Armed conflicts pose significant challenges for the international community. They prevent countries from developing, lead to a persistent outflow of refugees, and have a significant death-toll. For this reason, the ability of policymakers to prevent outbreaks and escalations is crucial. However, it is not an easy task.
Victor DeMiguel, Javier Gil-Bazo, Francisco J. Nogales and André A.P. Santos use three ML models improve fund performance predictions.
Hannes Mueller and Christopher Rauh present a new method of predicting conflict through news topics which are generated automatically from a topic model.