Strength and Money: An LCS Approach to Increasing Returns

This paper reports on a number of experiments where three different groups of artificial agents learn, forecast and trade their holdings in a real stock market scenario given exogeneously in the form of easily-obtained stock statistics such as various price moving averages, first difference in prices, volume ratios, etc. These artificial agent-types trade while learning during

• Type: Conference
• Year: 2000
• Where: IWLCS
• Authors: Sonia Schulenburg, Peter Ross
• Keywords: Artificial Agent-types Trade, IWLCS 2000, Machine Learning, Stock Market, Stock Market Scenario