Law of Large Numbers for Random LU-Fuzzy Numbers: Some Results in the Context of Simulation of Financial Quantities

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

Law of Large Numbers for Random LU-Fuzzy Numbers: Some Results in the Context of Simulation of Financial Quantities

Popis výsledku v původním jazyce

Financial problems can be analyzed by several ways. In the standard case, we assume that a given financial quantity in question is a stochastic (or random) variable, ie. it follows some probability distribution and its possible states can get prescribedparticular probabilities. However, in financial modeling it can appear that the estimation of parameters of such models (e.g. volatility) does not lead to reliable results, so that it can be fruitful to incorporate some kind of impreciseness. One can recognize an unnatural simplification of parameters that can lead to a loss of important information hidden in data. If one wants to apply Monte Carlo simulation to analyze a financial problem with values expressed by imprecisely defined numbers, it is important to show that random variables with imprecisely defined numbers satisfy the (strong) law of large numbers, as well. Otherwise such approach would have no sense. The aim of the paper is to provide a justification to this novel approac

Název v anglickém jazyce

Law of Large Numbers for Random LU-Fuzzy Numbers: Some Results in the Context of Simulation of Financial Quantities

Popis výsledku anglicky

Financial problems can be analyzed by several ways. In the standard case, we assume that a given financial quantity in question is a stochastic (or random) variable, ie. it follows some probability distribution and its possible states can get prescribedparticular probabilities. However, in financial modeling it can appear that the estimation of parameters of such models (e.g. volatility) does not lead to reliable results, so that it can be fruitful to incorporate some kind of impreciseness. One can recognize an unnatural simplification of parameters that can lead to a loss of important information hidden in data. If one wants to apply Monte Carlo simulation to analyze a financial problem with values expressed by imprecisely defined numbers, it is important to show that random variables with imprecisely defined numbers satisfy the (strong) law of large numbers, as well. Otherwise such approach would have no sense. The aim of the paper is to provide a justification to this novel approac

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 14th International Conference on Finance and Banking : 16-17 October 2013, Ostrava, Czech Republic

ISBN

978-80-7248-939-8

ISSN

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e-ISSN

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Počet stran výsledku

7

Strana od-do

124-130

Název nakladatele

Silesian University, School of Business Administration

Místo vydání

Karviná

Místo konání akce

Ostrava

Datum konání akce

16. 10. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000345575000015