Trading ebook Finance - Neural Prediction of Weekly Stock Market Index

However it is possible that dynamic and non linear

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Unformatted text preview: analysis. However, it is possible that dynamic and non-linear relationships exist which cannot be modeled by traditional time series analysis methods [3]. This, is the motivation for application of neural networks to financial time series analysis. A huge amount of research is being done on the application of neural networks to stock markets. Some of the applications include prediction of IBM daily stock prices [4], a trading system based on prediction of the daily S&P 500 index [5], short term trend prediction using dual-module networks [6], weekly index prediction [7], monthly index prediction using radial basis functions [8] etc. Some of these papers use the past values of the stock index only, as the input to the neural network so as to obtain the future values, while some use additional fundamental and financial factors as inputs. This project explores the effect that short and long term interest rates have on the stock market, in particular on the S&P 500 index. It is well known that an increase in interest rates tends to lower the stock market a...
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This note was uploaded on 07/20/2012 for the course ECON 203 taught by Professor Girishdev during the Spring '12 term at Indian Institute of Technology, Kharagpur.

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