Edgar van Tuyll van Serooskerken, head of Quantitative Strategies at Pictet Wealth Management, explains how Pictet uses machine learning for two purposes: first, to hunt for profitable investment opportunities; and second, to search for patterns in big data that are similar to those of past periods. For the first use, machine learning can sift through the mass of data we now have on the past prices of assets in various classes, on company performance and on macro-economic developments, in order to look for hidden treasure. It will hunt for relationships between data points that could allow us to make returns and we study them with our experts to see if they make sense – we don't just trust the machine and trade off them. Nonetheless, since 2013 we have come up with a whole series of automated strategies, which have beaten the hedge fund index by a wide margin. They tend to reflect human behaviour which doesn't change very much and makes those strategies stable for long periods.