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

Kód výsledku v 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>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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

Název v anglickém jazyce

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

Popis výsledku anglicky

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

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

<a href="/cs/project/GA13-25911S" target="_blank" >GA13-25911S: Bezarbitrážní modelování implikované volatility.</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

28th European Simulation and Modelling Conference Proceedings

ISBN

978-90-77381-86-1

ISSN

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e-ISSN

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Počet stran výsledku

5

Strana od-do

159-163

Název nakladatele

ETI - The European Technology Institute

Místo vydání

Ostend

Místo konání akce

FEUP - University of Porto

Datum konání akce

22. 10. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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