Charles-Albert Lehalle

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We propose a general framework for intra-day trading based on the control of trading algorithms. Given a generic parameterized algorithm, we control the dates (τ i) i at which it is launched, the length (δ i) i of the trading period and the value of the parameters (E i) i kept during the time interval [τ i , τ i + δ i [. This gives rise to a non-classical(More)
This paper addresses the optimal scheduling of the liquidation of a portfolio using a new angle. Instead of focusing only on the scheduling aspect like Almgren and Chriss in [2], or only on the liquidity-consuming orders like Obizhaeva and Wang in [33], we link the optimal trade-schedule to the price of the limit orders that have to be sent to the limit(More)
In this paper, we use a database of around 400,000 metaorders issued by investors and electronically traded on European markets in 2010 in order to study market impact at different scales. At the intraday scale we confirm a square root temporary impact in the daily participation, and we shed light on a duration factor in 1/T γ with γ 0.25. Including this(More)
This paper studies four trading algorithms of a professional trader, in a realistic two-sided limit order book whose dynamics are driven by the order book events. The identity of the trader can be either privileged or regular, either a hedge fund or a brokery agency. The speed and cost of trading can be balanced by properly choosing active strategies on the(More)
We derive explicit recursive formulas for Target Close (TC) and Implementation Shortfall (IS) in the Almgren-Chriss framework. We explain how to compute the optimal starting and stopping times for IS and TC, respectively, given a minimum trading size. We also show how to add a minimum participation rate constraint (Percentage of Volume, PVol) for both TC(More)
(2014): Real-time market microstructure analysis: online transaction cost analysis, Quantitative Finance, Taylor & Francis makes every effort to ensure the accuracy of all the information (the " Content ") contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever(More)
— Piecewise affine neural networks can be constructed to emulate any continuous piecewise affine function in any hypercube of its input space. This property can be used to initialize such a network with a set of linear controllers, where each of them is known to be efficient locally. This paper expose and illustrate this properties of piecewise affine(More)
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