Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Heng-Guo Zhang"'
Autor:
Heng-Guo Zhang, Libo Wu
Publikováno v:
IEEE Access, Vol 7, Pp 38356-38368 (2019)
Many bubble test methods do not have the ability to predict multiple bubbles in a high dimensional space now. Therefore, we propose a data-driven, self-adaptive evolutionary bubble prediction algorithm named WSADF. First, according to the invariance
Externí odkaz:
https://doaj.org/article/f505a418b7ce4193ae1c74ad112fe94b
Autor:
Heng-Guo ZHANG1 zszhg@126.com
Publikováno v:
Economic Computation & Economic Cybernetics Studies & Research. 2022, Vol. 56 Issue 3, p87-100. 14p.
Publikováno v:
Ekonomska Istraživanja, Vol 32, Iss 1, Pp 1621-1644 (2019)
Economic research-Ekonomska istraživanja
Volume 32
Issue 1
Economic research-Ekonomska istraživanja
Volume 32
Issue 1
This study utilises a time-varying wavelet analysis to examine the relationship between the onshore spot market and the offshore non-deliverable forward (N.D.F.) market of the Chinese Yuan (C.N.Y.). Given the presence of structural changes in the two
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fea120314e14355eb2b8ef650c1a3e16
https://doi.org/10.1080/1331677x.2019.1636697
https://doi.org/10.1080/1331677x.2019.1636697
Publikováno v:
Economic Modelling. 67:355-367
In this study, we propose a non-linear random mapping model called GELM. The proposed model is based on a combination of the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model and the Extreme Learning Machine (ELM), and can be us
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5eb1bd90c05d468a0889e0591cba3d36
https://doi.org/10.1016/j.econmod.2017.02.014
https://doi.org/10.1016/j.econmod.2017.02.014
Publikováno v:
Energy Economics. 95:104994
This paper dynamically measures news-driven information friction in China's carbon market theoretically and empirically. The biggest difference between this paper and the existing literature is that this paper does not assume that the information sho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::57ef94ba7a73f5a26cebbfca160d64d5
https://doi.org/10.1016/j.eneco.2020.104994
https://doi.org/10.1016/j.eneco.2020.104994
Publikováno v:
The Journal of International Trade & Economic Development. 25:857-879
This study examines the relationship between real effective exchange rates (REERs) and the consumer price index (CPI) in China, utilizing a bootstrap Granger full-sample causality test and a sub-sample rolling-window estimation. Considering structura
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9a324f7cf891ba7b4265a1fbdb05b27
https://doi.org/10.1080/09638199.2016.1142605
https://doi.org/10.1080/09638199.2016.1142605
© 2017, Springer Science+Business Media, LLC. Online Value-at-Risk (VaR) analysis in high-dimensional space remains a challenge in the era of big data. In this paper, we propose an online sequential learning non-parametric VaR model called OS-GELM w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8068013f6e2fbe932f42488a6a41b05e
https://hdl.handle.net/10453/134313
https://hdl.handle.net/10453/134313
Publikováno v:
Proceedings in Adaptation, Learning and Optimization ISBN: 9783319283722
In this paper, we propose a fast and efficient learning approach called WELM based on Extreme Learning Machine and 3-D Wavelet Dynamic Co-Movement Analysis to enhance the speed and precision of big data prediction. 3-D Wavelet Dynamic Co-Movement Ana
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::65a89e39a075e21991117fd837812899
https://doi.org/10.1007/978-3-319-28373-9_40
https://doi.org/10.1007/978-3-319-28373-9_40