With many trading firms approaching the physical limits of low-latency technology, the time has come to look at improving other areas of the trading process to more effectively and intelligently operate in the electronic marketplace. Speaking at last week’s A-Team Group Intelligent Trading Summit (formerly the Low Latency Summit) in New York, Alessandro Petroni, senior principle architect for Tibco Software proposed that we not only focus on trading faster, but also on trading smarter.
Highlighting the example of Knight Capital’s automated downfall, with some $190,000 lost every second during the trading disaster, Petroni made the case that trading fast is still ok, but trading fast and ‘dumb’ is a dangerous prospect. Instead, the focus for future development should not be just about engineering a faster system, but about performance, adapting to new opportunities and highlighting common threats to the system such as risk exposure. As an example of this growing trend, Petroni mentioned in his presentation a comment that he received from the head of trading at a top tier broker: “In the past 10 years, automated trading has risen from 5% to over 80% of all trades done each year. The ROI of intelligent automation on Wall Street cannot be computed – it’s worth billions and is a matter of survival.”
The need is for markets to look at not only consuming the market data they need, but also at making the right decisions on the basis of that data. Moving forward, Petroni suggested that the focus on the trading platform and its use should become more intelligent, and that the faster firms can experiment, test and create new things, the better. Vivek Ranadive, Tibco’s founder and CEO, originally put it like this: “The [need is] to capture the right information at the right time and act on it preemptively for a competitive advantage.”
Petroni argued that the time has come to focus on bringing in all data that is needed quickly, but more importantly to leverage it properly and make use of the different types of data that are available. For example, interest has sprung up around unstructured information, such as social media data, consumer tweets and so on. Petroni noted that there is a definite drive to effectively use this kind of informal data in the trading process.
Growing interest around Big Data was another topic that he touched on, and while the focus has been in recent years on the three Vs of velocity, variety and volume, Petroni said the focus moving forward is going to be about providing new perspectives on the data, driving better decisions and leveraging the data in new trading platforms.
Closing his presentation, Petroni emphasised algorithmic trading and time to market as being critical to survival. Looking forward, he noted the challenges of automating effectively and managing a massive amount of data while simultaneously creating intelligent analytics for more informed trading decisions.
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