Abstract: Large asset heterogeneity is one of the most salient features of over-the-counter
(OTC) markets. We first demonstrate, in a benchmark model, that asset heterogeneity results in market fragmentation, limiting the beneficial
network externality of liquidity. We then introduce quasi-consolidated (QC)
contract—a mechanism that enables assets of heterogeneous values to be
traded at a uniform price—into the benchmark model and show that it increases
total trading volume and social welfare by reducing market fragmentation.
Nevertheless, the uniform pricing of QC trading leads to a cheapest-to-
deliver effect, which harms liquidity for sellers who do not adopt QC trading;
it also lowers profits for these sellers and even some sellers who adopt
QC trading. Our model lays a foundation for analyzing liquidity and design
in OTC markets of heterogeneous assets.
Discussant: Patrick Blonien, Carnegie Mellon University
Abstract: We study the price impact of sales in bond markets. Using novel data on the transactions of financial firms in corporate and government bonds in the UK, we develop a new measure of non-fundamental selling pressure. We instrument for firms' sales of a bond with their sales of bonds other than the bond in question and exploit within issuer-time variation to identify selling pressure that is unrelated to the bond's fundamentals. The price impact of a sale depends critically on who is selling the asset: sales by dealers and hedge funds generate significantly larger impacts than sales of the same size by other investor types. Our results suggest that more attention should be devoted to risks to financial stability stemming from these impactful sellers.
Abstract: Fixed income funds carry significant duration risk from their use of interest rate derivatives (IRDs). This duration risk is hidden, as funds typically disclose portfolio duration weighted by market values instead of notionals, concealing their true risk. We find substantial variation in the duration of IRDs, both across funds and over time. Funds use IRDs not only for hedging but also for speculation, often disregarding the risk in their bond portfolios. During interest rate hikes in 2022 and 2023, funds that increased leverage through IRDs performed particularly poorly.
In contrast, those that increased leverage during interest rate cuts in 2020 achieved outperformance, reinforcing funds' inclination towards risk-taking during the later interest rate hikes.
Stanislava Nikolova, University of Nebraska-Lincoln
Alexander Philipov, George Mason University
Abstract: We study the impact of data uncertainty in corporate bonds on decision making. We provide a taxonomy of data choices a researcher is compelled to make when constructing a sample of monthly corporate bond returns, and investigate the impact of these choices on the researcher's conclusions. Using momentum as a case study, we show that different but reasonable data choices may lead to conflicting findings about a strategy's profitability and thus result in data uncertainty. We propose a Bayesian decision-making framework for a researcher faced with data uncertainty.
Discussant: Peter Feldhütter, Copenhagen Business School
