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Optimal Allocation Across Dark Pools as a Probabilistic Decision Problem

Vacslav Glukhov
The Journal of Trading Spring 2011, 6 (2) 30-34; DOI: https://doi.org/10.3905/jot.2011.6.2.030
Vacslav Glukhov
is the head of Quantitative Trading Strategies at Liquidnet Europe in London, UK.
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  • For correspondence: sglukhov@liquidnet.com
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Abstract

A liquidity-conscious trader facing the problem of the efficient execution of a sizable order these days has a multitude of execution venues ranging from traditional exchanges to MFTs to internalizing dark pools and institutional crossing networks. Typically, a more or less heuristic “liquidity seeking algorithm” is employed whereby a randomized strategy repeatedly exposes and re-exposes the order to one or multiple crossing venues while executing some quantity in the lit markets. The efficiency of these heuristic algorithms is never assured and missing is the predictability of the results. There are reasons for relatively slow adoption and development of quantitative dark trading algorithms: dark venues are characterized by a somewhat restrained information outflow. Yet, brokers and traders do possess some quantitative information about the quality of liquidity in the pools. The question remains: is it possible to engage a quantitative theory to make sure that allocation across dark venues is efficient and that it optimally utilizes all of the available information? The author’s answer is: affirmative. In this short article the author presents a straightforward quantitative optimal dark allocation framework. It is based on our experience developing dark allocation algorithms for the EMEA markets.

TOPICS: Statistical methods, VAR and use of alternative risk measures of trading risk

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The Journal of Trading: 6 (2)
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Optimal Allocation Across Dark Pools as a Probabilistic Decision Problem
Vacslav Glukhov
The Journal of Trading Mar 2011, 6 (2) 30-34; DOI: 10.3905/jot.2011.6.2.030

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Optimal Allocation Across Dark Pools as a Probabilistic Decision Problem
Vacslav Glukhov
The Journal of Trading Mar 2011, 6 (2) 30-34; DOI: 10.3905/jot.2011.6.2.030
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  • Article
    • Abstract
    • PROBABILISTIC DECISION FRAMEWORK
    • MODEL OF THE POOL
    • UTILITY FUNCTION AND CERTAINTY EQUIVALENT
    • OPTIMIZATION OF COSTS
    • COMBINING DARK AND LIT VENUES
    • CONCLUSION
    • REFERENCES
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