“Small data problems are where the amount of data available for model training is fundamentally limited. Small data problems often get a lot less attention than big data problems but they’re equally as important.” – Dr Chris Longworth “Why now? It comes down to several factors including computing power. We have seen a huge increase in the amount of computing power available and at a much lower cost.” – Dr Silvia Stanescu

Chris and Silvia presented a dynamic video, giving insights in a TED Talks style format into why small data is the new big data. Big data is key but small data is increasingly important. AI / machine learning uses historical data sets to learn and make predictions, but how does this work if the future is occurring ways we have not seen before? GAM Systematic thinks beyond the obvious and addresses the small data issue. If one has the expertise and specialisation to understand this, one can create investment products to support portfolio characteristics like positive convexity and liquidity / liquid diversifiers.