Simulation methodology for financial assets with imprecise data

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Simulation methodology for financial assets with imprecise data

Popis výsledku v původním jazyce

During last decades the stochastic simulation approach, both via Monte Carlo (MC) and Quasi Monte Carlo (QMC) has been vastly applied and subsequently analyzed in almost all branches of science. Very nice applications can be found in areas that rely on modeling via stochastic processes, such as finance. However, since financial quantities, opposed to natural processes, depend on human activity, their modeling is often very challenging. Many scholars therefor suggest to specify some parts of financial models by means of fuzzy set theory. In this contribution the recent knowledge of fuzzy numbers and their approximation is utilized in order to suggest fuzzy-MC simulation to modeling of returns of financial quantities, such as prices of stocks, commodities or exchange rates. Finally, three distinct types of potential fuzzy-stochastic models are suggested, including quantile estimation illustrations.

Název v anglickém jazyce

Simulation methodology for financial assets with imprecise data

Popis výsledku anglicky

During last decades the stochastic simulation approach, both via Monte Carlo (MC) and Quasi Monte Carlo (QMC) has been vastly applied and subsequently analyzed in almost all branches of science. Very nice applications can be found in areas that rely on modeling via stochastic processes, such as finance. However, since financial quantities, opposed to natural processes, depend on human activity, their modeling is often very challenging. Many scholars therefor suggest to specify some parts of financial models by means of fuzzy set theory. In this contribution the recent knowledge of fuzzy numbers and their approximation is utilized in order to suggest fuzzy-MC simulation to modeling of returns of financial quantities, such as prices of stocks, commodities or exchange rates. Finally, three distinct types of potential fuzzy-stochastic models are suggested, including quantile estimation illustrations.

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 29th International Conference on Mathematical Methods in Economics 2011 - part I

ISBN

978-80-7431-058-4

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

709-714

Název nakladatele

Professional Publishing

Místo vydání

Prague

Místo konání akce

Janska Dolina

Datum konání akce

6. 9. 2011

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

000309074600118