News and views from the Ancoa team

‘The Desk’ Industry Viewpoint: Fixed income & MiFID II by Stefan Hendrickx

This article first appeared in The Desk, 3rd February 2016.

Fixed income & MiFID II: Making sense of market abuse scenarios in an RFQ world

It is perhaps not surprising that regulation topped the agenda at this year’s Fixed Income Leaders Summit in Barcelona, which took place two weeks after ESMA’s MiFID II Regulatory Technical Standards (RTS) were issued.According to analyst, Rebecca Healey, “Conversations were dominated by the impact of MiFID II and how firms can best prepare ahead of 2017. Yet less than a third of the attendees admitted to having a strategy positioned to deal with the oncoming regulation”.

One of the key changes MiFID II/MiFIR is expected to bring to fixed income markets is the extension of the transparency regime to bonds. Liquid instruments will be subject to strict pre-trade transparency with requirements of request-for-quotation-based (RFQ) venues to publish bids, offers and depth of market. Because of this increased regulatory attention, firms can no longer put off the requirement for implementing a capable market surveillance system as required under the associated Market Abuse Regulation (MAR), due to be implemented in 2016. National regulators are also casting a questioning eye towards the fixed income markets with the FT recently reporting: “…the FCA is pushing MTF operators to upgrade their monitoring of market abuse, describing the majority of surveillance systems in February as ‘poor’”.

New methods required

Market surveillance technology is designed specifically to detect and to make evident any wrongdoing within the capital markets. In recent years, surveillance firms have been in competition to handle large quantities of data in central limit order book markets. However, with the emphasis now being placed on the fixed income (FI) products, analysis of the data collected can no longer make use of the usual methods used to identify market abuse scenarios. A complete rethink is due.

Benchmarking example: Fixed income surveillance vs the prevailing model

A simple example of where the prevailing cash equity model of surveillance breaks down for FI markets is in the construction of a reference price to help identify outliers. Typically this involves the ‘overlaying’ of proprietary trading data with a wider data set.

Many fixed income securities, however, are not permitted the luxury of a readily available market price due to their illiquid nature. Lack of a market price makes direct relative pricing analysis inaccurate and, in many cases, impossible. To overcome this, surveillance platforms often make use of composite pricing feeds taken from data vendors in order to permit the analysis of FI products for relative pricing analysis. These platforms help clients by providing a visualisation of the RFQ compared to a composite price, allowing the compliance officer to immediately see if the client has beaten the market price when trading. Being able to analyse and visualise data in this way is particularly powerful when looking for patterns such as price manipulation in an RFQ environment. These capabilities enable clients to keep track of dealers who consistently offer “bad” prices relative to the composite, allowing venues to profile the behaviour of different dealers. This can be done at the dealer level or quote pricing engine level.

Nevertheless, there are many fixed income products for which there is no composite pricing feed. So the question becomes, how can we spot outliers where there is no point of reference? Finally, to add to the challenges, tiering is yet another dimension to take into account to obtain sensible alerts and cut out the noise that would lead to false positives.

Ever important reference data

Fixed income surveillance requires accurate and in-depth reference data. In order to find a reference price for seldom-traded instruments, a similar, more liquid, type of instrument would need to be found. Price signals within that instrument could then be examined along with macroeconomic and sector news, and credit rating factors. What then becomes important is the comparison of the relationship between the less liquid and more liquid instruments. Overall, this is a much more sophisticated approach than is required for cash equities.

Forging new fixed income surveillance models

The updated European regulations require market operators and investment firms that operate a trading venue to report attempted market abuse, not only market abuse that materialised. To this purpose, they need to establish and maintain effective arrangements, systems and procedures aimed at preventing and detecting insider dealing (attempted or succeeded) and market manipulation.

A major aspect of this is to be able to adequately analyse data being fed into a surveillance platform for manipulation. To do this, surveillance firms should not attempt to map the distinctive equity surveillance model directly over to the FI markets. Instead, distinct models for surveillance, based on different products, venues and trading protocols should be implemented. Ultimately, compliance departments who understand their firm’s own lines of business should be encouraged to help define bespoke analytics and reports to help detect market abuse in line with their business model.



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  • ian hunt

    Nice outline of a vexing problem. Let me add a different, or at least complimentary, approach to your suggestion of continuously updated “reference data”.

    In my PhD research, I have developed a methodology to identify which trade venue participants are outliers, in the sense of being “overly informed” in their trades or “potentially abusive” in their quotes. The methodology only requires unbiased (in a statistical sense) periodic benchmark data. The point being, you can identify the participants you are after WITHOUT having to observe, or re-create, the continuous time price process in which they are trading.

    In other words, you can do surveillance without having to match a benchmark price with every (or in fact any particular) trade or quote.

    • Ian, thanks for your note. I would be very interested to read more on your research. To clarify, with reference data we mean meta data about the instruments, rather than market data. In that sense our approach may not be all that different. Will get in touch.

      • ian hunt

        Entendu. I should have put “benchmark data” rather than “reference data”. And I am, unfortunately, aware of the Herculean effort it takes to get all the details of many bonds into one database!

        Outside of the context you discuss above, there seems to be a market opening for a properly INDEPENDENT (and non-BB) provider of “fair-value” prices for bonds; something with which a middle office can [re]value the books that their front offices build. Maybe this is an opportunity for Ancoa, if you are already collating tonnes of reference data?

        I am primarily interested in classifying traders or entities as “noise traders” or “informed traders”. This would serve market abuse detection in several ways. First, it is in the spirit of “proactive surveillance” – hunting for overly-informed trading is the first step in identifying market abuse. Secondly, it is built upon proper statistical inferences, which would give some flesh to the bare-bones term “suspicion” (used in the regulations). Thirdly, it helps sift the “skilful” from the “lucky”, which reduces the chance of following up dead ends.

        Anyway, it is only a small part of the compliance picture that you are interested in. And there are two obvious gaps in my methodology within this context. First, it is designed to indentify systematic effects rather one-off instances. Secondly, it is silent about whether skilled trading is due to legitimate or nefarious use of information.

        If you are keen to discuss anything offline please send me an email: ihunt (at) bunhill (dot) co (dot) uk

    • Damien

      what is the best way to get in contact with you? you can also reach us at info[ @ ] ancoa [ . ] come

      • Approve.

        Stefan Hendrickx
        Ancoa Software Ltd
        *Contextual Surveillance. Insightful Analytics.*

        Office *+44 20 8408 1610*
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