David Stolin

Frenemies: How Do Financial Firms Vote on Their Own Kind?

The financial sector is unique in being largely self-governed: the majority of financial firms’ shares are held by other financial institutions. This raises the possibility that monitoring of financial firms is especially undermined by conflicts of interest due to personal and professional links between these firms and their shareholders. To investigate this possibility, we scrutinize the aspect of the financial sector’s self-governance that is directly observable: mutual fund companies’ voting of their peers’ stock. We find that considerations specific to investee firms’ membership in the same industry as their investors do indeed impact voting. This impact is in the direction of supporting the investee’s management. We show that the own-industry effect reduces director efficacy and lowers firm value as a result. We extend our analysis to other financial companies and show that they also tend to vote more favorably when it comes to their peers. Our results suggest that peer support is a corrupting factor in the financial sector’s governance.

Predicting stock return correlations with brief company descriptions

ABSTRACT A series of influential papers by Hoberg and Phillips measure the similarity of pairs of companies based on a textual analysis of their business descriptions and show these measures to be useful in a variety of research contexts in finance. Hoberg and Phillips derive the similarity measures from a comparison of word lists extracted from extensive business descriptions contained in US companies’ electronic 10-K filings. Unfortunately, this method is of little use in non-US settings, where lengthy English-language company self-descriptions are not available on a consistent basis. Instead, we use semantic fingerprinting to extract such similarity measures from much shorter but globally available third-party company descriptions. We show that our approach significantly predicts stock return correlations even after controlling for past correlations and for membership in the same industry. Remarkably, company similarity measures based on brief third-party company descriptions predict stock return correlations significantly better than those based on much longer company self-descriptions.

Intra-Dealer Integration

This paper examines the quotation behaviour of dealers who made markets in the same stocks on both NASDAQ and either EASDAQ or the LSE. Whereas previous studies examine international integration at the market level, we examine integration at the dealer level. In other words, do dealers within the same market-making firm use information from their arm on the opposite side of the Atlantic in forming their own quotes? We find that while there is some evidence of integration at the market level, integration is hard to detect at the dealer level. The results are largely unaffected by differences in fungibility between our two samples.