Fundamental analysis and technical analysis integrated system for stock filtration

• Main Authors: Eiamkanitchat N., Moontuy T., Ramingwong S.
• Format: Journal
• Published: 2017
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85000673434&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/40667
• Institution: Chiang Mai University

© 2016, Springer Science+Business Media New York. Fundamentals and technical investigation is a technique which enhances decision making for stock investors. The fundamental analysis includes looking at any information, other than the trading patterns of the stock itself, which can affect the cost and the perceived value of a stock. Technical analysis is an exchanging apparatus utilized to assess securities and endeavor to forecast their future development by breaking down insights accumulated from exchanging action, such as price movement and volume. This system utilizes data mining techniques to analyze various stock information and the factors to create a logical decision model. This helps new and inexperienced investors to make less errors as well as make the stock market more approachable to the general community. This research focuses on a high performance stock selection using the fundamental analysis of individual stocks, which is reflected in the financial statements. Ten criteria calculated from stock financial statement reports are proposed for the analysis. The 10 years of historical fundamental information on organizations recorded in Thailand stock exchange were clustered into three groups and used the fundamental criteria to classify the interesting return stocks selection. The multilayer perceptron neural network is used in the training process to verify the clustering results. For the technical analysis, experimental results reveal that the exponential moving average technique is the most favorable and thus being selected to apply in our system. To affirm the productivity of the suggested stocks, an experiment using information from the system’s decision model based on the Stock Exchange of Thailand data in the year 2015 is conducted. After the activities from 5000 simulated portfolios, the average returns of the ports are positive. In fact, the ports gain almost three times higher than the average market yield. This indicates the efficiency of the system’s stock filtering and decision making capabilities.