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Market Microstructure

Paper Session

Monday, Jan. 5, 2026 1:00 PM - 3:00 PM (EST)

Loews Philadelphia Hotel, Commonwealth Hall A1
Hosted By: American Finance Association
  • Chair: Stacey Jacobsen, Southern Methodist University

You Can Only Lend What You Own: Inferring Daily Institutional Trading from Security Lending Supply

Yashar Barardehi
,
Chapman University
Zhi Da
,
University of Notre Dame
Peter Dixon
,
U.S. Securities and Exchange Commission
Junbo Wang
,
Louisiana State University

Abstract

Institutions make their equity holdings lendable, allowing us to use the daily change in lendable shares to proxy daily net institutional trading in each stock. Our proxy better tracks quarterly changes in institutional ownership than existing alternatives, or even a subset of actual institutional trades, especially if we allow the corresponding elasticity to vary across stocks. Using this proxy, we document (1) price momentum anomaly obtains only if institutional trading and intraday returns oppose during the portfolio formation period, consistent with under-reaction; (2) negative short-term return predictability, consistent with transitory institutional price impacts; (3) institutions unwind holdings before earnings announcements and re-establish them afterwards, suggesting the earnings announcement premium is trade-driven; and (4) institutions provide liquidity to retail investors, e.g., around stock splits.

The Modern Bond Market

Tomy Lee
,
Central European University
Chaojun Wang
,
University of Pennsylvania
Adam Zawadowski
,
Central European University

Abstract

The bond market is severely fragmented. We identify a simple innovation that counteracts this fragmentation: Rather than trading bonds one at a time as in existing models of trade, a bond trader simultaneously requests quotes for often dozens of bonds from the same set of dealers on modern bond platforms. The dealers may respond to all or some bonds, and the trader may accept some or even none of the quotes, possibly from different dealers. Such List requests comprise 73% of all requests on the largest platform and allow traders to simultaneously search over swaths of substitute bonds. We develop a simple model of simultaneous search and learning in which traders submit Lists in order to resolve price uncertainty and choose among substitute bonds. Two frictions underlie our model: First, bonds are partly substitutable, some more with each other than others. Second, traders do not know the current bond prices until they receive quotes. In equilibrium, each trader includes close substitute bonds into her List, and more so when there is greater uncertainty over prices or if quoted spreads are likely to be high. Our model yields sharp empirical predictions that we then test in the data from MarketAxess. Using requests for high-yield corporate bonds on the largest platform, we document that (i) traders substitute among bonds within each List, (ii) the substitution is stronger for bonds with similar maturities or ratings, (iii) a large fraction of unfilled bonds in Lists are never filled, and (iv) a List contains more substitute bonds when their prices are more uncertain.

Nocturnal Trading

Gregory Eaton
,
University of Georgia
Andriy Shkilko
,
University of Georgia
Ingrid Werner
,
Ohio State University

Abstract

Although relatively new, nocturnal trading in U.S.-listed equities, defined as trading between 8:00 p.m. and 4:00 a.m., has grown rapidly. This activity is predominantly retail-driven and concentrates in a relatively small subset of securities. A single trading platform dominates the nocturnal session, with liquidity supplied by only two market makers. Using unique transaction-level data, we show that despite limited liquidity-provider participation, trading costs remain relatively low. Moreover, despite the retail dominance, nocturnal trading contributes economically significant price discovery, particularly for non-U.S. firms and macro-oriented exchange-traded funds. While nocturnal traders appear to trade on price-relevant information, transaction costs leave average net profitability close to zero unless positions are held over longer horizons.

Intermediary Option Pricing

Julian Terstegge
,
Copenhagen Business School

Abstract

I find that intermediary inventory and equity illiquidity can explain most of the risk premium in S&P 500 options. I show that intermediaries' option inventory exposes them to ``gap risk', the risk of equity price changes over periods where low equity liquidity impedes an adjustment of equity market (delta) hedges. Intermediaries' gap risk can explain why negative option returns are heavily concentrated over nights and weekends, where equity liquidity is low. Contrary to common intuition, intermediaries' inventory gamma does not capture this inventory risk. Instead, I introduce the concept of ``shadow gamma', the expected option gamma in case of large negative equity market returns. Intermediaries' shadow gamma is large and negative, capturing the expected inventory losses in case of negative equity market returns, that result from intermediaries' short position in put options. I argue that gamma captures intraday risk, but shadow gamma captures overnight risk. Consistent with this argument, options' shadow gamma predicts options' night-returns, but not options' day-returns. Finally, I exploit the increase of overnight equity trading around 2006: I find significantly less negative option returns from Mondays to Fridays, relative to option returns over weekends, after 2006. This change in the option risk premium is concentrated in options where intermediaries are short, suggesting that intermediary inventory and equity liquidity jointly drive the option risk premium.

Discussant(s)
Matthew Ringgenberg
,
University of Utah
Edith Hotchkiss
,
Boston College
Thomas Ernst
,
University of Maryland
Dmitriy Muravyev
,
University of Illinois
JEL Classifications
  • G1 - General Financial Markets