Computational Econometrics and Financial Time Series
Description:
The track concerns with methodological and computational aspects of econometrics. Empirical aspects of analysing financial time series are also addressed.
Computational and financial econometrics have been of interest for a wide variety of researchers in economics, finance, statistics, mathematics and computing. Financial time series analyses focus on asset valuations over time with emphases on option pricing, volatility measurement, and modelling market microstructure effects. Apart from theoretical developments, financial time series analyses also have a high empirical content. The computational aspects of such analyses are of crucial importance since one typically deals with high-dimensional problems and large numbers of observations. Existing algorithms often do not utilize the best computational techniques for efficiency, stability, or conditioning. Furthermore, environments for conducting econometrics are inherently computer based. Integrated econometrics packages have grown well over the years, but still have much room for development.
The track is strongly connected with the 3rd International Conference on Computational and Financial Econometrics (CFE'09) and the special issues on Computational Econometrics of the Computational Statistics and Data Analysis. Papers containing strong computational statistical or econometric components or substantive data-analytic elements will be considered for publication in the 6th special issue on Computational Econometrics.
Submissions to this track should be directed to the (CFE'09) which takes place jointly with the ERCIM09 workshop.
Co-Chairs:
- Alessandra Amendola, University of Salerno, Italy
- Ana-Maria Fuertes, Cass Business School, City University, UK
- Marc Paolella, Swiss Bank Institute, University of Zurich, Switzerland
- Herman K. Van Dijk, Erasmus University Rotterdam, The Netherlands
Created by Computing & Statistics 2007