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Optimal trading using signals [article]

Hadrien De March, Charles-Albert Lehalle
2018 arXiv   pre-print
For other frameworks like the Cartea-Jaimungal or the Dang-Bouchard-Lehalle ones, F will be a function of time and of the remaining quantity to trade.  ... 
arXiv:1811.03718v1 fatcat:37uit6yaqjepdmk2hz42t4a4z4

Endogeneous Dynamics of Intraday Liquidity [article]

Mikołaj Bińkowski, Charles-Albert Lehalle
2018 arXiv   pre-print
In this paper we investigate the endogenous information contained in four liquidity variables at a five minutes time scale on equity markets around the world: the traded volume, the bid-ask spread, the volatility and the volume at first limits of the orderbook. In the spirit of Granger causality, we measure the level of information by the level of accuracy of linear autoregressive models. This empirical study is carried out on a dataset of more than 300 stocks from four different markets (US,
more » ... , Japan and Hong Kong) from a period of over five years. We discuss the obtained performances of autoregressive (AR) models on stationarized versions of the variables, focusing on explaining the observed differences between stocks. Since empirical studies are often conducted at this time scale, we believe it is of paramount importance to document endogenous dynamics in a simple framework with no addition of supplemental information. Our study can hence be used as a benchmark to identify exogenous effects. On the other hand, most optimal trading frameworks (like the celebrated Almgren and Chriss one), focus on computing an optimal trading speed at a frequency close to the one we consider. Such frameworks very often take i.i.d. assumptions on liquidity variables; this paper document the auto-correlations emerging from real data, opening the door to new developments in optimal trading.
arXiv:1811.03766v1 fatcat:37hfn2up3nhw7abbakyodexvtq

Optimal liquidity-based trading tactics [article]

Charles-Albert Lehalle, Othmane Mounjid, Mathieu Rosenbaum
2018 arXiv   pre-print
We consider an agent who needs to buy (or sell) a relatively small amount of asset over some fixed short time interval. We work at the highest frequency meaning that we wish to find the optimal tactic to execute our quantity using limit orders, market orders and cancellations. To solve the agent's control problem, we build an order book model and optimize an expected utility function based on our price impact. We derive the equations satisfied by the optimal strategy and solve them numerically.
more » ... Moreover, we show that our optimal tactic enables us to outperform significantly naive execution strategies.
arXiv:1803.05690v1 fatcat:f47ic6exzzb2xjp5xxhbgjtap4

Do Word Embeddings Really Understand Loughran-McDonald's Polarities? [article]

Mengda Li, Charles-Albert Lehalle
2021 arXiv   pre-print
Authors would like to thank Sylvain Champonnois for deep discussions about the nature of text polarity and biases of embeddings, Jean-Charles Nigretto for preliminary work on biases in doc2vec models,  ... 
arXiv:2103.09813v1 fatcat:mjfhdcfnfzhkxgpeuhss2aa26i

Incorporating signals into optimal trading

Charles-Albert Lehalle, Eyal Neuman
2019 Finance and Stochastics  
We incorporate a Markovian signal in the optimal trading framework which was initially proposed by Gatheral et al. (Math. Finance 22:445-474, 2012) and provide results on the existence and uniqueness of an optimal trading strategy. Moreover, we derive an explicit singular optimal strategy for the special case of an Ornstein-Uhlenbeck signal and an exponentially decaying transient market impact. The combination of a mean-reverting signal along with a market impact decay is of special interest,
more » ... nce they affect the short term price variations in opposite directions. Later, we show that in the asymptotic limit where the transient market impact becomes instantaneous, the optimal strategy becomes continuous. This result is compatible with the optimal trading framework which was proposed by Cartea and Jaimungal (Appl. Math. Finance 20:512-547, 2013). In order to support our models, we analyse nine months of tick-by-tick data on 13 European stocks from the NASDAQ OMX exchange. We show that order book imbalance is a predictor of the future price move and has some mean-reverting properties. From this data, we show that market participants, especially high-frequency traders, use this signal in their trading strategies.
doi:10.1007/s00780-019-00382-7 fatcat:j66j7hyctvhlngkvqpvtfe2ngm

Market Microstructure Knowledge Needed for Controlling an Intra-Day Trading Process [article]

Charles-Albert Lehalle
2013 arXiv   pre-print
Following Lehalle et al. (2010) , one can try to crudely model these two dynamics simultaneously.  ...  Lehalle et al. then introduce a more complex source to re-inject the orders in books containing market participants' forward views on the price.  ... 
arXiv:1302.4592v1 fatcat:vggns5ihfjefhlliwsm5hrhbxu

GENERAL INTENSITY SHAPES IN OPTIMAL LIQUIDATION

Olivier Guéant, Charles-Albert Lehalle
2013 Mathematical Finance  
Guéant, Lehalle and Fernandez-Tapia [25] considered in parallel the specific case of an exponential intensity for a risk-adverse agent.  ...  The optimal split of large orders across liquidity pools has then been studied by Laruelle, Lehalle and Pagès in [37] but the literature focuses perhaps more today on limit orders than on dark pools.  ... 
doi:10.1111/mafi.12052 fatcat:fccfmntcffcgveyvao6ruw4xlq

Incorporating Signals into Optimal Trading [article]

Charles-Albert Lehalle, Eyal Neuman
2018 arXiv   pre-print
Optimal trading is a recent field of research which was initiated by Almgren, Chriss, Bertsimas and Lo in the late 90's. Its main application is slicing large trading orders, in the interest of minimizing trading costs and potential perturbations of price dynamics due to liquidity shocks. The initial optimization frameworks were based on mean-variance minimization for the trading costs. In the past 15 years, finer modelling of price dynamics, more realistic control variables and different cost
more » ... unctionals were developed. The inclusion of signals (i.e. short term predictors of price dynamics) in optimal trading is a recent development and it is also the subject of this work. We incorporate a Markovian signal in the optimal trading framework which was initially proposed by Gatheral, Schied, and Slynko [21] and provide results on the existence and uniqueness of an optimal trading strategy. Moreover, we derive an explicit singular optimal strategy for the special case of an Ornstein-Uhlenbeck signal and an exponentially decaying transient market impact. The combination of a mean-reverting signal along with a market impact decay is of special interest, since they affect the short term price variations in opposite directions. Later, we show that in the asymptotic limit were the transient market impact becomes instantaneous, the optimal strategy becomes continuous. This result is compatible with the optimal trading framework which was proposed by Cartea and Jaimungal [10]. In order to support our models, we analyse nine months of tick by tick data on 13 European stocks from the NASDAQ OMX exchange. We show that orderbook imbalance is a predictor of the future price move and it has some mean-reverting properties. From this data we show that market participants, especially high frequency traders, use this signal in their trading strategies.
arXiv:1704.00847v3 fatcat:u3xfatzhvvfp7dlgrsifvgvkfy

A Mean Field Game of Portfolio Trading and Its Consequences On Perceived Correlations [article]

Charles-Albert Lehalle, Charafeddine Mouzouni
2019 arXiv   pre-print
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.  ...  This has motivated the present work in which we introduce an extension of the initial Cardaliaguet-Lehalle framework to the case of a multi-asset portfolio.  ...  A MEAN FIELD GAME OF PORTFOLIO TRADING 5 The initial Cardaliaguet-Lehalle model [13] , corresponds to d = 1, and a quadratic liquidity function of the form L(p) = κ|p| 2 .  ... 
arXiv:1902.09606v1 fatcat:5jkogabbhjcqriunl5n2w7cig4

Learning a functional control for high-frequency finance [article]

Laura Leal, Mathieu Laurière, Charles-Albert Lehalle
2021 arXiv   pre-print
This has been already observed in the context of game theoretical frameworks (Cardaliaguet and Lehalle 2018) .  ...  When the controller is a neural net, it is used multiple times before the loss function can be computed and improved via back propagation, in the spirit of (Lehalle and Azencott 1998) .  ...  In game theory versions of the optimal trading framework, they are usually called "agent preferences" (Cardaliaguet and Lehalle 2018) .  ... 
arXiv:2006.09611v2 fatcat:gzxbupawk5cnriabgz4kzsw23a

Market Impacts and the Life Cycle of Investors Orders

Emmanuel Bacry, Adrian Iuga, Matthieu Lasnier, Charles-Albert Lehalle
2014 Social Science Research Network  
For more details about trading algorithms, see Chapter 3.3 of [Lehalle and Laruelle, 2013] .  ...  ., 2005a] , [Gatheral, 2010] and [Lehalle and Dang, 2010] and for link with optimal trading see [Almgren and Chriss, 2000] , [Gatheral and Schied, 2012] and [Bouchard et al., 2011] ), or used by  ... 
doi:10.2139/ssrn.2532152 fatcat:uucp26hzirdv3msbqx2j5bt5he

Optimal posting price of limit orders: learning by trading

Sophie Laruelle, Charles-Albert Lehalle, Gilles Pagès
2013 Mathematics and Financial Economics  
doi:10.1007/s11579-013-0096-7 fatcat:j2rolch4fva7towoud2ycu4eoq

Market impacts and the life cycle of investors orders [article]

Emmanuel Bacry, Adrian Iuga, Matthieu Lasnier, Charles-Albert Lehalle
2014 arXiv   pre-print
For more details about trading algorithms, see Chapter 3.3 of [Lehalle and Laruelle, 2013] .  ...  ., 2005a] , [Gatheral, 2010] and [Lehalle and Dang, 2010] and for link with optimal trading see [Almgren and Chriss, 2000] , [Gatheral and Schied, 2012] and [Bouchard et al., 2011] ), or used by  ... 
arXiv:1412.0217v2 fatcat:f3y53lgtnff3ldnbyiosuyzudu

Market Impacts and the Life Cycle of Investors Orders

Emmanuel Bacry, Adrian Iuga, Matthieu Lasnier, Charles-Albert Lehalle
2015 Market Microstructure and Liquidity  
For more details about trading algorithms, see Chapter 3.3 of [Lehalle and Laruelle, 2013] .  ...  ., 2005a] , [Gatheral, 2010] and [Lehalle and Dang, 2010] and for link with optimal trading see [Almgren and Chriss, 2000] , [Gatheral and Schied, 2012] and [Bouchard et al., 2011] ), or used by  ... 
doi:10.1142/s2382626615500094 fatcat:fp2qoenpjzeypoz2pwhqzw2sbq

Mean field game of controls and an application to trade crowding

Pierre Cardaliaguet, Charles-Albert Lehalle
2017 Mathematics and Financial Economics  
For details about this standard framework, see [Cartea et al., 2015] , [Guéant, 2016] or [Lehalle et al., 2013, Chapter 3] .  ...  The academic answers to this need goes from mean-variance frameworks (initiated by [Almgren and Chriss, 2000] ) to more stochastic and liquidity driven ones (see for instance [Guéant and Lehalle, 2015  ... 
doi:10.1007/s11579-017-0206-z fatcat:ioudlwfwnza5xfpxoba5saqvs4
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