International Symposium on Econometrics (ise 2020)

International Symposium on Econometrics (ise 2020)

Asistiré:

jul
24

) — ()

Guilin, China(Grand Link Hotel)

桂山华星酒店 Mapa

International Symposium on Econometrics (ISE 2020)
Date: July 24-26, 2020
Venue: Guilin, China (Grand Link Hotel)
Website: https://www.marchconf.org/conference/ISE2020/
Online Submission:
https://www.marchconf.org/RegistrationSubmission/default.aspx?ConferenceID=1222
Email Submission: workshop3@126.com
About ISE2020:
International Symposium on Econometrics (ISE 2020) is to be held during July 24-26, 2020 in Guilin, China. This Conference will cover issues on Econometrics, Statistics, Financial engineering, Operational research and other Related Topics. It dedicates to creating a stage for exchanging the latest research results and sharing the advanced research methods in related fields. 
Publication and Presentation:
Publication: All the accepted papers will be published by a peer-reviewed open access journal that can ensure the widest dissemination of your published work, For more information, please contact us(workshop3@126.com).
Index: CNKI and Google Scholar  
Note: If you want to present your research results but do NOT wish to publish a paper, you may simply submit an Abstract to our Registration System.
Attendance Methods:
Package A: Regular Attendance (No Submission Required) USD 400 (RMB 2400)
Package B: Regular Attendance+Abstract+Presentation USD 450(RMB 2700)
Package C: Regular Attendance+Paper Publication+Presentation USD 600(RMB 3600)
Contact Us:
Email: workshop3@126.com
Tel: +86 132 6470 2250
QQ: 1349406763
WeChat: 3025797047 
Topics:
Topics are included but are not limited to:
Econometrics
Econometrics: methods and applications
Econometrics, operations research and statistics
Econometrics and statistics
Multidimensional data analysis
Financial engineering
Operational research
Financial mathematics and insurance
Business informatics
Finance: financial crises, risk management, financial markets
Applied mathematics in economy, management, logistics
The classical multiple linear regression model
Least squares

Ir al perfil de Selina Li
Organizador:
 Selina Li