Stock Market Timing Decisions Using Neuro Rough Set Forecasting Model

Modeling share market is a very difficult work for practitioners because of very chaotic and volatile characters of facts. Conversely, it is done by many experimental studies and a number of applied researchers have proficiently applied machine learning procedures to project stock market. It is all the times true shareholders in general get loss because of uncertain investment purposes and unsighted assets. This paper proposes a hybrid neuro rough set model to find optimal buy and sell of a share on Chittagong stock market. Our experimental results exhibit that the recommended hybrid model has higher precision than other considered forecasting models selected for this study. We believe that findings of this paper will be useful for stock investors to make a decision about optimal buy and/or sell time on this stock market.