Mikko S. Pakkanen

11 papers A* 1Misc 1Journal 8Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Diverse Approaches to Optimal Execution Schedule Generation.
CoRR
Robert de Witt, Mikko S. Pakkanen
2025 A* conf
Learning with Expected Signatures: Theory and Applications.
ICML
Lorenzo Lucchese, Mikko S. Pakkanen, Almut E. D. Veraart
2025 J jnl
Learning with Expected Signatures: Theory and Applications.
CoRR
Lorenzo Lucchese, Mikko S. Pakkanen, Almut E. D. Veraart
2022 — conf
Deep Hedging: Continuous Reinforcement Learning for Hedging of General Portfolios across Multiple Risk Aversions.
ICAIF
Phillip Murray, Ben Wood, Hans Buehler, Magnus Wiese, Mikko S. Pakkanen
2022 J jnl
πVAE: a stochastic process prior for Bayesian deep learning with MCMC.
Stat. Comput.
Swapnil Mishra, Seth R. Flaxman, Tresnia Berah, Harrison Zhu, Mikko S. Pakkanen, Samir Bhatt
2021 J jnl
Pathwise large deviations for the rough Bergomi model: Corrigendum.
J. Appl. Probab.
Stefan Gerhold, Antoine Jacquier, Mikko S. Pakkanen, Henry Stone, Thomas Wagenhofer
2019 J jnl
Hybrid simulation scheme for volatility modulated moving average fields.
Math. Comput. Simul.
Claudio Heinrich, Mikko S. Pakkanen, Almut E. D. Veraart
2018 J jnl
Pathwise large deviations for the rough Bergomi model.
J. Appl. Probab.
Antoine Jacquier, Mikko S. Pakkanen, Henry Stone
2017 J jnl
Hybrid scheme for Brownian semistationary processes.
Finance Stochastics
Mikkel Bennedsen, Asger Lunde, Mikko S. Pakkanen
2015 J jnl
Sticky Continuous Processes have Consistent Price Systems.
J. Appl. Probab.
Christian Bender, Mikko S. Pakkanen, Hasanjan Sayit
2012 Misc conf
An approximative method of simulating a duel.
WSC
Esa Lappi, Mikko S. Pakkanen, Bernt Åkesson