Predicting fraud by investment managers

Stochastic Herding by Institutional Investment Managers

This paper demonstrates that the behavior of institutional investors around the downturn of the U.S. equity markets in 2007 is consistent with stochastic herding in attempts to time the market. We consider a model of large number of institutional investment managers who simultaneously decide whether to remain invested in an assets or liquidate their positions. Each fund manager receives imperfe...

Individual Differences in Susceptibility to Investment Fraud

Predicting financial statement fraud using fuzzy neural networks

Fraud is a common phenomenon in business, and according to Section 24 of the Iranian Auditing Standards, it is the fraudulent act of one or more managers, employees, or third parties to derive unfair advantage and any intentional or unlawful conduct. Financial statements are a means of transmitting confidential management information about the<br ...

The Effect of Managers' Stability and the Stability of Institutional Stakeholders on the Probability of Fraud, by Employing Different Approaches to calculate Fraud

The purpose of this study was to investigate the effect of managers' stability and the stability of institutional stakeholders on the probability of fraud in companies. In line with the research goal, two hypotheses were developed. To test these two hypotheses using a systematic elimination method, a sample of 101 companies during the eight-year period between 2010 and 2017 was selected. In thi...

Investment, Shareholder Monitoring and The Economics of Corporate Securities Fraud

In this study, I investigate the economic determinants of firms’ propensity to commit securities fraud and the determinants of fraud detection. The analysis is based on a new handcompiled fraud sample of private securities class action litigation suits filed between 1996 and 2003 involving allegations of accounting irregularities. I use econometric methods to account for the unobservability of ...