Market Frictions and Market Power
Paper Session
Friday, Jan. 5, 2024 10:15 AM - 12:15 PM (CST)
- Chair: Carole Comerton-forde, University of Melbourne
Competing for Dark Trades
Abstract
Trading at dark pools demands examination due to its importance as an exchange mechanism. In January 2021, trading outside public stock exchanges reached 47.2% of total U.S. equity trading volume, up from 39.9% a year earlier. Buy-side investors favor dark to lit trading venues due to their lower information leakage and trading costs (Menkveld et al., 2017), even though these venues are slower and less likely to match buyers with sellers. But do traders substitute across the dark pools?We evaluate how the availability of trading venues affects the evolution of dark trading. We show that a regulatory restriction of dark trading at the most prominent platform has a detrimental effect on dark trading activity. Annual dark trading decreases by more than 50% over the half-a-year restriction period. Consistent with investors' sticky relationships with specific dark pools, our results suggest that substitution across dark pools is remarkably low. We also show that restricting dark trading on a dominant platform does not lead to migration from dark to lit markets, traders revert to the other less transparent markets. 12% of the decrease in ban-related trading volume migrates to the systemic internalizers. Our findings are consistent with the European regulation failing to guide dark traders to lit markets.
Market Power in the Securities Lending Market
Abstract
We document the presence of market power in the equity securities lending market and evaluate its impact on different investor groups and valuations. Our analysis reveals high market concentration, non-competitive fees, and low inventory utilization in the cross-section of stocks. Motivated by this evidence, we develop and estimate a dynamic asymmetric-information model that sheds light on the benefits of this current market structure for both security lenders and short sellers. We find that lending fee income raises shares lenders’ equity valuations by 1.5% for large-cap, low-fee stocks, by up to 25% for small-cap stocks, and by even more than 100% for nano-cap stocks. Our model further yields estimates of the distribution of alphas from shorting different segments of the cross-section of stocks, indicating that fees reduce short sellers’ profits by about 60%.When A Market Is Not Legally Defined As A Market: Evidence From Two Types of Dark Trading
Abstract
Trading on off-exchange platforms as a whole is commonly referred to as dark trading. However, it encompasses ATSs (alternative trading systems) and Non-ATSs, each of which is subject to different regulations. ATSs are legally classified as market places, like exchanges, and therefore must adhere to fixed non-discretionary methods for executing orders. In contrast, Non-ATSs can exercise discretion on a per-order basis to determine which orders to execute internally and which to route out to other venues. In this study, we examine two exogenous identical transparency shocks and show that legal distinctions between ATSs and Non-ATSs can result in significant economic disparities in their market quality. Specifically, we find that ATSs are more vulnerable to adverse selection compared to Non-ATSs. Moreover, transparency magnifies disparities in market quality, except for execution speeds. Transparency leads to improved execution speeds on both ATSs and Non-ATSs. However, it notably diminishes other market quality metrics on ATSs, while remarkably enhancing them on Non-ATSs. Our results provide insight into an ongoing debate surrounding the accuracy of (Boehmer, Jones, Zhang, & Zhang, 2021)’s (BJZZ) method in identifying retail trades, partially elucidating the disparities between BJZZ’s findings and its critiques. Additionally, our paper is closely tied to a recent SEC proposal aimed at enhancing the disclosure of order execution information, thereby carrying significant policy implications.Discussant(s)
Thomas Ernst
,
University of Maryland
Sabrina Buti
,
Paris Dauphine University
Matthew Ringgenberg
,
University of Utah
Amber Anand
,
Syracuse University
JEL Classifications
- G1 - General Financial Markets