KTH Matematik  

Matematisk Statistik

Tid: 24 september 2014 kl 10.15-11.00.

Rum 3721, Institutionen för matematik, KTH, Lindstedtsvägen 25, plan 7. Karta!

Föredragshållare: Fredrik Lannsjö

Titel: Forecasting the Business Cycle using Partial Least Squares (Master Thesis)

Abstract Partial Least Squares is both a regression method and a tool for variable selection, that is especially appropriate for models based on numerous (possibly correlated) variables. While being a well established modeling tool in chemometrics, this thesis adapts PLS to financial data to predict the movements of the business cycle represented by the OECD Composite Leading Indicators. High-dimensional data is used, and a model with automated variable selection through a genetic algorithm is developed to forecast different economic regions with good results in out-of-sample tests.

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Sidansvarig: Filip Lindskog
Uppdaterad: 25/02-2009