This paper explores sentiment-based trading strategies in commodity futures and investigates how momentum strategies can be enhanced with news sentiment. For several commodities, representing the main three commodity classes (energy, metals and agriculturals), we investigate the relationships between daily futures returns and commodity-specific news sentiment, obtained from Thomson Reuters News Analytics (TRNA).
We show that, for several commodities, sentiment-based trading strategies are profitable and that they outperform benchmark strategies that do not rely on sentiment. Furthermore, combining these trading strategies into a portfolio, i.e., executing several trading strategies simultaneously, leads to a high degree of diversification and significantly reduces the overall risk without sacrificing the return.
Dr Svetlana Borovkova
Currently an Associate Professor of Quantitative Finance at the Vrije Universiteit Amsterdam, Dr Svetlana Borovkova has specialized in applying mathematical and statistical methods to problems within quantitative finance and risk management.
Dr Borovkova's research extends in many areas, such as news analytics for finance, derivatives pricing, commodity markets and risk management in the face of new regulation.
She is also a consultant for the Dutch Central Bank and the founder and principal consultant of DataDecisions: Financial Risk Consultancy. Dr Borovkova is a frequent speaker on international conferences, such as Global Derivatives, Risk Minds, Bachelier Congress for Mathematical Finance, Sentiment Analysis and Behavioural Finance and others. Previously she held an assistant professor position in Delft University of Technology and a trading analyst position in Shell Trading, London.
She got her PhD in 1998 from the University of Groningen, The Netherlands, and Oregon State University, USA and MSc degree in applied mathematics and computer science from Moscow and Utrecht.