Ramon de Punder

I develop quantitative models for forecasting asset returns and their distributions, with a particular interest in online stochastic-gradient methods and forecast evaluation for portfolio risk management. At SlimBieden, I lead the model development team behind a production pipeline that turns machine-learning models into distributional forecasts sold daily to consumers and businesses in the Dutch housing market. My academic research develops the statistical and mathematical theory underlying these methods, with work published in the Journal of the American Statistical Association.