Mikko Pakkanen is a Reader in Data Science and Quantitative Finance in the Department of Mathematics at Imperial College London. He is currently on leave from Imperial and works as an Associate Professor in the Department of Statistics and Actuarial Science at the University of Waterloo, Canada.
Mikko's research is primarily in the intersection of data science, stochastic processes and quantitative finance, with particular emphasis on high-frequency financial data, market microstructure, volatility modelling and machine learning.
Mikko's personal website can be found at: www.mikkopakkanen.fi
Bennedsen M, Lunde A, Pakkanen MS, 2017, Hybrid scheme for Brownian semistationary processes, Finance and Stochastics, Vol:21, ISSN:0949-2984, 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