Sebastian Stöckl
Sebastian Stöckl
Home
CV
Blog
Research
Selected Publications
Working Papers
Research Projects
All papers
Talks
Teaching
Current teaching
Historic teaching & evaluations
Thesis topics
Links to Code & Data
Media Coverage
Contact
Light
Dark
Automatic
unsupervised machine learning
Diversifying Estimation Errors with Unsupervised Machine Learning
We use unsupervised machine learning to cluster stocks into equally weighted portfolios which in turn are plugged into minimum variance optimization.
Merlin Bartel
,
Sebastian Stöckl
Cite
ECSO-CMS 2022
World Finance Conference 2022
Austrian Workshop on Banking and Finance 2020
Cite
×