| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0598425 |
| utime |
20241114073644.7 |
| mtime |
20240921235959.9 |
| WOS |
001323540900024 |
| DOI |
10.1007/978-3-031-65993-5_24 |
| title
(primary) (eng) |
Estimation of Conditional Value-at-Risk in Linear Model |
| specification |
| page_count |
8 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0598452 |
| ISBN |
978-3-031-65992-8 |
| ISSN |
2194-5357 |
| title
|
Combining, Modelling and Analyzing Imprecision, Randomness and Dependence |
| page_num |
200-207 |
| publisher |
| place |
Cham |
| name |
Springer |
| year |
2024 |
|
|
| keyword |
conditional-value-at-risk |
| keyword |
averaged regression quantile |
| keyword |
two-step regression quantile |
| author
(primary) |
| ARLID |
cav_un_auth*0368969 |
| name1 |
Jurečková |
| name2 |
Jana |
| institution |
UTIA-B |
| department |
SI |
| full_dept (cz) |
Stochastická informatika |
| full_dept (eng) |
Department of Stochastic Informatics |
| department (cz) |
SI |
| department (eng) |
SI |
| country |
CZ |
| share |
33,3 |
| garant |
A |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0019770 |
| name1 |
Picek |
| name2 |
J. |
| country |
CZ |
|
| author
|
| ARLID |
cav_un_auth*0263018 |
| name1 |
Kalina |
| name2 |
Jan |
| institution |
UIVT-O |
| full_dept (cz) |
Oddělení umělé inteligence |
| full_dept |
Department of Artificial Intelligence |
| full_dept |
Department of Machine Learning |
| fullinstit |
Ústav informatiky AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
GA22-03636S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0435411 |
|
| project |
| project_id |
GA24-11146S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0474719 |
|
| abstract
(eng) |
The conditional value-at-risk (CVaR) represents a popular risk measure often exploited e.g. within portfolio optimization. The situation with a nuisance linear regression is considered here; in other words, we do not observe directly the loss Z of interest, but only Y=\beta _0+X\beta+Z, where the covariates are not under our control. We propose a novel estimator of CVaR(Z) based on the averaged two-step regression quantile combined with an R-estimate of regression parameters. |
| action |
| ARLID |
cav_un_auth*0472961 |
| name |
International Conference on Soft Methods in Probability and Statistics 2024 - SMPS 2024 /11./ |
| dates |
20240903 |
| mrcbC20-s |
20240906 |
| place |
Salzburg |
| country |
AT |
|
| RIV |
BB |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10103 |
| reportyear |
2025 |
| num_of_auth |
3 |
| mrcbC47 |
UIVT-O 10000 10100 10103 |
| presentation_type |
PR |
| mrcbC55 |
UIVT-O BB |
| inst_support |
RVO:67985556 |
| inst_support |
RVO:67985807 |
| permalink |
https://hdl.handle.net/11104/0356122 |
| cooperation |
| ARLID |
cav_un_auth*0472963 |
| name |
Technická Univerzita v Liberci, Ústav informatiky a výpočetní techniky AV |
| institution |
TUL, UIVT |
| country |
CZ |
|
| confidential |
S |
| arlyear |
2024 |
| mrcbU02 |
C |
| mrcbU12 |
978-3-031-65992-8 |
| mrcbU14 |
SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
001323540900024 WOS |
| mrcbU63 |
cav_un_epca*0598452 Combining, Modelling and Analyzing Imprecision, Randomness and Dependence Springer 2024 Cham 200 207 978-3-031-65992-8 Advances in Intelligent Systems and Computing 2194-5357 |
|