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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 Dec 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Use Generalized Pareto Survival Models to Estimation Optimal Survival Time for Myocardial Infarction Patients
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The survival analysis is one of the modern methods of analysis that is based on the fact that the dependent variable represents time until the event concerned in the study. There are many survival models that deal with the impact of explanatory factors on the likelihood of survival, including the models proposed by the world, David Cox, one of the most important and common models of survival, where it consists of two functions, one of which is a parametric function that does not depend on the survival time and the other a nonparametric function that depends on times of survival, which the Cox model is defined as a semi parametric model, The set of parametric models that depend on the time-to-event distribution parameters such as

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