Analysis and forecasting of financial time series using artificial neural network

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Date
2017-07
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G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand)
Abstract
Present work entitled “ANALYSIS AND FORECASTING OF FINANCIAL TIME SERIES USING ARTIFICIAL NEURAL NETWORK” treated the issue of developing an artificial neural network model which generates a buying signal based on Golden crossover and sell signal if 50 DMA crosses below 200 DMA and also, forecasts the stock index for future. Artificial neural networks are very good in the stock market prediction as they are non-linear and complex models. In this work, we have used the artificial neural network to predict the stock index and behavior (buy or sell signal) of financial time series. The presented study comprises five chapters. The first chapter is aimed to fulfill the basic need of introducing time series, artificial neural network and the use of neural network in the time series forecasting. Chapter two accomplished majority of passed research work related with the present work. Chapter three covers the material and methods used for the present study. We have presented the neural network for the prediction and simulated it in MATLAB software. Chapter four describes the result and discussion of the encountered taken in chapter three. The work has been summarized in chapter five. Along with the finding of the study, the literature used in the course of the study has been referred under the section of literature cited. The related study may be helpful for the investors of stock market to make wise decisions so that they can have maximum profit.
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