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Document Details
Document Type
:
Thesis
Document Title
:
Using Personal informatics System and Genetic Algorithm to improve investment in stock market
استخدام نظام المعلومات الشخصية والخوارزميات الجينية لتحسين الاستثمار في سوق الأسهم
Subject
:
Faculty of Computing and Information Technology
Document Language
:
Arabic
Abstract
:
The financial market is extremely attractive since it moves trillion dollars per year. Several investors have been investigating a way to predict future prices by using a variety of algorithms that use fundamental analysis and technical analysis. These tools are used by either professional speculators or amateurs to analyze the price movement of some financial assets. The use of genetic algorithms, neural networks, genetic programming combined with these tools in an attempt to find a profitable solution is very common. This study presents a prototype that utilizes personal informatics system (PI) and genetic algorithms (GAs) for short-term stock index prediction. The system works according to the following scheme: first, a pool of input variables are defined through technical data analysis. Then GA is applied to find an optimal set of input variables for a one day prediction. The data is gathered from the Saudi Stock Exchange (being the target market). Using PI will create a smart environment which enables the prototype to know user’s interests, provide privacy, and display results in professional way. The experimental results show that this way of predicting the stock price is promising. The highest accuracy obtained is 64.67% and the lowest one is 48.06%.
Supervisor
:
Dr. Salha Abdullah
Thesis Type
:
Master Thesis
Publishing Year
:
1438 AH
2017 AD
Added Date
:
Thursday, June 8, 2017
Researchers
Researcher Name (Arabic)
Researcher Name (English)
Researcher Type
Dr Grade
Email
خلود سالم البلادي
Albeladi, Khulood Salem
Researcher
Master
Files
File Name
Type
Description
40866.pdf
pdf
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