Large data sets and machine learning: applications to statistical arbitrage

DOI10.1016/j.ejor.2019.04.013zbMath1414.91435OpenAlexW2937013183MaRDI QIDQ2424788

Nicolas Huck

Publication date: 25 June 2019

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2019.04.013

zbMATH Keywords

financemachine learningbig datastatistical arbitrage

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Financial applications of other theories (91G80)

Related Items (8)

Credit default prediction from user-generated text in peer-to-peer lending using deep learning ⋮ Training trees on tails with applications to portfolio choice ⋮ Cross-impact of order flow imbalance in equity markets ⋮ Separating the signal from the noise -- financial machine learning for Twitter ⋮ Pairs trading via unsupervised learning ⋮ Statistical arbitrage: factor investing approach ⋮ Revealing pairs-trading opportunities with long short-term memory networks ⋮ Sparse regression for large data sets with outliers

Uses Software

• darch
• ISLR

Cites Work

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