Estimating risk of dynamic trading strategies from high frequency data flow

Yuri Balasanov; Alexander Doynikov; Victor Lavrent’ev; Leonid Nazarov

doi:10.1007/978-3-319-20910-4_12

Estimating risk of dynamic trading strategies from high frequency data flow

Yuri Balasanov^*, Alexander Doynikov, Victor Lavrent’ev, Leonid Nazarov

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

We consider the problem of risk management in the framework of low latency trading. We suggest an efficient method of real-time analysis of massive data flow from the market. The result of the analysis is a new risk measure Dynamic VaR (DVaR) for risk management of low latency trading robots. The work of DVaR is illustrated on a test example and compared with Traditional VaR and ex-post measure commonly used in high frequency trading.

Original language	English (US)
Title of host publication	Advances in Data Mining
Subtitle of host publication	Applications and Theoretical Aspects - 15th Industrial Conference, ICDM 2015, Proceedings
Editors	Petra Perner
Publisher	Springer Verlag
Pages	153-165
Number of pages	13
ISBN (Print)	9783319209098
DOIs	https://doi.org/10.1007/978-3-319-20910-4_12
State	Published - 2015
Externally published	Yes
Event	15th Industrial Conference on Data Mining, ICDM 2015 - Hamburg, Germany Duration: Jul 11 2015 → Jul 24 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9165
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	15th Industrial Conference on Data Mining, ICDM 2015
Country/Territory	Germany
City	Hamburg
Period	7/11/15 → 7/24/15

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-20910-4_12

Cite this

Balasanov, Y., Doynikov, A., Lavrent’ev, V., & Nazarov, L. (2015). Estimating risk of dynamic trading strategies from high frequency data flow. In P. Perner (Ed.), Advances in Data Mining: Applications and Theoretical Aspects - 15th Industrial Conference, ICDM 2015, Proceedings (pp. 153-165). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9165). Springer Verlag. https://doi.org/10.1007/978-3-319-20910-4_12

Balasanov, Yuri ; Doynikov, Alexander ; Lavrent’ev, Victor et al. / Estimating risk of dynamic trading strategies from high frequency data flow. Advances in Data Mining: Applications and Theoretical Aspects - 15th Industrial Conference, ICDM 2015, Proceedings. editor / Petra Perner. Springer Verlag, 2015. pp. 153-165 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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author = "Yuri Balasanov and Alexander Doynikov and Victor Lavrent{\textquoteright}ev and Leonid Nazarov",

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Balasanov, Y, Doynikov, A, Lavrent’ev, V & Nazarov, L 2015, Estimating risk of dynamic trading strategies from high frequency data flow. in P Perner (ed.), Advances in Data Mining: Applications and Theoretical Aspects - 15th Industrial Conference, ICDM 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9165, Springer Verlag, pp. 153-165, 15th Industrial Conference on Data Mining, ICDM 2015, Hamburg, Germany, 7/11/15. https://doi.org/10.1007/978-3-319-20910-4_12

Estimating risk of dynamic trading strategies from high frequency data flow. / Balasanov, Yuri; Doynikov, Alexander; Lavrent’ev, Victor et al.
Advances in Data Mining: Applications and Theoretical Aspects - 15th Industrial Conference, ICDM 2015, Proceedings. ed. / Petra Perner. Springer Verlag, 2015. p. 153-165 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9165).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Doynikov, Alexander

AU - Lavrent’ev, Victor

AU - Nazarov, Leonid

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PY - 2015

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N2 - We consider the problem of risk management in the framework of low latency trading. We suggest an efficient method of real-time analysis of massive data flow from the market. The result of the analysis is a new risk measure Dynamic VaR (DVaR) for risk management of low latency trading robots. The work of DVaR is illustrated on a test example and compared with Traditional VaR and ex-post measure commonly used in high frequency trading.

AB - We consider the problem of risk management in the framework of low latency trading. We suggest an efficient method of real-time analysis of massive data flow from the market. The result of the analysis is a new risk measure Dynamic VaR (DVaR) for risk management of low latency trading robots. The work of DVaR is illustrated on a test example and compared with Traditional VaR and ex-post measure commonly used in high frequency trading.

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Balasanov Y, Doynikov A, Lavrent’ev V, Nazarov L. Estimating risk of dynamic trading strategies from high frequency data flow. In Perner P, editor, Advances in Data Mining: Applications and Theoretical Aspects - 15th Industrial Conference, ICDM 2015, Proceedings. Springer Verlag. 2015. p. 153-165. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-20910-4_12

Estimating risk of dynamic trading strategies from high frequency data flow

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