Data Mining

Topics: Stock market, Data mining, Stock Pages: 8 (2278 words) Published: December 30, 2013
Stock Exchange forecasting with Data Mining and Text Mining (Marketing and Sales Analysis)
Full names : Fahed Yoseph
TITLE : Senior software and Database Consultatnt
(Founder of Info Technology System)
Date of submission: Sep 15th of 2013
Chapter 1
2.1 The research problem. 4
2.2 The objectives of the proposal.4
2.3 The Stock Market movement.5
2.4 Research question(s).6
3.Problem Statement
5.Significance of the Research
6.Research Scope
7. Contributions
10.Research Methodology


4.1 Research design.7
4.2 Data sources 8
4.3 Data collection techniques.8
4.4 Definitions of key terms, concepts and variables.9
4.5 Data analysis and interpretation.9
4.6 Ethical considerations.10

5.1 What is Data Mining.8
5.2 Benefits of Data Mining 8
5.3 What is Text Mining .8
5.4 Benefits of Text Mining .8
5.5 Tasks accomplished by Data and Text Mining .9

5.6 Software Vendors .9


Stock Market prediction Using Data Mining is the pathway for an accurate financial prediction. Using Data Mining historical numbers and Text Mining historical documents and time series concurrently, such as predicting the movements of stock prices based the historical data and the historical contents of the news using Data digits and Texual Data. Stock market data analysis needs the help of software intelligence and data mining pointers. The stock prices depend on gains and losses of certain publicly traded companies and political and economical events. Many people consider the stock Market prediction as gambling. Many stock brokers are unaware of the fact it is possible to generate constructive patterns by the analysis of stock prices. Data mining techniques can be applied on past and present financial data to generate patterns and make the right decision based on the generated data. In this proposal I will touch base on several attempts made by Researches for stock price prediction. These works show that data mining and Text Mining techniques can be applied for evaluation of past stock numeric data and past Texual events (News Articles) and acquire valuable information to make a close prediction. 2.Introduction

The stock market is the backbone of fast developing economies. Major Of capital infusion for companies across the country was made possible only thru shares sold to people. So our country growth is tightly affected by the performance of the stock market. Almost all the developing nations rely on their stock market for further growth. Almost 70% of traders in the stock market investment fearing the risky nature of the stock market. Considering the fact of lack of knowledge and awareness across the people, Stock market prediction with Data Mining plays a very crucial role in bringing more investors into the Stock market as well as to retain the existing investors. Generating predictions based on the historical price values of selected stocks. The fundamental analysis approach is finding out the true value of a stock and compares it with the current trading value and then making the best possible recommendation for the investors to buy stocks traded less the current value and stocks with potential price increase. In the case of Time series prediction linear flow prediction models are generated and historic patterns are traced. The rapid progress in digital data acquisition has led to the fast growing amount Data stored in databases, data Mining, the overwhelming data volume makes it difficult for human beings to extract them without a powerful and intelligent program.

2.1 The research problem

Financial analysts who invest in stock markets usually are not aware of the stock market behavior. They are facing the problem of stock trading as they do not know which stocks to buy and...
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