Simulation methodology for financial assets with imprecise data
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F11%3AA12012TV" target="_blank" >RIV/61988987:17610/11:A12012TV - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Alternativní jazyky
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, depends 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. Since many financial problems are too complex to be solved analytically even in a crisp case, it can be efficient to apply (Quasi) Monte Carlo simulation. In this contribution the recent knowledge of fuzzy numbers andtheir 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.
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, depends 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. Since many financial problems are too complex to be solved analytically even in a crisp case, it can be efficient to apply (Quasi) Monte Carlo simulation. In this contribution the recent knowledge of fuzzy numbers andtheir 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.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
BB - Aplikovaná statistika, operační výzkum
OECD FORD obor
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Návaznosti výsledku
Projekt
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Návaznosti
Z - Vyzkumny zamer (s odkazem do CEZ)
Ostatní
Rok uplatnění
2011
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Proceedings of the 29th International Conference on Mathematical Methods in Economics 2011
ISBN
978-80-7431-059-1
ISSN
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e-ISSN
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Počet stran výsledku
6
Strana od-do
709-714
Název nakladatele
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Místo vydání
Praha: VŠE Praha
Místo konání akce
Liptovský Ján, Slovensko
Datum konání akce
6. 9. 2011
Typ akce podle státní příslušnosti
EUR - Evropská akce
Kód UT WoS článku
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