Robust portfolio selection
|Author:||Bc. Inés Horváthová|
|Year:||2014 - summer|
|Leaders:|| RNDr. Michal Červinka Ph.D.
|Work type:|| Bachelors
|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.|
|Abstract:||In this thesis, we take the mean-risk approach to portfolio optimization.
We will rst dene 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