| bibtype |
J -
Journal Article
|
| ARLID |
0485151 |
| utime |
20240903170638.9 |
| mtime |
20180119235959.9 |
| SCOPUS |
85040725398 |
| WOS |
000424732300005 |
| DOI |
10.14736/kyb-2017-6-1026 |
| title
(primary) (eng) |
Stability, Empirical Estimates and Scenario Generation in Stochastic Optimization - Applications in Finance |
| specification |
| page_count |
21 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0297163 |
| ISSN |
0023-5954 |
| title
|
Kybernetika |
| volume_id |
53 |
| volume |
6 (2017) |
| page_num |
1026-1046 |
| publisher |
| name |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
|
| keyword |
stochastic programming |
| keyword |
stochastic dominance |
| keyword |
empirical estimates |
| keyword |
financial applications |
| author
(primary) |
| ARLID |
cav_un_auth*0101122 |
| full_dept (cz) |
Ekonometrie |
| full_dept (eng) |
Department of Econometrics |
| department (cz) |
E |
| department (eng) |
E |
| full_dept |
Department of Econometrics |
| share |
100 |
| name1 |
Kaňková |
| name2 |
Vlasta |
| institution |
UTIA-B |
| garant |
K |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0321097 |
| project_id |
GA15-10331S |
| agency |
GA ČR |
|
| abstract
(eng) |
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. |
| RIV |
BB |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10103 |
| reportyear |
2018 |
| num_of_auth |
1 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0280355 |
| confidential |
S |
| mrcbC86 |
3+4 Article|Proceedings Paper Computer Science Cybernetics |
| mrcbC86 |
3+4 Article|Proceedings Paper Computer Science Cybernetics |
| mrcbC86 |
3+4 Article|Proceedings Paper Computer Science Cybernetics |
| mrcbT16-e |
COMPUTERSCIENCECYBERNETICS |
| mrcbT16-j |
0.224 |
| mrcbT16-s |
0.321 |
| mrcbT16-B |
18.907 |
| mrcbT16-D |
Q4 |
| mrcbT16-E |
Q3 |
| arlyear |
2017 |
| mrcbU14 |
85040725398 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000424732300005 WOS |
| mrcbU63 |
cav_un_epca*0297163 Kybernetika 0023-5954 Roč. 53 č. 6 2017 1026 1046 Ústav teorie informace a automatizace AV ČR, v. v. i. |
|