Monthly Archives: June 2017

An extensive evaluation of seven machine learning methods for rainfall prediction in weather derivatives

Rainfall is a crucial phenomenon within a climate system, whose chaotic nature has a direct influence on water resource planning, agriculture and biological systems. Within finance, the level of rainfall over a period of time is vital for estimating the value of a financial security. In this study we evaluate seven machine learning methods for rainfall prediction in the context of weather derivatives.
Continue reading