Neural Prediction Of Weekly Stock Market Index

Neural Prediction Of Weekly Stock Market Index

The aim of this project is to predict the future values of the Standard & Poor’s 500 (S&P500) stock index based on its past values and the past values of some financial indicators.There have been many attempts at predicting stock market movements,most of them based on statistical time series models. Most of these attempts have been unsuccessful due to the complex dynamics of the stock market.The efficient market hypothesis says that stock prices rapidly adjust to new information by the time the information becomes public knowledge, so that prediction of stock market movements is impossible. This hypothesis seems to be correct for static and linear relationships explored traditionally using multiple regression tahlil. However, it is possible that dynamic and non-linearrelationships exist which cannot be modeled by traditional time series tahlil methods.This, is the motivation for application of neural networks to financial time series tahlil.

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