Work detail

Robust portfolio selection

Author: Bc. Inés Horváthová
Year: 2014 - summer
Leaders: RNDr. Michal Červinka Ph.D.
Consultants:
Work type: Bachelors
Language: English
Pages: 67
Awards and prizes: B.A. with distinction from the Dean of the Faculty of Social Sciences for an excellent state-final examination performance and for an extraordinarily good bachelors diploma thesis.
Link: https://is.cuni.cz/webapps/zzp/detail/136814/
Abstract: In this thesis, we take the mean-risk approach to portfolio optimization.
We will rst de ne risk measures in general and then introduce
three commonly used ones: variance, Value-at-risk (V aR) and
Conditional-value-at-risk (CV aR). For each of these risk measures we
formulate the corresponding mean-risk models. We then present their
robust counterparts. We focus mainly on the robust mean-variance
models, which we also apply to historical data using free statistical
software R. Finally, we compare the results with the classical nonrobust
mean-variance model.

Partners

Deloitte
McKinsey & Company
Moneta Money Bank

Sponsors

CRIF
ČSOB