Trading System Based on Support Vector Machines in the S&P500 Index
نویسندگان
چکیده
The aim of this paper is to develop a trading system based on Support Vector Machines (SVM) in order to use it in the S&P500 index. The data covers the period between 03/01/2000 and 30/12/2011. The inputs of the SVM are different forecasting algorithms: Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Momentum, Bollinger Bands and the Chicago Board Options Exchange Volatility Index (VIX). A SVM Classifier has been used in order to develop the trading system with a weekly forecast. The output of the SVM is the decision making for investors. The trading system works better in bearish movement of the S&P500 than bullish movement of the S&P500.
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تاریخ انتشار 2012