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India | Computer Science Engineering | Volume 4 Issue 6, June 2015 | Pages: 1958 - 1963
Using Association Rule Mining: Stock Market Events Prediction from Financial News
Abstract: Ability to predict direction of stock price accurately is very crucial for market dealers or investors to maximize their profits. Decision-making such as whether to buy, sell or hold of shares for investor in stock market is also another difficult task. Data mining techniques have been successfully shown to generate high forecasting accuracy of stock price movement and corresponding signals. Prediction of stock price is the activity of determining future state of the stock price by using various techniques. In presented work Data Mining Technique such as Association Rule Mining is used for prediction of stock market. Prediction is depends on technical trading indicators and closing prices of the stock. Rules are defined according to signal generated by each technical trading indicator and mapped across the current date query to generate the signals like buy, sell or holds the shares.
Keywords: Stock market prediction, Decision making, Association rule Mining, Data mining technique, Nave Bayes
How to Cite?: Shubhangi S. Umbarkar, Prof. S. S. Nandgaonkar, "Using Association Rule Mining: Stock Market Events Prediction from Financial News", Volume 4 Issue 6, June 2015, International Journal of Science and Research (IJSR), Pages: 1958-1963, https://www.ijsr.net/getabstract.php?paperid=SUB155622, DOI: https://dx.doi.org/10.21275/SUB155622