• Dr.M.Kumarasamy

Abstract : The purpose of this paper is to improving the predictions of stock market prices using latest technologies like artificial neural networks and deep neural networks. Already predictions of stock market prices done by time series and forecasting analysis. With the introduction of our latest technologies, further we can improve the predictions of stock market prices. It can be very useful for the stock market analyzers and business people who are involving in the share trading. With their ability to discover patterns in nonlinear and chaotic systems, neural networks offer the ability to predict market directions more accurately than current techniques. We can define the stock market as, stock is a share in the ownership of a company. Stock represents a claim on the company's assets and earnings. As you acquire more stock, your ownership stake in the company becomes greater. Whether you say shares, equity, or stock, it all means the same thing. Common market analysis techniques such as technical analysis, fundamental analysis, time series, forecasting analysis and regression are discussed and compared with neural network performance.

Keywords : Stock Market, Technical Analysis, Machine Learning, Time Series, Forecasting Analysis

"IMPROVING PREDICTION OF STOCK MARKET PRICES USING DEEP NEURAL NETWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.670-676, June 2019, Available :http://www.jetir.org/papers/JETIR1907M89.pdf

"IMPROVING PREDICTION OF STOCK MARKET PRICES USING DEEP NEURAL NETWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp670-676, June 2019, Available at : http://www.jetir.org/papers/JETIR1907M89.pdf