I am the Real Estate Professor Associate Professor of Finance at the Gatton College of Business and Economics at the University of Kentucky. Currently, my research focuses on financial advisors, financial misconduct, and governance.
We show that analysts incorporate geographically dispersed information about firms into individual forecasts and that limited analyst geographic diversity adversely affects consensus forecasts and firm liquidity. Using satellite imagery of U.S. retailers' parking lots, we find analysts shade their own forecast in the direction of local car counts relative to other analysts covering the same firm at the same time but from different locations. Examining all industries, we find firms with more geographically concentrated analyst coverage have higher consensus forecast errors and are less liquid. Evidence from shocks in geographic coverage due to brokerage closures suggest these relations are causal.
Presented at Inaugural New Technologies in Finance Conference (Columbia University), 2nd Future of Financial Information Conference (Stockholm University), 2nd QES Virtual NLP and Machine Learning in Investment Management, Northern Finance Association conference, NBER Big Data and Securities Markets Fall 2020 conference
We examine the effect of investors' prior experience with mutual fund families on their subsequent investment decisions. Using a sample from a large discount broker, we find that investors are significantly more likely to purchase funds from families with which they have previous experience. Our results are consistent with the influence of family-level reputation and robust to alternative explanations such as service quality, fee discounts, marketing, blind loyalty, or inertia. Further consistent with reputation theories, individuals' beliefs about more reputable families appear to change slowly. After experience-based purchases, investors earn higher returns even controlling for investor ability and within-family correlation.
Presented at the Professional Asset Management (Erasmus University), Financial Management Association, and Financial Management Association European conferences
We examine the effect of mandatory disclosure of misconduct on reputation management by firms and individual employees. Using a panel data set of Central Registration Depository public disclosures by nancial advisors, we exploit a set of NASD/FINRA rule changes that substantially increased disclosure of past misconduct. In 2004, NASD Rule 2130 (later FINRA Rule 2080) prohibited expungement of misconduct records except for allegations that are clearly spurious and required judicial approval for all expungements. We find that prior to the 2004 rule change certain information useful for predicting future misconduct was obfuscated. However, even after the 2004 rule change, the expungement process still emoved valuable information, and a later rule change did little to improve the situation.Using these changes in disclosure policy, we find that advisory firms are likely to dismiss employees for misconduct only when it is disclosed. Similarly, the labor market for advisors penalizes advisors only when an incident of misconduct is publicly disclosed - not for the misconduct itself.
Presented at the American Law and Economics Association, Northern Finance Association, SFS Calvacade - Asia conferences
Using a geographic measure of unethical culture developed by Parsons, Sulaeman and Titman (2018) and a novel dataset of financial advisors' childhood residences, we show that advisors who grow up in U.S. counties with less ethical cultures are more likely to commit misconduct as adults. Our identification strategy exploits variation in childhood backgrounds between advisors working together in the same branch office in adulthood, thereby overcoming the reflection problem. Our results are robust to controlling for other factors from the early-life experiences literature such as income, education, ethnicity and religiosity. We find that areas with high concentrations of advisors that hail from less ethical cultures have lower levels of household equity participation. Our findings have important implications for how regional cultural norms regarding misconduct evolve.
Presented at the FRA Early Ideas, Smokey Mountain, Western Finance Association, European Financial Association and Northern Finance Association conferences
We test whether personal real estate shocks affect professional misconduct by financial advisors. We use a panel of advisors' home addresses and examine within-advisor variation relative to other advisors who work at the same firm and live in the same ZIP code. We find a negative relation between housing returns and misconduct. We show that advisors' housing returns explain misconduct against out-of-state customers, breaking the link between customer and advisor housing shocks. Further, the results are stronger for advisors with lower career risk from committing misconduct, and for advisors with greater borrowing constraints.
We study the effect of a change in property rights on employee behavior in the industry for financial advice. Our identification comes from staggered firm-level entry into the Protocol for Broker Recruiting. The agreement waived non-solicitation clauses for advisor transitions among member firms, effectively transferring ownership of client relationships from the firm to the advisor. After the shock, advisors appear to take better care of client relationships by investing in client-facing industry licenses, shifting to fee-based advising, and garnering fewer customer complaints. Our findings support property rights-based investment theories of the firm and document offsetting costs to restricting labor mobility.
Using a novel data set of U.S. financial advisors that includes individuals' employment histories and misconduct records, we show that co-workers influence an individual's propensity to commit financial misconduct. We identify co-workers' effect on misconduct using changes in co-workers caused by mergers of financial advisory firms. The tests include merger-firm fixed effects to exploit the variation in changes to co-workers across branches of the same firm. The probability of an advisor committing misconduct increases if his new co-workers, encountered in the merger, have a history of misconduct. This effect is stronger between demographically similar co-workers.
We provide the first examination of hedge fund boards and their directors. The majority of directorships are held by extremely busy independent directors. These directors are sought after by funds because they have more reputational capital at stake, making them independent and credible monitors whose presence can certify fund quality to investors. Busy independent directors are more likely to be hired by high quality funds, and their departure from the board is associated with investor withdrawals. Moreover, funds with busy independent directors are less likely to commit fraud, abuse discretionary liquidity restrictions, or engage in performance-based risk shifting.
Differences in accrued gains and investors’ tax-sensitivity induce variation in a capital gains lock-in effect across mutual funds even for the same stock at the same time. Exploiting this variation, we show this effect influences funds’ governance decisions: higher capital gains decrease the likelihood a fund exits prior to contentious votes and increase the likelihood a fund votes against management. Consistent with tax motivation, these findings are concentrated among funds with tax-sensitive investors. Further, high aggregate capital gains across funds holding a stock predict a higher likelihood management loses a vote and a lower likelihood a contentious vote is proposed.
We use SEC rule changes to show that regulatory oversight reduces return misreporting by hedge funds. Specifically, we use a 2004 rule change that expanded SEC oversight of hedge funds and the 2006 revocation of this rule. Differences-in-differences tests show that, following the rule change, misreporting by newly regulated funds decreased. After revocation, funds that exited the regulatory system increased misreporting relative to funds that remained registered. Placebo tests show no change in misreporting by foreign funds exempt from the rule change. We show that regulatory oversight increased the level of flows and decreased the sensitivity of flows to underperformance.
We show that the allocation of managerial ownership to individuals within firms varies depending upon the joint distribution of decision control and decision management rights. Using a unique dataset of institutional investment management firms, we show that ownership is higher for managers: with both executive and operational responsibilities; when benefits of cooperation are higher; and with large contributions to firm value. Consistent with career concerns, we find increases in a manager's ownership are associated with increases in unsystematic risk. Ownership dispersion within the firm is associated with the allocation of monitoring and operational roles and the potential benefits of cooperation.
Employing an instrumental variable approach based on the regulatory change of tick sizes, I examine the link between the liquidity of a firm's equity and activism by large shareholders. I find that liquidity increases the likelihood of block formation. Blockholders of more liquid securities take smaller stakes that do not precommit them to monitor. I find evidence that the threat of exit from a block can discipline managers and that this threat is more effective when liquidity is higher. While liquidity increases exit from existing blocks, I find no evidence that share illiquidity forces blockholders to actively monitor.
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.
One bad apple, the saying goes, can ruin the bunch. So, too, with employees. Our research on the contagiousness of employee fraud tells us that even your most honest employees become more likely to commit misconduct if they work alongside a dishonest individual. And while it would be nice to think that the honest employees would prompt the dishonest employees to better choices, that’s rarely the case. Among co-workers, it appears easier to learn bad behavior than good.
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 at https://doi.org/10.13023/nsjd-rk62.
The international financial crisis of 2008 focused attention on linkages between international financial markets as the crisis quickly propagated across countries and markets. Understanding the extent of financial market contagion during crisis times requires identifying normal interdependence; that is, how markets move during normal times. Normal interdependence includes price and volatility spillovers that may arrive contemporaneously or with a delay. Once normal interdependence is recognized, financial contagion can be measured relative to this base as a cross-market change in the transmission channels—particularly in asset price comovements—after a shock in one market. This chapter surveys the evidence on the linkages between international financial markets in an effort to characterize understanding of normal interdependence and contagion.
We present a novel approach for neuron model specification using a genetic algorithm (GA) to develop simple firing neuron models consisting of a single compartment with one inward and one outward current. The GA not only chooses the model parameters, but also chooses the formulation of the ionic currents (i.e. single-state variable, two-state variable, instantaneous, or leak). The fitness function of the GA compares the frequency output of the GA-generated models to an I–F curve of a nominal Morris–Lecar (ML) model. Initially, several different classes of models compete within the population. Eventually, the GA converges to a population containing only ML-type firing models, that is, models with an instantaneous inward and single-state variable outward current. Simulations where ML-type models are restricted from the population are also investigated. This GA approach allows the exploration of a universe of feasible model classes that is less constrained by model formulation assumptions than traditional parameter estimation approaches.
We present a reduction of a Hodgkin-Huxley (HH)—style bursting model to a hybridized integrate-and-fire (IF) formalism based on a thorough bifurcation analysis of the neuron's dynamics. The model incorporates HH-style equations to evolve the subthreshold currents and includes IF mechanisms to characterize spike events and mediate interactions between the subthreshold and spiking currents. The hybrid IF model successfully reproduces the dynamic behavior and temporal characteristics of the full model over a wide range of activity, including bursting and tonic firing. Comparisons of timed computer simulations of the reduced model and the original model for both single neurons and moderate lysized networks (n = 500) show that this model offers improvement in computational speed over the HH-style bursting model.