A comparison between classical (ARIMA) forecasting methods for time series and regression based on Support Vector Machines. A huge set of economic time series is available to train and validate foreasting methods

Skills required: basic computer science skills; python might be the language of chooice

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Candidate: Alberto Paruta. Start: may 2016

Forecasting time series with Support Vector Regression