I am an Assistant Professor of Finance at the University of Richmond's Robins School of Business. At UR, I teach multiple sections of investments. My research focuses on corporate governance and financial intermediation. As a graduate student at the University of Kentucky, I led courses and seminars in corporate finance, Microsoft Excel, and Python programming.
I was born and raised south of New Orleans, Louisiana and obtained my Bachelor's and Master's degrees in finance from Louisiana State University. In my spare time, I enjoy traveling, motorcycling, and playing the guitar (poorly).
I propose a novel identification strategy to examine whether “passive” index funds participate in monitoring. Specifically, I examine how index funds vote their proxies on firms in its index that their family does not hold in actively managed funds. For a given proxy proposal at a given point in time, I find an index fund is more likely to oppose management on shares its family does not hold in its active funds than on shares its family does hold in its active funds. I further demonstrate index fund voting has effects on proposal passage rates and on shareholder value.
Presented at SEC PhD Consortium (2018), Eastern Finance Association (2019), University of Kentucky (2019), FMA PhD Student Consortium (2019), FMA Annual Meeting (2019), University of South Carolina (2019), The College of New Jersey (2019), Salisbury University (2019), Towson University (2019), University of Richmond (2019), The Citadel (2019).
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.
Following Dimmock and Gerken (2012) and Dimmock, Gerken, and Marietta-Westberg (2015), we use Form ADV data to construct an annual panel of registered investment advisors. Variable definitions are available at the data download site. If you use this dataset, please cite Dimmock, Farizo, and Gerken (2018) and Dimmock and Gerken (2012).
My favorite motorcycle routes (each is a link to an interactive Google Map): Highway 213 · Small Town Loop · Keeneland · UKY to EKU · Red River Gorge · The Mills · Dealers' Row · Raven Run and Jacks · Boones and Four Mile Road · Shaker Village · White Oak · Buckeye Ridge · 89 South · Stamping Ground · Ohio River · Daniel Boone National Forest · To Frankfort · Bighill Overlook