In the past few decades, stock market

In
the past few decades, stock market prediction became one of the major fields of
research due to its wide domain of financial applications. Stock market is
known for its dynamic nature, complication and non-linear nature. It is also
known as the equity market,
the stock market is one of the most vital components of a free-market economy.
Artificial neural network has seen massive interest in the over the last few
years. ANN is used in many areas like finance, medicine, research and
development and engineering. ANNs are mathematical models which were inspired
from the understanding of some ideas and aspects of the biological neural
systems such as the human brain. ANN may be considered as a data processing
technique that maps, or relates, some type of input stream of information to an
output stream of processing

“A
neural network is a system composed of many simple processing elements
operating in parallel whose function is determined by network structure,
connection strengths, and the processing performed at computing elements or
nodes” – DARPA Neural Network Study (1988).

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In
past traditional methods were used to predict stock market. After much research
it was observed that significant profit can be achieved even with slight
improvement in the prediction since the volume of trading in stock markets is
always huge. There are two methods used in this field

1)Statistics model: These are statistical
based approaches such as linear regression, Auto-regression and Auto-regression
Moving Average

2)Soft Computing: This technique includes
ANN, fuzzy logic, genetic algorithm.

A multilayer neural network has been used as
an universal function approximator(input, hidden layer and output) finds its
use in a number of fields like sales forecasting, data validation, customer
research, price forecasting, healthcare etc

Though
fuzzy logic and genetic algorithm are also used for stock prediction however, ANN
is one of the successful method which is widely used in solving prediction
solution. ANNs was used to solve variety of problems in financial time series
forecasting. For example, prediction of stock price movement became easier
using ANN model.

Neural
network has become an important method for stock market prediction because of
their ability large data sets which change rapidly in very short period. In
Feedforward (FF) Multilayer Perceptron (MLP), which is one of the 

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