slugObtaining an Accurate and Comprehensive Data Mining Model
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2014, Vol 2, Issue 6
Abstract
It is important for shareholders and potential investors to use relevant financial information to enable them to make good investment decisions in the stock market. Predicting stock performance is certainly very complicated and difficult. In the history of stock performance literature, no comprehensive, accurate model has been suggested to date for predicting stock market performance. A stock’s performance can, to some extent, be analyzed based on financial indicators presented in the company’s annual report. The annual report contains a vast amount of information that can be transformed into various ratios. Previous literature suggests that financial ratios are important tools for assessing future stock performance. Analysts, investors, and researchers use financial ratios to project future stock price trends. Ratio analysis has emerged, therefore, as one of the key parameters used by fund managers and investors to determine the intrinsic value of stock shares; thus, financial ratios are used extensively for the valuation of stock. Considerable attention has been given to understand the relationship between price and trading volume. Researchers have used opening price, closing price, day high price, day low price, average of these, return, Volatility in price as proxy of price of stock and average volume, traded volume, delivered volume, turnover (rupee value of total trade) as proxy of volume. It is better to use prediction interval than confidence interval. Prediction interval will be suited for both delivery and intraday trading. It is better to judge level of volume when market has started to have some practical significance of model. Trading volume of stock of constituent companies of CNX IT Index has feeble impact on closing prices. This could be due to the fact that market is in CNX IT Index is in correction stage due to higher expectations of traders regarding performance of companies. Finally, it can be said that linear regression model can be used to make educated guess for closing price of stock and level of index.
Authors and Affiliations
Anupa Sinha, Dr. S. K. Shrivastava
Keywords
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