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The effect of technical indicators on the movement of bank stock prices : Applied research in a sample of Iraqi private commercial banks
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This study aimed at indicators of technical analysis and their impact on a group of trading stock indices related to it, by standing on the methods used in technical analysis and its various models, diagnosing the obstacles and difficulties that the participants face in predicting stock prices, and proposing solutions and recommendations to overcome and overcome them. From a scientific and practical perspective.

Where the research community consisted of (25) Iraqi private commercial banks, while the research sample consisted of (3) banks with a percentage of (12%) of the research community. The study used the analytical approach to the financial statements during the period between (1/2/ 2022-30/4/2022), where the financial data (closing prices) for the shares of the banks of the research sample were calculated through the mathematical equations of the technical indicators, and then they were represented in the form of graphs to clearly identify the trading signals (buying and selling), and then the data was analyzed Using the statistical program (SPSS) to test the research hypotheses, where the results showed an effect between technical indicators (Relative Strength Index, Stochastic Indicator), and predicting stock price movement (sell signal, buy signal).

The study came out with a number of recommendations, the most important of which is the need for private Iraqi commercial banks to enhance the position of technical analysis as a qualitative tool used to improve the investor’s decision and increase the ability to analyze and forecast. The Academy should increase the spotlight on technical analysis by encouraging research and studies because of its great importance to the decision to invest in stocks in the future.

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Publication Date
Sun Sep 01 2024
Journal Name
Results In Engineering
Indole derivatives efficacy and kinetics for inhibiting carbon steel corrosion in sulfuric acid media
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Publication Date
Thu Oct 31 2019
Journal Name
Journal Of Theoretical And Applied Information Technology
AN ENHANCED EVOLUTIONARY ALGORITHM WITH LOCAL HEURISTIC APPROACH FOR DETECTING COMMUNITY IN COMPLEX NETWORKS
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Publication Date
Tue Dec 31 2024
Journal Name
Iraqi Geological Journal
Geomechanical Modeling and Artificial Neural Network Technique for Predicting Breakout Failure in Nasiriyah Oilfield
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Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Civil Engineering And Technology
Generalized tupled common fixed point theorems for weakly compatible mappings in fuzzy metric space
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Publication Date
Mon Nov 09 2015
Journal Name
Nternational Conference On Modern Trends In English Language And Literature/ Applied Linguistics Theme
Investigating EFL College Student's Errors in Recognizing and Producing Modal Auxiliary Verbs
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DBN Dr. Liqaa Habeb, International Journal of Multidisciplinary Reseach, 2015

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Publication Date
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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Publication Date
Wed Sep 09 2020
Journal Name
Frontiers In Plant Science
Red Light Controls Adventitious Root Regeneration by Modulating Hormone Homeostasis in Picea abies Seedlings
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Publication Date
Fri Nov 02 2018
Journal Name
Aci Special Publication
CFRP Repairing System at Openings in Reinforced Concrete T-Beams Cracked by Impact Loads
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Publication Date
Thu Aug 02 2018
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Performance Study for Mixed Transforms Generated by Tensor Product in Image Compression and Processing
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In all applications and specially in real time applications, image processing and compression plays in modern life a very important part in both storage and transmission over internet for example, but finding orthogonal matrices as a filter or transform in different sizes is very complex and importance to using in different applications like image processing and communications systems, at present, new method to find orthogonal matrices as transform filter then used for Mixed Transforms Generated by using a technique so-called Tensor Product based for Data Processing, these techniques are developed and utilized. Our aims at this paper are to evaluate and analyze this new mixed technique in Image Compression using the Discrete Wavelet Transfo

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Publication Date
Fri Jan 01 2021
Journal Name
Int. J. Nonlinear Anal. Appl.
Rough continuity and rough separation axioms in G<inf>m</inf>-closure approximation spaces
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The theory of general topology view for continuous mappings is general version and is applied for topological graph theory. Separation axioms can be regard as tools for distinguishing objects in information systems. Rough theory is one of map the topology to uncertainty. The aim of this work is to presented graph, continuity, separation properties and rough set to put a new approaches for uncertainty. For the introduce of various levels of approximations, we introduce several levels of continuity and separation axioms on graphs in Gm-closure approximation spaces.

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