I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
Enhanced Quantile Portfolio for Multifactor Model with Deep..:
, In:
2022 12th International Congress on Advanced Applied Informatics (IIAI-AAI)
,
Abe, Masaya
;
Nakagawa, Kei
- p. 293-296 , 2022
Link:
https://doi.org/10.1109/IIAIAAI55812.2022.00066
RT T1
2022 12th International Congress on Advanced Applied Informatics (IIAI-AAI)
: T1
Enhanced Quantile Portfolio for Multifactor Model with Deep Learning
UL https://suche.suub.uni-bremen.de/peid=ieee-9894643&Exemplar=1&LAN=DE A1 Abe, Masaya A1 Nakagawa, Kei YR 2022 K1 Deep learning K1 Asia K1 Organizations K1 Predictive models K1 Data models K1 Quadratic programming K1 Stock markets K1 deep learning K1 stock return prediction K1 multifactor model K1 quantile portfolio SP 293 OP 296 LK http://dx.doi.org/https://doi.org/10.1109/IIAIAAI55812.2022.00066 DO https://doi.org/10.1109/IIAIAAI55812.2022.00066 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)