Cédric Poutré

University of Montreal - Department of Mathematics and Statistics

PhD Graduate

C.P. 6128, succursale Centre-ville

Montreal, Quebec H3C 3J7

Canada

http://dms.umontreal.ca

SCHOLARLY PAPERS

3

DOWNLOADS

1,745

SSRN CITATIONS

4

CROSSREF CITATIONS

0

Scholarly Papers (3)

1.

The Profitability of Lead-Lag Arbitrage at High-Frequency

Number of pages: 53 Posted: 30 Sep 2022
Cédric Poutré, Georges Dionne and gabriel yergeau
University of Montreal - Department of Mathematics and Statistics, HEC Montreal - Department of Finance and HEC Montréal,
Downloads 855 (54,568)

Abstract:

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Lead-lag relationship, High-frequency trading, Statistical arbitrage, Limit order book, Cross-listed stocks, Econometric models.

International High-Frequency Arbitrage for Cross-Listed Stocks

Number of pages: 90 Posted: 22 Jul 2021 Last Revised: 31 Oct 2023
Cédric Poutré, Georges Dionne and Gabriel Yergeau
University of Montreal - Department of Mathematics and Statistics, HEC Montreal - Department of Finance and University of Montreal
Downloads 450 (121,699)

Abstract:

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Latency arbitrage, high-frequency trading, cross-listed stocks, mean-reverting arbitrage, international arbitrage, supervised machine learning

International High-Frequency Arbitrage for Cross-Listed Stocks

Number of pages: 58 Posted: 26 Mar 2022
Georges Dionne, Cédric Poutré and gabriel yergeau
HEC Montreal - Department of Finance, University of Montreal - Department of Mathematics and Statistics and HEC Montréal,
Downloads 125 (427,354)
Citation 2

Abstract:

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Latency arbitrage, High-Frequency Trading, cross-listed stocks, mean-reverting arbitrage, international arbitrage, supervised machine learning.

3.

Deep Unsupervised Anomaly Detection in High-Frequency Markets

Number of pages: 37 Posted: 13 Jul 2023
Cédric Poutré, Didier Chételat and Manuel Morales
University of Montreal - Department of Mathematics and Statistics, Polytechnique Montréal and University of Montreal
Downloads 315 (183,125)

Abstract:

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Limit order book, Time series anomaly detection, Deep learning, Trade-based manipulation, Dissimilarity model, Unsupervised learning