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  • It is very important that each risk model is validated, ie. it is verified whether it describes the risk on a given probability level sufficiently or not. One of the most popular methods is the backtesting, ie. utilizing of the past market data. In this paper, we focus on market risk modeling via subordinated Lévy models joined by ordinary elliptical copula functions. Selected combinations of models (geometric Brownian motion, variance gamma model, normal inverse Gaussian model for marginal distribution and Gaussian and Student copula functions for joint distribution) are assumed in order to verify the backtesting power of several combinations of normalized data as a basis for parameter estimation. It is documented that while the (linear) dependency structure is of a short memory, in order to estimate the higher moments (skewness and kurtosis) of the underlying distribution well, longer time series is required.
  • It is very important that each risk model is validated, ie. it is verified whether it describes the risk on a given probability level sufficiently or not. One of the most popular methods is the backtesting, ie. utilizing of the past market data. In this paper, we focus on market risk modeling via subordinated Lévy models joined by ordinary elliptical copula functions. Selected combinations of models (geometric Brownian motion, variance gamma model, normal inverse Gaussian model for marginal distribution and Gaussian and Student copula functions for joint distribution) are assumed in order to verify the backtesting power of several combinations of normalized data as a basis for parameter estimation. It is documented that while the (linear) dependency structure is of a short memory, in order to estimate the higher moments (skewness and kurtosis) of the underlying distribution well, longer time series is required. (en)
Title
  • Market risk backtesting via Lévy models and parameter estimation
  • Market risk backtesting via Lévy models and parameter estimation (en)
skos:prefLabel
  • Market risk backtesting via Lévy models and parameter estimation
  • Market risk backtesting via Lévy models and parameter estimation (en)
skos:notation
  • RIV/61989100:27510/10:10225492!RIV11-GA0-27510___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA402/08/1237), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 269696
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27510/10:10225492
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Backtesting, copula functions, financial institutions, market risk (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [CD0BCFEE9338]
http://linked.open...v/mistoKonaniAkce
  • České Budějovice
http://linked.open...i/riv/mistoVydani
  • České Budějovice
http://linked.open...i/riv/nazevZdroje
  • Mathematical Methods in Economics 2010
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Tichý, Tomáš
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000287979900107
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • University of South Bohemia
https://schema.org/isbn
  • 978-80-7394-218-2
http://localhost/t...ganizacniJednotka
  • 27510
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