Forecasting S&P500 Index Movement with Support Vector Machines
نویسندگان
چکیده
The aim of this research is to forecast the movement of SP&500 weekly. Support Vector Machine Classifier (SVMC) is used in order to examine the data. The data covers the period between 28/11/1997 and 29/12/2010. The inputs are technical analysis indicators such as the Moving Average Convergence Divergence (MACD) and the Relative Strength Index (RSI). SVMC is used to optimize the values of the MACD and RSI in order to determine the best situations to buy or sell the index. The two SVM outputs are the movement of the index and the probability of success to each forecast move. The best result has been achieved is a hit ratio of 92,3% using the SVM Classifier. The training data covers the period between 06/03/2009 and 06/10/2010. The testing data covers the period between 07/10/2010 and 29/12/2010. In conclusion, better results have been obtained analyzing short periods of S&P500 than using large periods.
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