No surprise that the financial trading sector has been one of Corvil's biggest customers. for some time. We hear lots today about "digital business" and "algorithmic business," and both have strong origins in this sector. When business is automated in this manner, the accuracy and timeliness of data inputs are imperative to achieve good outcomes. Accordingly, financial market data delivery has a direct impact on decision-making and competitiveness.
Every trading decision depends on market data, regardless of whether the trading execution strategy hinges on low-latency fills, minimizing market impact, or a proprietary algorithm. This dependency drives up the cost of market data both in terms of vendor pricing and the internal cost of delivering the data.
A new report from Burton-Taylor said that spending on financial market data has experienced the fastest year-on-year growth since 2011. The cost of obtaining the fastest connections to trading information for Bats, New York Stock Exchange and Nasdaq has risen from $72,150 to $182,775, according to a recent report by the Healthy Markets Association, which compared a month in 2012 with the same month in 2017.
The internal cost of delivering the data is also significant. Not only is the delivery infrastructure complex but we hear time and again from our customers how important it is to continuously monitor that data service performance is behaving as expected. Glitches happen, configurations change, old subscriptions aren't retired properly, and competitive advantage gained by these services leaches away bit by bit.
Such pressures are a compelling reason to talk to Corvil. Our argument is that traders who have invested so much on data services should use every means available to improve the integrity and performance of those services.
We have numerous real-world examples of solving difficult-to-spot technical issues with market data feeds enables firms to get more out of that expensive investment:
Improved feed handling performance by 200% issues which in turn improved the firm's PnL
Relative latency analysis of a newly purchased direct exchange data service informed feed selection which in turn improved the results of the firm's low-latency trading strategy
Identified that almost a third of the distribution capacity was consumed unnecessarily which increased the risk of intermittent slow or gapped market data that could impact trading execution.
Independent measurement of venue delivery time (with delays as high as 16 seconds) ended finger pointing between a European bank and an exchange and improved the ROI of the subscription
Validation that an exchange was "dense multicasting" many unwanted feeds to a global bank which increased the risk of intermittent slow or gapped market data that could impact trading execution
Unique per-instrument visibility provided new insights that an Online Investments Provider helped optimize price delivery during dynamic, high volatility conditions and helped minimize market risk exposure
Measuring how quickly algorithms respond to market data enabled a global bank optimize the responsiveness of execution systems led to a 40% improvement in retail order flow capture
These examples highlight the diversity of situations where continuous analysis of market data services helped firms get more value. Successful trading comes down to such fine margins that the granular scrutiny Corvil provides becomes a real differentiator and a way to maximize a return on investments made in market data. As those investments continue to rise the need for our services has never been greater.
Learn more about Corvil Analytics for Market Data.