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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