We propose a prediction model based on the minority game in which traders continuously evaluate a complete set of trading strategies with different memory lengths using the strategies’ past performance. Based on the chosen trading strategy they determine their prediction of the movement for the following time period of a single asset. We find empirically using stocks from the S&P500 that our prediction model yields a high success rate of over 51.5% and produces higher returns than a buy-and-hold strategy. Even when taking into account trading costs we find that using the predictions will generate superior investment portfolios.
|Number of pages||8|
|Publication status||Published - 2009|
|Event||Intelligent Data Engineering and Automated Learning - IDEAL 2009 - Burgos, Spain|
Duration: 23 Sep 2009 → 26 Sep 2009
|Conference||Intelligent Data Engineering and Automated Learning - IDEAL 2009|
|Period||23/09/09 → 26/09/09|