Iuliia Manziuk is a postdoctoral researcher at École Polytechnique, working on:
– Systematic strategies
– Reinforcement learning for optimal trading
– Optimal market making
Iuliia holds a PhD in Applied Mathematics from Université Paris-1 Panthéon Sorbonne under the supervision of Olivier Guéant. The title of her PhD is ‘’Optimal control and machine learning in finance: contributions to the literature on optimal execution, market making, and exotic options’’.
She has a Master 2 degree (M2) in Analysis and Policy in Economics from Paris School of Economics (PSE), a Master Degree (M1 and M2) in Applied Economics from Higher School of Economics (HSE) Moscow, and a Bachelor in Applied mathematics and Cybernetics from Moscow State University.
Bastien Baldacci and Iuliia Manziuk won Rising Star in Quant Finance – Risk Awards 2021: Rising stars in quant finance: Iuliia Manziuk and Bastien Baldacci
Papers:
- ”Optimal control on graphs: existence, uniqueness, and long-term behavior’’, with O. Guéant, published in ESAIM: Control, Optimisation and Calculus of Variations
- ”Accelerated Share Repurchase and other buyback programs: what neural networks can bring’’, with O. Guéant, J. Pu, published in Quantitative Finance.
- ”Optimal execution: a Deep Blue like approach”, with O. Guéant, technical report.
- ”Optimal Market Making: deep reinforcement learning approach’’, with O. Guéant, published in Applied Mathematical Finance.
- ”Market making and incentives design in the presence of a dark pool: a deep reinforcement learning approach’’, with B. Baldacci, T. Mastrolia, M. Rosenbaum, submitted to Operations Research
- ”Adaptive trading strategies across liquidity pools’’, with B. Baldacci, submitted to Market Microstructure and Liquidity.
- ”Liquidity Stress Testing using Optimal Portfolio Liquidation’’, with M. Weber, B. Baldacci, submitted to Risk Magazine.
- An approximate solution for options market-making in high dimension with Bastien Baldacci and Joffrey Derchu