The Journal of Finance publishes leading research across all the major fields of finance. It is one of the most widely cited journals in academic finance, and in all of economics. Each of the six issues per year reaches over 8,000 academics, finance professionals, libraries, and government and financial institutions around the world. The journal is the official publication of The American Finance Association, the premier academic organization devoted to the study and promotion of knowledge about financial economics.
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Search results: 9.
Crossing Networks and Dealer Markets: Competition and Performance
Published: 12/17/2002 | DOI: 10.1111/0022-1082.00281
Terrence Hendershott, Haim Mendelson
This paper studies the interaction between dealer markets and a relatively new form of exchange, passive crossing networks, where buyers and sellers trade directly with one another. We find that the crossing network is characterized by both positive (‘liquidity’) and negative (‘crowding’) externalities, and we analyze the effects of its introduction on the dealer market. Traders who use the dealer market as a ‘market of last resort’ can induce dealers to widen their spread and can lead to more efficient subsequent prices, but traders who only use the crossing network can provide a counterbalancing effect by reducing adverse selection and inventory holding costs.
Liquidity Externalities and Adverse Selection: Evidence from Trading after Hours
Published: 03/25/2004 | DOI: 10.1111/j.1540-6261.2004.00646.x
Michael J. Barclay, Terrence Hendershott
This paper examines liquidity externalities by analyzing trading costs after hours. There is less than 1/20 as many trades per unit time after hours as during the trading day. The reduced trading activity results in substantially higher trading costs: quoted and effective spreads are three to four times larger than during the trading day. The higher spreads reflect greater adverse selection and order persistence, but not higher dealer profits. Because liquidity provision remains competitive after hours, the greater adverse selection and higher trading costs provide a direct measure of the magnitude of the liquidity externalities generated during the trading day.
Click or Call? Auction versus Search in the Over‐the‐Counter Market
Published: 03/26/2014 | DOI: 10.1111/jofi.12164
TERRENCE HENDERSHOTT, ANANTH MADHAVAN
Over‐the‐counter (OTC) markets dominate trading in many asset classes. Will electronic trading displace traditional OTC “voice” trading? Can electronic and voice systems coexist? What types of securities and trades are best suited for electronic trading? We study these questions by focusing on an innovation in electronic trading technology that enables investors to simultaneously search many bond dealers. We show that periodic one‐sided electronic auctions are a viable and important source of liquidity even in inactively traded instruments. These mechanisms are a natural compromise between bilateral search in OTC markets and continuous double auctions in electronic limit order books.
Competition among Trading Venues: Information and Trading on Electronic Communications Networks
Published: 11/07/2003 | DOI: 10.1046/j.1540-6261.2003.00618.x
Michael J. Barclay, Terrence Hendershott, D. Timothy McCormick
This paper explores the competition between two trading venues, Electronic Communication Networks (ECNs) and Nasdaq market makers. ECNs offer the advantages of anonymity and speed of execution, which attract informed traders. Thus, trades are more likely to occur on ECNs when information asymmetry is greater and when trading volume and stock‐return volatility are high. ECN trades have greater permanent price impacts and more private information is revealed through ECN trades than though market‐maker trades. However, ECN trades have higher ex ante trading costs because market makers can preference or internalize the less informed trades and offer them better executions.
Automation versus Intermediation: Evidence from Treasuries Going Off the Run
Published: 09/19/2006 | DOI: 10.1111/j.1540-6261.2006.01061.x
MICHAEL J. BARCLAY, TERRENCE HENDERSHOTT, KENNETH KOTZ
This paper examines the choice of trading venue by dealers in U.S. Treasury securities to determine when services provided by human intermediaries are difficult to replicate in fully automated trading systems. When Treasury securities go “off the run” their trading volume drops by more than 90%. This decline in trading volume allows us to test whether intermediaries' knowledge of the market and its participants can uncover hidden liquidity and facilitate better matching of customer orders in less active markets. Consistent with this hypothesis, the market share of electronic intermediaries falls from 81% to 12% when securities go off the run.
Price Discovery without Trading: Evidence from Limit Orders
Published: 03/18/2019 | DOI: 10.1111/jofi.12769
JONATHAN BROGAARD, TERRENCE HENDERSHOTT, RYAN RIORDAN
We analyze the contribution to price discovery of market and limit orders by high‐frequency traders (HFTs) and non‐HFTs. While market orders have a larger individual price impact, limit orders are far more numerous. This results in price discovery occurring predominantly through limit orders. HFTs submit the bulk of limit orders and these limit orders provide most of the price discovery. Submissions of limit orders and their contribution to price discovery fall with volatility due to changes in HFTs’ behavior. Consistent with adverse selection arising from faster reactions to public information, HFTs’ informational advantage is partially explained by public information.
Relationship Trading in Over‐the‐Counter Markets
Published: 11/15/2019 | DOI: 10.1111/jofi.12864
TERRENCE HENDERSHOTT, DAN LI, DMITRY LIVDAN, NORMAN SCHÜRHOFF
We examine the network of trading relationships between insurers and dealers in the over‐the‐counter (OTC) corporate bond market. Regulatory data show that one‐third of insurers use a single dealer, whereas other insurers have large dealer networks. Execution prices are nonmonotone in network size, initially declining with more dealers but increasing once networks exceed 20 dealers. A model of decentralized trade in which insurers trade off the benefits of repeat business and faster execution quantitatively fits the distribution of insurers' network size and explains the price–network size relationship. Counterfactual analysis shows that regulations to unbundle trade and nontrade services can decrease welfare.
Does Algorithmic Trading Improve Liquidity?
Published: 01/06/2011 | DOI: 10.1111/j.1540-6261.2010.01624.x
TERRENCE HENDERSHOTT, CHARLES M. JONES, ALBERT J. MENKVELD
Algorithmic trading (AT) has increased sharply over the past decade. Does it improve market quality, and should it be encouraged? We provide the first analysis of this question. The New York Stock Exchange automated quote dissemination in 2003, and we use this change in market structure that increases AT as an exogenous instrument to measure the causal effect of AT on liquidity. For large stocks in particular, AT narrows spreads, reduces adverse selection, and reduces trade‐related price discovery. The findings indicate that AT improves liquidity and enhances the informativeness of quotes.
Time Variation in Liquidity: The Role of Market‐Maker Inventories and Revenues
Published: 01/13/2010 | DOI: 10.1111/j.1540-6261.2009.01530.x
CAROLE COMERTON‐FORDE, TERRENCE HENDERSHOTT, CHARLES M. JONES, PAMELA C. MOULTON, MARK S. SEASHOLES
We show that market‐maker balance sheet and income statement variables explain time variation in liquidity, suggesting liquidity‐supplier financing constraints matter. Using 11 years of NYSE specialist inventory positions and trading revenues, we find that aggregate market‐level and specialist firm‐level spreads widen when specialists have large positions or lose money. The effects are nonlinear and most prominent when inventories are big or trading results have been particularly poor. These sensitivities are smaller after specialist firm mergers, consistent with deep pockets easing financing constraints. Finally, compared to low volatility stocks, the liquidity of high volatility stocks is more sensitive to inventories and losses.