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on Market Microstructure |
| By: | Weibing Huang; Mathieu Rosenbaum; Pamela Saliba |
| Abstract: | We build an agent-based model for the order book with three types of market participants: informed trader, noise trader and competitive market makers. Using a Glosten-Milgrom like approach, we are able to deduce the whole limit order book (bid-ask spread and volume available at each price) from the interactions between the different agents. More precisely, we obtain a link between efficient price dynamic, proportion of trades due to the noise trader, traded volume, bid-ask spread and equilibrium limit order book state. With this model, we provide a relevant tool for regulators and market platforms. We show for example that it allows us to forecast consequences of a tick size change on the microstructure of an asset. It also enables us to value quantitatively the queue position of a limit order in the book. |
| Date: | 2019–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1902.10743&r=all |
| By: | Shino Takayama (School of Economics, The University of Queensland) |
| Abstract: | This paper studies the manipulation of prices by using a dynamic version of the Glosten and Milgrom (1985) model with a long-lived informed trader. We make a fundamental contribution by clarifying the conditions under which a unique equilibrium exists, and in what situations this equilibrium involves manipulation of prices by the informed trader. Furthermore, within the unique equilibrium, we characterize bid–ask spreads and show that bid and ask prices are monotonically increasing in the market maker’s prior belief. Finally, we propose a computational method to find equilibria in the model. Our simulation results confirm our theoretical findings and find multiple equilibria in some cases. |
| Keywords: | Market microstructure; Glosten–Milgrom; Insider trading; Dynamic trading; Price formation; Sequential trade; Asymmetric information; Bid–ask spreads. |
| JEL: | D82 G12 |
| Date: | 2018–10–02 |
| URL: | http://d.repec.org/n?u=RePEc:qld:uq2004:603&r=all |
| By: | Charles-Albert Lehalle; Charafeddine Mouzouni |
| Abstract: | This paper goes beyond the optimal trading Mean Field Game model introduced by Pierre Cardaliaguet and Charles-Albert Lehalle in [Cardaliaguet, P. and Lehalle, C.-A., Mean field game of controls and an application to trade crowding, Mathematics and Financial Economics (2018)]. It starts by extending it to portfolios of correlated instruments. This leads to several original contributions: first that hedging strategies naturally stem from optimal liquidation schemes on portfolios. Second we show the influence of trading flows on naive estimates of intraday volatility and correlations. Focussing on this important relation, we exhibit a closed form formula expressing standard estimates of correlations as a function of the underlying correlations and the initial imbalance of large orders, via the optimal flows of our mean field game between traders. To support our theoretical findings, we use a real dataset of 176 US stocks from January to December 2014 sampled every 5 minutes to analyze the influence of the daily flows on the observed correlations. Finally, we propose a toy model based approach to calibrate our MFG model on data. |
| Date: | 2019–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1902.09606&r=all |