Predicting Investor Behaviour in European Bonds Markets - A Machine Learning Approach (Presentation Slides)
Posted: 25 Oct 2019
Date Written: September 20, 2019
Abstract
We are predicting primary market demand of investors in ESM bond issues using regression trees. Using a bagged tree methodology, we already get useful forecasts. Using feature impact, we characterize the behaviour of different investor types. On some single investors, the direction of demand change can be forecasted. Forecast quality is expected to improve considerably when enhancing database and refining technology.
Keywords: Bond markets, Investor behaviour, Order books, European Stability Mechanism, Market access
JEL Classification: G11, G23, D53, E44
Suggested Citation: Suggested Citation
Hillebrand, Martin and Winant, Bastien and Mravlak, Marko and Schwendner, Peter, Predicting Investor Behaviour in European Bonds Markets - A Machine Learning Approach (Presentation Slides) (September 20, 2019). Available at SSRN: https://ssrn.com/abstract=3457081
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