EcoSta 2020

The 4th International Conference on Econometrics and Statistics (EcoSta 2020) will take place at the Yonsei University, Seoul, South Korea, 20-22 July 2020.

The 3rd International Conference on Econometrics and Statistics, EcoSta 2019, has taken place at the National Chung Hsing University (NCHU), Taiwan, 25-27 June 2019, and gathered about 660 participants.

This Conference is co-organized by the Working Group on Computational and Methodological Statistics (CMStatistics), the network of Computational and Financial Econometrics (CFENetwork), and the Institute of Data Science and School of Business of the Yonsei University.

The journal Econometrics and Statistics (EcoSta) and its supplement, the Annals of Computational and Financial Econometrics, and the Computational Statistics & Data Analysis are the main sponsors of the conference. Selected peer-review papers will be considered for publication in a special peer-reviewed, or regular, issues of the Journals Econometrics and Statistics, and Computational Statistics & Data Analysis.

For further information please contact info@cmstatistics.org or info@CFEnetwork.org.

Aims and Scope

This conference invites oral and poster presentations containing substantial advances in the broad areas of econometrics and/or statistics. All topics within the scope of the journal Econometrics and Statistics will be considered. Topics of interest include, but not limited to:

Part A. Econometrics: estimation of econometric models and associated inference, model selection, panel data, measurement error, time series analyses, filtering, portfolio allocation, option pricing, quantitative risk management, systemic risk and market microstructure, forecasting, volatility and risk, credit risk, pricing models, portfolio management and emerging markets.

Part B. Statistics: high-dimensional problems, functional data analysis, robust statistics, resampling, dependence, extreme value theory, spatial statistics, Bayesian methods, statistical learning, nonparametric statistics, multivariate data analysis, parametric & semi parametric models, numerical methods in statistics, and substantial statistical applications in other areas such as medicine, epidemiology, biology, psychology, climatology and communication. Innovative algorithmic developments are welcome, as are the computer programs and the computational environments that implement them as a complement.