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yuriy nevmyvaka
yuriy nevmyvaka
Managing Director, ML Research, Morgan Stanley
Zweryfikowany adres z morganstanley.com
Tytuł
Cytowane przez
Cytowane przez
Rok
Reinforcement learning for optimized trade execution
Y Nevmyvaka, Y Feng, M Kearns
Proceedings of the 23rd international conference on Machine learning, 673-680, 2006
3392006
The Penn-Lehman automated trading project
M Kearns, L Ortiz
IEEE Intelligent systems 18 (6), 22-31, 2003
1262003
Empirical limitations on high frequency trading profitability
M Kearns, A Kulesza, Y Nevmyvaka
arXiv preprint arXiv:1007.2593, 2010
1062010
Censored exploration and the dark pool problem
K Ganchev, Y Nevmyvaka, M Kearns, JW Vaughan
Communications of the ACM 53 (5), 99-107, 2010
882010
Machine learning for market microstructure and high frequency trading
M Kearns, Y Nevmyvaka
High Frequency Trading: New Realities for Traders, Markets, and Regulators, 2013
872013
Market making and mean reversion
T Chakraborty, M Kearns
Proceedings of the 12th ACM conference on Electronic commerce, 307-314, 2011
732011
High-frequency trading: New realities for traders, markets and regulators
D Easley, L de Prado, M Mailoc, M O'Hara
(No Title), 2013
312013
Electronic trading in order-driven markets: efficient execution
Y Nevmyvaka, M Kearns, M Papandreou, K Sycara
Seventh IEEE International Conference on E-Commerce Technology (CEC'05), 190-197, 2005
292005
Lag-Llama: Towards Foundation Models for Time Series Forecasting
K Rasul, A Ashok, AR Williams, A Khorasani, G Adamopoulos, ...
arXiv preprint arXiv:2310.08278, 2023
182023
Machine learning for market microstructure and high frequency trading, High Frequency Trading: New Realities for Traders, Markets, and Regulators
M Kearns, Y Nevmyvaka
Risk Books, 2013
142013
Modeling temporal data as continuous functions with process diffusion
M Biloš, K Rasul, A Schneider, Y Nevmyvaka, S Günnemann
132022
Modeling temporal data as continuous functions with stochastic process diffusion
M Biloš, K Rasul, A Schneider, Y Nevmyvaka, S Günnemann
International Conference on Machine Learning, 2452-2470, 2023
122023
Provably convergent Schrödinger bridge with applications to probabilistic time series imputation
Y Chen, W Deng, S Fang, F Li, NT Yang, Y Zhang, K Rasul, S Zhe, ...
International Conference on Machine Learning, 4485-4513, 2023
122023
Empirical Limitations On High-Frequency Trading Profitability SSRN Working Paper, 17
M Kearns, A Kulesza, Y Nevmyvaka
September, 2010
72010
(In) Stability properties of limit order dynamics
E EvenDar, SM Kakade, M Kearns, Y Mansour
Proceedings of the 7th ACM conference on Electronic commerce, 120-129, 2006
62006
Pursuit-evasion without regret, with an application to trading
L Dworkin, M Kearns, Y Nevmyvaka
International Conference on Machine Learning, 1521-1529, 2014
42014
High Frequency Trading
M O’Hara, ML de Prado
Risk Books, London, 2013
42013
Risk Bounds on Aleatoric Uncertainty Recovery
Y Zhang, J Lin, F Li, Y Adler, K Rasul, A Schneider, Y Nevmyvaka
International Conference on Artificial Intelligence and Statistics, 6015-6036, 2023
32023
Optimized execution Via order book simulation
Y Nevmyvaka, M Kearns, A Papandreou, K Sycara
Available at SSRN 671963, 2005
32005
Empowering Time Series Analysis with Large Language Models: A Survey
Y Jiang, Z Pan, X Zhang, S Garg, A Schneider, Y Nevmyvaka, D Song
arXiv preprint arXiv:2402.03182, 2024
22024
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