Value-at-risk — the comparison of state-of-the-art models on various assets

Karol Kielak and Robert Ślepaczuk
Additional contact information
Karol Kielak: Quantitative Finance Research Group; Faculty of Economic Sciences, University of Warsaw

No 2020-28, Working Papers from Faculty of Economic Sciences, University of Warsaw

Abstract: This paper compares different approaches to Value-at-Risk measurement based on parametric and non-parametric approaches. Three portfolios are taken into consideration — the first one containing only stocks from the London Stock Exchange, the second one based on different assets of various origins and the third one consisting of cryptocurrencies. Data used cover the period of more than 20y. In the empirical part of the study, parametric methods based on mean-variance framework are compared with GARCH(1,1) and EGARCH(1,1) models. Different assumptions concerning returns’ distribution are taken into consideration. Adjustment for the fat tails effect is made by using Student t distribution in the analysis. One-day-ahead 95%VaR estimation is then calculated. Thereafter, models are validated using Kupiec and Christoffersen tests and Monte Carlo Simulation for reliable verification of the hypotheses. The overall goal of this paper is to establish if analyzed models accurately estimate Value-at-Risk measure, especially if we take into account assets with various returns distribution characteristics.

Keywords: risk management; Value-at-Risk; GARCH models; returns distribution; Monte Carlo Simulation; asset class; cryptocurrencies (search for similar items in EconPapers)
JEL-codes: C14 C4 C45 C53 C58 G13 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2020
New Economics Papers: this item is included in nep-ecm, nep-fmk, nep-ore and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.wne.uw.edu.pl/index.php/download_file/5800/ First version, 2020 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:war:wpaper:2020-28

Access Statistics for this paper

More papers in Working Papers from Faculty of Economic Sciences, University of Warsaw Contact information at EDIRC.
Bibliographic data for series maintained by Marcin Bąba (mbaba@wne.uw.edu.pl).