A Hierarchical Simulation Based Software Architecture For Back-Testing And Automated Trading

Koors, Arne; Page, Bernd

doi:10.7148/2011-0275-0282

Cited by 3 publications

(13 citation statements)

References 11 publications

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“…A successful ATS must have two operation modes: (i) back-test mode, when the system runs in simulation mode using previously archived inputs and is employed in the designing, tuning, and testing of trading strategies; and (ii) live mode, or interactive mode [15], when the system is connected to the market and is continually receiving new data and ready to produce and route new orders.…”

Section: System Architecture Modelmentioning

confidence: 99%

“…Trading systems implement one or more trading strategies, and automated trading systems, or ATS, are those that are partially or totally implemented by computer programs without discretionary human interventions [15].…”

Section: System Architecture Modelmentioning

confidence: 99%

“…Koors and Page [15] evaluated the state of the art of trading system architectures examining the literature and commercial products. The authors characterized the simulation and interactive running modes of ATS, when the systems operate in back-test mode or in live trading mode, respectively; and evaluated how basic architectures for ATS respond to the problem of adaptation to market changing conditions.…”

Section: Introductionmentioning

confidence: 99%

“…This adaptive behavior may be hard to accomplish, mainly due to changing environments that increase the risk of effectiveness of trading strategies, which is frequently known only after performance degradation is verified [15].…”

Section: Introductionmentioning

confidence: 99%

“…A trading strategy can be defined as a systematic sequence of actions taken with the goal of effectively executing trades, typically consisting of a set of entry, exit, and order execution rules. Automated trading strategies are those that are partially or totally implemented by computer programs without discretionary human interventions [15].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

System architecture for on-line optimization of automated trading strategies

Freitas¹,

Freitas²,

Souza³

2013

Proceedings of the 6th Workshop on High Performance Computational Finance

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This work proposes a new automated trading system (ATS) architecture that supports multiple strategies for multiple market conditions through hierarchical trading signals generation employing h-signals, which are trading signals that are generated using other trading signals. The central idea of the proposed system architecture is to decompose the trading problem into a set of tasks handled by distributed autonomous agents under a minimal central coordination. We implemented the proposed ATS using a software architecture that employed a publish/subscribe communication model. In the current stage of development, we are able to run our ATS in back-test mode with moving-average crossover strategies on minute-by-minute market databases. We achieved very satisfactory performance results, processing 306.791 database rows representing more than two years of data in only 47 seconds.

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Section: System Architecture Modelmentioning

confidence: 99%

Section: System Architecture Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

System architecture for on-line optimization of automated trading strategies

Freitas¹,

Freitas²,

Souza³

2013

Proceedings of the 6th Workshop on High Performance Computational Finance

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Intelligent trading architecture

Freitas¹,

Freitas²,

Souza

2015

Concurrency and Computation

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SUMMARYThis work presents the Intelligent Trading Architecture (ITA), which is a new automated trading system architecture that supports multiple strategies for multiple market conditions through hierarchical trading signals generation. The central idea of the proposed system architecture is decomposing the trading problem into a set of tasks that are handled by distributed autonomous agents under a minimal central coordination. With this kind of architecture, we can take advantage of currently available and future high-performance computing systems. These systems, due to the way computer architecture has evolved in the recent past and foreseeable future, are composed of multiple processor cores. We are implementing the ITA software architecture employing the Carnegie Mellon Navigation (CARMEN) robot control software and using a publish/subscribe communication model. Together, CARMEN and this communication model allow the implementation of high-performance, scalable parallel computing systems that leverage the architecture of multi-core systems. For this work, we evaluated the data structures and algorithms employed by the symbol module of the ITA software architecture, which is responsible for maintaining the synchronized local copies of exchanges limit order books (LOB) for the instruments traded by the system. Our LOB implementation strongly outperformed a reference implementation in all evaluated parameters by more than one order of magnitude in some cases, achieving average throughputs of 4 million orders/s when creating new orders, 3 million orders/s when changing existing orders, and 17 million orders/s when querying orders. Copyright

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