Mr Georgy Urumov

Qualifications:

2023 Level 7 Special Study Supporting Learning in Higher Education

2022 MSc (Hons) Big Data Technologies; University of Wesminster - Distinction

2002 MSc (Hons) Finance and Economics; London School of Economics

2001 BSc (First Class Honours) Banking and International Finance; Bayes Business School

2018 BSc (Hons) Combined Stem; Open University

Short Summary

Research focus is on time series and forecasting. Cover both traditional econometric models and new machine learning techniques. My current research is focused on volatile and non-stationary data forecasting techniques with particular focus on Deep learning and Support Vector machines. 

https://westminsterresearch.westminster.ac.uk/item/vzq7v/clustering-...

https://ieee-is-2022.ibspan.waw.pl/Conference-program.pdf

Georgy Urumov and Panagiotis Chountas: Essay on Volatility Clusters and Time Series Prediction financial


In brief

Research areas

Fractals, Fuzzy, Fractal Brownian Motion, Machine Learning Techniques, Artificial Intelligence, Forecasting, Neural Networks, Math, Fractal Math, Fuzzy Fractal Math and Support Vector Machines, Clustering

Skills / expertise

2022 MSc Big Data Technologies; University of Westminster (Distinction), 2002 MSc (Hons) Finance and Economics, London School of Economics, 2001 BSc(1st Class Hons) Banking and International Finance, Bayes Business School and 2018 BSc (Hons) Combined STEM Open University

Supervision interests

Math, Fintech, Statistics, Economics