The purpose of this study is to evaluate the predictive power of ARMA/GARCH models through the implementation of a momentum strategy on all stocks traded on the New York Stock Exchange (NYSE) and the NASDAQ stock market. The data series is tested for serial-correlation in their daily stock price returns, followed by several screening and filtering phases. A floating order ARMA/GARCH model is used to capture the signal from the noise in the data, which is used to forecast future prices. It is shown that the tickers that are successfully predictable carry their momentum into the short-term future. A trading strategy is then proposed and tested to validate the above market returns resulted from this predictive behavior of the tickers.
MSc of Finance Project-Simon Fraser University
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