MULTISTAGE MULTIVARIATE NESTED DISTANCE: AN EMPIRICAL ANALYSIS
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F18%3A10401759" target="_blank" >RIV/00216208:11320/18:10401759 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=ld1qo9ueCM" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=ld1qo9ueCM</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14736/kyb-2018-6-1184" target="_blank" >10.14736/kyb-2018-6-1184</a>
Alternative languages
Result language
angličtina
Original language name
MULTISTAGE MULTIVARIATE NESTED DISTANCE: AN EMPIRICAL ANALYSIS
Original language description
Multistage stochastic optimization requires the definition and the generation of a discrete stochastic tree that represents the evolution of the uncertain parameters in time and space. The dimension of the tree is the result of a trade-off between the adaptability to the original probability distribution and the computational tractability. Moreover, the discrete approximation of a continuous random variable is not unique. The concept of the best discrete approximation has been widely explored and many enhancements to adjust and fix a stochastic tree in order to represent as well as possible the real distribution have been proposed. Yet, often, the same generation algorithm can produce multiple trees to represent the random variable. Therefore, the recent literature investigates the concept of distance between trees which are candidate to be adopted as stochastic framework for the multistage model optimization. The contribution of this paper is to compute the nested distance between a large set of multistage and multivariate trees and, for a sample of basic financial problems, to empirically show the positive relation between the tree distance and the distance of the corresponding optimal solutions, and between the tree distance and the optimal objective values. Moreover, we compute a lower bound for the Lipschitz constant that bounds the optimal value distance.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GJ18-01781Y" target="_blank" >GJ18-01781Y: Dynamic and granular loss reserving with copulae - DaGLoRCo</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Kybernetika
ISSN
0023-5954
e-ISSN
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Volume of the periodical
54
Issue of the periodical within the volume
6
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
17
Pages from-to
1184-1200
UT code for WoS article
000457070200007
EID of the result in the Scopus database
2-s2.0-85064192757