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City Index case study:     Delivering quality equities pricing

Delivering quality equities pricing and enhanced system stability through effective latency monitoring

As Gautam Dixit, Head of Pricing and Analytics at City Index explains ‘ensuring our customers benefit from the best and lowest latency pricing is fundamental at City Index’.  The company is committed to offering a market leading service and the ability to consistently publish fast and competitive prices plays a major role in achieving this goal.

Replacing a legacy pricing engine, City Index were keen to gain detailed insight into their new system’s performance, so they could fully understand their clients’ experience and as Gautam Dixit described ‘we wanted to know what we didn’t know’.

Identifying latency sources

To detect opportunities to further enhance performance, City Index needed to be able to very quickly pinpoint and resolve any possible latency sources throughout their price flow.  They required a real-time solution that would identify delays in the data they received from exchanges, the processing of this data by their pricing engine and their price distribution infrastructure.

Independent performance monitoring

To avoid the potential pitfalls associated with employing internal monitoring solutions, such as clock drift, the possibility of impacting the performance of the item being monitored and other system issues that can influence accurate latency measurement, City Index had determined they wanted independent and external performance monitoring.

 

The Approach: Non-intrusive network monitoring

To achieve these goals, Velocimetrics deployed non-intrusive network capture agents at multiple points throughout the complete price production process.  Velocimetrics then correlated the information, a process which involves linking the data captured at different points together, to reconstruct a seamless end-to-end flow and association techniques were then applied to identify the relationships between these flows.  In doing so, the particular market data ticks used to generate individual pricing could be distinguished, identifying the tick to price flow and the timings for each individual hop.

‘The really cool thing about the Velocimetrics model, that we have implemented on our Equities trading platform, is that it is done on the wire.  Because it is done on the wire, it doesn’t impact any of our processes at all, so we are able to monitor our environment without impact and that’s very important.’

Gautam Dixit, Head of Pricing and Analytics, City Index

The measurements delivered
This solution enabled City Index to easily understand:

  • The exact time that market data was arriving at their gateway
  • How long it took for their pricing engine to consume this data and price individual instruments
  • The time it then took their price distribution system to disseminate spreads out to customers

By comparing timings to expected performance, latency issues could be quickly detected.  Also, by implementing the Velocimetrics Market Data Quality module, City Index were able to gain staleness indicators. 

Comparing system performance

By implementing Velocimetrics on their live high availability systems and infrastructure, City Index is now able to more effectively compare real-time system performance relative to historical norms, supporting efforts to consistently publish high quality pricing.

Additionally, by deploying Velocimetrics within their pre-production environment, City Index can conduct accurate and automated performance testing on system changes.  They can test capacity using representative volume levels and compare results with historical norms, supporting system stability in real-world market conditions.

 

The Results

The increased insight Velocimetrics offers has enabled City Index to quickly identify opportunities to enhance performance across their price production infrastructure and be instantly alerted if they are at risk of publishing prices late.  Here are some examples of how the solution has proven beneficial:

Assuring the delivery of fast and reliable pricing

City Index are now able to continuously monitor the latency between market data origination through to price publication.  The degree of accuracy provided enables City Index to be confident in the prices distributed, as Gautam Dixit describes, with Velocimetrics ‘we are adding an additional layer of quality and risk management to our pricing.’

Detecting market data quality issues

Velocimetrics has enabled City Index to quickly detect degradation in the quality of data received from the exchange, as Gautam Dixit explains ‘We now know if there is a problem with the exchange extremely quickly, if there is an issue with a stale price we may know, before maybe the exchange knows, as there are patterns.’  Velocimetrics alerts City Index of these abnormalities, enabling them to effectively manage this operational risk and investigate whether it is an exchange or connectivity issue.

The solution has helped City Index ensure clients continually benefit from a stable, repeatable and maintainable service.  Having successfully deployed the solution within their equities environment the project’s next stage will focus on their foreign exchange infrastructure.

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With Velocimetrics we are monitoring our whole pricing infrastructure from source to distribution’

Gautam Dixit, Head of Pricing and Analytics, City Index

About City Index

cityindex_logo

  • A leader in spread betting, CFDs and forex trading
  • 2 million+ trades transacted every month for retail investors in over 50 countries worldwide
  • Provides access to indices, shares, currencies, commodities, bonds and interest rate markets

Goals

  • Monitor real-time pricing performance and quality from the exchange to City Index’s clients
  • Minimise the impact of monitoring so that production systems and infrastructure have a near zero impact

Approach

  • Non-intrusive network monitoring
  • Hop-by-hop latency measurement
  • Deployment across production and pre-production environments

Results

  • Identified improvements to garbage collection
  • Exposed network peak capacity issues
  • Instant detection of market data quality issues