Source: Skyler Technology

Date: June 2007

Type: Case Study

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Overview: As the number of offered algorithms grow, it becomes harder to differentiate between them. With a generic pool of algorithms, an increasing number of buy side firms and proprietary trading desks are requiring faster, smarter, and most importantly, highly customized trading algorithms to meet their specific trading needs. Skyler’s C3 Algorithmic Container Solution provides a plug’n’play, easy to integrate and impressively fast algorithmic trading framework that can be quickly adapted to address the highly custom needs of next generation trading The Skyler C3 Algorithmic Container Solution allows you to: * Embed custom indicator calculation or algorithms into the data flow * Run the analytics over real-time and historical views of trade, quote, and order data * Configure, parameterize, and execute custom algorithms as part of the query execution on a per user basis * Embed third party libraries for the algorithm execution (e.g. Matlab) * Run analytics over more data due to the Skyler C3 compression capability * Speed up overall algorithm execution due to all in-memory processing * Embed algorithmic container as a shared library into other trading applications * Rapid prototyping via Python Scripting capabilities * Comes with in- and output adapters to standard feed, feed handling and messaging infrastructure * Rapid algorithm development via simulation tools and adapters to direct exchange feeds The main benefits for the customer include a significant improvement in algorithmic trading speed and quality while reducing development time and cost.

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