Abstract: Investors act as a liquidity back-stop in the corporate bond market. By providing liquidity, investors help ease dealers’ balance sheet constraints, especially during market stress. During the March 2020 Dash-for-Cash, in bonds where investors stopped providing liquidity, transaction costs rose by 38%. We find the composition of types of liquidity providers – rather than just their presence – shapes trading costs. Dealers relying on flexible-mandate investors, such as hedge funds, are more resilient to liquidity shocks. Dealers offer discounts to investors for past liquidity services to maintain liquidity provider networks. These discounts represent two-thirds of relationship discounts.
Does big data devalue traditional expertise? Evidence from Active Funds Managers, with Maxime Bonelli. First Draft: July 2023. Latest draft: February 2025
Abstract:We investigate how the availability of alternative data affects the performance of active mutual funds that rely on traditional expertise to produce information. To do so, we evaluate the impact of the release of stock-specific data, which provide new information but require data science expertise to leverage. We find that this release significantly reduces mutual funds’ stock-picking abilities in covered stocks, with a stronger effect for funds that rely on traditional expertise, like industry specialization, leading them to divest from covered stocks. Alternative data can therefore reshape the determinants of fund performance by reducing the value of traditional information sources.
Algorithmic pricing and liquidity in securities markets, with Jean-Edouard Colliard and Stefano Lovo. First Draft: October 2022. Latest draft: May 2025
Abstract: We study “Algorithmic Market Makers” (AMs) that use Q-learning algorithms to set prices for a risky asset. We find that while AMs successfully adapt to adverse selection, they struggle to learn competitive pricing strategies. This failure is driven by limited experimentation and noisy feedback regarding the profitability of undercutting a competitor. Consequently, an increase in AMs’ profit volatility tends to result in less competitive market outcomes. These features leave identifiable patterns: for example, AMs earn higher rents in the absence of adverse selection, and their bid-ask spreads respond asymmetrically to symmetric shocks to their costs.
The horizon of investors’ information and corporate investment,with Olivier Dessaint and Laurent Frésard. First Draft: October 2022. Under revision.
Abstract: We study how the quality ofinvestors’information across horizons influences investment. In our theory, managers care about how investment is impounded in current stock prices. Because prices imperfectly reflect investment’s value, they under-invest. However, they under-invest less when investors have better information about thehorizon matching that of their projects. Using a measure of projects’ horizon obtained from the text of regulatory filings, we find that improvements in investors’ long-term (short-term) information induce firms with long-term (short-term) projects to invest more, especially when managers focus on current stock prices. Therefore, the quality ofinvestors’information across horizons has real effects.
Old working papers
“Linkage Principle, Multidimensional Signals and Blind Auctions”, with Stefano Lovo, 2004 (draft on SSRN)
“Price formation and order placement strategies in a dynamic order driven markets”, 1995 (draft)
Thierry Foucault 