Statistics in Finance
|Dr. Roxana Halbleib (Konstanz University)
|Prof. Dr. Yarema Okhrin (Augsburg University)
Tasks, Goals and Contents:
The committee provides a platform for the exchange and development of ideas and results in the field of statistics and econometrics with applications in finance. The committee aims to build bridges between theoretical and empirical research with the purpose of finding solutions to problems and challenges in the analysis, modeling, and forecasting of financial economic data that have very complex structures.
- Empirical financial data analysis provides important insights into the complexity of financial time series and their temporal and cross-sectional interdependence.
- Theoretical modeling of financial variables addresses the methodological challenges of capturing complex structures of financial market data and devising tractable econometric solutions.
- Forecasting techniques for financial variables and measures offer methodological solutions to provide accurate predictions with respect to future uncertainties and complex interdependencies within and across different financial instruments and markets.
- Machine learning with financial applications provides solutions from areas of high-dimensional data analytics and machine learning to understand and analyze (e.g., through data mining) financial data. This is reflected in modeling and predicting future events and outcomes through supervised and unsupervised learning.
The committee meets regularly and also regularly participates in the Statistical Week program.
The committee was established in 2014.