Mikko S. Pakkanen

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Asger LundePartner, Copenhagen EconomicsVerified email at copenhageneconomics.com
Mikkel BennedsenAarhus UniversityVerified email at econ.au.dk
Swapnil MishraAssistant Professor at National University of SingaporeVerified email at nus.edu.sg
Samir BhattProfessor of Machine Learning and Public Health University of CopenhagenVerified email at sund.ku.dk
Almut VeraartImperial College LondonVerified email at imperial.ac.uk
Bezirgen VeliyevAssociate Professor, Department of Economics, Aarhus UniversityVerified email at econ.au.dk
Phillip MurrayImperial College LondonVerified email at imperial.ac.uk
Kim ChristensenAarhus UniversityVerified email at econ.au.dk
Antoine JacquierImperial College LondonVerified email at imperial.ac.uk
Matthew J PennData Scientist, Como 1907Verified email at st-annes.ox.ac.uk
Charles WhittakerImperial College LondonVerified email at imperial.ac.uk
Jani LukkarinenProfessor of mathematical physics, University of HelsinkiVerified email at helsinki.fi
Mark PodolskijProfessor of Probability and Statistics, University of LuxembourgVerified email at uni.lu
Jose Manuel CorcueraProfesor de Matemáticas Universidad de BarcelonaVerified email at ub.edu
Hasanjan SayitAssociate Professor of Mathematics, Xi'Jiao-Liverpool UniversityVerified email at xjtlu.edu.cn
Seth Flaxmanassociate professor at OxfordVerified email at cs.ox.ac.uk
Thomas A. MellanProtocol LabsVerified email at protocol.ai
Xenia MiscouridouUniversity of Cyprus, Imperial College LondonVerified email at ucy.ac.cy
Jürgen SchmiegelAarhus UniversityVerified email at eng.au.dk
Lorenzo LucchesePhD student, Imperial College LondonVerified email at imperial.ac.uk

Mikko S. Pakkanen

Reader in Data Science and Quantitative Finance, Imperial College London

Verified email at imperial.ac.uk - Homepage

Quantitative Finance Statistical Finance Probability Theory Data Science


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Decoupling the short-and long-term behavior of stochastic volatility M Bennedsen, A Lunde, MS Pakkanen Journal of Financial Econometrics 20 (5), 961-1006, 2022	179	2022
Hybrid scheme for Brownian semistationary processes M Bennedsen, A Lunde, MS Pakkanen Finance and Stochastics 21, 931-965, 2017	161	2017
Turbocharging Monte Carlo pricing for the rough Bergomi model R McCrickerd, MS Pakkanen Quantitative Finance 18 (11), 1877-1886, 2018	89	2018
State-dependent Hawkes processes and their application to limit order book modelling M Morariu-Patrichi, MS Pakkanen Quantitative Finance 22 (3), 563-583, 2022	68	2022
A GMM approach to estimate the roughness of stochastic volatility AE Bolko, K Christensen, MS Pakkanen, B Veliyev Journal of Econometrics 235 (2), 745-778, 2023	55*	2023
Asymptotic theory for Brownian semi-stationary processes with application to turbulence JM Corcuera, E Hedevang, MS Pakkanen, M Podolskij Stochastic processes and their applications 123 (7), 2552-2574, 2013	55	2013
Pathwise large deviations for the rough Bergomi model A Jacquier, MS Pakkanen, H Stone Journal of Applied Probability 55 (4), 1078-1092, 2018	51	2018
Stochastic integrals and conditional full support MS Pakkanen Journal of Applied Probability 47 (3), 650-667, 2010	46	2010
Assessing relative volatility/intermittency/energy dissipation OE Barndorff-Nielsen, MS Pakkanen, J Schmiegel Electronic Journal of Statistics 8 (2), 1996-2021, 2014	24	2014
Brownian semistationary processes and conditional full support MS Pakkanen International Journal of Theoretical and Applied Finance 14 (04), 579-586, 2011	23	2011
Limit theorems for power variations of ambit fields driven by white noise MS Pakkanen Stochastic Processes and their Applications, 2014	22	2014
Functional limit theorems for generalized variations of the fractional Brownian sheet MS Pakkanen, A Réveillac Bernoulli 22 (3), 1671-1708, 2016	18	2016
Microfoundations for diffusion price processes MS Pakkanen Mathematics and financial economics 3, 89-114, 2010	17	2010
Deep hedging: Continuous reinforcement learning for hedging of general portfolios across multiple risk aversions P Murray, B Wood, H Buehler, M Wiese, M Pakkanen Proceedings of the Third ACM International Conference on AI in Finance, 361-368, 2022	16	2022
VAE: a stochastic process prior for Bayesian deep learning with MCMC S Mishra, S Flaxman, T Berah, M Pakkanen, H Zhu, S Bhatt Statistics and Computing 32 (96), 1-16, 2022	16*	2022
Unifying incidence and prevalence under a time-varying general branching process MS Pakkanen, X Miscouridou, MJ Penn, C Whittaker, T Berah, S Mishra, ... Journal of Mathematical Biology 87 (2), 35, 2023	15*	2023
Discretization of L\'evy semistationary processes with application to estimation M Bennedsen, A Lunde, MS Pakkanen arXiv preprint arXiv:1407.2754, 2014	13	2014
Hybrid marked point processes: Characterization, existence and uniqueness M Morariu-Patrichi, MS Pakkanen Market Microstructure and Liquidity 4 (03n04), 1950007, 2018	10	2018
Deep hedging: learning to remove the drift under trading frictions with minimal equivalent near-martingale measures H Buehler, P Murray, MS Pakkanen, B Wood arXiv preprint arXiv:2111.07844, 2021	9	2021
Sticky continuous processes have consistent price systems C Bender, MS Pakkanen, H Sayit Journal of Applied Probability 52 (2), 586-594, 2015	9	2015

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