Le trading algorithmique

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Ten algorithmic trading trends in the lead-up to 2010
As algorithmic trading enters the mainstream, Dr John Bates and Mark Palmer of Progress Software give 10 predictions for the future
APAMA, A REVOLUTIONARY trading platform based on event stream processing (ESP) technology, has led the way in innovation since its entranceinto the electronic trading scene in 2002. The adoption of Apama began with JPMorgan and Deutsche Bank and its advancement has presaged the evolution of the algorithmic trading market. Four years later, with algorithmic trading entering the mainstream of trading operations, our unique vantage point gives us pause to consider what is next. Here are 10 predictions for the future of algorithmictrading, looking ahead to 2010: ing strategies. With algorithmic trading being adopted by firms of various shapes and sizes, the need for technology that supports unique trading techniques will continue to grow.

DR JOHN BATES Founder and vice-president Apama products, Progress Software

MARK PALMER Vice-president event stream processing, Progress Software

Once the domain of only the largestinstitutions, algorithmic trading is now entering the mainstream, triggering an ‘algorithmic trading arms race’. In 2002, having algorithmic tools was enough to generate alpha. Buy-side firms were content to use pre-packaged ‘black-box’ algorithms. However, the game has changed. Alpha now goes to the firm with the best algorithms – and what is considered ‘best’ changes by the day. Only the firmsthat can introduce new algorithms quickly will stay ahead. The future promises more of the same, with the landscape dominated by those who have the most effective, innovative, evolvable algorithm and algorithmic trading strategies.

1. Algorithmic innovation, not adoption, is state-of-the-art

The core foundation of Apama is ESP, a new technology that monitors streaming event data, such as marketdata feeds, analyses those streams and identifies patterns among those events. With ESP, traders can identify market patterns and use the information to develop trading strategies. Providing an alternative to potentially commoditised black-box strategies, ESP-powered platforms enable traders to modify, tweak, test and evolve algorithms. Also called complex event processing, ESP was originallyapplied to algorithmic trading. Now its reach is extending to real-time risk management, smart order routing, market making and fraud detection. There will be a greater uptake of ESP technology in coming years.

3. Increased use of platforms based on ESP technology

4. Algorithmic everything: the convergence of the front and back office

The explosion of the hedge fund and alternativeinvestment market has changed the competitive landscape, challenging sell-side institutions to optimise their client services. Concurrently, the buy-side is demanding increased anonymity and control over their trad-

2. The rise of the buy-side as an algorithmic powerhouse

Historically, calculating risk exposure was often conducted in batch at the end of the trading day. Now, firms are beginning toincorporate traditionally backoffice functions, such as changes to foreign exchange (FX) risk exposure, into their front-office operations. This reinforces the need for real-time risk monitoring. If performed in real time, value-at-risk (VaR) calculations can provide up-to-the-millisecond visibility into potential exposure, evaluating trades based on their potential risk impact. Should a trade pushexposure over key levels, it can be prevented before the trade is executed. Firms will increas-



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