Fidessa Group PLC has released its preliminary results for FY 2017. The numbers are indicative of improved performance for the company during the year.

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Fidessa’s yearly revenue increased by 7% YoY, reaching £353.9 million, relative to 2016’s results of £331.9 million.

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Revenues Breakdown

Of the total £353.9 million in revenues, 66% were accumulated from the company’s activity outside of Europe, showing a well-diversified operational capacity.

Another interesting factor with regard to the revenue total, is the specification that recurring revenue represents 88% of the total revenue amount in 2017.

Additional Data

Fidessa’s adjusted profit before tax improved as well, reaching £54.3 million, up 10% from 2016 levels of £49.5 million. The company’s adjusted profit after tax remained positive, with an 11% appreciation, to reach £40.4 million.

The company’s adjusted diluted EPS posted a similar climb of 11%, with a release at 103.9 pence, up from the preceding year’s mark of 93.7 pence.

While Fidessa’s cash generation in 2017 remained relatively high at £92.4 million, the value was actually 3% lower than 2016 results of £95.2 million.

With regard to company dividends, Fidessa announced that 2017 induced a Final Dividend per share mark of 29.7 pence, for a 5% YoY increase from 28.2 pence.

As the Special Dividend per share remained constant YoY at 50.0 pence, the total value of dividends for 2017 was released at 79.7 pence per share.

Fidessa's Outlook

Chris Aspinwall, CEO of Fidessa, provided comment on the company’s outlook for the upcoming year and beyond: “2017 has been an important year for the financial markets as they prepared for the new MiFID II regulations which are finally coming into force after many years of discussion and debate. This change is likely to result in a significant transformation to the way in which financial markets operate, with requirements for increased transparency and efficiency creating greater need for automation of global workflow and much tighter integration across a range of technologies.”

MiFID II Impact

As mentioned in Mr. Aspinwall’s comments, MiFID II will continue to make its impact across financial markets. Toward the end of last year, Fidessa reached an agreement with US futures broker RJ O’Brien, to implement the distribution of Fidessa’s futures and options workstation to RJ O‘Brien’s institutional clients.

A similar deal was struck with ABG Sundal Collier, a Norway-based investment bank that caters to institutional clients. ABG Sundal Collier agreed to the terms, with the intention of using Fidessa’s workflow platform to provide clients with the brokerage services in the equities and derivatives markets.

Perhaps more importantly, the deal enabled ABG Sundal Collier to improve its stance of compliance with MiFID II.

In an effort to improve its user interface and experience, Fidessa partnered with ChartIQ in early 2017. The partnership helped to enhance Fidessa’s interface, by providing its clients with charting and customization features, as well as an array of  Analytics   Analytics Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. 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Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability. Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision making. In the trading space, analytics are applied in a predictive manner in an attempt to more accurately forecast the price. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analytics may also be structured with a descriptive model, where readers attempt to draw a correlation and better understanding as to how and why traders react to a particular set of variables. Traders sometimes implement technical indicators such as moving averages, Bollinger Bands, and breakpoints which are built upon historical data and are used to predict future price movements. How Analytics Relates to Algo TradingAnalytics are relied upon in the concept of algorithmic trading where software is programmed to autonomously signal and/or execute buy and sell orders based upon a series of predetermined factors. In the institutional space, Algo-trading has become vastly competitive over the years as trading institutions seek to outperform competitors through automated systems and the virtual application of trading strategies.The digestion and computation of analytics are also seen in the emerging field of high-frequency trading, where supercomputers are used to analyze multiple markets simultaneously to make near-instantaneous automated trading decisions. Platforms that support HFT have the capability to significantly outperform human traders.This is due to the innate ability to be able to comprehensively analyze big data sets while taking under do consideration an innumerable sum of factors that humans are incapable of comprehending in such speed. Additionally, analytics are seen with backtesting. Backtesting is used by traders to test the consistency and effectiveness of trading strategies and software-based trading solutions against historical price data. Backtesting also serves as an ideal playground for the further development of high-frequency trading as well as evaluating the performance of manual or automated trades. Analytics will continue to have an increasingly significant role in trading as emerging technologies and the advancement of trading applications progress beyond human capability. Read this Term to induce greater and more accurate data for clients.