| Machine learning in finance MF Dixon, I Halperin, P Bilokon Springer International Publishing, 2020 | 410 | 2020 |
| Machine learning in finance (Vol. 1170) MF Dixon, I Halperin, P Bilokon Springer International Publishing 10, 978-3, 2020 | 73 | 2020 |
| Transformers versus LSTMs for electronic trading P Bilokon, Y Qiu arXiv preprint arXiv:2309.11400, 2023 | 16 | 2023 |
| A domain-theoretic approach to Brownian motion and general continuous stochastic processes P Bilokon, A Edalat Proceedings of the Joint Meeting of the Twenty-Third EACSL Annual Conference …, 2014 | 12 | 2014 |
| Machine Learning and Big Data with kdb+/q J Novotny, PA Bilokon, A Galiotos, F Délèze John Wiley & Sons, 2019 | 11 | 2019 |
| Applications of reinforcement learning MF Dixon, I Halperin, P Bilokon, MF Dixon, I Halperin, P Bilokon Machine Learning in Finance: From Theory to Practice, 347-418, 2020 | 9 | 2020 |
| Feedforward Neural Networks MF Dixon, I Halperin, P Bilokon, MF Dixon, I Halperin, P Bilokon Machine Learning in Finance: From Theory to Practice, 111-166, 2020 | 7 | 2020 |
| Numerical solution of differential equations S Amen, P Bilokon, A Brinley Codd, M Fofaria, T Shah Available at SSRN 4847160, 2004 | 7 | 2004 |
| Exploring the advantages of transformers for high-frequency trading F Barez, P Bilokon, A Gervais, N Lisitsyn arXiv preprint arXiv:2302.13850, 2023 | 6 | 2023 |
| Benchmarking specialized databases for high-frequency data F Barez, P Bilokon, R Xiong arXiv preprint arXiv:2301.12561, 2023 | 6 | 2023 |
| Market regime classification with signatures P Bilokon, A Jacquier, C McIndoe arXiv preprint arXiv:2107.00066, 2021 | 5 | 2021 |
| C++ design patterns for low-latency applications including high-frequency trading P Bilokon, B Gunduz arXiv preprint arXiv:2309.04259, 2023 | 4 | 2023 |
| Iterated and exponentially weighted moving principal component analysis P Bilokon, D Finkelstein arXiv preprint arXiv:2108.13072, 2021 | 4 | 2021 |
| Simulation of Fractional Brownian Motion and Related Stochastic Processes in Practice: A Straightforward Approach YCC Wong, P Bilokon Available at SSRN, 2024 | 3 | 2024 |
| Machine Learning and Big Data with KDB+/Q: Q, High Frequency Financial Data and Algorithmic Trading PA Bilokon, J Novotny John Wiley & Sons, Incorporated, 2019 | 3 | 2019 |
| Combining Deep Learning on Order Books with Reinforcement Learning for Profitable Trading KS Jaddu, PA Bilokon arXiv preprint arXiv:2311.02088, 2023 | 2 | 2023 |
| A compendium of data sources for data science, machine learning, and artificial intelligence P Bilokon, O Bilokon, S Amen arXiv preprint arXiv:2309.05682, 2023 | 2 | 2023 |
| Frontiers of machine learning and finance MF Dixon, I Halperin, P Bilokon, MF Dixon, I Halperin, P Bilokon Machine learning in finance: From theory to practice, 519-541, 2020 | 2 | 2020 |
| Inverse reinforcement learning and imitation learning MF Dixon, I Halperin, P Bilokon, MF Dixon, I Halperin, P Bilokon Machine Learning in Finance: From Theory to Practice, 419-517, 2020 | 2 | 2020 |
| From Deep Learning to Deep Econometrics. R Stok, P Bilokon, J Simonian Journal of Financial Data Science 6 (2), 2024 | 1 | 2024 |
Igor HalperinFidelityEmail verificata su fmr.com
