Recently, Diebold and Li (2003) obtained good forecasting results for yield curves in a reparametrized Nelson-Siegel framework. We analyze similar modeling approaches for price curves of variance swaps that serve nowadays as hedging instruments for options on realized variance. We consider the popular Heston model, reparametrize its variance swap price formula and model the entire variance swap...

• We present a system to forecast crop yield with machine learning at regional level. This fully automated selects the best features and model. Leaving one year out is required rigorously assess model performance. Yield forecasts based on are accurate even in low-yielding years. Extensive calibration deliver significant gains predictive power. Forecasting yields important for food security, par...

Model reuse can be limited by software design, which often forces third parties to completely rewrite new versions of existing models before adapting them to new needs. This tendency removes resources from the development and improvement of models, and from the extension of their domain, leading to the proliferation of software having many different implementations of the same algorithms. A com...