Proposed investment decision support system for stock exchange using text mining method

Author(s):  
Salam Al-augby ◽  
Sebastian Majewski ◽  
Kesra Nermend ◽  
Agnieszka Majewska
2020 ◽  
Vol 11 (02) ◽  
Author(s):  
Lucky Kartanto

At present, investment is well known in Indonesian society, investment awareness by the public has begun to increase along with the existence of several investment instruments that are widely offered by bank financial institutions, non-bank financial institutions, as well as various types of investment options on the Indonesia Stock Exchange. According to Sophar Lumbantoruan (1996), the notion of investment is equity participation in other companies. One form of investment known to the general public is shares traded on the Indonesia Stock Exchange. Investing always considers the results and risks that will be faced by Investors. Not all investors understand the theory of investing in stocks, especially in selecting shares in a portfolio in order to produce a certain rate of return with minimal risk. This study aims to find a decision support system (DSS) based on Financial Technology that will provide information related to stock recommendations that should be bought by investors. Stock Selection in this study are shares of listed companies listed on the Kompas 100 Index, the Analysis Technique used in this study is the Single Index Model. This research can produce recommendations for investors to buy shares in a portfolio that will provide certain benefits with minimal risk. Keyword- Investment, Decision Support System, Financial Technology, Single Index Model, Porfolio


Author(s):  
Prasanta Kumar Dey

The evaluation and selection of industrial projects before investment decision is customarily done using marketing, technical, and financial information. Subsequently, environmental impact assessment and social impact assessment are carried out mainly to satisfy the statutory agencies. Because of stricter environment regulations in developed and developing countries, quite often impact assessment suggests alternate sites, technologies, designs, and implementation methods as mitigating measures. This causes considerable delay to complete project feasibility analysis and selection as complete analysis requires to be taken up again and again until the statutory regulatory authority approves the project. Moreover, project analysis through the above process often results in suboptimal projects as financial analysis may eliminate better options as more environment friendly alternative will always be cost intensive. In this circumstance, this study proposes a decision support system which analyses projects with respect to market, technicalities, and social and environmental impact in an integrated framework using analytic hierarchy process, a multiple attribute decision-making technique. This not only reduces duration of project evaluation and selection, but also helps select an optimal project for the organization for sustainable development. The entire methodology has been applied to a cross-country oil pipeline project in India and its effectiveness has been demonstrated.


Symmetry ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1426
Author(s):  
Mehmet Erkan Yuksel ◽  
Huseyin Fidan

Grey relational analysis (GRA) is a part of the Grey system theory (GST). It is appropriate for solving problems with complicated interrelationships between multiple factors/parameters and variables. It solves multiple-criteria decision-making problems by combining the entire range of performance attribute values being considered for every alternative into one single value. Thus, the main problem is reduced to a single-objective decision-making problem. In this study, we developed a decision support system for the evaluation of written exams with the help of GRA using contextual text mining techniques. The answers obtained from the written exam with the participation of 50 students in a computer laboratory and the answer key prepared by the instructor constituted the data set of the study. A symmetrical perspective allows us to perform relational analysis between the students’ answers and the instructor’s answer key in order to contribute to the measurement and evaluation. Text mining methods and GRA were applied to the data set through the decision support system employing the SQL Server database management system, C#, and Java programming languages. According to the results, we demonstrated that the exam papers are successfully ranked and graded based on the word similarities in the answer key.


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