RETURN PERFORMANCE VOLATILITY AND ADAPTATION IN AN AUTOMATED TECHNICAL ANALYSIS APPROACH TO PORTFOLIO MANAGEMENT

摘要

This paper discusses the design of a quantitative computational intelligence portfolio management system and evaluates the advantages of some adaptive mechanisms to enable the system to adjust its management approach as market conditions change. A detailed analysis of the performance of the system outside is also provided. It is found that an adaptive methodology where trading rules are able to adjust to market conditions performs better, having greater excess returns and lower volatility than a fixed rule approach. We consider several performance metrics, including portfolio alpha and information content.