Researcher ORCID Identifier
Stephen G. Dimmock: https://orcid.org/0000-0003-3404-9307
Joseph D. Farizo: https://orcid.org/0000-0001-8130-6252
William C. Gerken: https://orcid.org/0000-0002-5601-8395
Dataset Creation Date
2018
Release Date
8-2018
Publisher
University of Kentucky Libraries
Description
We document the prevalence and variety of frauds committed by investment managers. We show that prior legal and regulatory violations, conflicts-of-interest, and monitoring disclosures available via the Security and Exchange Commission’s Form ADV are useful for predicting fraud. Additional tests show that fraud by rogue employees is more predictable than firm-wide fraud, but both types of fraud are significantly predictable. We revisit the fraud prediction model of Dimmock and Gerken (2012) and test its performance out-of-sample (using fraud cases discovered since that article’s publication). We find the model has significant predictive power for the out-of-sample cases. To encourage additional research in this area, we have made the data used in this chapter publicly available here.
Digital Object Identifier (DOI)
https://doi.org/10.13023/nsjd-rk62
Rights
© 2018 Stephen G. Dimmock, Joseph D. Farizo, and William C. Gerken
This dataset and the additional files are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (https://creativecommons.org/licenses/by-nc-sa/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided that the dataset creators and source are credited, that changes (if any) are clearly indicated, and that the derivative work is distributed under the same license.
Supporting Information
Two other files are available as the additional files noted at the end of this record.
Additional file 1: A list of variables with descriptions
Additional file 2: This file maps the CRD number in the ADV file to the Thomson Reuters MGRNO and MGRNAME identifiers. The dataset creators thank Chishen Wei of Singapore Management University for making this file available.
File Format
Dataset: DTA file (.dta)
Additional file 1: Microsoft Excel worksheet (.xlsx)
Additional file 2: Microsoft Excel comma separated values file (.csv)
File Size
Dataset: 630 MB
Additional file 1: 31 KB
Additional file 2: 2.34 MB
Related Publications
Dimmock, Stephen G., and William C. Gerken. “Predicting Fraud by Investment Managers.” Journal of Financial Economics 105, No. 1 (2012): 153-173. https://doi.org/10.1016/j.jfineco.2012.01.002
“Misconduct and Fraud by Investment Managers" by Stephen G. Dimmock, Joseph D. Farizo, and William C. Gerken in the forthcoming Wiley handbook “Corruption and Fraud in Financial Markets: Malpractice, Misconduct and Manipulation” edited by Carol Alexander and Doug Cumming.
Farizo, Joseph D. Essays on Financial Institutions and Advisors. https://doi.org/10.13023/etd.2020.080
How to Cite this Dataset
Dimmock, Stephen G.; Farizo, Joseph D.; and Gerken, William C., "Misconduct and Fraud by Investment Managers" (2018). Finance & Quantitative Methods Research Data. https://doi.org/10.13023/nsjd-rk62
Dimmock, Stephen G., and William C. Gerken. “Predicting Fraud by Investment Managers.” Journal of Financial Economics 105, No. 1 (2012): 153-173. https://doi.org/10.1016/j.jfineco.2012.01.002
“Misconduct and Fraud by Investment Managers" by Stephen G. Dimmock, Joseph D. Farizo, and William C. Gerken in the forthcoming Wiley handbook “Corruption and Fraud in Financial Markets: Malpractice, Misconduct and Manipulation” edited by Carol Alexander and Doug Cumming
List of variables
matching_crd_mgrno.csv (2406 kB)
CRD number mapping
Notes
Dataset creators' personal profiles: