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dc.contributor.authorNdiritu, John M
dc.date.accessioned2013-05-20T15:10:10Z
dc.date.available2013-05-20T15:10:10Z
dc.date.issued2010
dc.identifier.citationM.Sc (Information Systems)en
dc.identifier.urihttp://erepository.uonbi.ac.ke:8080/xmlui/handle/123456789/23977
dc.descriptionMaster of Science Thesisen
dc.description.abstractStock exchanges like the Nairobi Stock Exchange (NSE) release daily, weekly, and other periodic data. This data, if filtered and stored can be of important use for stock market analysis using technical analysis methods. Currently technical analysis tools are being developed due to their perceived added advantage to those analysts who use them over those who don't. Emphasis has been on moving average based trading systems which are the simplest and most popular trend-following systems among practitioners. According to the (dual) moving average method is one of the few technical trading procedures that is statistically well defined. Both the Simple Moving Average (SMA) and the Exponential Moving Average (EMA) have been used in the system decision support. The Dual Moving Average Crossover system generates trading signals by identifying when the short-term trend rises above or below the longterm trend The goal of this project IS to develop a Technical Trading Support System (TTSS), an information system that uses selected technical indicators and charts overlay tool that can be used by market analysts and professionals. The system is developed to enable the users t9 store the data, to generate charts that aid data visualization, identify trend and enhance arralyst decision making process. System analysis, design and development methods are used to analyze, design, document, build and test the system.en
dc.description.sponsorshipUniversity of Nairobien
dc.language.isoenen
dc.titleTechnical Trading Support System (TTSS); A Stock Market Analyst Support Systemen
dc.typeThesisen
local.publisherSchool of computing and informatics, University of Nairobien


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