Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
Please note that all times are shown in the time zone of the conference. The current conference time is: 30th Sept 2023, 08:07:38am CEST
1Bayes Business School, United Kingdom; 2IESE Business School
Discussant: Sabrina Buti (Université Paris Dauphine-PSL)
We show that, consistent with empirical evidence, access to order flow information allows traders to supply liquidity via contrarian marketable orders. An informational friction resulting from lack of market transparency can, however, make liquidity demand upward sloping, inducing strategic complementarities: traders demand more liquidity when the market becomes less liquid, fostering market illiquidity. This can generate instability with an initial dearth of liquidity degenerating into a liquidity rout (as in a flash crash), an event that is more likely to occur when market opacity hampers liquidity supply via marketable orders. Our theory also predicts that, when the market is fragile, traders faced with the largest price impact are those consuming more liquidity at equilibrium. Keywords: Liquidity fragility, flash crash, market information.
Uncertainty about What’s in the Price
Joel Peress1, Daniel Schmidt2
1INSEAD, France; 2HEC-Paris, France
Discussant: Sophie Moinas (Toulouse School of Economics)
A critical question facing speculators contemplating to trade on private information is whether their signal has already been priced in by the market. In our model, speculators assess the novelty of their information based on recent price movements, and market makers are aware that speculators might be trading on stale news. An asymmetric response to past price movements ensues: after price increases, buy volume—because it may result from stale news trading—has a lower price impact than sell volume (and vice versa after price decreases). Consequently, return skewness is negatively related to lagged returns. We find strong support for these and other predictions using a comprehensive sample of US stocks.