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. |
