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
. This, is the motivation for application of neural networks to financial time series
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 , a
trading system based on prediction of the daily S&P 500 index , short term trend
prediction using dual-module networks , weekly index prediction , monthly index
prediction using radial basis functions  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.
- Spring '12