Graphical share market data rep .Net-Project
is a speculator on a Stock Market, aside from having money to spare, needs at least one other thing — a means of producing accurate and understandable predictions ahead of others in the Market, so that a tactical and price advantage can be gained.


This work demonstrates that it is possible to predict one such Market to a high degree of accuracy. Neural network predictions were obtained for the daily Market close 5 days ahead, and 25 days ahead, as measured in mean square error and in root mean square error.

To measure percentage accuracy, each individual test case prediction was compared with the actual market outcome, and total percentage accuracy for the whole test set was similarly calculated. Comparisons were also drawn with predictions for the same test cases using four types of Multiple Linear Regression.

The neural network results indicated that predictions based upon the lowest mean square error bear little relationship to the same test cases, when measured in terms of overall percentage accuracy.  


Existing System:     

       Maintaining the data of Stock Market manually is very difficult where we deal with huge amount of data and the data will be changing frequently depending upon the share market.

Viewing of the required data is also a big problem and end-user will not get the clear idea about the flow of the system.

Proposed System:

                    For the lay person, or a Stock-Market speculator, it was also shown that predictions can be produced to a high level of accuracy, in a readily understandable format. This application is totally integrated system with different sub systems like multi user Security, financial module integration. For now the software has the Organizer and Trader module. The organizer will hold all the master data that are required as part of the application. The Trader will involve uploading the daily Trade files received from NSE.

All this trade information’s are captured in the tables. The data from the master tables are displayed in different formats using reports as part of daily information to the clients who trade with the Stock brokers. Design and Development of Client, Organizer, Reports modules.