Stability, Empirical Estimates and Scenario Generation in Stochastic Optimization - Applications in Finance

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00485151" target="_blank" >RIV/67985556:_____/17:00485151 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.14736/kyb-2017-6-1026" target="_blank" >http://dx.doi.org/10.14736/kyb-2017-6-1026</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.14736/kyb-2017-6-1026" target="_blank" >10.14736/kyb-2017-6-1026</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Stability, Empirical Estimates and Scenario Generation in Stochastic Optimization - Applications in Finance

Popis výsledku v původním jazyce

Economic and financial processes are mostly simultaneously influuenced by a random factor and a decision parameter. While the random factor can be hardly influenced, the decision parameter can be usually determined by a deterministic optimization problem depending on a corresponding probability measure. However, in applications the „underlying“ probability measure is often a little different, replaced by empirical one determined on the base of data or even (for numerical reason) replaced by simpler (mostly discrete) one. Consequently, real one and approximate one correspond to applications. In the paper we try to investigate their relationship. To this end we employ the results on stability based on the Wasserstein metric and L1 norm, their applications to empirical estimates and scenario generation. Moreover, we apply the achieved new results to simple financial applications. The corresponding model will a problem of stochastic programming.

Název v anglickém jazyce

Stability, Empirical Estimates and Scenario Generation in Stochastic Optimization - Applications in Finance

Popis výsledku anglicky

Economic and financial processes are mostly simultaneously influuenced by a random factor and a decision parameter. While the random factor can be hardly influenced, the decision parameter can be usually determined by a deterministic optimization problem depending on a corresponding probability measure. However, in applications the „underlying“ probability measure is often a little different, replaced by empirical one determined on the base of data or even (for numerical reason) replaced by simpler (mostly discrete) one. Consequently, real one and approximate one correspond to applications. In the paper we try to investigate their relationship. To this end we employ the results on stability based on the Wasserstein metric and L1 norm, their applications to empirical estimates and scenario generation. Moreover, we apply the achieved new results to simple financial applications. The corresponding model will a problem of stochastic programming.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GA15-10331S" target="_blank" >GA15-10331S: Dynamické modely rizika portfolia hypoték</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název periodika

Kybernetika

ISSN

0023-5954

e-ISSN

—

Svazek periodika

53

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

21

Strana od-do

1026-1046

Kód UT WoS článku

000424732300005

EID výsledku v databázi Scopus

2-s2.0-85040725398