Multiple Time Series Forecasting Using Quasi-Randomized Functional Link Neural Networks

Author： Moudiki Thierry   Planchet Frédéric   Cousin Areski  

Publisher： MDPI

E-ISSN： 2227-9091|6|1|22-22

ISSN： 2227-9091

Source： Risks, Vol.6, Iss.1, 2018-03, pp. : 22-22

Access to resources Favorite

Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.

Previous Menu Next

Abstract

Related content

Multivariate Functional Time Series Forecasting: Application to Age-Specific Mortality Rates

By Gao Yuan   Shang Han Lin  

Risks, Vol. 5, Iss. 2, 2017-03 ,pp. : 21-21

MDPI

Access to resources Recommend Favorite

Financial Time Series Forecasting Using Empirical Mode Decomposition and Support Vector Regression

By Nava Noemi   Di Matteo Tiziana   Aste Tomaso  

Risks, Vol. 6, Iss. 1, 2018-02 ,pp. : 7-7

MDPI

Access to resources Recommend Favorite

Nonlinear Time Series and Neural-Network Models of Exchange Rates between the US Dollar and Major Currencies †

By Allen David E.   McAleer Michael   Peiris Shelton   Singh Abhay K.  

Risks, Vol. 4, Iss. 1, 2016-03 ,pp. : 7-7

MDPI

Access to resources Recommend Favorite

Forecasting Interest Rates Using Geostatistical Techniques

By Arbia Giuseppe   Di Marcantonio Michele  

Econometrics, Vol. 3, Iss. 4, 2015-11 ,pp. : 733-760

MDPI

Access to resources Recommend Favorite

Forecasting Value-at-Risk Using High-Frequency Information

By Huang Huiyu   Lee Tae-Hwy  

Econometrics, Vol. 1, Iss. 1, 2013-06 ,pp. : 127-140

MDPI

Access to resources Recommend Favorite