Work detail

Scrutinizing Parametric Value-at-Risk Measure under Real-World Assumptions

Author: Bc. Zuzana Rusá
Year: 2015 - summer
Leaders:
Consultants:
Work type: Bachelors
Language: English
Pages: 46
Awards and prizes:
Link: https://is.cuni.cz/webapps/zzp/detail/151427/
Abstract: The thesis compares an industry-standard parametric Value-at-Risk estimate with alternative
approaches. The intention of the thesis is to find out, whether, or to what extent can the
inappropriate assumption of normally distributed returns influence the Value-at-Risk estimate.
We used the exceedance rate as a back-testing procedure in order to test the accuracy of
parametric Value-at-Risk estimate. We look whether the exceedance rate of the estimates
approaches the given confidence level or not. We contrasted the parametric measure to its
historical and Monte Carlo counterparts. The latter assumes Student’s t-distribution as an
example of a fat-tailed distribution, because the estimate of tails is crucial for the accuracy of
Value-at-Risk estimate.
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