Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Mao, Xiuping"'
Publikováno v:
In Econometrics and Statistics January 2020 13:84-105
Publikováno v:
In International Journal of Forecasting October-December 2017 33(4):1105-1123
Autor:
Mao, Xiuping
Publikováno v:
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
instname
Mención Internacional en el título de doctor
This dissertation focuses on the analysis of Stochastic Volatility (SV) models with leverage effect. We propose a general family of asymmetric SV (GASV) models and consider in detail two particular
This dissertation focuses on the analysis of Stochastic Volatility (SV) models with leverage effect. We propose a general family of asymmetric SV (GASV) models and consider in detail two particular
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::278573c982025205f01c83b06ef059dd
http://hdl.handle.net/10016/20582
http://hdl.handle.net/10016/20582
Publikováno v:
Biometric Recognition ISBN: 9783319254166
CCBR
CCBR
Face verification has been extensively studied in recent decades. Nevertheless, face verification for identity card has subject to relatively little attention. This paper proposes a block statistical features(BSF) learning method combining with local
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ce78cf96f97e2f5e333f09a690a91da7
https://doi.org/10.1007/978-3-319-25417-3_6
https://doi.org/10.1007/978-3-319-25417-3_6
Akademický článek
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Publikováno v:
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
instname
In this paper we propose a new class of asymmetric stochastic volatility (SV) models, which specifies the volatility as a function of the score of the distribution of returns conditional on volatilities based on the Generalized Autoregressive Score (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::e6d2a361662a9ebceca7404012fcec31
http://hdl.handle.net/10016/19577
http://hdl.handle.net/10016/19577
Publikováno v:
Biometric Recognition 10th Chinese Conference, CCBR 2015, Tianjin, China, November 13-15, 2015, Proceedings; 2015, p43-50, 8p