A Sober Walk Down Wall Street, Risks and Benefits of a Trend Following Strategy

Sammanfattning: This thesis examines an investment strategy referred to as trend following. We construct a rule-based trading algorithm, built solely on past prices and volatility, aiming at capturing trends in futures markets. We explore whether standard theoretical risk factors and more recently presented momentum-related risk factors can explain the time-variation in trend following excess returns. A holistic perspective is also exerted, in which the impact of including a divergent component to a standard 60/40 portfolio (a portfolio that is 60% invested in equities and 40% invested in bonds) is examined. The strategy is tested against an investment universe comprising of 76 global and liquid futures contracts, to represent a real-life implementable strategy. Our results show a low explanatory power of standard theoretical risk factors and a statistically significant positive alpha, amounting to 0.9% on a monthly basis. This finding challenges the random walk hypothesis and shed new light on the often criticised field of technical analysis. We document a significant and positive relationship between the strategy and time series momentum. Despite this, the strategy generates a positive and significant alpha of 0.4% on a monthly basis above time series momentum. This implies that intuitive trading-rules based on past price movements are efficient tools that can be utilised to create alpha. The strategy also delivers a positive and significant alpha above the industry benchmark, suggesting that Commodity Trading Advisor (CTA) funds occasionally divert from their core principals, in favor of less successful strategies. Finally, we find evidence that the inclusion of a trend following component to a standard 60/40 portfolio can increase risk-adjusted returns, reduce left-tail risk and enhance the ability to recover following drawdowns.