“Inventory Management, Dealers’ Connections and Prices in OTC Markets” with Jean-Edouard Colliard and Peter Hoffman. Last revised: December 2019.
- Predicts that the distribution of aggregate inventories between core and peripheral dealers affect the distribution of transaction prices and bid-ask spreads in OTC markets.
- Latest draft (SSRN) available here.
- Online appendix available here.
- Abstract:We propose a new model of trading in OTC markets. Dealers accumulate inventories by trading with end-investors and trade among each other to reduce their inventory holding costs. Core dealers have access to a more efficient trading technology than peripheral dealers, who are heterogeneously connected to core dealers and trade with each other bilaterally. Connectedness affects prices and allocations if and only if the peripheral dealers’ aggregate inventory position differs from zero. The resulting price dispersion increases in the size of this position. The model generates new predictions about the joint effects of peripheral dealers’ connectedness and dealers’ aggregate inventories on transaction prices, both among dealers and between dealers and their clients.
“Demand for information, uncertainty and the response of U.S. treasury securities to news”, with Hedi Benamar and Clara Vega. Last Revised: May 2019. Presented at the NBER conference on big data and the Future of Financial Information Conference.
- Shows that information demand is high when macro-economic uncertainty is high
- Latest draft available (SSRN),
- Abstract:We propose to use information demand about a source of risk as a measure of investors’ uncertainty. Consistent with this idea, we show, using novel data on financial news consumption, that there is a positive correlation between information demand about macroeconomic factors perceived as affecting the path of future interest rates and other measures of uncertainty about future interest rates. Moreover, an increase in information demand about these factors ahead of influential macroeconomic announcements predicts an increase in the reaction of U.S Treasury note yields to these announcements, consistent with our hypothesis that information demand is high when uncertainty is high.
A new survey on HFT: “Is trading fast dangerous“, forthcoming in Global Algorithmic Capital Markets: High Frequency Trading, Dark Pools, and Regulatory Challenges, 2019.
“Noisy Stock Prices and Corporate Investment” with Olivier Dessaint, Laurent Frésard, and Adrien Matray. Accepted for publication in the Review of Financial Studies.
- Shows that non fundamental shocks to firms’ stock prices affects corporate investment because managers use stock prices a signals and have limited ability to filter out the noise in these signals
- Advance Access at the Review of Financial Studies, Latest draft available (SSRN). On-line Appendix, Slides
- Abstract: Firms significantly reduce their investment in response to non-fundamental drops in the stock price of their product-market peers. We argue that this result arises because of managers’ limited ability to filter out the noise in stock prices when using them as signals about their investment opportunities. The resulting losses of capital investment and shareholders’ wealth are economically large, and affect even firms that are not facing severe financing constraints or agency problems. Our findings offer a novel perspective on how stock market inefficiencies can affect the real economy, even in the absence of financing or agency frictions.