Abstract

http://ssrn.com/abstract=1832770
 
 

References (23)



 
 

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Predicting Fraud by Investment Managers


William Christopher Gerken


University of Kentucky - Finance

Stephen G. Dimmock


Nanyang Technological University - Division of Finance

August 7, 2011

Networks Financial Institute Working Paper No. 2011-WP-09

Abstract:     
We test the predictability of investment fraud using a panel of mandatory disclosures filed with the SEC. We find that disclosures related to past regulatory and legal violations, conflicts of interest, and monitoring have significant power to predict fraud. Avoiding the 5% of firms with the highest ex ante predicted fraud risk would allow an investor to avoid 29% of fraud cases and over 40% of the total dollar losses from fraud. We find no evidence that investors receive compensation for fraud risk through superior performance or lower fees. We examine the barriers to implementing fraud prediction models and suggest changes to the SEC's data access policies that could benefit investors.

Number of Pages in PDF File: 47

Keywords: Fraud, Investment Fraud, Operational Risk, SEC, Disclosure, Form ADV

JEL Classification: G2, G20, G28, K2, K22

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Date posted: May 9, 2011 ; Last revised: August 8, 2011

Suggested Citation

Gerken, William Christopher and Dimmock, Stephen G., Predicting Fraud by Investment Managers (August 7, 2011). Networks Financial Institute Working Paper No. 2011-WP-09. Available at SSRN: http://ssrn.com/abstract=1832770 or http://dx.doi.org/10.2139/ssrn.1832770

Contact Information

William Christopher Gerken (Contact Author)
University of Kentucky - Finance ( email )
College of Business & Economics
Lexington, KY 40506-0034
United States
Stephen G. Dimmock
Nanyang Technological University - Division of Finance ( email )
S3-B1B-76 Nanyang Avenue
Singapore, 639798
Singapore
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