Trust Busting: The Effect Of Fraud On Investor Behavior

Umit G. Gurun

University of Texas at Dallas – Naveen Jindal School of Management

Noah Stoffman

Indiana University – Kelley School of Business – Department of Finance

Scott E. Yonker

Cornell University – Dyson School of Applied Economics and Management

November 3, 2015

Kelley School of Business Research Paper No. 15-70


We study the effects of trust on investor behavior and investment flows by exploiting the geographic dispersion of victims of a multi-billion dollar Ponzi scheme. Investors in communities that were more exposed to the fraud subsequently withdrew assets from investment advisers and increased cash deposits at banks. Exposed advisers were also more likely to close. Advisers who provide services that can build trust — such as financial planning — experienced much lower withdrawals. Our evidence suggests that the trust shock was transmitted through social networks. Taken together, our results show that trust is a critical determinant of asset allocation and has real economic effects.

Trust Busting: The Effect Of Fraud On Investor Behavior – Introduction

Trust underlies most financial transactions. In the presence of incomplete contracts, an investor must have some degree of trust in a financial intermediary before being willing to invest.

In this paper, we empirically study the effects of trust on investor behavior and investment flows by exploiting a large shock to investor trust. In the framework of Gennaioli, Shleifer, and Vishny (2015), trust in financial intermediaries has two facets: first, confidence that one’s assets will not be stolen; and second, feeling that one’s assets are “in good hands,” thereby reducing anxiety about taking risk. The trust shock we study could lead investors to update their beliefs about the risk of theft, causing them to withdraw investments from delegated managers in favor of the relative safety of banks. We find strong evidence that investors did precisely that, but, consistent with the predictions of Gennaioli et al. (2015), we also show that money managers who provide additional services that can build trust—such as providing financial planning advice—suffered very little from withdrawals.

To identify the causal effects of a trust shock, we exploit the collapse of the multi-billion dollar Ponzi scheme orchestrated by Bernard Madoff, which was uncovered in December 2008. The Mado? fraud provides a particularly good testing ground to study trust for a number of reasons. First, the fraud was extremely large, and directly affected many geographically dispersed investors.2 Second, the fraud was explicitly a shock to trust of at least some investors, as is made clear from the 113 victim impact statements that were submitted to the court, which mention “trust” 45 times. Third, because the fraud targeted a particular group of investors, we are able to study how the trust shock is transmitted through social networks.


A common factor in the success of a Ponzi scheme is whether an “affinity” link is present between the perpetrator and the targeted victims. In a study of 367 Ponzi schemes, Deason, Rajgopal, and Waymire (2015) find that after family and friends, the most common affinity link cited by the SEC in Ponzi schemes is common religion. The Madoff scheme was an example of such a fraud, with many Jewish people and organizations becoming victims. The losses were widely felt in the Jewish community, with a number of charities being forced to cut back operations, and in some cases, close.3 We therefore refer to the Jewish community as the “affinity group” for this episode of fraud.

In addition to the direct effect of a shock to trust on Madoff victims, we draw on evidence that social connections and geographic proximity influence investment behavior (Hong, Kubik, and Stein, 2005; Ivkovic and Weisbenner, 2007; Pool, Stoffman, and Yonker, 2014) to hypothesize that other investors who are socially connected to a victim or members of the same affinity group are also more likely to suffer a reduction in trust. We exploit the relative clustering of victims in certain areas to implement difference-in-difference tests that enable us to identify the causal effect of trust on investor behavior.


The firm through which the fraud was perpetrated, Bernard L. Madoff Investment Securities, LLC (BLMIS), was regulated by the Securities and Exchange Commission (SEC) under the Investment Advisors Act of 1940 as a registered investment adviser (RIA). Despite having received several tips of suspicious behavior, the SEC did not act until Madoff’s son turned his father in.4 Thus, in the eyes of some, the Madoff fraud was seen as a failure of the SEC.5 People lost trust in the system. Indeed, using Gallup survey data, we confirm that people who were more exposed to the Mado? fraud reported larger declines in confidence in the criminal justice system than unaffected people; these results are confined to college-educated people and those with higher levels of income.

Investors may have thought that if a former chairman of the NASDAQ could perpetrate such a fraud, how many other fraudsters might exist among investment advisers? Following this logic, we expect to see abnormal outflows from SEC RIAs and inflows into safe bank deposits in treated areas. To test this, we use court documents to identify the direct victims of the Madoff fraud by name and address. We then aggregate the number of victims in a particular geographic area, and define the treatment as the relative concentration of victims in that area. We construct a panel of investment adviser flows using a data set that we construct to provide detailed information on annual assets under management (AUM) and the clientele locations for all SEC RIAs. We also collect branch-level cash deposits at banks from the FDIC’s Summary of Deposits data. Together, these data allow us to use a difference-in-difference framework to estimate the effects of the shock to trust on both the amount invested in delegated assets held with RIAs as well as in relatively safe bank deposits.


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