Conference Agenda
Please note that all times are shown in the time zone of the conference. The current conference time is: 1st Nov 2024, 12:14:46am CET
|
Session Overview |
Session | |||
MM 06: Man or Machine?
| |||
Presentations | |||
ID: 2112
HFTs and Dealer Banks: Liquidity and Price Discovery in FX Trading 1Bank for International Settlements; 2University of New South Wales; 3University of St. Gallen; 4Vrije Universiteit Amsterdam In this paper, we characterise the liquidity provision and price discovery roles of dealers and HFTs in the FX spot market during the sample period between 2012 and 2015. We find that they have different responses to adverse market conditions: HFT liquidity provision is less sensitive to spikes in market-wide volatility, while dealer bank liquidity is more robust ahead of scheduled macroeconomic news announcements when adverse selection risk is high. In periods of extreme levels of volatility, such as the ‘Swiss De-peg’ event in our sample, HFTs appear to withdraw almost all liquidity while dealers remain. In normal times, we also find that HFTs contribute to market liquidity by passively trading against the pricing errors created by dealers’ aggressive trade flows. On price discovery, HFTs contribute the dominant share, mostly through their high-frequency quote updates which incorporate public information. In contrast, dealers contribute to price discovery more through trades that impound private information.
ID: 1982
Algorithmic Pricing and Liquidity in Securities Markets HEC Paris, France We let “Algorithmic Market-Makers” (AMs), using Q-learning algorithms, choose prices for a risky asset when their clients are privately informed about the asset payoff. We find that AMs learn to cope with adverse selection and to update their prices after observing trades, as predicted by economic theory. However, in contrast to theory, AMs charge a mark-up over the competitive price, which declines with the number of AMs. Interestingly, markups tend to decrease with AMs’ exposure to adverse selection. Accordingly, the sensitivity of quotes to trades is stronger than that predicted by theory and AMs’ quotes become less competitive over time as asymmetric information declines.
ID: 717
Relationship Discounts in Corporate Bond Trading 1Bank for International Settlements, Switzerland; 2Bank of England We find that clients with stronger past trading relationships with a dealer receive consistently better prices in corporate bond trading. The top 1% of relationship clients face a sizeable 67% drop in transaction costs relative to the median client - an effect which is particularly strong during the COVID-19 turmoil. We find clients' liquidity provision to be a key driver of relationship discounts: clients to whom balance-sheet constrained dealers can turn to as a source of liquidity, are rewarded with relationship discounts. Another important motive for dealers to quote better prices to relationship clients is because these clients generate the bulk of dealers' profits. Finally, we find no evidence that extraction of information from clients' order flow is related to relationship discounts.
|
Contact and Legal Notice · Contact Address: Privacy Statement · Conference: EFA 2023 |
Conference Software: ConfTool Pro 2.6.151+TC © 2001–2024 by Dr. H. Weinreich, Hamburg, Germany |