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|Title:||Stock forecasting system||Authors:||He, Hong.||Keywords:||DRNTU::Engineering::Electrical and electronic engineering::Applications of electronics||Issue Date:||2009||Abstract:||In stock market, the successful prediction of stock price movements, coupled with an appropriate trading strategy, will result in substantial monetary rewards. Currently, a number of stock analysis methods have emerged for stock prediction tasks. Among them is technical analysis. Technical analysis is a way of gathering and processing price and volume information of a particular security by applying mathematical equations and then plotting the resulting data onto graphs to predict future price movements. It is a very popular method used for stock price predictions, which however is quite complex. Nowadays, there are various technical analysis theories coming out, and therefore, using technical analysis to predict stock price movements with high accuracy has always been a great concern. This report will explain how to utilize the technical analysis to earn profit. Firstly, the theoretical background of technical analysis is reviewed, and followed by the technical analysis which is applied to five securities, DBS, Capital Land, SIA, UOB and SingTel, selected from Singapore stock market. Subsequently, a stock forecasting methodology is proposed, and a stock forecasting system is built based on the forecasting methodology using platform of MATLAB. At the last stage, the system is evaluated by applying the actual data from the securities, DBS, Capital Land, SIA, UOB and SingTel. This system is revealed to achieve an overall hit rate up to 46% to make a profit larger than 5%. The most inspiring point is that there are no negative total profits made for any of the selected 5 securities. The result shows that this system is adequate to facilitate the trader to make trading decisions. Meanwhile, this system can also help the investor to analyze the stocks’ appreciation potential. In a word, this forecasting system is an effective guiding tool for investment in Singapore stock market.||URI:||http://hdl.handle.net/10356/18401||Rights:||Nanyang Technological University||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Student Reports (FYP/IA/PA/PI)|
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Updated on Dec 5, 2020
Updated on Dec 5, 2020
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