Marcos Lopez de Prado

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David EasleyProfessor Economics and Information Science, Cornell UniversityAdresse e-mail validée de cornell.edu
Maureen OHaraProfessor of Finance, Cornell UniversityAdresse e-mail validée de cornell.edu
Jonathan (Jon) M. BorweinLaureate Professor University of NewcastleAdresse e-mail validée de newcastle.edu.au
Qiji Jim ZhuWestern Michigan UniversityAdresse e-mail validée de wmich.edu
Alexander LiptonFellow, MIT Connection Science and EngineeringAdresse e-mail validée de mit.edu
Kesheng WuLawrence Berkeley National LaboratoryAdresse e-mail validée de lbl.gov
Francesco A. FabozziData Science Doctoral Candidate, Stevens Institute of TechnologyAdresse e-mail validée de stevens.edu
Peter CarrDepartment Chair, Finance and Risk Engineering, Tandon School, NYUAdresse e-mail validée de nyu.edu
Amir SalehipourThe University of Sydney Business SchoolAdresse e-mail validée de sydney.edu.au
Gili RosenbergAmazon Quantum Solutions LabAdresse e-mail validée de amazon.com
Horst SimonDirector, ADIA LabAdresse e-mail validée de adialab.ae
Zhibai ZhangNYUAdresse e-mail validée de nyu.edu
Joseph SimonianAutonomous Investment TechnologiesAdresse e-mail validée de autoinvestec.com
Jung Heon SongKLA-TencorAdresse e-mail validée de kla-tencor.com
Alex SimLawrence Berkeley National LaboratoryAdresse e-mail validée de lbl.gov
Stephanie GerNorthwestern UniversityAdresse e-mail validée de u.northwestern.edu
Antoine JacquierImperial College LondonAdresse e-mail validée de imperial.ac.uk
Oleksiy KondratyevImperial College LondonAdresse e-mail validée de imperial.ac.uk
Neil CalkinClemson UniversityAdresse e-mail validée de clemson.edu
Vincent ZoonekyndQuantitative research and development lead, ADIAAdresse e-mail validée de adia.ae

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Marcos Lopez de Prado

Professor of Practice, School of Engineering, Cornell University

Adresse e-mail validée de cornell.edu - Page d'accueil

Mathematical finance asset management hedge funds


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Advances in Financial Machine Learning M Lopez de Prado Wiley 1, 1-400, 2018	785*	2018
The microstructure of the ‘Flash Crash’: Flow toxicity, liquidity crashes and the probability of informed trading D Easley, M Lopez de Prado, M O'Hara The Journal of Portfolio Management 37 (2), 118-128, 2010	650	2010
Flow toxicity and Liquidity in a high frequency world D Easley, M Lopez de Prado, M O’Hara Review of Financial Studies 25 (5), 1457-1493, 2012	624	2012
Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation N Díaz-Rodríguez, J Del Ser, M Coeckelbergh, ML de Prado, ... Information Fusion 99, 101896, 2023	391	2023
Building diversified portfolios that outperform out-of-sample M Lopez de Prado Journal of Portfolio Management, 2016	378	2016
The Sharpe Ratio Efficient Frontier DH Bailey, M Lopez de Prado The Journal of Risk, 2012	271	2012
Solving the optimal trading trajectory problem using a quantum annealer G Rosenberg, P Haghnegahdar, P Goddard, P Carr, K Wu, ML De Prado Proceedings of the 8th workshop on high performance computational finance, 1-7, 2015	269	2015
Pseudomathematics and financial charlatanism: The effects of backtest over fitting on out-of-sample performance DH Bailey, JM Borwein, ML de Prado, QJ Zhu Notices of the AMS 61 (5), 458-471, 2014	230	2014
The Volume Clock: Insights into the High Frequency Paradigm D Easley, M Lopez de Prado, M O'Hara The Journal of Portfolio Management, 2012	206	2012
Machine learning for asset managers MML de Prado Elements in Quantitative Finance, 2020	193	2020
The deflated Sharpe ratio: Correcting for selection bias, backtest overfitting and non-normality DH Bailey, M López de Prado Journal of Portfolio Management 40 (5), 94-107, 2014	151	2014
The probability of backtest overfitting DH Bailey, J Borwein, M Lopez de Prado, QJ Zhu Journal of Computational Finance, forthcoming, 2016	147	2016
Discerning Information from Trade Data D Easley, M O'Hara http://ssrn.com/abstract=1989555, 2015	136	2015
Microstructure in the machine age D Easley, M López de Prado, M O’Hara, Z Zhang The Review of Financial Studies 34 (7), 3316-3363, 2021	90	2021
The 10 reasons most machine learning funds fail M López de Prado Journalof Portfolio Management, Forthcoming, 2018	79	2018
Bulk classification of trading activity D Easley, M Lopez de Prado, M O’Hara Johnson School Research Paper Series 8 (6), 14, 2012	72	2012
The Exchange of Flow Toxicity D Easley, M Lopez de Prado, M O'Hara The Journal of Trading 6 (2), 8-13, 2011	60*	2011
VPIN and the flash crash: A rejoinder D Easley, MML de Prado, M O'Hara Journal of Financial Markets 17, 47-52, 2014	56	2014
Detection of false investment strategies using unsupervised learning methods M López de Prado, MJ Lewis Quantitative Finance 19 (9), 1555-1565, 2019	51	2019
An open-source implementation of the critical-line algorithm for portfolio optimization DH Bailey, ML de Prado Algorithms 6 (1), 169-196, 2013	46	2013

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