A Study on use of Artificial Intelligence for Stock Market Prediction - An Exploratory Re

Stock market predictions are driven both by data published by stock exchanges as well as human behaviour (behavioural finance). To a large extent human interventions in a decision making process may lead to wrong judgements there by resulting in losses to the investors. Institutional investments are more risky since it involves huge money of large no of investors. This has led to need for more predictive behaviour: which could best be achieved through artificial intelligence. Artificial intelligence helps  in  conceiving  large  quartiles  of  data  there  by  making  investment  decisions more accurate. It summarizes the findings of systematic approach over building trade system and an application of artificial intelligence (mainly genetic algorithms and neural networks). To find out the best solutions while the use of artificial intelligence principles gives traders a powerful tool in building robust trading system. This study pertains to historical data as well as the conclusions derived from analysing other extual data including quarterly results and press release.