The Journal of Finance

Does Floor Trading Matter?

Published: 10/27/2024   |   DOI: 10.1111/jofi.13401

JONATHAN BROGAARD, MATTHEW C. RINGGENBERG, DOMINIK ROESCH

Although algorithmic trading now dominates financial markets, some exchanges continue to use human floor traders. On March 23, 2020 the NYSE suspended floor trading because of COVID‐19. Using a difference‐in‐differences analysis around the closure of the floor, we find that floor traders are important contributors to market quality. The suspension of floor trading leads to higher spreads and larger pricing errors for treated stocks relative to control stocks. To explore the mechanism, we exploit two partial floor reopenings that have different characteristics. Our finding suggests that in‐person human interaction facilitates the transfer of valuable information that algorithms lack.

Reusing Natural Experiments

Published: 05/24/2023   |   DOI: 10.1111/jofi.13250

DAVIDSON HEATH, MATTHEW C. RINGGENBERG, MEHRDAD SAMADI, INGRID M. WERNER

After a natural experiment is first used, other researchers often reuse the setting, examining different outcome variables. We use simulations based on real data to illustrate the multiple hypothesis testing problem that arises when researchers reuse natural experiments. We then provide guidance for future inference based on popular empirical settings including difference‐in‐differences, instrumental variables, and regression discontinuity designs. When we apply our guidance to two extensively studied natural experiments, business combination laws and the Regulation SHO pilot, we find that many results that were statistically significant using single hypothesis testing do not survive corrections for multiple hypothesis testing.

A Multiple Lender Approach to Understanding Supply and Search in the Equity Lending Market

Published: 11/26/2012   |   DOI: 10.1111/jofi.12007

ADAM C. KOLASINSKI, ADAM V. REED, MATTHEW C. RINGGENBERG

Using unique data from 12 lenders, we examine how equity lending fees respond to demand shocks. We find that, when demand is moderate, fees are largely insensitive to demand shocks. However, at high demand levels, further increases in demand lead to significantly higher fees and the extent to which demand shocks impact fees is also related to search frictions in the loan market. Moreover, consistent with search models, we find significant dispersion in loan fees, with this dispersion increasing in loan scarcity and search frictions. Our findings imply that search frictions significantly impact short selling costs.

Short‐Selling Risk

Published: 12/15/2017   |   DOI: 10.1111/jofi.12601

JOSEPH E. ENGELBERG, ADAM V. REED, MATTHEW C. RINGGENBERG

Short sellers face unique risks, such as the risk that stock loans become expensive and the risk that stock loans are recalled. We show that short‐selling risk affects prices among the cross‐section of stocks. Stocks with more short‐selling risk have lower returns, less price efficiency, and less short selling.

Anomaly Time

Published: 07/18/2024   |   DOI: 10.1111/jofi.13372

BOONE BOWLES, ADAM V. REED, MATTHEW C. RINGGENBERG, JACOB R. THORNOCK

We examine the timing of returns around the publication of anomaly trading signals. Using a database that captures when information is first publicly released, we show that anomaly returns are concentrated in the first month after information release dates, and these returns decay soon thereafter. We also show that the academic convention of forming portfolios in June underestimates predictability because it uses stale information, which makes some anomalies appear insignificant. In contrast, we show many anomalies do predict returns if portfolios are formed immediately after information releases. Finally, we develop guidance on forming portfolios without using stale information.