Summary
Mikko Pakkanen is a Senior Lecturer in the Department of Mathematics at Imperial College London and a Fellow of the Data Science Institute at Imperial.
His current research is primarily in the intersection of data science and quantitative finance, with particular emphasis on high-frequency financial data, market microstructure and volatility.
Mikko is currently teaching the following modules:
- Quantitative Risk Management (MSc in Mathematics and Finance, core)
- Deep Learning (MSc in Mathematics and Finance, elective)
- Introduction to Statistical Finance (MSc in Statistics, elective)
- Advanced Statistical Finance (MSc in Statistics, elective)
Mikko's personal website can be found at: www.mikkopakkanen.fi
Selected Publications
Journal Articles
Bennedsen M, Lunde A, Pakkanen MS, 2017, Hybrid scheme for Brownian semistationary processes, Finance and Stochastics, Vol:21, ISSN:1432-1122, Pages:931-965
Pakkanen MS, Réveillac A, 2016, Functional limit theorems for generalized variations of the fractional Brownian sheet, Bernoulli, Vol:22, ISSN:1350-7265, Pages:1671-1708
Barndorff-Nielsen OE, Pakkanen MS, Schmiegel J, 2014, Assessing Relative Volatility/Intermittency/Energy Dissipation, Electronic Journal of Statistics, Vol:8, ISSN:1935-7524, Pages:1996-2021
Pakkanen MS, 2014, Limit theorems for power variations of ambit fields driven by white noise, Stochastic Processes and Their Applications, Vol:124, ISSN:0304-4149, Pages:1942-1973