Trends in FX Trading 2017 — All-to-all in All but Name

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March 6, 2017

Trends in FX Trading 2017 — All-to-all in All but Name

This report explores significant shifts in the global spot FX trading environment that took place between 2015 and 2017. Following the release of the Bank for International Settlements’ (BIS) triennial FX survey in 2016, which found spot volumes dropped 19% since 2013, this report explores the changing dynamics of the spot FX market. In doing so, the report illuminates a market structure that is moving from broker-dealer-dominated dealer-to-dealer (D2D) and dealer-to-client (D2C) structure to an all-to-all (A2A) structure.

https://research.greyspark.com/2017/trends-in-fx-trading-2017/

News : Regulation : SI regime : Dan Barnes

By

Ian Rycott

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March 3, 2017

BROKERS WARNED ON SI REGIME MISSTEPS.

Regulators have expressed concern over banks’ plans for operating systematic internalisers (SIs) under the revised Markets in Financial Instruments Directive (MiFID II). Dealers have shown interest in transforming their broker-crossing networks (BCNs) into SIs under the new regime, as well as launching fixed income SIs. However using SIs to trade in highly liquid instruments would appear to fall foul of the regulatory framework.

“I want to stress that an SI is something in which you need to put risk,” said Philippe Guillot, executive director for the markets directorate at Autorité des Marchés Financiers. “As a national competent authority I will look at the revenue sources of an SI. If you have risk you need to put the risk somewhere because you want to make profit. So if the revenues do not – for the majority – come from [taking] risk I will think there is an issue.”

The SI regime is a framework for trading mechanisms under MiFID II. It applies to an investment firm “which, on an organised, frequent and systematic, and substantial basis, deals on its own account by executing client orders outside a regulated market (RM), a multilateral trading facility (MTF), or organised trading facility (OTF) without operating a multilateral system.”

Speaking at the FIX Trading Event in London on 2 March 2017, Guillot said that risk which was transferred in a sub-second time period was more akin to multi-lateral trading. Under the rules that would push the trading mechanism towards the regulatory categories of MTF or OTF.

“Do you think that an SI, who is saying that the [transfer of] risk is working on a delay of a few microseconds, is making money based on that risk?” he asked, adding that a firm which thought about the SI regime as an option for its crossing business might find “it is an investment that is short lived.”

The definition of ‘frequent and systematic’ hinges on the number of over-the-counter (OTC) trades in the financial instrument carried out by the investment firm on its own account, when executing orders for clients. The ‘substantial basis’ definition is weighted against the proportion of over-the-counter trading conducted by the investment firm in relation its own trading in a specific financial instrument or across total trading in the European Union in a specific financial instrument.

Clearing up issues around the regime will be of great importance to buy-side traders. In the fixed income markets 55% of buy-side firms intend to route to an SI under the new regime, according to a new research paper by block-trading venue Liquidnet. Entitled ‘MiFID II – An Action plan for 2017’, the paper surveyed 32 heads of trading for buy-side firms with nearly US$10 trillion in assets under management.

The European Securities and Markets Authority (ESMA) has said it will publish the data necessary for firms to operate as an SI at 1^st August 2018, setting the registration date for firms wanting to operate as SIs to 1^st September 2018. Liquidnet’s research indicated just 46% of head traders were positive about the delay.

In a question and answers document published in January 2017, ESMA wrote, “the earliest mandatory deadline on which firms must comply with the SI regime, when necessary, is 1 September 2018 although MiFID II and MiFIR apply from 3 January 2018. However, ESMA stresses that investment firms can opt-in to the SI regime for all financial instruments from 3 January 2018 as a means of complying, for example, with the trading obligation for shares.”

If there is a schism between regulators and the sell side around the transfer of BCNs to the SI regime, it could be exacerbated if broker-dealers decide to operate their BCNs on a ‘business as usual’ basis past 3rd January 2018. It is unclear if they could source the data necessary to meet the frequent, systemic and substantial definitions which needs to be determined pre-trade.

Equally if there are disagreements about whether risk is being taken within SIs, authorities may feel that liberties are being taken. In the worst case scenario, They may feel the need to clamp down on the use of the regime, citing abuse.

“I don’t think the banks realise how political this is,” warned one senior market observer.

©BestExecution 2017

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The Payments Landscape in Australia — The Disruption of Innovative Technologies

By

Ian Rycott

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February 24, 2017

The Payments Landscape in Australia — The Disruption of Innovative Technologies

In Australia, technology driven innovation and increasing fintech-focused competition is catalysing the digital disruption of the payments landscape. Since the Reserve Bank of Australia’s Payments System Board endorsed an industry proposal for new real-time payments infrastructure in 2013, the Australian retail consumer market has experienced a major shift as the range of point-of-sale (POS) hardware, and software solutions offered by fintech start-ups and independent POS technology vendors has grown.

https://research.greyspark.com/2017/the-payments-landscape-in-australia/

News : Tackling order book fragmentation

By

Ian Rycott

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February 22, 2017

CLEAN SWEEP TACKLES ORDER BOOK FRAGMENTATION AT UBS MTF.

Be24_UBS_RichardSemark5 UBS MTF, the broker-owned multilateral trading facility (MTF), has implemented a new order type and rolled out waivers across its three order books to increase trading efficiency.

“We didn’t want to fragment the liquidity within UBS MTF,” says Richard Semark, CEO of UBS MTF. “Having clients send large orders to one book and then if unsuccessful after a period of time, pulling that and sending to another book would not be an efficient or an attractive way of trading on UBS MTF.”

The trading venue, ranked as Europe’s second largest dark pool according to BATS Trading data, says it is responding to regulatory change, specifically the preparation for MiFID II, which comes into effect in January 2018.

In a note to members, the MTF reported that it now operates under two waivers – Large in Scale (LIS) and Reference Price Waiver (RPW) – for execution on the its mid, bid and offer books.

“There is clearly an increasing appetite to trade larger sizes,” says Semark. “We are seeing that across the market and we wanted to make sure that UBS MTF was able to offer that functionality. Since the introduction of the LIS waiver we see members execute in large size, then we see them coming back to try and do that again. So actually the growth in the number of LIS trades that we have had has been – whilst not huge – has been quicker than I expected.”

The MTF has also introduced a new execution instruction so members can seek liquidity in the three order books, with one single order, known as the order book sweep (OBS). It offers an alternative to the single peg price as an execution instruction. Traders can instruct an order be conducted either a half, or a full, sweep across peg types.

A half sweep will execute at the primary peg, or if no immediate execution is possible, the order will be eligible for execution at the mid-peg price. A full sweep should lead to execution at the primary peg, and if no immediate execution is possible, the order will be eligible for immediate execution at the mid-peg, then at the market peg if it is still not executed partially or fully at the mid.

Semark notes, “While the sweep order type is a fairly small proportion of our orders at the moment, it’s certainly something which is attractive to members because it does allow them to try and take advantage of the near touch before moving to mid or far touch. We are seeing some increases in how members are using that.”

©BestExecution 2017

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On The Performance Of VWAP Execution Algorithms

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GlobalTrading

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February 22, 2017

By Hellinton H. Takada, Ph.D. Vice President of Quantitative Research at Itaú Asset Management and Tiago M. Magalhães, Ph.D. Senior Analyst of Quantitative Research at Itaú Asset Management

Undoubtedly, the volume weighted average price (VWAP) is widely used as an industry standard approach to measure equity execution performance. The average executed price is usually compared with the corresponding VWAP benchmark. In this context, our objective is the introduction and application of a statistical procedure to measure more adequately the performance of equity trades using VWAP as a benchmark. However, it is also important to have in mind that depending on the execution procedure and the performance evaluation purposes, it is necessary to have other benchmarks than VWAP. For instance, when the opportunity cost is very relevant or the execution strategy is opportunistic, it becomes important to consider the implementation shortfall.

The measurement of the execution performance is imperative due to regulators’ and investors’ requirements related to transaction cost analysis (TCA) and best execution. However, there are many difficulties related to empirical researches on the subject. Obviously, the lack of public data showing the trades per execution makes the studies scarcer. Additionally, the underlying execution strategy must be comparable with VWAP. Consequently, we focus on our private database of Brazilian equities’ trades using third-party VWAP execution algos. The idea is to show the aggregate performance of such algos from several brokerage firms to give an overview of the local VWAP execution services and, at the same time, to illustrate our statistical methodology based on a statistical bootstrapping methodology.

In our dataset of executed trades using VWAP algos, there are more than 10,000 observations from 2014 until the first quarter of 2016. As expected, there is a high autocorrelation structure between observations belonging to the same day, that is, the executed trades over a day are slices of a very larger order. Since correlated data make the statistical analyses more complicated, as our first step we break such autocorrelations aggregating per day the financial values of all the individual trades. Using statistical tests, it is possible to verify the independence of the obtained daily financial values. It is highly probable that there are many larger orders being executed over several days. However, at least empirically, the autocorrelation caused by them seems to be negligible when they are mixed with other execution flows.

Basically, our performance metric is the financial result in basis points over the VWAP benchmark. Usually the transaction costs of the investment strategies are all calculated on an annual basis. Consequently, it makes sense to also present the performance of the executions on an annual basis. Another point to consider is that the distribution of the daily metric possesses a higher uncertainty than the distribution of the annual metric. In Figure 1, we show the obtained cumulated distributions of the daily and annual metrics. The details related to the statistical procedure to obtain the graphs are presented in the next paragraphs. Yet, it is common to see just the publication of the mean or the median of the daily metrics leading to erroneous inferences.

Actually, the publication of the entire distribution of the metric is of utmost importance.

It is important to remember that we have the daily metric from the aggregation of the individual trades to avoid autocorrelation and, consequently, we also have the distribution of the daily metric. Unfortunately, the calculation of the distribution of the annual metric using the distribution of the daily metric is not so straightforward because the annual metric is a random variable equal to a ratio of sums of daily random variables. Furthermore, the annual aggregation of the individual trades is useless because we do not have several years to obtain the annual distribution. The alternative is the use of a nonparametric method where we do not impose any specific structure for the related problem. Consequently, our objective is to avoid making any additional assumptions to obtain the desired annual distribution.

Bootstrapping
Particularly, we adopt the bootstrapping method from statistics. In statistics, bootstrapping refers to any test or metric that relies on random sampling with replacement from a predefined dataset. This technique allows estimation of the sampling distribution of almost any statistic using random sampling methods, that is, a bootstrapping method lets us obtain useful information such as the statistical moments (mean, standard deviation, etc.) and percentiles (median, quartiles, etc.) of the distribution of interest. Obviously, the number of samplings must be enough to obtain a distribution that does not change significantly after adding new samplings. The cumulated distributions obtained using the bootstrapping method for the daily and annual metrics are presented in Figure 1. As previously mentioned, the distribution of the daily metric has a much higher uncertainty than the distribution of the annual metric.

As a final remark, an interesting empirical observation using our private dataset is that the median and mean of the daily metric distribution are slightly negative. On the other hand, the same statistics of the annual metric distribution are positive. Consequently, the VWAP execution algos from our dataset generate alpha in relation to the VWAP benchmark on an annual basis. Unfortunately, it is not possible to observe such alpha in a daily basis. It is interesting that the accumulation of the daily metrics with negative median and mean results in an annual metric distribution with positive median and mean. Finally, it is also clear that the annual metric distribution possesses a positive asymmetry meaning that there is a higher probability of the occurrence of extreme positive outcomes than extreme negative outcomes.

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MMT – The Journey So Far

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GlobalTrading

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February 22, 2017

By Anna Branch, Global Head of Market Data at Fidessa and Co-chair, FIX MMT Steering Committee

When the FPL Trust assumed control of the MMT (Market Model Typology) project, it assured the openness of the standard, but it also brought it into the well-oiled mechanism of FIX Trading Community’s technical committees.

In the two years since, the FIX MMT Technical Committee has achieved much of its to-do list in terms of developing the standard and preparing both the industry and regulators for its full rollout. Today, MMT logic is ready to begin lowering post-trade costs across the buy-side, sell-side and at trading venues.

The makeup of the committee has been one of its strengths all along, as we have involved venues, vendors, sell-side and buy-side to ensure all angles of the implementation are covered. This broad crosssection will certainly aid in speeding adoption and implementation of MMT.

Since the MMT initiative came under the umbrella of the FIX Trading Community, a state-of-the-art and neutral management of the MMT standard has been implemented and the governance structure of MMT has been aligned to FIX guidelines.

During 2015, the MMT model entered a mature phase and is currently being actively used and published by exchanges and vendors alike. By the end of 2015, 15 trading venues had implemented the MMT logic into their market data systems.

In the summer of 2016 we officially introduced MMT v 3.01 that accommodates the applicable MiFID II Regulatory Technical Standards (RTSs):

• The trade flags stipulated within RTS 1 for equities and equity-like financial instruments
• The trade flags stipulated within RTS 2 for non-equity financial instruments

Transparency in fragmentation
The MMT was designed to find a practical solution for standards on post-trade equity data that could be adopted industry-wide.

Following the implementation of the original MiFID rules in 2007, and the competition that fostered in the trading venue space, market fragmentation became an inevitable by-product. Action was needed to meet the challenges in the area of equity market data, in particular post-trade transparency, in order that the management and development of the relevant standards could be established.

The commercial value for the market is in the expected efficiency gains, which will create cost savings for all participants. The rollout of this is already underway, but when it is fully implemented, post-trade costs will be reduced across the street.

The MMT initiative was developed through the collaborative efforts of exchanges, MTFs (multilateral trading facilities), market data vendors and trade reporting venues all committed to improving the consistency and comparability of data from multiple sources.

Matthew Bumstead, Global Product Manager for Market Data Feed (B-PIPE) at Bloomberg and Co-chair of the MMT Technical Committee, comments: “MMT v3 is the fifth iteration of a five-year long initiative to create an industry-driven post-trade execution type standard that will be adopted by European market operators, posttrade publication arrangements and market data vendors alike, with the potential for global adoption outside of Europe. Incorporating, but going above and beyond, the trade flags stipulated in the ESMA Regulatory Technical Standards 1 and 2, MMT will provide a consistent yet more efficient MiFID II conforming view of the trade type descriptors, facilitating tighter compare-and-contrast analysis across market data from multiple sources.”

The MMT Steering Committee brought the initiative under the jurisdiction of the FIX Protocol Limited Trust in 2014. Participants from exchanges, data vendors and reporting venues have been working hard over two years to translate the original 2010 CESR Technical Working Group recommendations into practical action under the well-established values and governance standards of FPL.

Communication, cooperation
Interaction between regulators and the MMT working groups was a challenge during 2015 and 2016, in order to clarify the MiFID II requirements for MMT. Steering Committee members as well as Technical Committee members (all chairs) engaged in constructive dialogue with regulators seeking clarification in order to make sure the FIX MMT data model fulfills all trade flagging requirements for post-trade transparency purposes (RTS 1 and RTS 2 especially).

Commenting on the transparency flags, Irina Sonich-Bright, Credit Suisse’s Head of Business Development AES Europe and Co-chair of the FIX Transparency Working Group, said: “The MMT standard was developed to address the issues of post-trade transparency under MiFID 1. Being one of the earlier adopters of the standard meant that there was no second thought on how the challenges of the MiFID II post-trade transparency flags should be addressed. The shares trading community has been using MMT standard to flag different types of trades for a number of years now which means that the standard is already fully integrated into the existing equities trading systems.

“MiFID II post-trade transparency requirements outlined by ESMA in its technical standards document echoed and enhanced the work MMT has achieved in equities so far. The new challenge was to extend the standard to the non-equity products. The FIX MMT team and Transparency Working Group collaboratively jumped to the challenge to provide the industry with the optimal solution for the MiFID II mandated post-trade transparency flags across multiple asset classes.”

Uniting Technology And Regulation

By

GlobalTrading

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February 22, 2017

By Will Haskins, for GlobalTrading

With only months to go until MiFID II’s regulatory requirements come into force, Europe’s trading desks are readying themselves to meet the new trade reporting and enhanced best execution mandates.

As ever, much of the concern is over the cost of the new reporting regimes. Even as market participants wait for further clarification on rules for extraterritoriality, the work must begin. Trading desks need to make sensible assumptions about those issues with outstanding interpretations to make sure the technology and workflows are ready to be deployed.

While larger buy-sides will use this as an opportunity to extract further technology resources from cost-conscious management, smaller firms may struggle with the added burden. For the larger asset managers, the minimum requirement that buy-sides demonstrate best execution for their end clients will likely be expanded into a TCA analysis engine to rival those traditionally developed by the sell-side. For the smaller investment firms, the increased burden of proof may encourage them to outsource more of their trading operations to their brokers or third party service providers who can amortise the technology development cost across multiple clients. Speaking at the recent GlobalTrading Uniting Regulation and Technology Roundtable in London, kindly hosted by Itiviti, many of the buy-sides present said they were already testing new platforms to meet MiFID II compliance in January 2017. One of the buy-sides present had already started development on marrying parent TCA data with order routing data and granular tick data in the cloud. Another buy-side explained how MiFID II has reduced their ability to lean on brokers, as best execution and trade reporting has to be handled internally.

However, there will still be opportunities for sell-sides to provide delegated or assisted services for MiFID II reporting obligations, and this conversation will be on-going through 2016 and into 2017. Buy-sides currently use aggregators to access conditional venues, as large-in-size venues will be a major part of buy-side trading going forward, but the access will sit more comfortably within the buy-side, perhaps as a service offered through their EMS providers. This will likely change the broker’s role in such a trade from a value added one to that of connectivity.

One of the headaches buy-sides will encounter is the challenge of measuring the quality of their trade when they have multiple conditional orders in multiple venues, where there may be a match in one or multiple venues. Sequencing may offer a possible solution, but this may place the buy-side at risk of lowering their reputational score within certain venues. Certain buy-sides are willing to rest liquidity for long times, in large size, in venues that they trust, but the problem comes when the other side of the trade meets the trader in one of eight venues, but then the initial resting liquidity appears to fail in the other seven. Ironically, the attendees agreed the attempts to re-aggregate liquidity appear to be a counteraction to MiFID I’s fragmentation of liquidity.

The shift to trading more in blocks, driven by dark trading caps, must be solved by new technology, as one buy-side trader lamented the amount of sizable liquidity on their blotter that they are currently unable to represent on the venues they participate in. Whereas sales traders previously solved this situation, the current regulatory environment pushes buy-sides to search for a technological solution that already existed in human form.

The question was raised as to whether buy-sides using voice traders should hold them to the same market impact standard as their algo providers and the tentative answer was yes. Both algos and voice traders pass through the same TCA process, and one buy-side trader suggested voice traders be held to an even higher standard. Even under MiFID II, technology will continue to be an enabler of trading, even if it is a high touch trader using an algo to execute the trade.

Much of the recent focus has been on the raw compliance side of MiFID II implementation, and ensuring all regulatory obligations are met. Traders need to transition into the long-term perspective of asking how they can run an effective trading business, while operating within MiFID II’s regulatory requirements. However, most firms seem to be successful when focused on one or the other, which has given rise to outsourcing components of the non-focal point: e.g. trading to EMS providers or reporting to brokers.

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In From The Cold – The Buy-Side Use Of Derivatives

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GlobalTrading

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February 15, 2017

By Gianluca Minieri, Global Head of Trading, Pioneer Investments

Many changes have occurred over the last ten years in the way that investment firms manage their strategies. Certainly at Pioneer Investments, we have seen a significant increase in the volumes of derivatives over the last few years. Ten years ago, asset managers like Pioneer (long only asset managers, insurance companies, pension funds) were all very traditional investors. They mostly managed plain vanilla strategies investing almost entirely in cash instruments, so mainly bonds and equities. In terms of investment, there was less pressure to perform given the market back then, so more focus on investment ideas and opportunities to exploit. The last ten years have been very challenging for institutional investors due to a combination of factors:

• the ultra-low interest rate environment,
• low volatility,
• negative rates in some cases and
• significant regulatory change.

In this environment, asset managers have had to significantly expand their product offerings due to competition and the increasing challenge of finding investment opportunities. The resulting trend that the asset management industry in general has taken, has been to increase the sophistication of investment strategies in an effort to improve performance, find new investment opportunities and beat the competition. The resulting trading strategies have consequently become more complex and more sophisticated. Often these strategies now cut across different asset classes, different instruments and different currencies. Directional strategies are combined with hedging activities, so derivatives are combined with cash instruments. Fixed income instruments are combined with equities across the same order, so the sophistication of our investment strategies has increased.

Increased use of derivatives
This type of environment has been the primary catalyst that has led to a significant increase in the use of derivatives in the financial industry in general. One very practical example is the increased demand from our clients for Absolute Return strategies; meaning strategies that can or have the potential to generate returns in ‘all-weather’ conditions. These strategies are, by definition, derivatives intensive, because they need to employ a wide range of different instruments, both cash and derivatives, and that are both listed and over-the-counter (OTC).

Increased volumes
At Pioneer we have seen an increase in volumes of over 80% over the last year (yoy), with 120% over the last two years. Also, 90% of our business was traditionally on the spot-FX market, but today a significant portion of our business is made using FX-forwards. Over the last two years we have seen a 150% increase in terms of FX volumes. As a head of trading, I have had to consider if there is any way we might trade more efficiently to minimise or reduce our risk and cost. Our investment processes, in line with the rest of the industry, reflects that derivatives can have a multitude of uses.

Today’s derivative strategies
At Pioneer, we use derivatives for hedging, but also for yield enhancement. One of the typical uses for derivatives is to create overlay strategies. These strategies can provide exposure to specific risks on top of the core investment strategy for yield enhancement purposes. We also exploit derivatives to provide protection, with derivatives delivering a tailored exposure to a specific risk in a much more effective way than using an underlying instrument. Examples might include: covering a specific bucket on the interest rate curve, coverage for a specific duration, or to cover a specific sub-sector equity exposure. These are all situations where you can actually tailor your coverage by using derivatives, which wouldn’t be achievable using a cash instrument.

Another use of derivatives are the portable alpha overlays, where you use a derivative to exceed performance of a given market or a given exposure, through an investment in another unrelated asset class.

Derivatives managing risk
We see derivatives as a very valuable tool to optimise the way we manage our investment strategies because only derivatives can actually allow you to hedge the unwanted risk. Through the use of derivatives, the portfolio manager can exactly manage the risks that he wants to manage. Any unwanted risk, any risk that he doesn’t feel like managing, or that he doesn’t feel like sustaining, he can actually hedge very efficiently using a derivative instrument. Very rarely do we use them to speculate on the movement on the underlying asset. Derivatives are a set of precision tools that are available to the industry as a whole.

If you consider the way that the market has changed since the introduction of some regulatory measures, like MiFID 1 for example, you have seen the fragmentation of liquidity, the reduction of liquidity and so on. The reality is that markets have become more complicated. Policy makers have made it more difficult for investment banks to play the role that they used to play in financial markets. There are fewer capital providers and fewer market-makers, resulting in there being fewer firms that are ready to take risk on their book. Clearly, in financial markets you can never eliminate risk: a risk never disappears, it is only transferred on to someone else. Now, the asset management company has to take on that risk. A lot of risk has been transferred and now sits with us to manage. In the primary market, before a new issuance was raised, the underwriter took on the majority of risk. Today, the new issue (the new bond or stock) only takes place after it has been pre-sold to clients, with the asset manager taking on the risk.

As a result, we need to be more active in the way that we manage our investment strategies. Derivatives offer this type of possibility because you can buy or sell them with a small up-front cost. Sometimes they are more liquid than the underlying asset. If you want to hedge a specific risk for a short period of time, you just take a derivative exposure and then you unwind it when you don’t need it anymore. It is much more efficient. Derivatives often offer a better level of liquidity.

The consequences of implementing these derivative strategies
Going back a few years, the term ‘derivatives’ had negative connotations for many investors and regulators, mainly because they were widely misunderstood tools. This has changed. There also used to be a perception that the only way you could improve the management of your derivatives was to hire specialist, skilled people. Certainly we still need to have staff skilled in managing derivatives but the key to improvement is in the education and training of staff across the organisation – from the trader, to top management of the company, to people that manage the back office. Derivatives are very demanding, not only from an operational perspective, but also from an investment perspective; they carry more risk.

Derivatives create leverage, which means that when you take a position in derivatives you are taking a position that is bigger than your funded position. Leverage can amplify your returns, but it can also amplify losses. A small movement in the underlying assets can actually cause a large price difference in the value of the derivatives. It’s important for firms not only to have skilled staff that can trade them, but also to improve the knowledge and education across the whole company on how to manage a derivative through its lifecycle – from the time you trade the derivative, to the time that the derivative is in the NAV of the fund. This is the secret to success.

Proper infrastructure is essential: your order management system (OMS) and execution management system (EMS) must ensure that the order on a derivative is actually managed through the entire system. It is absolutely key that every single step of the cycle of the trade is done within the system. Processes must be formalised so everyone knows what to do and when. Systems must be capable of managing all the more demanding phases in the post-trade environment. For example, the complexity that extends from managing corporate actions, the contractual agreement, pricing and collateral management. Derivatives are complicated, and therefore demanding from an operational and administrative perspective, so systems, infrastructure, and tight processes are absolutely key.

Nothing Is As Constant As Change: How To Achieve Better Outcomes And Embrace Change to Realise Meaningful Results

By

GlobalTrading

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February 15, 2017

By Roger McAvoy, Regional Sales Director, Asia Pacific and Andrew Cromie, Global Head of Product Management for Institutional Investors, 360T Group

The buy-side recognises that the FX landscape is fundamentally changing. This evolution has a number of direct and indirect macro drivers which, will be about transparency, liquidity and the underlying technology.

At the highest level, regulatory change continues to influence the buy-side dealing desk and the asset manager as a firm. In the past, a buy-side institution might have set up FX execution as a part of the middle office, client services teams or back office operations purely to achieve efficiencies in workflow and error reduction. In other cases, FX might have been done by the equity broker or the custodian of the underlying funds.

Today, more and more heads of dealing have teams and technology that cover multiple asset classes on the execution desk and the amount of FX managed and executed from a central dealing desk continues to increase. With that, there is an even greater focus on how to achieve better transparency and execution quality, improved risk reduction and further trading and operational efficiencies, including automation. Buy-side participants have highlighted that their challenge is how to achieve greater technology adoption, integration, and efficiencies without the budget of a large bank, and how to stay on top of all the choices available to them.

Best execution
For some buy-side participants, the goal of best execution is simple, such as just being able to prove where the market was at the point of execution when the FX is transacted either through competition or at mid-rate in a fixing order. For others, there is a deeper focus on how to optimise the many decisions that are made before execution that greatly influences the outcome of the orders, for example:

Which orders and which funds should I deal with first?
Should I net offsetting orders for different accounts, across single or multiple currencies?
How long do I hold onto orders in the hope they will net?
What should my netting strategy be, and what should the timing and frequency look like?
How much “market risk” am I incurring when I hold onto an order?
Am I better off using an algo, and at what size?
What is the inflection point where I trade all risk, or am I better off splitting it up to lesson market impact?
At what point should I move from electronic to voice and how do I still capture that electronically to be able to analyse it?

Asset managers have a greater demand for a broader set of FX market data and analytics in order to achieve “best execution” policies, understand trader performance measurement, counterpart management, and workflow optimisation. This is driven, in part, as the buy-side dealing desk looks to embrace technology and standards that have been well-developed in the equities markets, and implement the advanced FX technology traditionally only available in the hands of the sell-side. As a result, expectations are high for what should be achievable by the buy-side. Within the OTC FX market structure and practice there is still a gap that is often a result of what banks are capable of versus what liquidity they are willing to provide and how.

TCA standards

In many cases, when it comes to transaction cost analysis (TCA), there are few standards for how transaction costs are analysed. As a result, for example, the United Kingdom’s Financial Conduct Authority (FCA) released a consultation proposal (CP16/30) in October 2016 that would require asset managers to provide full disclosure of transaction costs in a standardised format to pension schemes that, directly or indirectly, invest in their funds. This means any asset manager with funds under management for UK pension plans will need to ensure their technology can capture not only the time stamp for the calculation of an arrival price, but also individual time stamps and market prices for each trade execution and individual fills. In the FX market, having the right data warehouse and analytical tools to store and report these values on demand, and an easy to access and understand granular audit trail, will become increasingly more important.

With banks also under increased regulatory pressure, there will be more focus on bank pricing behaviour, e-pricing strategies across distribution platforms, and on their ability to take on and warehouse risk. Having more transparency into counterpart behaviour, pricing quality, and any resultant market impact (for example, not warehousing risk and going to the interbank market) will become increasingly important for the buy-side to further their control of execution quality on the desk. This new understanding will enable buy-side firms to go to the best bank in any given situation rather than rely on “gut feeling”. Measurement will drive informed, proactive decisions and support the asset management firm in an increasingly more regulated global environment.

Application of new technologies
For many years, larger banks have been building out tools and analytics which help them hold or exchange risk with other participants efficiently using quantifiable data, resulting in better predictability in their trading outcomes and profitability. The sell-side continues to embrace even greater automation, more sophisticated auto-pricing strategies and the development of bank algorithms to capture client flow and offset risk. While it is certainly possible to build out the infrastructure to measure this, the overhead to store this data, let alone to use it, is highly expensive. The buy-side is able to leverage the FX dealing platform provider to help with these issues, which includes not only data warehousing, but also the opportunity to engage meaningfully around best practice.

Data analytics and execution technology are now intertwined and having the ability to leverage that data can provide insight beyond the most basic TCA. For example, although post-trade TCA tells a story, in general it is not a reflection of market conditions (whether they be “normal” or not) before, during and after execution. You also need to consider how your benchmark data is sourced and how relevant those prices are relative to your quoted volumes and eligible counterparts.

These are just a few of the questions that we hear from asset managers as they try to build a quantifiable, repeatable process. Knowing where to source this data and how to carry-out this type of analysis are some of the new demands of the interaction. This type of information will help asset managers make better informed decisions around the merits or costs associated with the execution strategy.

The buy-side embraces new ideas and technology that will help them evolve their workflow, address broader market structure and execution quality issues. These are the clear focus of the immediate horizon. Drilling down there are further consideration to bear in mind: working with providers that have a bias for buy-side requirements (or working with providers whose purpose is aligned to the outcomes you desire), getting the right FX data analytics with no hidden fees, and gaining access to alternative solutions that help to deal with liquidity fragmentation.

During the past few years, a broader choice of multibank trading technology providers is now available, beyond the traditional FX technology solutions. These providers bring much needed market-neutral FX trading technology, data warehousing and analytics into the dealing workflow and investment process. Gone are the days of having to solely rely on bank-developed or bank-owned technology for FX execution. More measured, independent solutions that address the client’s needs can now be quickly and easily implemented. These ‘enablers of evolution’ can be plugged into many processes, including order management systems (OMS) using FIX connectivity and other integrated workflows.

While not all providers are capable of offering the right solutions and engagement, or have the ability to scale with client and regulatory demand around these issues, those that do are finding more and more invitations to help with solving the dilemma.

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Pre-Trade Risk Assessment Across Multiple Channels

By

GlobalTrading

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February 15, 2017

By Marcus Consolini, Managing Director, Head of Asia Pacific/Japan, Ullink

Nowadays, market participants face increasingly complex challenges when trying to assess their risk exposure across markets, asset classes and order flows. In the post-trade world there is a high level of integration of risk measurement and management processes, but in the pre-trade world there is certainly less. This is because many participants still have segregated silos for their different trading channels, such as DMA, DSA, Care and Dark Pools. Attempting to aggregate the pre-trade risks of each discrete channel, requires a strong understanding of their differences, the ability to install centralised and localised risk controls, and the expertise to manage technology and system integration.

Trading channels – the issues with vertical silos and risk exposure
Sell-side market participants that provide a broad range of services to clients continue to be faced with a major challenge. What kind of risks exist within distinct vertical trading silos and how should they be both individually and collectively managed? Traditionally, Chinese walls were erected between specific trading activities because risk, technology and operational demands differed. A lower compliance burden, often with prohibitive costs for running an integrated and centralised platform, and less sophisticated trading clients, meant aggregation across trading silos was never put in place.

However, in today’s markets, increasingly sophisticated clients are simultaneously trading across multiple silos, requiring market participants to manage risk in a single consolidated layer. The fact that the segregation of trading activities often results in increased risk exposure for the sell-side market participant and less flexibility for the trading clients, means that those who can implement an integrated and flexible aggregation layer should be able to retain and attract further business.

Specifically, clients are looking for the ability to trade across multiple channels with a market participant that can manage their risk limit across those various channels: essentially, providing one firm but fluid trading limit that incorporates all market and asset classes. This can only be achieved with a horizontal risk layer that sits on top of the individual vertical trading silos.

Centralisation and localisation – the issues with multiplicity and aggregation
While this horizontal risk layer would provide market participants with a consolidated picture of a client’s overall exposure across multiple trading channels, there is a further issue to address: what risks can and should be centralised and what risks must remain localised, for example whether at the exit point of an algorithm or a best execution engine, before entering a dark pool or a crossing engine?

In practice, there are really two types of risk assessment involved with many trading platforms offering multiple channels and strategies. First, there is what a specific client is actually doing, that is, what are the aggregated positions they hold across markets, asset classes and channels. Second, what is trading on the markets at any point in time through the sell-side market participant, that is, their full real-time market exposure. The first assessment gives a complete view of trading activity for all clients across all channels – effectively the client safety net. The second assessment looks at trades just before they exit the platform and hit the market – effectively the market participant’s safety net. The first assessment is where risk can and must be aggregated, while the second is where segregated systems dealing only with specific risks reside.

Business integration – the issues with different risk categories
Although aggregation across channels is required in order to accurately assess total risk exposure, the next challenge is how to set up the risk controls needed for each discrete channel. For instance, the risk parameters and validations when placing an order directly onto an exchange, for instance DMA, are and should be different to placing a basket of orders within a fully automated strategy. This often results in multiple trading systems provided by multiple vendors coexisting in the same environment.

When trading in a straight DMA channel, buy-side clients are the originators of orders and they retain complete control of the orders, with the ability to amend or cancel them whenever they want. Risk control in this scenario is relatively straight forward, as points of failure in this trading path are minimised.

However, the scenario becomes more complex within fully automated trading strategies, such as algorithmic trading. Buy-side clients neither retain full or direct control of their orders on the market, nor does the automated strategy placing those orders directly on the market have control. Rather the trader ends up with a handful of static parameters that are sometimes not even adjustable in real time. In the event that something in the algorithmic strategy goes wrong – and it has happened with alarming frequency during the past few years – it is not always guaranteed that the buy-side clients or the market participants themselves will have the ability to intervene and take control over the execution process. This highlights that the type of risk controls required compared with a straight-through DMA channel are different in nature and complexity and should remain segregated.

The problem is that buy-side and sell-side market participants have tended to adopt the fastest and, apparently, most efficient platforms and supporting systems to meet immediate competitive demands, without fully-understanding the risk assessment tasks that they might need to perform. The result is a technology stack that is a mix of in-house built and vendor-supplied systems. As both international and local regulation increases and compliance demands rise, obsolete platforms and architecture must either be completely re-built, re-engineered, or aggregated and consolidated. Hence, working with technology partners that are globally present and domestically locally focused is becoming increasingly necessary.

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