Abstract
Recently, Algorithmic Trading has attracted a lot of attention. It is estimated that brokers alone will have to spend close to $10 million dollars a year to build and maintain algorithms and the market-data infrastructure. Apart from this, buy-side institutions are still in the midst of an adoption phase. According to a recent estimate by Wall Street and Technology, only 15-20% of the buy-side firms have broadly adopted Algorithmic Trading. Partnerships are being formed in this space between brokers and OMS vendors to provide buy side firms with the best services.

This whitepaper is directed towards identifying the algorithms being used in ‘Algorithmic Trading’ in the Industry. The role of FIX in propagating ‘Algorithmic Trading’ has also been touched upon as a generic standard is needed to give the buy-side an interoperable standard for interfacing with brokers’ algorithmic trading servers. Further some futuristic thoughts which involve evolution in the fields of Optimization techniques, Artificial Intelligence techniques and Advanced Statistical methods which facilitate better modeling of complex problems have also been attempted. However, the scope of this paper is restricted to the use of Brute Force techniques like Genetic Algorithms.

Author Mahesh Sunderaraman

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