Supplementary Material for "A Machine Learning Attack on Illegal Trading"
9 Pages Posted: 21 Jan 2021 Last revised: 6 Dec 2022
Date Written: March 12, 2022
Abstract
This supplementary document contains information regarding the run times of the NN DTW and ARMA(1,1) illegal insider trading detection models. Details regarding the implementation of the ARMA(1,1), Gaussian Mixture Model (GMM), One-Class Support Vector Machine (OCSVM) and Isolation Forrest (iForest) models which are used as anomaly detection benchmarks in the paper ``A Machine Learning Attack on Illegal Trading" are also provided.
JEL Classification: C1,G1,G2
Suggested Citation: Suggested Citation
James, Robert and Leung, Henry and Prokhorov, Artem, Supplementary Material for "A Machine Learning Attack on Illegal Trading" (March 12, 2022). Available at SSRN: https://ssrn.com/abstract=3727753 or http://dx.doi.org/10.2139/ssrn.3727753
Do you have negative results from your research you’d like to share?
Feedback
Feedback to SSRN
If you need immediate assistance, call 877-SSRNHelp (877 777 6435) in the United States, or +1 212 448 2500 outside of the United States, 8:30AM to 6:00PM U.S. Eastern, Monday - Friday.