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ESTIMATION OF VAR AND CVAR FROM FINANCIAL DATA USING SIMULATED ALPHA-STABLE RANDOM VARIABLES

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F14%3A00437673" target="_blank" >RIV/67985556:_____/14:00437673 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    ESTIMATION OF VAR AND CVAR FROM FINANCIAL DATA USING SIMULATED ALPHA-STABLE RANDOM VARIABLES

  • Original language description

    It is of great importance for those in charge of measuring and managing financial risk to analyse financial data by determining a certain probabilistic model. These data usually possess distribution with tails heavier than those of normal distribution. The class of alpha-stable distributions can be chosen for modelling financial data since this probabilistic model is able to capture asymmetry and heavy tails. In this paper, mixed alpha-stable model is applied for the analysis of return data of Lithuanian pension funds that usually contain a significant number of zero values. The distribution fitting and simulation algorithm are also described. Risk measures VaR (Value-at-Risk) and CVaR (Conditional Value-at-Risk) are chosen to evaluate the characteristics of return data, especially the degree of heavy tails. VaR and CVaR are estimated from return data, then computed from simulated data when using mixed alpha-stable law and finally compared to the measures obtained using alpha-stable mo

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BB - Applied statistics, operational research

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GA13-25911S" target="_blank" >GA13-25911S: Arbitrage-free modelling of implied volatility.</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2014

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    28th European Simulation and Modelling Conference Proceedings

  • ISBN

    978-90-77381-86-1

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    159-163

  • Publisher name

    ETI - The European Technology Institute

  • Place of publication

    Ostend

  • Event location

    FEUP - University of Porto

  • Event date

    Oct 22, 2014

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article