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Optimal trading using signals
[article]
2018
arXiv
pre-print
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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]
2018
arXiv
pre-print
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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,
arXiv:1811.03766v1
fatcat:37hfn2up3nhw7abbakyodexvtq
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... , 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.
Optimal liquidity-based trading tactics
[article]
2018
arXiv
pre-print
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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.
arXiv:1803.05690v1
fatcat:f47ic6exzzb2xjp5xxhbgjtap4
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... Moreover, we show that our optimal tactic enables us to outperform significantly naive execution strategies.
Do Word Embeddings Really Understand Loughran-McDonald's Polarities?
[article]
2021
arXiv
pre-print
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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
2019
Finance and Stochastics
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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,
doi:10.1007/s00780-019-00382-7
fatcat:j66j7hyctvhlngkvqpvtfe2ngm
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... 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.
Market Microstructure Knowledge Needed for Controlling an Intra-Day Trading Process
[article]
2013
arXiv
pre-print
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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
2013
Mathematical Finance
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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]
2018
arXiv
pre-print
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2017 pre-print arXiv:1704.00847v2 fatcat:k2blvyqr4jcanjguxbmjh255qiOther Versions
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
arXiv:1704.00847v3
fatcat:u3xfatzhvvfp7dlgrsifvgvkfy
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... 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.
A Mean Field Game of Portfolio Trading and Its Consequences On Perceived Correlations
[article]
2019
arXiv
pre-print
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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]
2021
arXiv
pre-print
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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
2014
Social Science Research Network
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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
2013
Mathematics and Financial Economics
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Market impacts and the life cycle of investors orders
[article]
2014
arXiv
pre-print
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2014 pre-print arXiv:1412.0217v1 fatcat:hfubcrfbtbgihd3vy4mcqoq5k4
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
2015
Market Microstructure and Liquidity
Preserved Fulltext
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The file type is application/pdf.
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
2017
Mathematics and Financial Economics
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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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