NEURAL NETWORKS WITH TECHNICAL INDICATORS IDENTIFY BEST TIMING TO INVEST IN THE SELECTED STOCKS

Selections of stocks that are suitable for investment are always a complex task. The main aim of every investor is to identify a stock that has potential to go up so that the investor can maximize possible returns on investment. After identification of stock the second important point of decision making is the time to make entry in that particular stock so that investor can get returns on investment in short period of time. There are many conventional techniques being used and these include technical and fundamental analysis. The main issue with any approach is the proper weighting of criteria to obtain a list of stocks that are suitable for investments. This paper proposes an improved method for stock picking and finding entry point of investment that stock using a hybrid method consist of self-organizing maps and selected technical indicators. The stocks selected using our method has given 19.1% better returns in a period of one month in comparison to SENSEX index.