Risk.net Synthetic data made with machine learning will struggle to capture the caprice of financial markets Quant investors often complain they have only a single version of history against which to test their ideas. One way to get round the problem has been to make history up. Quants have done that for a long time already – using bootstrapping or Monte Carlo simulations to create alternative time series data for the backtests they run. A new idea, though, is to employ machine learning techniques to invent wholly artificial data. Quants are experimenting with these models and say they can produce data indistinguishable in some cases from the real thing.