At Winton it all starts with data. We gather and clean vast, rich datasets. Not only financial data, but anything that might help us to understand how markets behave. Our approach is rooted in science and statistical inference, rather than financial theory - and implemented by a large team of researchers with backgrounds ranging from bioinformatics to astrophysics.
Using statistical and mathematical modelling, data visualisation, pattern recognition and machine learning techniques, we tease out subtle predictive signals that form the basis of our investment systems. Such signals are always weak and barely distinguishable from noise, which is why our researchers are drawn from academic disciplines where techniques for dealing with low signal-to-noise ratio problems have been honed. Our expertise in determining the statistical strength of our research findings - combined with appropriate risk and cost controls - underpins the design of our investment strategies.
Our significant investment in this research-led approach is dedicated to our aim of delivering long-term capital appreciation for our investors.
We’ve been at the forefront of the quantitative approach to systematic investing for more than 20 years.