper is concerned with the modeling and building of the hybrid models (ARMAX-GARCH) and (ARMAX-GARCHX), assuming three different random error distributions: Gaussian distribution, Student-t distribution, as well as the general error distribution and the last two distributions were applied for the purpose of capturing the characteristics of heavy tail distributions which have a Leptokurtic characteristic compared to the normal distribution. This research adopted a modern methodology in estimating the parameters of the hybrid model namely the (two-step procedure) methodology. In the first stage, the parameters of the linear model were estimated using three different methods: The Ordinary Least Squares method (OLS), the Recursive Least Square Method with Exponential Forgetting Factor (RLS-EF), and the Recursive Prediction Error Method (RPM). In the second stage, the parameters of the nonlinear model were estimated using the MLE method and employing the numerical improvement algorithm (BHHH algorithm).

 

 

 

The hybrid models have been applied for modeling the relationship between the exogenous time series represented by the exchange rate and the endogenous time series represented by the unemployment rate in the USA for the period from (January 2000 to December 2017 i.e. 216 observations), and also the out-of-sample forecasts of unemployment rate in the last twelve values of (2018). The forecasting performance of the hybrid models and the competing individual model was also evaluated using the loss function accuracy measures (MAPE), (MAE), and the robust (Q-LIKE). Based on statistical measurements, the results showed the hybrid models improved the accuracy and efficiency of the single model. () hybrid model error whose conditional variance follows a GED distribution is the optimal model in modeling the bivariate time series data under study and more efficient in the forecasting process compared with the individual model and the hybrid model. This is due to having the lowest values for accuracy measures. Different software packages (MATLAB (2018a), SAS 9.1, R 3.5.2 and EViews 9) were used to analyze the data under consideration.

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
The Use of the Regression Tree and the Support Vector Machine in the Classification of the Iraqi Stock Exchange for the Period 2019-2020
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 The financial markets are one of the sectors whose data is characterized by continuous movement in most of the times and it is constantly changing, so it is difficult to predict its trends , and this leads to the need of methods , means and techniques for making decisions, and that pushes investors and analysts in the financial markets to use various and different methods in order to reach at predicting the movement of the direction of the financial markets. In order to reach the goal of making decisions in different investments, where the algorithm of the support vector machine and the CART regression tree algorithm are used to classify the stock data in order to determine

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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
The awareness degree of teacher students in Arabic language department and their supervisors at Al-aqsa University for their future role in knowledge age
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The study aimed to identify the awareness degree of teacher students in the department of Arabic language and their supervisors at Al-aqsa University for their future roles in the age of knowledge. To achieve this objective, descriptive- analytical approach was used. The instruments of this study were two questionnaires: first one consist of (20) item for teacher students, and the second consist of (27) item for educational supervisors which covered three roles: professional, technological, and humanitarian. The sample was (120) student selected randomly, and (39) supervisors of Arabic language. The result revealed that the mean of degree awareness of teacher students and their supervisors of future role are (3.857), (3.472) respectively

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Measuring and analyzing the effect of foreign debt on the gross domestic product in Morocco for the period 1990-2017 using the ARDL Test
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The research aims to identify the magnitude of the impact of external debt on the gross domestic product in Morocco, and the importance of research lies in the role that external debt plays in addressing structural imbalances, if it is best disposed of according to well-studied economic plans by specialists in this regard, especially if these debts are directed with Other resources, as it helps pay the costs of these debts (debt servicing) that the external debt also raises the level of gross domestic product, and the research starts from the hypothesis that: There is an effect of foreign debt on the GDP in Morocco, has contributed in one way or another to The exacerbation of the external debt, which affected the m

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Publication Date
Thu Aug 10 2023
Journal Name
Migration Letters
The Effectiveness of E-Training in Developing the Skills of Designing E-Courses for Teachers of Arabic in the Colleges of Education in Iraq
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This study aimed to examine the effects of electronic training to improve the skills of designing electronic courses for teachers of Arabic language in the colleges of education in Iraq. The descriptive approach is applied and the sample included 145 teachers of Arabic who were selected randomly from the colleges of education in Iraq. Moreover, the results reflected that e-training is effective in improving the skills related to designing online educational courses for teachers of Arabic in the colleges of education in Iraq. Besides, there was no difference between the mean of the respondents' responses to the total score of the tool on the role of electronic training to develop the skills related to electronic courses designing for teacher

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Publication Date
Sun Jun 01 2014
Journal Name
International Journal Of Physics And Research (ijpr)
CALCULATIONS OF MOLTIPOLE MIXING RATIOS FOR GAMMA TRANSITIONS OF Yb POPULATED FROM Yb REACTION USING -RATIO, CONSTANT STATISTICAL TENSOR AND LEAST SQUARES FITTING METHODS
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The - mixing ratios of -transitions from levels in populated in the reactions are calculated in present work using - ratio, constant statisticalTensor and least squares fitting methods The results obtained are in general, in good agreement or consistent, within the associated uncertainties, with these reported in Ref.[9],the discrepancies that occurs are due to inaccuracy existing in the experimental data The results obtained in the present work confirm the –method for mixed transitions better than that for pure transition because this method depends only on the experimental data where the second method depends on the pure or those considered to be pure -transitions, the same results occur in – method

Publication Date
Sat Sep 01 2018
Journal Name
Journal Of Interdisciplinary Nanomedicine
Evaluation of intraductal delivery of poly(ethylene glycol)‐doxorubicin conjugate nanocarriers for the treatment of ductal carcinoma in situ (DCIS)‐like lesions in rats
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Abstract<p>Ductal carcinoma in situ is the most commonly diagnosed early stage breast cancer. The efficacy of intraductally delivered poly(ethylene glycol)‐doxorubicin (PEG‐DOX) nanocarriers, composed of one or more DOX conjugated to various PEG polymers, was investigated in an orthotopic ductal carcinoma in situ‐like rat model. In vitro cytotoxicity was evaluated against 13762 Mat B III cells using MTT assay. The orthotopic model was developed by inoculating cancer cells into mammary ducts of female Fischer 344 retired breeder rats. The ductal retention and in vivo antitumour efficacy of two of the six nanocarriers (5 kDa PEG‐DOX and 40 kDa PEG‐(DOX)<sub>4</sub>) were investigated based o</p> ... Show More
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Publication Date
Fri May 10 2019
Journal Name
Research Journal Of Chemistry And Environment
Solid Phase Extraction of Theophylline in Aqueous Solutions by Modified Magnetic Iron Oxide Nanoparticles as an Extractor Material and Spectrophotometry Technique for the Determination
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new, simple and fast solid-phase extraction method for separation and preconcentration of trace theophylline in aqueous solutions was developed using magnetite nanoparticles (MIONPs) coated with aluminium oxide (AMIONPs) and modified with palmitate (P) as an extractor (P@AMIONPs). It has shown that the developed method has a fast absorbent rate of the theophylline at room temperature. The parameters that affect the absorbent of theophylline in the aqueous solutions have been investigated such as the amount of magnetite nanoparticle, pH, standing time and the volume, concentration of desorption solution. The linear range, limit of quantification (LOQ) and limit of detection (LOD) for the determination of theophylline were 0.05-2.450 μg mL-

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Publication Date
Sun May 01 2016
Journal Name
Journal Of Engineering
Prediction of Ryznar Stability Index for Treated Water of WTPs Located on Al-Karakh Side of Baghdad City using Artificial Neural Network (ANN) Technique
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In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe

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Publication Date
Mon Jan 01 2018
Journal Name
نسق
Content analysis of the chemistry book for the third intermediate grade according to habits of mind in light of the educational reform project (2061)
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Publication Date
Wed Jul 24 2024
Journal Name
مداد الآداب
Navigating the Evolving Tourism Landscape: Examining the Challenges and Opportunities for TripAdvisor and Travelocity in the Era of AI:A Comparative Analysis of Innovation Strategies
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The tourism industry has undergone exponential transformation, reshaped by online travel agencies (OTAs), shifting consumer preferences, and technological advancements. Established OTAs like TripAdvisor and Travelocity face pressures to adapt their strategies to capitalize on these disruptive landscape changes. This research involves a comparative analysis examining the key challenges confronting TripAdvisor and Travelocity, with a focus on opportunities to leverage artificial intelligence (AI) in enhancing personalization and the traveler experience. The study utilizes publicly available data on the companies and academic literature on AI innovation diffusion. Findings reveal that while TripAdvisor has actively developed AI-based trip plan

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