Big Data 2.0 The future of quantitative investing Raffaele Savi Co Head, Scientific Active Equity October 2016
I spent the last several years answering these questions What s the big deal about big data, machine learning and artificial intelligence? Do they really matter for investing or is it just marketing? Do you really make any money out of it? 2
1/3: It s always all about alpha Fundamentals Big Data Text Macroeconomics Machine learning Internet search Flows Competitive dynamics Quality of management Supply/demand imbalance All or none of the above You choose α Natural language processing Cloud computing You name it Social medial Vision Sensors The startup that will show up next Monday at your office 3
2/3: A world of possibilities. For illustrative purposes only 4
3/3: It s often more familiar than you think More leading Online Search GPS traffic data E-transactions receipts Booked sales Website traffic Satellite images Credit card data More accurate 5
Lately I started getting different questions 6
A big, big change is coming Small Data Low Dimensionality Linear, Static Big Data High Dimensionality Non Linear, Dynamic 7
Three important consequences 1 Process and roles 2 Breadth and depth 3 Horizon and impact From: batch research, modular investment process To: online learning, end-toend agents From: broad and persistent factors To: stock specific, time specific models From: intraday focus, low reach/impact To: multi-month horizon focus, high reach/impact 8
More important than ever 9
It s a wonderful time to be a quant Small Data Low Dimensionality Linear, Static Big Data High Dimensionality Non Linear, Dynamic A lot of energy and talent today still spent on marginal research It won t matter in the end: it s going to be either smart beta or big data The transition is in full swing, the industry is changing The best is yet to come 10
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