| bibtype |
J -
Journal Article
|
| ARLID |
0581659 |
| utime |
20240304105837.0 |
| mtime |
20240119235959.9 |
| SCOPUS |
85183570255 |
| DOI |
10.1016/j.frl.2024.105003 |
| title
(primary) (eng) |
Fan charts in era of big data and learning |
| specification |
| page_count |
7 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0361997 |
| ISSN |
1544-6123 |
| title
|
Finance Research Letters |
| volume_id |
61 |
| publisher |
|
|
| keyword |
Fan charts |
| keyword |
Probabilistic forecasting |
| keyword |
Machine learning |
| author
(primary) |
| ARLID |
cav_un_auth*0242028 |
| name1 |
Baruník |
| name2 |
Jozef |
| institution |
UTIA-B |
| full_dept (cz) |
Ekonometrie |
| full_dept (eng) |
Department of Econometrics |
| department (cz) |
E |
| department (eng) |
E |
| full_dept |
Department of Econometrics |
| country |
CZ |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0462008 |
| name1 |
Hanus |
| name2 |
Luboš |
| institution |
UTIA-B |
| full_dept (cz) |
Ekonometrie |
| full_dept |
Department of Econometrics |
| department (cz) |
E |
| department |
E |
| country |
CZ |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| source |
|
| cas_special |
| project |
| project_id |
GX19-28231X |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0385135 |
|
| abstract
(eng) |
We propose how to construct big data-driven macroeconomic fan charts, using machine learning methods to reflect the information in 216 relevant economic variables. Such data-rich fan charts do not rely on restrictive model assumptions and allow the exploration of non-Gaussian, asymmetric, heavy-tailed data and their non-linear interactions. By allowing complex patterns to be learned from a data-rich environment, our fan charts are useful for decision making that depends on the uncertainty of a potentially large number of economic variables — most public policy issues. |
| reportyear |
2025 |
| RIV |
AH |
| result_subspec |
WOS |
| FORD0 |
50000 |
| FORD1 |
50200 |
| FORD2 |
50202 |
| num_of_auth |
2 |
| inst_support |
RVO:67985556 |
| permalink |
https://hdl.handle.net/11104/0349774 |
| mrcbC61 |
1 |
| confidential |
S |
| article_num |
105003 |
| mrcbC91 |
C |
| mrcbT16-e |
BUSINESSFINANCE |
| mrcbT16-j |
1.201 |
| mrcbT16-D |
Q2 |
| arlyear |
2024 |
| mrcbU14 |
85183570255 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
WOS |
| mrcbU63 |
cav_un_epca*0361997 Finance Research Letters 1544-6123 1544-6131 Roč. 61 č. 1 2024 Elsevier PRINT |
|