Efficiency of the price formation process in presence of high frequency participants: a mean field game analysis

By A. Lachapelle, Jean-Michel Lasry, Charles-Albert Lehalle, Pierre-Louis Lions. 2013

115 citations recorded by the source corpus.

This paper deals with a stochastic order-driven market model with waiting costs, for orderbooks with heterogenous traders. Offer and demand of liquidity drives price formation and traders anticipate future evolutions of the orderbook. The natural framework we use is mean field game theory, a class of stochastic differential games with a continuum of anonymous players. Several sources of heterogeneity are considered including the mean size of orders. Thus we are able to consider the coexistence of Institutional Investors and high frequency traders (HFT). We provide both analytical solutions and numerical experiments. Implications on classical quantities are explored: orderbook size, prices, and effective bid/ask spread. According to the model, in markets with Institutional Investors only we show the existence of inefficient liquidity imbalances in equilibrium, with two symmetrical situations corresponding to what we call liquidity calls for liquidity. During these situations the transaction price significantly moves away from the fair price. However this macro phenomenon disappears in markets with both Institutional Investors and HFT, although a more precise study shows that the benefits of the new situation go to HFT only, leaving Institutional Investors even with higher trading costs.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/7242ae16cb9cba7f0197d7f113a6068574d7d52a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Finance

Citations in the corpus

Mean Field Games Models—A Brief Survey (2013, background): “Various applications and additional models have been worked out in detail in [7, 10, 41, 53, 54, 67, 75, 79, 81, 84, 86, 87] (see also the special edition on Netw.”
Mean Field Control and Mean Field Game Models with Several Populations (2018, background): “Some important applications can be found in finance [47, 4, 42, 18], economy [31, 29, 43, 19, 2, 28], systemic risk [27, 17], energy production [32, 20], or crowd motion [50, 44, 3].”