Key details
Dr Karolos Korkas
Senior Lecturer in Data Science
Dr Karolos Korkas stands as a senior lecturer in Data Science at the University of 杏吧app下载, blending his extensive academic expertise with a wealth of practical experience garnered over multiple years in the realms of electronic trading, risk management, and modelling within major banking institutions. He holds a PhD in Statistics from the London School of Economics (LSE), MSc in Statistics from LSE, MSc in Finance and Investment from Durham University Business School, and BA in Business Management (Information Systems) from ASOEE. He was also a Fellow in Finance at the Department of Finance of LSE.
His PhD studies were fully funded by EPSRC.
Responsibilities within the university
Module leader
- Statistical Techniques and Time Series
Module contribution
- Programming Fundamentals for Data Science
- Research Methods and Mathematics Project
Research / Scholarly interests
Dr Korkas's research interests span the following fields:
- change-point detection in univariate time series, regression models and multivariate volatility processes.
- Non-stationary time series and modelling
- Ensemble methods for forecasting
Recent publications
Korkas, K.K., 2022. Ensemble binary segmentation for irregularly spaced data with change-points. Journal of the Korean Statistical Society, 51(1), pp.65-86.
H. Cho and K. Korkas (2018) segMGarch: Multiple Change-Point Detection for High-Dimensional GARCH Processes. [written in R and C++] (Available on CRAN)
Cho, H. and Korkas, K.K., 2022. High-dimensional GARCH process segmentation with an application to Value-at-Risk. Econometrics and Statistics, 23, pp.187-203.
Korkas, K.K. and Pryzlewicz, P., 2017. Multiple change-point detection for non-stationary time series using wild binary segmentation. Statistica Sinica, pp.287-311.
Presentations
Marcus Evans 4th Edition Model Risk Management (2023), London, UK;