FIXGLOBAL.COM
Q3 • 2017 • Issue #63
G LO B A LT R A D I N G
Harnessing Big Data To Transform Fixed Income Trading Chris Rice, Senior Managing Director, Global Head of Trading, State Street Global Advisors
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GARRETT ASSET MANAGEMENT, HKEX, IEX, INVESCO
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GlobalTrading’s Editorial Think Tank Dear Readers, Automation is taking over many humdrum, time-consuming operational processes in the financial industry and algorithms implement portfolio strategies as well as optimize trade execution. Meanwhile, there is a lot of focus on the potential of artificial intelligence (AI) and machine learning to take on ever more tasks, and perhaps reduce humans to monitoring and other passive roles. However, new technology is likely to continue to require complementary skill-sets from people. Trading experience, networks and market savvy might diminish as job requirements, but quant expertise will be essential. Bill Hebert Co-Chair, Global Member Services Committee, FIX Trading Community
For instance, there are many components within best execution such as controlling risk and avoiding errors, explicitly managing orders, minimizing slippage and adding other value throughout the entire trade cycle. Best execution, as stipulated by Markets in Financial Instruments Directive (MiFID) II, is concerned with achieving the optimum outcome on a consistent basis, and not simply on attaining the best price available at a given time for an individual trade. Several factors must be considered, including transaction speed, order size, the likelihood of execution in prevailing market conditions and the certainty of settlement. Intuition based on experience, pattern recognition and understanding as well as personal networks all help in these processes, and are likely to continue to complement evolving technologies – at least for the near future.
Carlos Oliveira Brandes Investment Partners
Emma Quinn AB
Greg Lee Barclays
Michael Corcoran ITG
On the other hand, fixed income markets are playing catch-up with equities markets where traders have benefited for several years from greater visibility and access to liquidity due to automation. But, advances in data accessibility and processing through machine learning and other AI technologies are transforming fixed income traders’ ability to build a new generation of smart order routing platforms. These new dashboards are bridging many of the price discovery and pre-trading liquidity gaps that once challenged fixed income traders. But, just as machines in other areas of activity have not fully replaced people, algorithms are unlikely to replace humans altogether. Besides, as a panellist pointed out during our New York roundtable discussion in June: If your job can be eliminated by a computer, then how long would you actually want to do that job? Best Regards,
Bill Hebert Co-Chair, Global Member Services Committee, FIX Trading Community
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Publishers’ Note GlobalTrading is proudly published by HM Publishing in support of the FIX Protocol and the FIX Trading Community. GlobalTrading is the official quarterly publication of the the FIX Trading Community, however, the content does not necessarily represent the opinions of the FIX Trading Community. The opinions expressed in this publication are not necessarily those of the publishers or of the institutions of the contributing author. Although care has been taken to ensure the accuracy of the information contained within the publication, neither the publishers, authors nor their employers can be held liable for any inaccuracies, errors or omissions; nor held liable for any actions taken on the basis of the views expressed, or information provided within this publication. No part of this publication covered by the publisher’s copyright may be reproduced, stored in a retrieval system or transmitted, in any form or by any means, be they graphic, electronic or mechanical, including photocopying, without the written permission of the publisher. Any unauthorised use of this publication will result in immediate legal proceedings. All Rights Reserved © 2017
CONTENTS 5
FOCAL POINT
5 Harnessing Big Data To Transform Fixed Income Trading - Chris Rice, State Street Global Advisors 9 Machine Learning And The Future of Finance - Elliot Noma, Garrett Asset Management
17
52
OPINION
AMERICAS
27 Transforming Legacy Systems Jay Boyd, Invesco
17 Separating Trade Execution And Research - Stephane Loiseau, Société Générale 21 Assembling The Best Technology Stack - Steve Grob, Fidessa 25 Best Execution Monitoring: Lip Service Simply Isn’t Enough - Duncan Begg, ITG Asia Pacific
49 Trade Automation: Panacea Or Placebo - Rupert Walker, GlobalTrading
30 How Much Security Is Enough? - Mark Vos, Iress
52 IEX Launches Listings Venue - Sara Furber, IEX
34 Enabling Best Execution - Damian Bierman, Portware
EUROPE
36 Different Flavours Of Self-Match Prevention - Vaibhav Sagar, Open System Tech
55 Implementation Of MiFID II Testing Requirements By Trading Venues And Investment Firms - Matthias Burghardt, Boerse Stuttgart
ASIA
39 Catalysts For Change: HKEX Hosting Services Ecosystem Forum 2017 - Rupert Walker, GlobalTrading
58 Turquoise Plato Block Discovery - Robert Barnes, Turquoise
INSIGHT
13 Openness: The New Word In Trading - Michael Chin, Thomson Reuters Financial & Risk
-
PRODUCT OVERVIEW
INDUSTRY 43 Unplugging Alpha In Indian Markets - Jyoti Rai, Associate Director, Edelweiss Prime Brokerage Services 46 A Renewed Focus On Innovation - Rupert Walker, GlobalTrading
62 FIX Trading Community Members MY CITY 64 Mumbai - Jyoti Rai, Associate Director, Edelweiss Prime Brokerage Services
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FOCAL POINT | 5
Harnessing Big Data To Transform Fixed Income Trading By Chris Rice, Senior Managing Director, Global Head of Trading, State Street Global Advisors
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New data mining and architecting techniques are helping to bridge the transparency gaps that once challenged fixed income traders. Best execution in fixed income markets has always been more challenging than in equity markets in which traders have a greater line of sight into securities trading at higher volumes across automated markets. By contrast, fixed income mostly trades over the counter and is characterised by fragmented price sources and less accessible data. However, advances in data accessibility and
“Improved IOI data, combined with information from other bond pricing sources and platforms, as well as liquidity cost scores, furnishes enhanced insight and the potential to negotiate a better price.” processing through machine learning and other artificial intelligence technologies are transforming fixed income traders’ ability to build a new generation of smart order routing platforms. These new dashboards are bridging many of the price discovery and pre-trading liquidity gaps that once challenged fixed income traders. The advent of new fixed income trading platforms has created more information than ever before about transactions and counterparties. Fixed income market participants are increasingly trying to harness the power of these expanded data sources to gain greater insights into market liquidity and enhance trading decisions.
GLOBALTRADING | Q3 • 2017
As a result of new infrastructure improvements, dealers now provide liquidity indications of interest (IOI) to the buy-side much more frequently throughout the trading day than before. Even just a few years ago there was often just one IOI in the morning. This provides buy-side traders with a far better and timelier snapshot of actual dealer liquidity. This improved IOI data, combined with information from other bond pricing sources and platforms, as well as liquidity cost scores, furnishes enhanced insight and the potential to negotiate a better price. Buy-side firms are leveraging this information and in varying forms have been able to consolidate much of this data within their order management systems to make access easier for traders to digest and exploit. This data is also helping fixed income portfolio managers build more resilient strategies that take liquidity conditions into account at the design rather than the execution stage. There have also been other more formalised initiatives to improve fixed income liquidity and market transparency. For instance, Project Neptune, a collaboration of large banks and buy-side firms, has created a powerful centralised source of information around available fixed income securities. While it is not a trading platform, it nevertheless helps solve some of the opacity and liquidity challenges in the broader industry context of lower inventory and poor information transparency. The explosion in pre-trade and post-trade data will increase even further with the implementation of the European markets in financial instruments directive (MiFID) II in January 2018. Managers with the technology and expertise to mine and architect this new data into actionable insights will enjoy a competitive advantage. At SSGA, we are creating the next generation of data processing and visualization techniques to improve our ability to harness new data sources and incorporate those insights into dynamic dashboards that help our traders and portfolio managers achieve better execution. Better data visualization and dashboards New data visualization tools have improved the collaboration between trading desks and portfolio managers. The ability to dynamically filter and
FOCAL POINT | 7
Chris Rice, Senior Managing Director, Global Head of Trading, State Street Global Advisors
“New data visualization tools have improved the collaboration between trading desks and portfolio managers.� interpret large data sets in differing visual formats has created an important feedback loop for trader and portfolio management teams aimed at constant process improvement. The dashboards enable more precise data customisation for targeted audiences (for example, traders versus portfolio managers
versus group CIOs) and allow end users to detect anomalies in trading costs, volumes or counterparty activities. During the past year, we have rolled out dynamic dashboards to traders that enable them to hone in on their trading activity over a given time period. Counterparties can be analysed by volumes traded or associated transaction costs. Traders can review the performance of counterparty over time or narrow down performance in certain markets or trading styles. As a predictive feature, this may flag counterparty strengths or weaknesses as a guide for future trading activity. This is particularly important information for those fixed income sectors where liquidity is scarce. March of the machines As advances in machine learning and other artificial intelligence (AI) technologies are applied more
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“We are quickly moving to the state where we will be able to automatically capture datasets from across the entire lifecycle of fixed income trading activity.” This iterative process of improving the volume, quality and representation of pre- and post-trade fixed income data has several important benefits for investors. Most immediately it helps fixed income traders augment the inherent price discovery challenges of trading fixed income securities in fragmented and less transparent venues, thus improving their ability to provide best execution. More importantly it provides a powerful advantage to fixed income portfolio managers by equipping them with far more reliable liquidity data across fixed income sectors as they design their strategies to minimize market frictions and maximize efficient execution. broadly to automating and refining pre- and posttrade fixed income data, we expect that both traders and portfolio managers will benefit. We are quickly moving to the state where we will be able to automatically capture datasets from across the entire lifecycle of fixed income trading activity – from cash flows to execution. This expanded universe of data (RFQs, liquidity, market data, execution data, qualitative commentary, historic cash flows, etc.) will help to incorporate trade execution directly into the portfolio management process and improve speed to market. We envisage a not-too-distant future in which our traders will routinely be using AI technology to improve pre-trade price discovery and optimize execution.
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FOCAL POINT | 9
Machine Learning And The Future of Finance
By Elliot Noma PhD, Managing Director, Garrett Asset Management
Artificial intelligence has conquered games and image recognition, but will it master investing? The short answer is yes, but how soon and how complete will the conquest be? Machine learning methods have had impressive recent successes. These include defeating humans at chess, Jeopardy, poker and Go, as well as providing superior image and speech recognition. Developers strive to create tools that automate decision making and that can mimic or exceed human performance for specific tasks. The range of tasks and the variety of methods influence current successes and the way forward. This means that there can be large differences in the short-term outlook of machine learning methods in
finance, with some areas quickly embracing artificial techniques (AI) while other areas require the development of new methods. AI and machine learning are often used interchangeably since they convey a general idea that software can make intelligent decisions, and intelligence implies the ability to learn over time. However, the ability to learn new concepts is different from the appearance of intelligent behaviour. Some methods, such as unsupervised learning, need little guidance, while others such as support vector machines require extensive training. Linear regression models have a great deal of statistical theory backing their application, but for neural nets the theory is still being developed. Moreover, models of learning vary based on the criteria used to evaluate success.
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Tabulating the performance of even the largest pool of loans is done easily and accurately. Over time, machine learning tools can become increasingly sensitive to deviations from what is expected and are therefore highly useful tools in fraud detection. Different detectors can also be linked together to identify deviant behaviour.
“The ability to learn new concepts is different from the appearance of intelligent behaviour.�
Elliot Noma PhD, Managing Director, Garrett Asset Management
AI is being applied to finance in several ways. These include the automation of many tasks, handling basic functions and the ability to change over time as the software adapts to new market conditions. Strengths 1. Automation: When incorporated into data feeds, models extract information from inputs, classify them into useful categories and initiate actions autonomously or through human intervention. These actions are consistent and can be improved over time. Automation allows quicker evaluation of inputs for an investor trying to determine the utility of a new dataset. It enables a detailed look at large amounts of data produced by sensors in the Internet of Things. Trading models can be developed quickly as older models become obsolete. 2. Handle the mundane: Software excels at monitoring every-day occurrences. It can easily monitor the performance of a physical device to determine that the device is functioning correctly.
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3. Adapt over time: Machine learning techniques require training data so they can predict the best actions in normal situations. As data sets expand, the software can be adapted to increase the number of features that it can monitor. This makes decision making more nuanced. In addition, as new categories are added in supervised learning, the granularity of the decision process improves with more data. However, machine learning methods need customisation for different domains. For instance, neural nets are usually trained on images of a standard size to better fit the internal network. A neural net analysing text may be better structured using a different internal configuration. In finance, these challenges may extend beyond just the geometry of connections making up the network. Challenges 1. Time to learn: Machine learning techniques require training data so they can excel at predicting the best actions in normal situations. They are weakest when classifying unusual situations where there are few training cases and exceptional drivers dominate. Also, some data may arrive at specified intervals such as the announcements of central banks or quarterly corporate financial reports. In contrast, other fields can accelerate their data collection by increasing their web traffic of recruiting evaluators. Using a variety of models to
FOCAL POINT | 11
analyse data from multiple sources may help here, as techniques such as boosting maximize the contribution of each model and data set. Furthermore, learning can take place at several levels and for different purposes. For instance, you may talk to a chatbot which appears to exhibit intelligence. It answers your questions and may have some learning as you continue to converse with it – but only so far. Another example is an algorithm which ostensibly learns to detect images of cats, but might be actually creating a rule on the brightness of the background. These structures point to differences in our expectations of how AI learns and what it retains. This makes the individual methods impressive in many contexts, but lacking in aspects of intelligence that we take for granted in our interactions with other people. These include a memory of context and our ability to notice deviations from our expected context. Humans also assume that certain information will be learned even if we are not aware we are learning it. We also expect that when asked, we can give some justification for our decisions and perceptions. 2. Continuous stream of input data: Another challenge is modelling a continuous flow of information whose time boundaries may be unknown or indeterminate. This is unlike image processing which analyses individual images in isolation or game-playing programs which use well-defined conclusions that can be used unambiguously to define victory or defeat. In contrast, the time horizon of financial investments is usually not fixed as personal and business circumstances change over time as does the evaluation of investment success 3. Lack of stationarity: Images of cats do not change over time as our image processing capabilities improve. However, trading strategies and markets as a whole adapt depending on external events and actions by traders and money managers. In some markets, new trading algorithms may have a very short useful life. Often these changes are due to events outside the world of finance, so they are beyond the horizon of most models. 4. Crowded trades: The use of common data sets and common machine learning methodologies can lead to crowded trades which limit profitability for some
strategies. It also moves overall market risk from individual portfolios to the market as a whole, similar to how the convergence of risk management methods increased systemic risk. However, there is a wide range of methodologies for machine learning and the number of datasets is expanding as new tools and measures are created, which mitigates concentration risk. 5. Lack of transparency: Of greater concern is the acceleration of the investment process and the decreased insight into why decisions are made. Combined with the lack of understanding of how non-normal markets are handled by software this should raise concerns about how the system copes with periods of high volatility or events such as the “flash crash” of May 2010. Software and hardware are prone to bugs, and humans need to keep a tight control of the behaviour of machines as they take over more and more tasks.
“Machine learning techniques are weakest when classifying unusual situations where there are few training cases and exceptional drivers dominate.” Applications Among the various applications across finance - credit, operations, trading cycle - each has different characteristics that play to the current strengths and weaknesses of machine learning. One cannot generalise within such broad categories, but certain specific applications are most compelling. For instance, many operational and trade execution functions can take advantage of automation to recognise the normal. Routine execution and trading functions can be best conducted using algorithms in normal markets. Some brokerage and banking functions can be streamlined as investment advisers are cued to sales opportunities by software that considers customers’ past trades and investment
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preferences. Credit verification already uses a high degree of automation and could be made even more accurate by considering more complex patterns of the borrower and adjusting the weights to these factors based on changes seen in customer behaviour. All these software tools are used within the world of human activities that have consequences for individuals and whose rules are set by humans. For the immediate future, humans will need to give oversight to computer activities and continue to handle the exceptional situations. This is especially true since the reasons a program makes a decision are very different from the heuristics used by humans. Also, methods for computers to explain the logic behind their decisions to humans are still in their infancy. This lack of communication is especially important when determining the blind spots of an algorithm. Software cannot dictate an investor’s preference for risk or intuitions about specific opportunities. Much remains outside the view of models such as the activities of governments and central banks to affect the markets, especially during exceptional situations. Just as other machines in other areas of activity have not fully replaced people, machine learning
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“The use of common data sets and machine learning methodologies can lead to crowded trades which limit profitability for some strategies.” algorithms are unlikely to replace people altogether. Software will, however, change the number of people doing specific tasks and the skillsets of those remaining. The one certainty is that machines will further disrupt the financial industry.
INSIGHT | 13
Openness:
The New Word In Trading By Michael Chin, Managing Director, Co-Head of Trading, Thomson Reuters Financial & Risk
Open platforms allow clients to leverage multiple best-of-breed components in order to enhance performance, reduce risk and cut costs. Today’s trader needs to be able to connect to their counterparties, find liquidity, transact and prove best execution, with fewer resources than in years past. Fortunately, the rise of open trading platforms across the industry is helping to make this ask a reality, incorporating the key functions they require across the full trade life cycle, from pre-trade through post-trade. Top trading platforms are often constructed from multiple proprietary and best-of-breed vendor systems, integrated to provide a seamless workflow and powered by a single source of market data to ensure consistency. They strive to meet the needs of market participants who demand openness, interoperability and connectivity between clients, partners, suppliers and their own employees.
In response to these demands, and in alignment with our open platform strategy for trading, Thomson Reuters acquired REDI, an award-winning, cross-asset execution management system, in January 2017. Through the acquisition, REDI is being integrated into both Eikon, our next generation financial markets desktop, and the Elektron market data platform. This integration provides a powerful buy-side trading workflow solution with interoperability between the platforms. Challenges and trends The need to adopt an open platform strategy is prompted by several macro trends that affect, in one way or another, all members of the financial industry. First, there are pressures to minimize the total cost of ownership (TCO) of the trading stack and maximize scalability and agility. Financial firms are under intense cost constraints as regulation and competition are forcing a change in business models,
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“An open platform business acquires, connects and matches disparate systems and networks to enable providers and consumers to do business, and does so without necessarily owning all the assets in the value chain.” and prompting a shift from products to platforms and from customers to communities. Cost-containment is likely to persist, acting as catalyst for technology innovation. Meanwhile, creating, distributing and monetizing new products and services will remain a challenge for both the buy and sell side. Second, regulatory compliance is increasingly complex, costly and global. New obligations around transparency and risk management are coming into force, but within in a market structure that is still evolving in an unclear fashion. Third, the momentum towards automation is relentless. Algorithmic trading extends across asset classes, while straight through processing, risk aggregation and liquidity fragmentation are driving further electronification . Next generation users also have greater technology expectations, forcing the creation of digital strategies and leading to the emergence of fintech firms that are disrupting existing operating models. The new financial consumer expects the same seamless, user-friendly experience for their trading platform as they have when making an online retail purchase or downloading a new smartphone app. Finally, financial services are increasingly data and content driven. Greater market transparency is generating valuable new sources of data, but the task of aggregating and integrating these can be extremely resource intensive.
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Michael Chin, Managing Director, Co-Head of Trading, Thomson Reuters Financial & Risk
As a result of these trends, both the buy side and sell side are considering major changes in their technology choices. According to a recent survey by Aite Group, 58% of buy-side and 79% of sell-side firms are likely” or ”very likely” to consolidate and/or rationalize their trading infrastructure. They are turning to modular technologies that will help them scale, lower their TCO, offer frictionless integration and allow them to connect to the broadest set of content and liquidity partners for trading. What is an open platform business? An open platform business is unique in that it acquires, connects and matches disparate systems and networks to enable providers and consumers to do business, and does so without necessarily owning all the assets in the value chain. Perhaps just as important, it’s a business model with a go-to-market mind set, and not just a technology approach. Many of today’s wildly successful enterprises use this model. At a basic level, these businesses link together
INSIGHT | 15
consumers and providers. They also treat every participant across the platform as a customer, and provide environments in which those participants can create value, both for themselves and for others. Platform foundations A successful open trading platform, such as the one we have built at Thomson Reuters, requires three critical building blocks: the tools, “gravitational pull” and the flow.
“Greater market transparency is generating valuable new sources of data, but the task of aggregating and integrating these can be extremely resource intensive.” The tools are the mechanisms that allow customers and third parties to engage with and use the platform. These include application programming interfaces (APIs), technology platform access, contracting and permission services, network distribution capabilities and various developer instruments. The “gravitational pull” incorporates those elements that make a platform a “must have” for market participants. These are unique news and specialist content sets, data delivery and aggregation tools, standards for ease of use and integration, unique search tools, a superior desktop experience and, importantly, human expertise.
“The flow is made up of the participants themselves, who offer the connectivity and communications services and usage analytics that help bring together the community and facilitate transactions.” Trading in an open platform world Participants with an open platform community include exchanges and other trading venues, content and intelligence sources, banks and brokerages, regulators and central banks. They offer platform access, developer tools and APIs, as well as contracting, billing, permissioning and network distribution services. Consumers include asset and wealth managers, banks and brokerages, hedge funds and corporate treasuries, governments, regulators and central banks. They use a platform to transact, connect and communicate, as well as leverage analytics and end user tools and services. The key concept and differentiator for the best platforms is to be “open”. This means allowing all participants to discover, create and deliver value, build relationships and transact.
The flow is made up of the participants themselves, who offer the connectivity and communications services and usage analytics that help bring together the community and facilitate transactions. By understanding what drives the value and transaction flow across communities, a platform operator can actually help to increase and sustain that flow.
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INSIGHT | 17
Separating Trade Execution And Research By Stephane Loiseau, Managing Director, Head of Cash Equities & Global Execution Services – Asia Pacific, Société Générale MiFID II’s commission unbundling provisions will have a widespread impact on global financial services and lead to the emergence of more independent research platforms. The implementation of MiFID (Markets in Financial Instruments Directive) I a decade ago established a harmonised investment services framework in Europe. It also led to a wide-spread adoption of low-key unbundling of stock trading commissions, separating a broker’s advisory service from order execution. However, MiFID II, which will come into force on 3 January 2018, will have much more explicit prescriptions and a wider ranging impact, affecting not just how European fund managers conduct business, but also on buy-side firms in Asia and the US.
The legislation considers payment for research (or any other service) through trade execution commissions an inducement and is therefore not allowed. The regime also sets tougher rules on the transparency of research costs, which must be disclosed by asset managers. It is likely that the regulation will equally impact US and Asia firms whether they trade in the EU or not. It also means that US and Asia subsidiaries in the EU will have to conform. Currently, there is limited unbundling of trade commissions and research in Asia, mainly due to the complexity and diversity of the region’s markets. Yet, there has been a prevailing awareness that advisory services and order execution should be separated, albeit informally. The advent of MiFID II has hardened
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“For all asset classes, the sellside needs to determine how the buy-side should pay for different components and methods of delivery.” the perspective, solidifying a previously nebulous undertaking to distinguish between the two services. In the US, where the Securities and Exchange Commission prohibits cash payment for research from the profit and loss account, a majority of fund managers said according to various press reports that MiFID II is likely to have an impact on their business models as they intend to unbundle commissions, although it’s not clear how they will do so or even value research. Global adoption of unbundling There are two main reasons why Asia and US fund managers are becoming more MiFID II aware. First, there is a commercial motive: they operate in a highly competitive market, and asset owners are likely to select fund managers who demonstrate best practice. This is especially important when pitching for sovereign fund mandates in Asia and the Middle East whose activities are subject to close public scrutiny, and where maximizing performance, therefore also minimizing costs, are amongst the key objectives. Second, there is a business imperative: the scope of MiFID II outside Europe is still unclear, but it is likely to be wide and probably extraterritorial, so fund managers need to be prepared to avoid being blindsided, while adoption on a worldwide basis will facilitate internal operational efficiency for the largest firms. The MiFID II provisions cover all types of research, including macroeconomic analysis and strategic advice, as well as stock, rates and credit recommendations. Although the separation of trade execution and research costs
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Stephane Loiseau, Managing Director, Head of Cash Equities & Global Execution Services – Asia Pacific, Société Générale for equities has already been applied by some buy-side firms, fixed income is entering new territory. There are no explicit commissions paid for dealing in bonds, and there is no connection between research costs and trading spreads. For all asset classes, the sell-side needs to determine how the buy-side should pay for different components and methods of delivery, distinguishing between basic web content, discrete research portals and premium services such access to a star analyst, strategist or economist. Meanwhile, a buy-side firm basically has three options for allocating costs. First, the transactional method funds a Research Payment Account (RPA) that incorporates a Commission Sharing Agreement (CSA) with sell-side firms, separating trade execution costs from research costs. Second, the accounting method funds segregated Research Payment Accounts (RPA) internally, matching invoices from research providers with their application to clients’ proportional interest in a portfolio. The third way is simply to pay for research from the firm’s profits. This has the attraction of being subject to less regulatory oversight, but some
INSIGHT | 19 firms might take one of the two RPA routes if they have already implemented a degree of payment unbundling and allocation system for their clients. Certainly, the adoption of the RPA method will make buy-side firms more aware of the value of specific research and this closer scrutiny will put pressure on sell-side firms to produce consistently high-quality content. An unforeseen consequence of MiFID II’s rule might be concentration risk, with fewer banks and brokerages providing research and a reduction in trade execution counterparties as some sellside firms, starved of commission income, pull out of markets. Perversely, this could lead to a re-bundling, creating an oligopoly between the largest investment banks and asset managers. Independent research platforms On the other hand, independent research providers should be given a boost. Regulation is pushing buy-side firms towards them in order to ensure there is no suspicion of tacit links between trade execution and research, and independent firms with low costs should be able to compete on price with banks and brokerages struggling with high fixed costs and vulnerable revenue streams.
“It is likely that the regulation will equally impact US and Asia firms whether they trade in the EU or not.” However, research specialists need to establish credibility with fund managers, especially if they are a new entrant to the market up against well-established bank incumbents. There are companies that aggregate research, package and sell it to fund managers, but an alternative model, that takes advantage of new technologies, offers a more efficient and customised service.
for investment insight focused on the Asian markets, to provide its institutional clients access to equity research based on real-time demand and matched to individual investment mandates using predictive technology.
“An unforeseen consequence of MiFID II’s rule might be concentration risk, with fewer banks and brokerages providing research and a reduction in trade execution counterparties.” Customers receive research provided by around 400 highly ranked analysts, academics, data scientists and strategists covering more than 1600 companies across 15 Asian markets. Many of the analysts previously worked at major financial institutions and prefer the independence of working in smaller, autonomous firms. A platform such as Smartkama offers fund managers an ecosystem that is fully compliant with MiFID II’s unbundling prescriptions, avoiding suspicions of brokerage inducement while ensuring access to the best research, judged on its own merits. Independent research platforms are likely to develop further as many sell-side firms are forced to choose between maintaining costly own research capabilities or focussing on trade execution. A bifurcation of function seems to be an inevitable consequence of MiFID II’s unbundling provisions.
Last year, Société Générale signed an agreement with “Smartkarma”, a curated online platform
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INSIGHT | 21
Assembling The Best Technology Stack By Steve Grob, Group Strategy Director, Fidessa The traditional build or buy dichotomy is being eroded by the costs incurred to keep pace with persistent regulatory changes and rapid technological advances. Brokerages and investment managers frequently face a choice: whether to build a technology stack internally for their trading operations or purchase the full package from a vendor. Both options have distinct advantages and drawbacks. An organically devised system can ensure that the firm gets exactly what it needs, it has an opportunity to differentiate from others and the firm is not dependent on a third party if it wants to make adjustments to the system. However, it is expensive and there is a risk that the project loses its discipline, becomes unfocused, and is vulnerable to staff or departments pursing their own agendas – and even to a new chief technology officer keen to make their individual mark. Although there have been some successes, there have been many disasters. The alternative, a vendor-supplied tech stack, can be scaled for individual requirements, made
fit for purpose and can easily be adjusted for future needs. On the other hand, the firm is tied to a particular vendor, which can reduce flexibility and potentially creates legacy burdens later. In the past, larger firms tended to build their own stacks and smaller firms used a vendor, but there is a change underway.
“In the past, larger firms tended to build their own stacks and smaller firms used a vendor, but there is a change underway.” The cost of building from scratch and maintaining systems is now much higher. Continual waves of regulation have become the new normal, as have constant new developments in technology
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sophistication. At the same time the market evolves too, creating opportunities that need to be addressed, such as the shift from active to passive investment and the resulting surge in ETF trading. But underpinning all of this is the simple fact that the economics of the industry are not what they used to be, and so everyone is faced with doing more with less. For instance, Fidessa supports more than 200 equity and futures markets globally. Each of these might introduce two upgrades a year prompted by regulatory or other requirements. And so 400
“Increasingly, investment firms are only differentiating themselves with the top level of the technology stack.”
Much of the different lower level technology that is necessary to instruct, transact and settle trades in exchanges and platforms across the world can be homogenised by firms like Fidessa. As a result, these different venues can be represented as a single, normalised surface to clients and they simply need to plug their tools into this layer to access liquidity. This creates tremendous efficiencies for both buyand sell-side firms and not just in their equities businesses, but also for derivatives, foreign exchange and even fixed income. It allows firms to concentrate on developing and retaining high value intellectual property - those smart algorithms, enhanced liquidity connectivity and solid risk controls that distinguish them from rivals.
necessary adjustments need to be made to Fidessa’s systems before any value-added improvements are made. This overhead only makes sense if the cost can be shared over multiple clients.
Indeed, increasingly, investment firms are only differentiating themselves with the top level of the technology stack, such as their algorithms, multiasset trading capabilities and how they manage and integrate their activities with a central risk book.
A third way To resolve these problems, a third way has become increasingly popular: firms are no longer faced with the traditional dichotomy of build or buy.
The further up the technology stack, the greater amount of intellectual property. But, inevitably, today’s ultra-sophisticated, jealously-protected algorithm soon becomes humdrum and mass-produced.
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INSIGHT | 23
“A typical choice is to amalgamate static or reference data into one securities master storage centre, using systems shared by financial firms and implemented across different asset classes.� So, firms are examining the best way to use thirdparty components in their tech stack, working out ways to glue the pieces together. A typical choice is to amalgamate static or reference data into one securities master storage centre, and Fidessa and other vendors have created systems shared by leading financial firms and implemented across different asset classes.
Steve Grob, Group Strategy Director, Fidessa
Post-trade operations in particular are woefully inefficient. Many of the processes are still conducted manually, so there is plenty of room for improvements in cost, speed, accuracy, risk management and compliance. For instance, it should be straightforward to install FIX-based utilities for post-trade processes in a similar way to pre-trade order-routing. Greater sophistication, the rapid rate of technological innovation and constant regulatory prescriptions are raising the costs while shortening the shelflives of home-grown systems. Hence, the trend, the direction of travel is in only one direction: towards a wider adoption of the build and buy model.
Q3 • 2017 | GLOBALTRADING
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INSIGHT | 25
Best Execution Monitoring: Lip Service Simply Isn’t Enough By Duncan Begg, Electronic Product Manager, ITG Asia Pacific
A data-driven broker selection tool demonstrates a process-driven, quantitative approach to execution performance measurement. As the implementation date for Markets in Financial Instruments Directive (MiFID) II fast approaches, regulators are sending a clear message to the investment community: Make sure that you perform robust analysis of the effectiveness of your order execution arrangements. This should come as no surprise. As part of the FCA’s 2014 Thematic Review TR14/13, the U.K. regulator expressed its withering assessment that “most firms lacked effective monitoring capability to identify best execution failures or poor client outcomes,” a requirement of MiFID II. The FCA went on to demand that “firms must take action to ensure that their monitoring is helping to deliver best execution for clients on a consistent basis.”
In short, the requirement to implement regular, effective monitoring is clear and unambiguous. The more pressing question, then, becomes one of approach—how to ensure that the monitoring process deployed will meet MiFID II’s standard of taking “all sufficient steps to obtain … the best possible result for their clients.” To address these new higher standards, an acceptable monitoring process should combine at least the following aspects: • It should employ data-driven quantitative approaches • The data should be sufficiently clean and structured in a way that readily allows for analysis and consolidation • The data collected should be unbiased, allowing for direct comparisons of execution quality • The monitoring process should be ongoing and repeated regularly
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26 | INSIGHT
“One approach to helping meet the monitoring challenge involves decoupling the selection of an execution strategy from the selection of a broker.” Using a data-driven selection tool One approach to helping meet the monitoring challenge involves decoupling the selection of an execution strategy from the selection of a broker. Under this method, a buy-side trader would retain focus on strategy selection (VWAP, VP, IS, etc.) while the choice of execution broker is determined by preconfigured allocation percentages. Because the allocation a broker receives is driven by the broker’s target percentage of orders (and not other considerations), the execution sample should be less prone to bias in its composition. Assuming enough flow is sent, all brokers should receive a representative sample of orders spanning different liquidity profiles, volatility groups, spreads, industry sectors and countries. This would provide a better foundation for comparing execution quality among brokers. A data-driven broker selection tool is designed to be the infrastructure component that manages the transmission of orders to execution brokers in line with allocation targets. It consists of a database of historical order allocations and fills, a network providing connectivity to execution brokers, and the algorithm for determining to which broker a new order will be sent. Additionally, by serving as a centralised hub through which order executions flow, this tool naturally functions as a repository for collecting the resulting execution data in a standardised format. In the context of ITG’s data-driven broker selection tool, Algo Wheel, the allocation algorithm is driven
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exclusively by percentage targets explicitly set by the investment manager (e.g., 10% to Broker A, 8% to Broker B, etc.) These targets can be updated at any time, and it is up to investment managers to decide how often they wish to analyse execution performance and potentially update broker allocations within the algorithm. A data-driven broker selection tool is not necessarily touted as a turnkey solution to automate and analyse all execution performed by an investment manager. Different orders require different levels of attention. In the case of illiquid securities or difficult markets, taking “all sufficient steps” may require a much more hands-on approach to order execution. Instead, the selection tool is commonly used to assess the quality of execution for orders that do not require the careful attention of the buy-side trader. Depending on factors such as portfolio concentration, institutional versus retail client base, investment style and inflow/redemption activity, the proportion of orders that fit the mold for a selection tool will vary. For some managers, appropriate orders will account for a small proportion of orders and the tool may be of limited benefit. However, for managers whose daily flows significantly feature uncomplicated orders, the broker selection tool potentially delivers better workflow efficiency and execution monitoring. Moreover, its implementation demonstrates a process-driven, quantitative approach to execution performance measurement. Judging from the language surrounding MiFID II, that is something the industry can expect regulators to focus on beginning 3 January, 2018.
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Transforming Legacy Systems By Jay Boyd, Application Services Technology Officer, Invesco
Implementing large-scale systems programmes requires commitment and discipline at all stages of the transformation process as asset managers aim to take advantage of new technologies. The asset management industry is at a crossroads. It is facing several external factors that are causing many firms to reassess their operating models. New financial technology is providing many exciting opportunities for firms to expand their capabilities, but it is going to be through the transformation of their legacy systems and processes that they will achieve the leverage they are looking for in preparation for the future. The transformation of legacy systems and processes are typically large, expensive programmes that touch many parts of the organisation. They usually involve changing a substantial, end-toend process that has been in place for many years, whose scope is not fully known and whose architects are often no longer available.
There are two primary objectives: First, introduce new systems and processes and achieve all of the stated upfront goals. Second, replace the hidden cottage industry processes that have been established over the years on top of the legacy systems. These are usually undocumented, opaque, and their scale and scope are unclear. There are many components to establishing and completing a large-scale transformation programme, but six are critical: • Clear vision • Executive sponsorship • Well-defined road map • Programme leadership • Planning • Strong execution Clear vision It all begins with the vision. If a vision cannot be executed, it is nothing more than fantasy, therefore it should be aspirational, but also achievable. It should
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28 | OPINION
“They usually involve changing a substantial, end-to-end process that has been in place for many years, whose scope is not fully known and whose architects are often no longer available.” be put together in such a way that everyone in the firm understands what it is and why it is important. Large-scale programmes take time, resources and money. They often build a foundation for future growth and scale, but can also be unpopular since they are not necessarily the “latest and greatest” hot items. It can feel like a home repair to some – necessary but what does it get me? This makes it easy for people to question the programme. It is often perceived as being in the way of what they want or believe is important. Staff need to see that it is more than repairing your home, that it is vital for growth. Executive sponsorship Executive buy-in is absolutely key to the success of a programme. Executive support ensures that it will have the resources, continued prioritisation, air-cover, and the necessary cheerleading. An executive sponsor should be spreading the benefits of the programme and counter nay-sayers sceptical of the programme’s value, fearful of the changes the it will bring or even jealous that it could derail one of their own priorities. Sponsorship can also help ensure that the true cost estimates are transparent, and not being glossed over. Road map Once you have your vision, you begin to build your road map. The vision is “where you want to go” and the road map is “how you are going to get there.”
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Jay Boyd, Application Services Technology Officer, Invesco It should define the approximate timeframe to deliver the entire body of work, each discrete project and its timeframe, the primary deliverables for each project and the value or benefit derived from each project. You are looking to deliver value in incremental pieces that make sense, without waiting until the big bang at the end of the programme. Solution architects are required to design the work appropriately, and provide insight and direction on how to integrate the different pieces as they emerge. Programme leadership When a firm decides to take on a large-scale initiative, it must put into place a management and resource structure that will get the job done as fast and as efficiently as possible. Create the leadership team of the programme by carving out the best people within the firm for the job, and then making this their full-time job. While the firm may find it necessary to bring in external expertise to help with various aspects of the programme, they should be putting as many of their own resources in leadership positions as possible. Where external leadership is necessary, it is best to put “two-in-a-box” so that someone from the organisation can learn new skills from external experts. This is a both an investment in the firm and an investment in one of its key leaders.
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“You are looking to deliver value in incremental pieces that make sense, without waiting until the big bang at the end of the programme.”
The programme director must be someone who is capable of making decisions and empowered to make them. They must be someone who can sell the vision of the programme, inspire team members about its value, and initiate and drive through change. The programme manager is another key position. They must be willing to help moderate disputes, resolve design issues, and ensure consistent communications across the programme. Often this role is the ‘glue’ the pulls the entire program together. Planning The planning phase itself is typically a time-boxed period when requirements, timeframes and resources are defined. Here, you should identify many of the unknowns of the vison and road map phases. You will write any necessary RFPs, evaluate the responses and make vendor selections, plan the execution phase and build materials for the project governance process. Execution There are three crucial issues to highlight: First, an understanding that plans can go wrong. The programme needs to be flexible enough to adapt and adjust. Implementation will take longer than expected and be more complex than anticipated. A balance must be found between scope expansion and scope control to accommodate the likelihood that the plan will change. Providing the programme with a limited contingency bucket can be an effective way to control reasonable scope expansion for the unknowns, while proper oversight from a programme steering committee can provide a cap for scope control.
Second, is decision making. Mangers must have the ability to make decisions with less than perfect information, make decisions that are best for the programme, and be able to pivot if the decision is not working as expected. Third, is having a robust change-management plan in place. Change management is how the programme will engage the business, where new processes are established, training is conducted, manuals written and test plans and cases devised.
“Large-scale programmes take time, resources and money, but while they often build a foundation for future growth and scale, they can also be unpopular.” Conclusion These elements may seem to be basic requirements to ensure a successful large-scale transformative programme, but they are often overlooked or not sustained. There is also one more critical component. There should be assessment points that allow for decisions to be made to either continue to the next phase of the programme, pivot it or if necessary discontinue the programme. This prevents the firm from having to make a single big commitment, and reassures stakeholders that there are controls in place that deal with the unexpected.
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30 | OPINION
How Much Security Is Enough? By Mark Vos, Chief Information Security Officer, Iress Cybersecurity has become a significant and increasing cost of doing business, but by striving for a “best fit” solution, it can be a business enabler. As a security and risk professional, I am often asked: “how much security is enough?” It seems a simple enough question, but it manages to trip up so many people. So what is the right answer? Is there a nice sound bite that one can give? Well, not really. In a dynamic environment of increasing security threats, firms have a big challenge on their hands to ensure they continue to: • Get their security governance structure right and clearly articulate roles and responsibilities • Obtain executive level buy-in and sponsorship
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• Base security investments on risk • Use security as a business enabler, not just a cost • Establish a security awareness programme • Continue to assess and adjust their security capabilities to changes in the environment It is certainly complicated. Barely a day passes without a press report relating to a security issue, and all financial services organisations now face greater security threats to their people, assets and operations from such diverse sources as: • Terrorism • Fraud and financial crime (both internal and external) • Organised crime, including money laundering • Information security threats from hackers and computer viruses
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The best fit model It is becoming more common for organisations to strive for a “best fit” solution as opposed to obtaining “best practice” in every security matter. It’s about being commercial and pragmatic in the way security is managed. Conforming to best practice is an extremely expensive exercise that does not necessarily deliver business benefits equal to or greater than the expenditure required to get there. A best fit model is about understanding what the risks are, and applying the most appropriate risk mitigation strategy to reduce them, as opposed to applying the best practice processes regardless of the associated risk.
Mark Vos, Chief Information Security Officer, Iress The level of complexity involved in managing such a diversity of threats means that cybersecurity has become a significant and increasing cost of doing business. The challenge is to develop a holistic approach to security management that responds to each of these demands in a coordinated, cost effective, and efficient way. Where are firms focusing their InfoSec investment? Our larger clients are spending millions in transforming their security functions and improving their security management practices across a range of areas, including: • Risk management • Information security • Fraud and investigations • Forensics • Anti-money laundering • Physical security • Business continuity • Crisis management. For many, this investment represents a significant shift away from the manner in which they have traditionally managed security. It is also placing huge demands on their security teams to develop new management skills, and places demand on their partners and service providers.
“The level of complexity involved in managing diversity of threats means that cybersecurity has become a significant and increasing cost of doing business.” So how much security is enough? A good place to start is to identify the top risks your business is likely to face and find commercially pragmatic solutions that remediate those risks. And that’s exactly what firms must be focused on doing right now Global-scale cyberattacks such as the Wannacry ransomware attack and, more recently, the huge malware attack that brought chaos to the Ukraine before spreading internationally, can inflict real damage on an organisation, both in its ability to function and its reputation. They are also a big reminder of the risks we all face - but let’s keep things in perspective. The reality is, you’re far more likely to suffer an internal security breach than from an external threat. According to a recent PWC report, half of the worst cybersecurity incidents were due to inadvertent human error.
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32 | OPINION
When it comes to information security, people and process are critical. You can have the best patch management practices in the world, but if your employees aren’t being vigilant, you’re wide open to many different types of attack. The bottom line is that your company culture is what will ultimately define your security posture and its effectiveness. What are you up against? However good your defences, you need to work on the assumption that malware will get through from time-to-time. At that point it will be your diligence and awareness that makes the difference. So what sort of nasties are you up against? • Bots and Zombies • Ransomware • Rootkits • Spyware • Trojan horse • Virus What these do is exploit vulnerabilities – either those of a system or an individual. Every 40 seconds, a company is hit with ransomware (in the first quarter, 2016 it was every two minutes). By far the most common delivery vehicles for ransomware are attachments sent directly to your users in increasingly believable emails from seemingly trustworthy sources. A review by IBM Security found that the number of ransomware-infected emails sent this year has already increased 6,000% compared with 2016. Cyber criminals are looking for an easy target and it’s your employees they are more likely to target, rather than your software. Humans have now moved ahead of machines as the top target for cyber criminals. Awareness and breaking bad habits remain the biggest challenges when it comes to fighting phishing. A 2016 study on IT security infrastructure by the FriedrichAlexander University, reported that 78% of respondents knew about the risk of unknown links in emails, yet they click anyway! So what can you do? Don’t leave InfoSec to the IT department Ten years ago, the job title “Information Security Analyst” didn’t exist. Today, there is a genuine worldwide shortage of qualified and experienced
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InfoSec specialists. They are in high demand, and with good reason. As the cyber threat grows and evolves, so must your cyber defence resources. Three years ago, we set up a dedicated global information security team tasked with protecting our environment and those of our clients’. We recruited specialist subject matter experts who could educate others and keep up with ever-evolving cyber threats and techniques. The team was integrated into the business, not set apart as a traffic cop.
“A best fit model is about understanding what the risks are, and applying the most appropriate risk mitigation strategy to reduce them.” It’s their responsibility to perform and communicate information security within the business and make it everyone else’s responsibility too. It quickly became obvious that if we were going to do this successfully, we needed to take a client centric approach to everything we did. That meant: • Defining metrics of the effectiveness of information security and providing that to the board to get their buy-in on commensurate information security investment • Having a team that could influence colleagues and internal stakeholders • Communicating information security in a clear and effective manner • Focusing on the company culture, driving the importance of protecting client data, and other sensitive data Make your people your first line of defence Cyber security is an ongoing battle. Make your people your first line of defence by developing information security awareness and vigilance among your employees so that everyone has the right level of knowledge about security and feels responsible for it.
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A check-box training exercise is no longer enough. There must be a continued and concerted effort to bring about a real change in culture and behaviour. It is a big ask for InfoSec teams. Employees are more tech savvy than ever before, often finding it easier to use their own familiar devices, apps and programmes than your authorised solutions. So-called “shadow IT” and BYOD pose new risks and challenges for IT and InfoSec teams who must not only adapt to accommodate these new ways of working, acknowledging where there is a real business need for greater flexibility and ease of use, but at the same time protect the business. Be prepared to try different approaches to help the InfoSec message stick. 70% of millennials admit to bringing in outside devices into the work environment, against IT policies. 60% say they aren’t concerned about corporate security when they use personal apps instead of corporate apps. You have a challenge on your hands to find ever-more creative and impactful ways to communicate security messages to all of your internal stakeholders. You’ll need a range of tactics up your sleeve: • Regular internal communications – using all channels • Multi-media communications, such as videos, blogs • Promote and reward positive behaviour where people demonstrate “doing the right thing” in relation to information security • Put into every staff member’s business plans a measure and KPI in relation to information security • Have your CEO discuss the importance of information security to the company on a regular basis • Educate and build awareness in fun and engaging ways, such as gamification
than 1850 of them, not just the 12 that sit in the dedicated information security team.
“By far the most common delivery vehicles for ransomware are attachments sent directly to your users in increasingly believable emails from seemingly trustworthy sources.” Ultimately, the only thing protecting your business from becoming a cybercrime victim is your people, so layer your technology defences with a powerful human shield. Remain vigilant and continue to strengthen and evolve your security practices. As Einstein said, “We can’t solve problems by using the same kind of thinking we used when we created them.”
Layer your defences Our InfoSec team has more than quadrupled in size over the past 2 years, and now has 12 people dedicated to Information Security which is a reflection of the growing importance we place on cybersecurity and also a direct response to the growing threat level the financial services industry faces. In that time, we achieved the ISO/IEC 27001 security certification, the internationally-recognised best practice framework for managing information security. It should also be noted that our first line of defence is our people, more
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34 | OPINION
Enabling Best Execution
By Damian Bierman, Head of Asia-Pacific, Portware
Trading systems need to incorporate new configurations and capabilities to meet the best execution requirements of MiFID II. One of the most important themes of Markets in Financial Instruments Directive (MiFID) II is its “best execution” mandate. Investment firms must take all sufficient steps to obtain, when executing orders of any financial instrument, the best possible result for their clients. Best execution is focused on achieving the optimum outcome on a consistent basis, and not simply on attaining the best price available at a given time for an individual trade. Several factors must be considered, including explicit costs such as fees and commissions and implicit costs such as those tied to signalling risk. In addition, transaction speed, order size, the likelihood of execution in prevailing market conditions and the certainty of settlement must also be taken into account.
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Firms will be expected to show how they have incorporated each of these factors into their best execution procedures, and to support their conclusions with unbiased quantitative analysis, such as transaction cost analysis (TCA). This emphasis on achieving best execution, and the incorporation of so many elements in its demonstrable realisation, means that unsurprisingly the efficiency and accuracy of a firm’s trading system has assumed paramount importance in the countdown to MiFID II’s implementation in January 2018. Both buy- and sell-side firms will need to comply with the tougher regulations, and helping them meet those requirements continues to be priority for vendor suppliers. System upgrades Systems will have to be upgraded in at least two fundamentals ways. First, they will require new configurations in order to capture substantially more
OPINION | 35
interest (IOI) and comparing them with actual broker transaction closure. Moreover, visual enhancements can add greater immediate clarity by showing broker scores and by displaying specific IOI-related reports. Tick data can also be made available, which allows clients to measure execution prices against historical tick movements for performance measurements, such as interval volume weighted average price. In addition, allocation information can be stored in a data warehouse and made available for on-demand retrieval so performance at an account level can also be attributed.
Damian Bierman, Head of Asia-Pacific, Portware identifying data than before. These include trader details, legal entity identifier (LEI) configurations and codes that explain the reasons for individual trades. Order entry screens must also be enhanced to secure a variety of relevant data points necessary at the time of the transaction. Second, firms will need their trading systems to provide the tools and analysis capabilities that allow them to demonstrate compliance with objective TCA or other trade execution cost measurements. Broker analysis and scoring metrics, access to tick data, and even allocations will all become important for providing firms the level of granularity they need to ensure that their procedures and systems conform.
“The level of complexity involved in managing diversity of threats means that cybersecurity has become a significant and increasing cost of doing business.” Portware’s role is to help ensure that its clients are able to analyse and justify every decision that they make at each stage during the trade cycle. This means giving them access to data, organising it so it is easily auditable and providing the capability to adhere consistently to their best execution policies.
There are several ways vendors such as Portware can help institutions implement and maintain their best execution objectives. Broker analysis dashboards can rank counterparties’ performance by stock, sector, venue and algorithm, and also by order size and trade execution in specific market conditions. Relative performance can be gauged further by collating and storing indications of
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36 | OPINION
Different Flavours Of Self-Match Prevention By Vaibhav Sagar, Senior Technology Consultant, Open System Tech
Brokerages need to customise their EMS to avoid crossing orders with the MPIDs on external trading venues. One of the major compliance issues for broker dealer firms is to avoid crossing each other’s orders at a particular exchange. If both sides of the order are represented by the same market participant identifiers (MPID) and if this action results in a price movement the broker firm could face potential fines or even temporary suspension from trading for price manipulation. Although each individual desk internally crosses transactions, orders from two different desks with the same MPID can reach and cross on the exchange. To avoid these scenarios, exchanges and other external trading venues provide an option to enable Self-Match Prevention (SMP) across an MPID. This SMP can be enabled with several configurations, as described below: 1. Simply cancel a sitting passive order: If an incoming aggressive order will cause a selfmatch with an existing passive order, the passive
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live order is cancelled first and then the new aggressive order will participate in the market and any open quantity will sit in the market. 2. Trade through the market and cancel a sitting passive order: If an incoming aggressive order will cause a self-match with an existing passive order, the aggressive order will first participate with other entities in the market and any open quantity will sit in the market and the passive live order will be cancelled. 3. Reject an incoming (taking) order: If an incoming aggressive order will cause a self-match with an existing passive order, then the incoming aggressive order will be rejected while the passive order will continue to be live in the market. 4. Trade through the market and self-match the rest: If an incoming aggressive order will cause a self-match with an existing passive order, then the aggressive order will first execute with other live orders in the market and only the remaining
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trader has to continuously keep track of when the other aggressive crossable order can be resent for execution. This again produces a scenario where positions cannot be squared off instantly resulting in positional risk. In configuration four, since the orders can cross with each other, the challenge is how these orders which are marked as “internal trades” are reported for clearing. If these self-crossed internal trades are not reported for trade clearing, then the broker dealer needs to filter out these internal executions so as to avoid trade brakes.
Vaibhav Sagar, Senior Technology Consultant, Open System Tech
quantity will be self-matched and this execution is marked as an “internal trade”. Also, the remaining orders will remain live in the market. This is the best of all solutions since it avoids cancellation of any live orders and hence creates fewer order management system (OMS), and position and trade risk complexities.
“The best solution avoids cancellation of any live orders and hence creates fewer OMS, and position and trade risk complexities.” In all cases, additional custom development in the execution management system (EMS) is required to handle self-cross executions.
However, the choice depends upon the flavour of SMP implemented by the destination exchange and also the flavour the client prefers. Each implementation has its own set of challenges. In configurations one and two, which involves the cancellation of an active live order, there are OMS and position risk issues. Since the order is cancelled by the exchange, the OMS has to have a stated provision or else manual intervention is required for the order to be resent to the exchange at a later time. Until then, the cancelled order results in a position on the book and hence is an open risk. In configuration three, where all new crossable incoming orders are rejected, the OMS or a human
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ASIA | 39
Catalysts For Change:
HKEX Hosting Services Ecosystem Forum 2017
By Rupert Walker, Managing Editor, GlobalTrading New products, the extension of China Connect and service upgrades are strengthening HKEX’s role as a leading financial hub. Hong Kong Exchanges and Clearing (HKEX) continues to develop its markets infrastructure and introduce new products across asset classes to meet the requirements of investors and issuers. In addition, it is consolidating its position as the global offshore renminbi (CNH) hub, and facilitating further trading linkages with Mainland China through an extension of the Connect programme. HKEX’s Data Centre plays a key role for all market participants through the range and quality of its technology, with around a half of cash equities and derivatives trading now transacted through its colocation facilities, said Jonathan Leung, Senior Vice President and Head of Hosting Services at HKEX, to delegates at the HKEX Hosting Services Ecosystem Forum 2017 held on 25 May. The hosting part of the Data Centre’s capabilities include tier 4 data centre specification, low latency direct market feeds for cash and derivatives trading, an interactive ecosystem environment supporting trading, broad telecommunications carrier access and flexible power and space packages offering both racked and caged environments.
Prudent technology investment Indeed, HKEX has a long history of technological innovation, although it is always cautious about introducing unproven systems, preferring a prudent approach, according to Richard Leung, Deputy Group CIO and Chief Technology Officer at HKEX. It first created an electronic central clearing and settlement system in 1992 and in the following year set up a first-generation order matching and execution platform for cash transactions, extending it to derivatives in 1995. HKEX is upgrading its platform to deploy the latest open systems technology, but with a minimum of disruption for users. In 2011, HKEX Orion, a major technology upgrade programme that enabled HKEX to offer hosting services, was launched, and now the next generation systems are being developed and deployed. HKEX is naturally examining fintech innovations, but is aware of their risks so is wary about adopting them, said Leung. Distributed ledgers might improve post-trade operations and HKEX is reviewing its possibilities, but is concerned about the security risks of selecting a blockchain system when there are competing designs and encryptions available that could make its choice redundant. There are several applications of the Cloud that exchanges could use and HKEX introduced virtualisation six years
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40 | ASIA
ago, but there are data sovereignty concerns. Big data is actually quite easy to collect, but acquiring and applying the right analytical tools is the challenge. There is no first mover advantage from adopting these new technologies in the financial market infrastructure space; instead there are dangers from moving too quickly, argued Leung. Retaining customers’ trust and ensuring data security must be HKEX’s priority, he added. Nevertheless, HKEX is continuing to expand the scope and quality of its hosting services as an ecosystem for participants, rather than as a commercial enterprise. HKEX hosted as of August 2017 a historical high of 592 trading participants on its securities market. The momentum of southbound Stock Connect trading has increased significantly. Products such as Exchange Traded Funds (ETFs) have added to market turnover, and HKEX is keen to further promote Leveraged and Inverse Products (L&I Products). Meanwhile the average daily turnover of securities market turnover for the first seven months of 2017 was HK$77.4 billion ($9.9 billion), an increase of 16% compared with HK$66.7 billion for the same period last year. New products and services The roadmap for 2017/2018 includes the potential launch of the “Next Generation” Orion Trading Platform for the securities market by at the end of this year, and continued development of the Stock Connect schemes to potentially include more products, said Kenneth Kok, Head of Cash Trading, Markets Division at HKEX.
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“HKEX’s Data Centre plays a key role for all market participants through the range and quality of its technology, with around a half of cash equities and derivatives trading now transacted through its co-location facilities.” The recently implemented phase 2 of the closing auction session (CAS) includes regulated short-selling. For those participants concerned about the risks, it is important to note that CAS phase 1, launched in July 2016, caused no increase in price volatility, despite warnings by critics, noted Kok. Instead, it led to a substantial take-up by institutional investors allowed to execute trades at closing prices. Julien Martin, Head of FIC Product Development, Market Development at HKEX explained three main pillars of HKEX’s strategy. First, the growth of the cash market through Mainland and international investors and the implementation of Bond Connect; second, the development of exchange-traded rates and credit derivatives and of deliverable futures; and third, the expansion of over-the-counter (OTC) clearing capabilities, especially for renminbi, he said. Bond Connect, which was launched in July, strengthens Hong Kong’s role in offshore renminbi, making the territory an even more relevant international financial centre. The initial focus of Bond Connect is on northbound investment into Mainland China’s vast domestic bond market. The objective is to minimise inconvenience for international investors through cooperation with the Mainland China’s foreign exchange authorities, the implementation of nominee structure, no quotas and
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eligibility similar to the existing investor access to interbank bond market. The onshore Rmb10 trillion interbank bond market is set to overtake Japan as the world’s second largest bond market within 10 years, yet foreign investors own less than 2% of it. The People’s Bank of China has a target of 10-15% foreign ownership, and there are strong policy incentives, such as a stable renminbi (now benchmarked against a basket of 24 currencies) and liquid short-dated bonds with attractive yields.
“The initial focus of Bond Connect is on northbound investment into Mainland China’s vast domestic bond market.” HKEX is gaining market share in offshore renminbi from banks, because of restrictions and costs. The USD/CNH futures contract on the exchange is one of the most active in the world, traded by numerous clients and supported by eight market makers. Plans are being prepared for it to trade overnight, and three new indices have been introduced in partnership with Thomson Reuters. In addition, HKEX was the first exchange to launch physical USD/CNH options. Benefits of Hong Kong ETFs The global ETF market eclipsed $4 trillion in assets in the second quarter of this year and is expected to grow to over $6 trillion in the next five years. ETFs have grown enormously in popularity among long- and short-term retail and institutional investors attracted by their liquidity, quick access and cost efficiency. While Asia Pacific’s ETF market is in the earlier stages of development, Hong Kong has been a leader since 1999. Asia-based investors are becoming increasingly aware of the diversity and the tax advantages of ETFs
listed in Hong Kong, but more education is needed, said Brian Roberts, Head of ETPs, Market Development at HKEX. ETFs make up between 6 and 7% of HKEX’s average daily cash market turnover, which is impressive considering ETFs make up less than 2% of Hong Kong’s equity market capitalisation. As more institutional and retail investors become aware of the advantages of ETFs, HKEX could experience further growth, according to Roberts. Retail investor participation in ETFs is around 10% compared with 15%-to-20% of the cash market, so their involvement in ETFs should grow as they learn more about their advantages. Interest in ETFs and the size of the market are growing in Asia, not least because of the tax benefits of Hong Kong-listed products, agreed Sean Cunningham, head of capital markets for iShares and index investing APAC
“Interest in ETFs and the size of the market are growing in Asia, not least because of the tax benefits of Hong Kong-listed products..” at Blackrock. Clients have gone to the US and Europe for liquidity, but there has been an increase in the number of Hong Kong products that overseas investors can trade in their own time zone, he said. The current HKEX ETF strategy has three principal components. HKEX aims to encourage product diversity through expanding ETF and L&I listings; improve market access, delivery and liquidity; and focus on regional and international education about the tax efficiency and other benefits of Hong Kong-listed ETFs. Hong Kong should grow its share of global ETF listings and trading and firmly establish itself as the Asia hub. It has a supportive ecosystem made up of sophisticated
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investors, ancillary financial services and, of course, access to Mainland China. China Connect expands The Connect programmes are continuing to evolve in order to attract investors. Although the Connect scheme is a closed loop for purchases and sales of securities, repatriation of northbound capital is much easier than from investments made through the Qualified Foreign Institutional Investor and other schemes, because there is no lock-in period, said Christopher Hui, Head of Project Management at HKEX. Moreover, since Shenzhen Stock Connect there are no longer aggregate quotas, and planned enhancements include the introduction of real-time delivery versus payment (RDVP) settlement, which will help address concerns about potential counterparty risk. In the future, Mainland insurance companies are likely to be substantial southbound investors in order to diversify portfolios, find liquidity and enhance yields, noted Vernon Willis at Haitong Securities in a panel discussion chaired by Jessica Morrison, director, equity trading at Deutsche Bank. Blackrock’s Cunningham pointed out that trade execution reliability in A-shares is essential, perhaps especially for index houses. He and his fellow speakers agreed that the inclusion of A-Shares with the MSCI’s global emerging market index would be major boost for the schemes – and which subsequently occurred in June. Chris Lee, Senior Vice President, Client and Marketing Services, Market Development at HKEX pointed out that there have been several changes to Connect since the scheme was first launched and noted RDVP settlement will be available by the end of the year. Already, HKEX has improved the comfort factor for beneficial ownership and there has been considerable success working with the regulators of Irish and Luxembourg funds. Nick Ronalds, managing director, equities at ASIFMA agreed that RDVP is a very significant development, especially for UCITs as European regulators had expressed graves concerns about counterparty risk. But, there are other problems, such as holiday trading and meeting T+0 deadlines for CNH settlement.
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According to Andy Maynard, head of Asia Pacific execution services at HSBC, the CNH’s lack of liquidity is a big concern and a limiting factor, causing trading ebbs and flows. Pre-funding has become difficult and the renminbi was very volatile during the past year. Global long-only emerging market funds dominate northbound flows, but even they don’t consider Mainland China a great investment prospect at present. It’s not so much the restrictions within the Connect programme or even the index status of A-shares that account for muted volumes, but rather that the strategic investment case is not compelling.
“HKEX has a long history of technological innovation, although it is always cautious about introducing unproven systems, preferring a prudent approach.” Nevertheless, the Connect schemes are expanding Hong Kong’s role as a gateway to Mainland China, and HKEX is keen to strengthen its position as a leading global financial centre.
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Unplugging Alpha In Indian Markets
By Jyoti Rai, Associate Director, Business Development & Advocacy, Edelweiss Prime Brokerage Services The investment case for India is compelling, overseas access is becoming easier, capital markets are developing rapidly and domestic financial firms are adopting the latest technologies.
including manufacturing, oil and steel, foreign direct investment was encouraged and important regulators such as the Securities and Exchange Board of India (Sebi) and the Insurance Regulatory and Development Authority (Irda) were established.
Today, India is witnessing a paradigm shift owing to a convergence of steadfast vision, inclusive economic growth and deep policy reforms that are intended to benefit all Indians. In spite of global headwinds, India’s GDP rate has been sustainable with the government achieving a fine balance between fiscal prudence and growth.
Economic growth was volatile during this transition phase, but it was a prelude to spectacular annual growth rates from 2004, reaching over 9% a year towards the end of the decade. Foreign portfolio investment flowed into the country’s expanding capital markets and the rupee strengthened.
Phases of reform During a period of market liberalization in the early nineties, India introduced a raft of reforms that effectively ended the license raj, the expression for the serpentine assortment of bureaucratic regulations that often stifled business and enterprise. Private companies were allowed to enter key sectors,
The 2008 global financial crisis revealed that this hyper-expansion was unsustainable and fragile, and a period of steady consolidation was nurtured from 2008 to 2013. Prudent risk management insulated India from the worst of the fallout from the worldwide recession, but not from some domestic financial scandals.
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“Investment rules are now clearer, and overseas funds are able to tap into India’s increasingly sophisticated capital markets more easily than before.” Jyoti Rai, Associate Director, Business Development & Advocacy, Edelweiss Prime Brokerage Services
High profile exits from India by Fidelity and Walmart could have shaken the confidence of policy makers committed to a careful and circumspect reform, but they remained firm and introduced important regulatory frameworks such as the General Anti Avoidance Rule and the BEPS Report. Meanwhile, there has been significant reform and development across all sectors of the economy, including telecommunications, banking, asset management, aviation, fast-moving consumer goods and hospitality, as well as a vibrant technology sector. Investor access to India growth In a major restructuring three years ago, Sebi introduced the Foreign Portfolio Investment (FPI) regime that categorised non-resident investors into three groups determined by their risk profiles and know-your-client requirements. Registration procedures were also made simpler. We at Edelweiss, have been seeing an influx of FPI registrations coming through during the past three years. Interestingly, the number of FPI registrations has gone up exponentially in the last calendar year, climbing to a high of over 8,500. This saw a further spike after the recent prohibition on offshore derivative instruments on Indian derivatives contracts. Building on the “ease of access” syntax, we
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have ensured that a new FPI does not have to approach multiple service providers – Edelweiss India is an authorized custodian and conducts the required KYC to issue new FPI certificates, in addition to helping apply for India tax ID, trade and execution set-up and futures clearing. Edelweiss has set-up dedicated KYC and on-boarding teams at our offshore locations in Asia, London and New York as well, which has reduced the FPI set-up and Go-Live timelines. COOs across fund houses have appreciated this “one-stop-shop” approach along with dedicated hand-holding for the nuanced requirements of getting an FPI ID for India. Investment rules are now clearer, and overseas funds are able to tap into India’s increasingly sophisticated capital markets more easily than before. The average daily trading volume of the National Stock Exchange and Bombay Stock Exchange combined is $3.5 billion and daily volume of the top five single futures contracts is between $75 million and $80 million. Emerging trends in India’s financial markets include: • Domestic savings are moving to equities • Investments in mutual funds are rising steadily, growing fourfold in the past five years. • Corporate bond markets are opening up and becoming exchange traded • Currency markets are more accessible, with offshore participation allowed • New products such as REITs and InVITs offer great opportunities • Distressed assets and the private debt market are growing rapidly
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• Markets are supported by robust technology and infrastructure Direct market access Indian financial services companies such the Edelweiss Group provide a range of high technology products and services to a large and diversified client base that includes corporations, institutions and individuals. Edelweiss’s offerings span multiple asset classes and consumer segments across domestic and global geographies. As one of the country’s leading institutional equities businesses, Edelweiss delivers seamless execution and innovative research products to more than 300 active institutional investors. It is a pioneer in algorithmic trading in India and offers a complete suite of proprietary, exchange approved algorithms, tailored to suit the Indian markets. Edelweiss offers direct market access (DMA) and FIX connectivity, catering to over 200 clients and also provides Direct Strategy Access (DSA) services with both one-touch and no-touch DSA options. Moreover, Edelweiss-DMA has a working relationship with major FIX connectivity providers that enables easy and quick on-boarding of clients with the platform. In addition, Edelweiss offers ultra-low latency DMA to high frequency trading clients.
“Domestic financial firms with ambition are prepared to facilitate overseas investment through the adoption of the latest technologies.” upgraded with the latest certified hardware and software designs and coding techniques. Production support and monitoring is also automated. The investment case for India is clearly compelling and policy makers are keen to ease foreign access to the country’s high potential capital markets in a steady and sober fashion. Meanwhile, domestic financial firms with ambition are prepared to facilitate overseas investment through the adoption of the latest technologies.
The system is tested robotically for around one million cases and conditions and is continually
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A Renewed Focus On Innovation
By Rupert Walker, Managing Editor, GlobalTrading
Technology and regulation are re-shaping the trading industry in a shifting geopolitical environment, according to speakers at the 15th Asia Pacific Trading Summit, 2017. The trading industry is facing many challenges as it prepares for the implementation of important regulatory changes and adapts to rapid advances in technology. In normal circumstances, the tasks confronting all industry participants would be substantial, but recent shifts in the structure of markets and investor behaviour as well as political uncertainties compound the difficulties. Yet, the mood was upbeat at the 15th Asia Pacific Trading Summit (2017) organized by the FIX Trading Community in Hong Kong on 18 May, with speakers and delegates at the region’s largest one-day electronic trading event invigorated by the opportunities offered by regulatory change and inspired by a future shaped with innovative technologies, including artificial intelligence (AI) and machine learning.
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“While start-up disruption in many ways is over-hyped, this technology, over time, will revolutionize not only investment banking and trading, but how the economy operates. The [financial] industry is at an inflexion point,” said Larry Tabb, founder and research chairman of TABB Group, in an opening keynote speech. Tabb also examined how several factors including the state of the markets, regulation and uncertainty about President Trump are affecting and, in some ways, hindering a clear development of the trading environment. In recent years, markets in leading economies have been distorted by post-financial crisis asset purchases by central banks and a host of reactive proscriptions rigorously enforced. Yet, in the US at least, the trajectory of regulatory reform is uncertain since the election of President Trump, with market participants receiving mixed-messages: on the one hand anticipating a roll-back of major parts of the 2010 Dodd-Frank legislation, and on the other, bemused by
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“A progression of liquidity provider to buy-side trading shops is sensible given the risk tolerance and regulatory environment facing the traditional banks and brokerages.” the lack of clear direction and tangible action by the new administration. Of course, the economic and geopolitical shape of the world is in flux too. New fulcrums and centres of power – in particular the continued rise of China – are determining where financial industries concentrate their resources and adjust to new challenges. The post-lunch keynote speech was delivered by MSCI-veteran Chris Ryan, now chairman and CEO of First Capital Partners and co-founder of Digital Finance Media, who was able to avoid having to find ways to deflect the usual queries about the MSCI’s plans to include China A-shares in its benchmark indices (which finally took place a few days later anyway), and instead concentrate on how China’s markets will drive Asia’s investment agenda. “China’s markets have just begun to flex their muscles: better financial infrastructure, better access and
“Active fund management strategies have been constrained by an increase in stock de-listings, a significant shift to passive funds among investors and a substantial decline in stock market volatility.” international diplomacy and trade will bring us all many more opportunities,” said Ryan. Regulatory imperatives Meanwhile, the financial industry throughout the world is focussed on the implementation of the Markets in Financial Instruments Directive (MiFID) II in January 2018, which will likely lead to the growth of multi-lateral trading systems and banks’ systematic internalisers at the expense of traditional exchanges as both buy- and sell-side firms try to meet their obligations to achieve best trade execution through access to all sources of potential liquidity as well as cutting costs. Transparency, liquidity and tight dealing spreads are indispensable for all asset classes, from ETFs to foreign exchange, noted Wai Kin Cahn, at XTX Markets Arjen Gaasbeek at Flow Traders Asia. In fact, a “progression of liquidity provider to buy-side trading shops is sensible given the risk tolerance and regulatory environment facing the traditional banks and brokerages,” argued Matthew Hassan, head of platform sales at Nomura Securities. The European legislation will also have other farreaching effects on the industry too, especially a reduction in research budgets as the buy-side unbundles its research consumption from trade commissions. According to Benjamin Quinlan, CEO and managing partner at Quinlan & Associates, MiFID II’s unbundling
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regulations are set to fundamentally disrupt the global investment research industry as we know it. Yet, it is also “an opportunity to re-invent research models and continue to increase focus on trading services,” said Stephane Loiseau, managing director, head of cash equities and global execution services at Société Générale. In addition, active fund management strategies have been constrained by an increase in stock de-listings, a significant shift to passive funds among investors and a substantial decline in stock market volatility. These trends have been caused by combination of the burdens imposed from regulation, sustained bull markets fuelled by central bank liquidity and the rising impact of new financial technology. Humans or machines A consequence has been the reappearance of a question that often recurs during periods of instability, and which was explicitly posed at the Hong Kong event, namely: Is innovation back in fashion again? Few speakers disagreed with Edward Mangles, regional director, Asia Pacific, FIX Trading Community and director of GlobalTrading who observed that today “innovation is changing people’s minds”. In particular, advances in artificial intelligence and machine learning are gaining traction in the financial industry. “Finance, just like any IT intensive industry, bears the greatest risk of being disrupted by AI,” argued Gerardo Salandra, CEO and founder and Rocketbots, while Eugene Kanevsky, global head of electronic trading at CLSA pointed out that AI is at the core of a new generation of agency algorithms. However, it is important to identify exactly how these new technologies will have the greatest impact and value. As Kris Longmore, co-founder and head of quantitative research at Quantify noted in a presentation, if machine learning is the engine, then data is the fuel that drives it. “Machine learning is a great way to extract new structured data sets from unstructured content…New financial data is arising from text mining, transactions and analysis, and the internet of things,” agreed Stephen Malinak, global head of persistent analytics and data science, financial & risk division at Thomson Reuters.
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“Machine learning is a great way to extract new structured data sets from unstructured content.” Whether or not the adoption of more sophisticated technologies in the financial industry will eventually cause the redundancy of human agency in the trading process is debatable – and, naturally, a sensitive issue for market players. Samir Rath, CEO and founder of Blue Pool reckoned that “machine intelligence will turbocharge humans not replace them”, but Francis So, co-chair of the Asia Pacific Steering Committee, FIX Trading Community and head of trading Asia, BNP Paribas Dealing Services went further. “The trading desk will be run by technologists and engineers in 15 years’ time,” he said. However, there were also more circumspect, if not sceptical voices too amid the prophets of radical change. Marcus Consolini, managing director of corporate acquisitions at Odyssey Capital Group spoke for several delegates, especially those with long experience in the industry. “The death of the sales-trader never happened despite predictions to the contrary. We will either adopt disruptive technology into the trading environment or we will continue to be driven by regulation and the same slow change of the past 15 years,” he said.
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Trade Automation: Panacea Or Placebo Write-up by Rupert Walker, Managing Editor, GlobalTrading Automation throughout the trading process is increasing rapidly, but there are roles for human agency, according to participants at a roundtable discussion in New York City. Trade automation continues to be driven by regulatory requirements for best execution and stimulated by the rapid development of new technologies. It can help remove human bias, enhance surveillance, and explain trade execution in a systematic way and benchmark its performance. Eventually artificial intelligence and machine learning will likely further reduce the role of human agency in the trade process, but now there is still demand for staff with quantitative skills, managerial expertise and even personal networks and market knowledge built on experience. At its best, automation is about solving problems for clients, increasing trade execution efficiency and achieving scalability, agreed panellists at an Itivitisponsored roundtable discussion hosted by IEX at its office in the World Trade Center, Manhattan on 27 June. One panellist recounted an anecdote from an electronic trading conference a few years ago when a speaker, with tongue in cheek (perhaps) predicted that soon dealing desks would be fully automated - and protected from meddlesome humans by a guard dog.
However, if automation goes wrong, problems can grow exponentially without human monitoring and override capability. In fact, financial firms have learned from experiences a decade ago and put in controls concurrent with technology installation since 2008, and the industry is now generally a safer place. Third parties can be a better, more cost-efficient option for trade surveillance functions, such as identifying spoofing and front running, and making control adjustments. A lot of trading surveillance is already automated, but patterns are changing and bad behaviour is becoming more heinous and difficult to identify. In some markets, often the best that can be done is merely to flag a signal that a trader might be being spoofed or layered. Technology transfer Automation is well-established in developed equities markets, and is increasingly deployed in the operational processes of passive funds to match indexes and reduce tracking errors. Algorithms are sufficiently different and can execute diverse strategies, which ensures trading is not homogenous and one-directional – at least in normal market conditions. For instance, smaller fund management firms often tend to be very active with distinctive strategies implemented by their own homegrown algorithms.
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Dealing desks, especially at large asset managers, can tailor their trading strategies to match the diverse styles, such as momentum or value-driven, of their portfolio managers and automate the processes. Regulation increasingly requires buy- and sell-side firms to explain and justify execution, especially outlier trades, in a systematic fashion. One consequence of greater compliance costs in illiquid transactions might be to force some firms out of business.
consistent channels to access it. Too often data quality is compromised and inadequate, which should prompt vendor suppliers to gain an edge over competitors if they can provide reliable sources and feeds. Moreover, cybersecurity and lax controls are a perennial problem.
Banks, fund managers and vendors are applying similar technologies to other asset classes, including fixed income and foreign exchange, but the transfer is far from easy. Markets have their own idiosyncrasies, levels of liquidity and dealing practices; fixed income, in particular, suffers from sparse data.
Besides, outsourcing data quality carries inherent risks because it implies extending complete trust to an external party and surrendering control over a vital part the automated system.
Many banks believe that they can differentiate themselves with clients by retaining a proprietary data management capability.
Data integrity Algorithms are only as good as their inputs, and sometimes a human is needed to identify and explain why an outcome is wrong, that is, to validate the data.
Machines and humans On a practical level, it seems clear that humans at brokerages are still needed to manage risk, supervise systems, oversee the connection between clients and automated processes, and interpret regulation – lawyers will always be in demand somewhere.
Indeed, accurate and relevant data inputs are essential, so a major challenge is to find clean data and institute
Rarely do machines just speak to machines. Instead, automation simplifies, streamlines and codifies the trade
Adrian Facini,
Product and Program Management, IEX Group
“
Although a lot of trading surveillance is automated, patterns are changing and bad behaviour is becoming more heinous. We deploy predicative protections to counter these increasingly sophisticated arb strategies.
”
Jim Northey,
Senior Vice President, Strategy and Research, Itiviti
“
At some point humans can’t compete with machines. Automation is taking over time-consuming operational processes such as client on-boarding, and algorithms are already trading news as well as implementing portfolio strategies which suggest that the investment manager’s role might become obsolete too.
”
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James Rubinstein,
Americas Head of Algorithmic Trading and Analytics, UBS
“
Algorithms are only as good as their inputs, and sometimes a human is needed to identify and explain why an outcome is wrong, that is, to validate the data. Humans are also still needed to manage risk, monitor systems and oversee the connections between clients and automated systems.
”
Leo Li,
Senior Investment Project Manager, The Vanguard Group
“
Vanguard’s fund management approach combines the experience of our long-tenured indexing experts with state-of-the-art management tools, including automation. This approach allows us to track benchmarks with greater precision while rigorously managing risk.
”
order cycle, which helps sales-traders provide a better service for their clients.
is fresh and relevant. They are more dynamic than previously, when they were rule-based and static.
In some cases, automated processes are introduced for traditional mainstream trades while high value transactions are performed manually. In addition, the development of more sophisticated algos and the introduction of artificial intelligence (AI) technology means that the dichotomy is actually reversing: humans handle the basic transactions and machines manage the exotic, high-value trades.
Perhaps at some point humans can’t compete with machines. Automation is taking over time-consuming operational processes such as client on-boarding, and algorithms are already trading news as well as implementing portfolio strategies - which suggest that the investment manager’s role might become obsolete too.
Although many banks have been working on aspects of AI, such as predictive analysis for several years, there is now more clarity about its wider potential and more structure about its employment. It is being used to identify pattern variations and implementation shortfalls, examine alternative scenarios and process more variables.
Besides, if your job can be eliminated by a computer, then how long would you actually want to do that job? And new technology will continue to require complementary skill sets from people. Trading experience, networks and market savvy might diminish as job requirements, but quant expertise will be highly valued and, ultimately, essential.
Machines learn from history rather than in real-time, but access to extensive contemporaneous data sources, including news and social media, mean that the history
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IEX Launches Listings Venue
With Sara Furber, Head of Listings, IEX
An SEC decision removes one of IEX’s last remaining hurdles to becoming a primary listing venue and will encourage corporate issuers who demand a fairer, cheaper service. IEX was launched more than four years ago to protect investors from unfair advantages enjoyed by predatory high frequency traders in the equities secondary market. Now, IEX is taking an initiative in the primary markets that should alleviate many of the problems encountered by corporate issuers with listings in other exchanges. In early August, IEX gained approval from the Securities and Exchange Commission (SEC) to introduce opening and closing auctions. Moreover, the SEC also gave the go-ahead for IEX to enable the transfer of listings from other exchanges and hold opening auctions for initial public offerings (IPOs) on listing day.
introduce dedicated IEX-listed test symbols and quote its listed securities on Network B data feeds, and generate and distribute daily list files. The IEX auction process provides electronic price discovery mechanisms that match orders in IEX-listed securities at a single price using a double auction. These auctions enable IEX participants to execute against On-Open and On-Close interest at the exchange. During the process, IEX will calculate and disseminate current price, size, imbalance information, auction collar information and other relevant information about future auctions. It will also introduce four new order types for use in auctions exclusively: two for the opening auction (Market-On-Open, Limit-On-Open) and two for the closing auction (Market-On-Close, Limit-On-Close).
The decision cleared the last significant obstacle for IEX to become a primary market venue for companies in mid-October, challenging the duopoly held by the New York Stock Exchange (NYSE) and Nasdaq.
Perhaps naturally, the incumbents would prefer that they retained their dominant position, but the SEC has clearly shown its preference for further competition and choice, and has been constructive during IEX’s application process.
For its operations, IEX will support security directory and auction information messages on its market data feeds,
IEX’s auction aims to broaden investor participation and prevent market manipulation, which is reflective of IEX’s
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sustain relationships with its clients and provide them with a more supportive voice. Just like IEX’s market data, IEX’s auction data will be free with equal access for all participants, which creates a level playing field for all investors. IEX will disseminate information every second, compared with longer periods by Nasdaq and NYSE. IEX also plans to offer an alternative pricing model to its listed companies, that reflects it’s client-centric, service driven approach. In practice, this means a lower-cost, flat fee; a refreshing alternative to the complex array of additional levies are charged for corporate actions, such as mergers, rights issues or stock-splits. This reflects
Sara Furber, Head of Listings, IEX core philosophy. In fact, IEX was first started to protect investors from predatory traders, and mitigate against speed advantages. Long-term investors in particular have been enticed by IEX’s protective innovations, superior execution quality, and their free-access, pay-as-you-trade pricing model. When it launches its primary market capability, IEX initially plans to persuade companies to shift their listings from other exchanges, then later, after building a track record for successful auctions and accumulating a critical mass of listings, it will be in a position to attract IPOs. IEX should also increase its share of secondary market trading because a company’s stock tends to trade more frequently on its home exchange at the open and close of trading. Moreover, between 5% and 15% of daily trading volume takes place at the opening and closing auctions, and these are the segments that IEX aims to tap.
“The SEC has clearly shown its preference for further competition and choice.” feedback from companies who felt they were being treated as products, rather than clients and sometimes faced surcharges in excess of their annual listings fee. In order to compete, other exchanges will likely have to offer better services – although business models that rely on complex fee structures and by selling data might struggle to change. Of course, there will be challenges. IEX will need to overcome some understandable inertia in order to attract listings by companies that are drawn by the apparent prestige of a NYSE listing and the glamour of ringing the opening bell, the ticker tape in Times Square and the CNBC market commentary. However, ethical and fiduciary responsibility should prevail and listing choices are likely to be based on efficiency and cost, rather than branding.
Shareholder alignment Arguably, NYSE and Nasdaq compete largely on branding and marketing. IEX believes it offers companies a service-oriented value proposition, that aligns itself with and takes responsibility for the interests of its shareholders. IEX intends to build and
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Implementation Of MiFID II Testing Requirements By Trading Venues And Investment Firms
By Matthias Burghardt, Head of Xitaro Exchange System Development, Boerse Stuttgart If you consider MiFID II testing requirements are a challenge, you might have a problem with your established processes today. Boerse Stuttgart is approaching the last quarter of a two-year Markets in Financial Instruments Directive (MiFID) II project which is dominated by development and testing activities. MiFID II requires trading venues and investment firms to implement substantial changes in existing processes and technology. As Boerse Stuttgart Group operates not only a trading venue but also an investment firm, EUWAX AG, requirements have to be fulfilled for both entities. Before work was carried out an examination was needed to identify the differences and commonalities in requirements between investment firms and trading venues. MiFID II testing requirements on investment firms and trading venues are based on Articles 17 and 48 and are further specified in the regulatory technical standards 6 and 7. Article 17 requires investment firms engaged in algorithmic trading to ensure their systems are fully tested. Article 48 requires regulated markets to ensure their trading systems can perform orderly trading under conditions of severe market stress and
meet strict testing criteria. In addition, regulated markets shall require members to carry out appropriate testing of algorithms and provide environments to facilitate such testing. According to Article 18(5) these requirements do not only apply to regulated markets but to multilateral trading facilities (MTFs) and organised trading facilities (OTFs) as well. Regulatory Technical Standards (RTS) 6 and 7 provide the details on MiFID II’s testing requirements for investment firms and trading venues, respectively. There are six areas to consider when implementing MiFID II: Staffing, general testing methodology, conformance and algorithm testing, testing environments, stress testing and the role of selfassessments. Let’s explore in more detail. 1) Staffing: You need to have a sufficient number of qualified and expert staff to manage your trading systems and algorithms. The requirements on investment firms and trading venues are remarkably similar, but investment firms need to have staff with technical knowledge of trading systems, algorithms and strategies. Trading venues need to have staff with
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“Investment firms should establish clearly delineated methodologies to develop and test their systems, algorithms or strategies.” of the investment firm’s algorithmic trading systems with the system of the trading venue. In particular, conformance testing should prove that the systems interact as intended, verify basic functionalities, test connectivity and recovery. Trading venues should document the results by issuing a conformance test report. Matthias Burghardt, Head of Xitaro Exchange System Development, Boerse Stuttgart knowledge of the trading systems, algorithms and the types of trading undertaken by the members.
In addition to conformance testing which covers only the basic functionality, trading venues must require members to certify that their algorithms have been tested to avoid contributing to or creating disorderly trading conditions. This is a task investment firms can do without any interaction with the trading venue.
2) General testing methodology: MiFID II requirements on the general testing methodology may not be new, but it’s wise to check your processes and documentation. The goal of testing is to ensure that systems do not behave in an unintended manner. But, similar to the staffing requirement, stakes are higher for investment firms than for trading venues. Investment firms should establish clearly delineated methodologies to develop and test their systems, algorithms or strategies. They should also adapt their testing methodologies to the trading venues and markets where the trading algorithm will be deployed. On the other hand, trading venues are required to make use of clearly defined development and testing methodologies and be able to demonstrate at all times that they have taken all reasonable steps to avoid their trading systems contributing to disorderly trading.
However, before an algorithm is deployed, investment firms must certify and explain their algorithm testing activities to the trading venues. Trading venues are expected to include all testing obligations in their rules and regulations. Critically, conformance testing is made a condition in the due diligence for members of trading venues.
3) Conformance and algorithm testing: Investment firms and trading venues must work together to ensure conformance of the investment firm’s trading algorithms with the trading system. Trading venues must require their members to test the conformance
Trading venues should provide a conformance testing environment and require members to use it. Despite there being no strict requirement for members to use it, they should also provide access to an algorithmic testing environment which is as realistic as possible.
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4) Testing environments must be strictly separated from production environments in both investment firms and trading venues. Investment firms should use a testing environment separated from production. Some firms may opt to use testing environments provided by a trading venue, direct electronic access (DEA) provider or vendor, but they need to retain full responsibility. They also need to use their testing environment for stress tests.
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5) Stress tests shall be used by investment firms and trading venues, respectively, to verify their systems’ performance. Investment firms must – as part of their annual self-assessment – test that algorithmic trading systems can withstand increased order flows or market stresses. This is done by running high message and trade volume tests using twice the number/volume of the last six months maximum. Trading venues should – in the context of their self-assessment – simulate adverse scenarios, including members’ activities in all trading phases, segments and instruments.
“Adverse scenario tests should be based on an increased number of messages received, unexpected behaviour and a random combination of normal and stressed market conditions.” Adverse scenario tests should be based on an increased number of messages received (baseline is the highest number of messages per second during the last five years), unexpected behaviour and a random combination of normal and stressed market conditions. It is important to note that stress tests are executed separately by investment firms and trading venues and have a different focus. Investment firms concentrate on testing an increased system load whereas trading venues concentrate their testing activities on adverse scenarios and an unexpected behaviour of their operational functions. There is no requirement regarding common stress testing activities. 6) Self assessments should be regarded by investment firms and trading venues as an opportunity to determine their specific MiFID II implementation needs. Investment firms are required to perform an annual self-assessment considering nature, scale and complexity of their business. Similarly, trading venues should perform a self-assessment at least once a year, but before the deployment of a trading system.
should be determined according to a self-assessment. Similarly, trading venues should – according to RTS 7 recital 5 – lay down their requirements with respect to their systems and apply them in conjunction with a self-assessment since not all trading models present the same risks. Therefore, some organisational requirements may not be appropriate for certain trading models. In particular, the specific requirements to be set should be considered according to the nature, scale and complexity of the algorithmic trading activity. In other words, the European Securities and Markets Authority (ESMA) acknowledges that: (a) investment firms and markets are not necessarily equal in terms of nature, scale and complexity; (b) the specific application of requirements may take these differences into consideration; and (c) self-assessments could be considered a chance to explain the specific implementation measures. If you consider MiFID II testing requirements a challenge, you might have a problem with your established processes today.
“Requirements on investment firms are higher than on trading venues.” Most of the requirements are probably already fulfilled by markets and their participants. MiFID II imposes the same standards on each investment firm and on each trading venue making it a level playing field. However, requirements on investment firms are higher than on trading venues. You probably do not have to implement completely new processes, but you may need to verify this and update your documentation. And last but not least, self-assessments need to be performed at least annually and don’t forget they are also a chance to explain your MiFID II compliance to your regulator.
According to RTS 6 recital 8, compliance with the specific organisational requirements for investment firms
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58 | PRODUCT OVERVIEW
Turquoise Plato Block Discovery By Robert Barnes, CEO, Turquoise At a time of global passive indexation and an electronic order book environment that naturally leads to small average trade sizes, investors that wish to outperform benchmarks are calling for innovation in electronic block trading. To answer this call and still trade in the presence of anticipated MiFID II double volume caps, one needs a respected trading mechanism that can match orders received above 100% of Large In Scale (LIS) thresholds determined per stock by ESMA, the European Securities and Markets Authority. Designed in Europe and refined in partnership with both buy-side and sell-side, Turquoise Plato Block Discovery is a Large In Scale (LIS) electronic execution channel that works. Activity continues to grow, setting new records.
Figure 1: Turquoise Plato Block Discovery already has matched €32.2 billion ($27.3 billion) since 20 October 2014 go-live and 31 July 2017, of which more than €28.1 billion or 87% has matched since September 2016.
Turquoise Plato Block Discovery has registered new records above the volumes of June 2016, the month of the UK Referendum. Turquoise Plato Block Discovery set a new monthly record by value traded in July 2017 of €5.49 billion, a 3% increase over prior record of €5.33 billion set in June 2017 and more than 9x that of July 2016. Such
record activity highlights strong support of the trading community and scalability of Turquoise Plato Block Discovery. Turquoise Plato Block Discovery has more than two and a half years of empirical data evidencing quality execution featuring: high firm up rates, low reversion, higher average trade sizes in an Open Access multilateral order book mechanism where consistently more than half of value traded – 56% in July 2017 – already is above 100% Large In Scale.
Turquoise Plato Block Discovery: higher trade sizes in an open access multilateral order book mechanism Turquoise Plato Block Discovery is a broker neutral mechanism for executing anonymous block orders Turquoise Plato Block Discovery: higher trade sizes in an open access mul8lateral order above 100% of LIS thresholds. Today, orders entered Turquoise Plato Block Discovery is a broker neutral mechanism for execuEng anonymous are eligible to participate if above 25% LIS. of LIS thresholds. Today, orders entered are eligible to parEcipate if above 25% LIS. ESMA sets current LIS thresholds relative to an ESMA sets current LIS thresholds relaEve to an Average Daily Turnover (ADT) metric that Average Daily Turnover (ADT) metric that segments one of five Bands that set a security’s respecEve threshold. securities into one of five Bands that set a security’s respective threshold. Table 1: ESMA Bands by ADT and respecEve LIS ESMA Bands by ADT = Average Daily Turnover
ESMA Bands (€ LIS)
ADT < €500k = Band 1
Band 1 (€ 50k)
€0.5m < ADT< €1m = Band 2 €1m < ADT< €25m = Band 3 €25m < ADT< €50m = Band 4 ADT > €50m = Band 5
Band 2 (€ 100k) Band 3 (€ 250k) Band 4 (€ 400k) Band 5 (€ 500k)
Table 1: ESMA Bands by ADT and respective LIS
Table 2: Turquoise Plato Block Discovery where trades are above Large In Scale: Septemb
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ESMA Bands (€ LIS)
Value Traded (€), where trades > LIS
Trade Count, where trades > LIS
Average Trade Size (€)
Average Trade Size Multiple of LIS
Max Tra Size (€
Band 1 (€ 50k)
243,245,099
1,768
137,582
2.8x
2,830,0
Band 4 (€ 400k)
4 ADT > €50m = Band 5
Band 5 (€ 500k)
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Table 2: Turquoise Plato Block Discovery where trades are above Large In Scale: September 2016 – July 2017 ESMA Bands (€ LIS)
Value Traded (€), where trades > LIS
Trade Count, where trades > LIS
Average Trade Size (€)
Average Trade Size Multiple of LIS
Max Trade Size (€)
Country
Band 1 (€ 50k)
243,245,099
1,768
137,582
2.8x
2,830,085
Germany
Band 2 (€ 100k)
140,163,993
666
210,456
2.1x
2,518,091
UK
Band 3 (€ 250k)
3,216,548,619
6,572
489,432
2.0x
5,417,891
Switzerland
Band 4 (€ 400k)
2,403,779,496
3,155
761,895
1.9x
5,663,713
Germany
Band 5 (€ 500k)
10,101,564,81 9
9,554
1,057,31 3
2.1x
13,109,83 5
Italy
Table 2: Turquoise Plato Block Discovery where trades are above Large In Scale: September 2016 – July 2017
Turquoise Plato Block Discovery key observaEons from Table 2 for the period since September 2016 are that: Turquoise Plato Block Discovery key observations from to trade with LIS pre-trade transparency waiver • Where traded acEvity is above LIS, the average trade size is approximately double or more Emes the LIS Table 2 forthreshold across all respecEve ESMA Bands of liquidity: Average Trade Size MulEple of LIS ranges from 1.9x to the period since September 2016 are that: at midpoint and save half the bid offer spread = • Where traded lower implicit costs. 2.8x. activity is above LIS, the average All of the bands have recorded a maximum successful single trade size well over €1 million, the largest to date trade•size is approximately double or more times the • Because larger trades that match with minimal being €13.1 million, this was a single trade in Eni, the global energy company with primary lisEng on Borsa LIS threshold across all respective ESMA Bands of market impact and lower implicit costs contribute Italiana. liquidity: Average Trade Size Multiple of LIS ranges to long term investment returns. • Turquoise Plato Block Discovery trades for ESMA Band 5 blue chips above ESMA LIS consistently average more from 1.9xthan €1 million per trade. to 2.8x. • Because it shows Turquoise Plato Block Discovery •All of the bands have recorded a maximum successful is a working LIS electronic execution channel. singleTurquoise Plato Block Discovery trades for ESMA Band 5 blue chips above LIS consistently average more than €1 trade size well over €1 million, the largest to date million per trade and are more than 100x larger than the €10,000 average trade sizes for the same ESMA Band 5 being €13.1 million, this was a single trade in Eni, Helping investors get their business done blue chips matching using conEnuous midpoint mechanisms. This is shown clearly in Figure 2. the global energy company with primary listing on To visualise what these larger trades look like Borsa Italiana. compared to average trading activity resulting •Turquoise Plato Block Discovery trades for ESMA from continuous order book activity, consider Y the 2 Band 5 blue chips above ESMA LIS consistently following example of UK-listed company Next average more than €1 million per trade. plc displayed in Figure 3. The intraday price chart displays time on the x-axis and price on the y-axis Turquoise Plato Block Discovery trades for ESMA Band with trade prints enriched by trade size. Investors 5 blue chips above LIS consistently average more than are trading shares of UK company, Next plc, on €1 million per trade and are more than 100x larger than multiple trading platforms, including the electronic the €10,000 average trade sizes for the same ESMA order book of its primary listing destination, London Band 5 blue chips matching using continuous midpoint Stock Exchange, and Turquoise. This illustration mechanisms. This is shown clearly in Figure 2. shows the prices and sizes of trades by investors on 9 March 2017. Turquoise trade prices are Why does this matter? similar to those of the primary Stock Exchange, • Because orders with size above ESMA Large In and Turquoise trade sizes serve both the smallest Scale received by a venue can continue in MiFID II and largest orders through its single connection for
Figure 2: Where ESMA Band 5 stocks trade above LIS via Turquoise Block Discovery, the average trade size is more than €1 million per trade, and this is more than 100x larger than the average trade sizes arising from a mechanism of dark pool continuous trading
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60 | PRODUCT OVERVIEW
Figure 3: Turquoise Plato Block Discovery offers additional electronic execution channels to help investors get their business done: for example, Next, the top five trades here are via Turquoise Plato Block Discovery and represent 19% – and Turquoise overall 32% – share of trading on this day
straight through processing from trading in London to settlement into Euroclear UK & Ireland. In this example, Turquoise not only enables investors to access a third of the order book value traded that day, Turquoise also matched the very largest order trades of all venues during the day via its award winning electronic block trading innovation Turquoise Plato Block Discovery.
Figure 4: Turquoise Plato Uncross high quality execution destination by frequency % of times that the primary mid- price moves by any amount at fixed times after a dark pool trade, according to LiquidMetrix independent analysis:
How does Turquoise Plato Block Discovery work? Members send conditional messages called Block Indications to Turquoise Plato Block Discovery. When there is a potential match between a buyer and a seller, and both are able to get their respective Minimum Execution Size filled, Turquoise Plato Block Discovery sends an automated Order Submission Request (OSR) that requests each member send a Qualifying Block Order into Turquoise Plato Uncross. Turquoise Plato Block Discovery: low reversion of Turquoise Plato Uncross is positive differentiation Turquoise Plato Uncross is an innovation that provides randomised uncrossings during the trading day, ideal for larger and less time sensitive passive orders. Turquoise Plato Uncross has been the subject of multiple studies since 2013 by LiquidMetrix, the independent analytics firm that specialises in venue performance metrics and execution quality analysis.
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Source: LiquidMetrix
PRODUCT OVERVIEW | 61
Figure 4 shows that for Turquoise Plato Uncross after one second following execution, the PBBO mid reference price has changed in less than 10% of occasions, as per independent analysis by LiquidMetrix; this compares well with the 50% for continuous dark pools. The insight by LiquidMetrix is that “Turquoise Plato Uncross matching happens at times less correlated with market movements and within the EBBO more readily than continuous dark book executions across all relevant venues”. From an execution point of view, large orders left resting on Turquoise Plato Uncross are less susceptible to gaming or adverse selection that orders left on other continuously matching MTF Dark pools. The proportion of Turquoise Plato Uncross trades executing outside the prevailing EBBO is lower (= better) than continuous dark book trades.” The value traded via Turquoise Plato Block Discovery in June 2017 was more than 35x the value traded in October 2015, and yet the high quality and low reversion of the Turquoise Plato Uncross™ periodic random matching remains resilient and positively differentiated compared with that of continuous matching dark pools. Turquoise Plato Block Discovery: high firm up rates and robust reputational scoring Turquoise Plato Block Discovery has more than two and a half years’ worth of empirical measurements evidencing consistently high firm up rates. These high firm-up rates result from robust automated reputational scoring, which measures the difference between the original block indication and the subsequent firm order.
Since launch, more than 90% of OSRs resulted with firm orders into Turquoise Plato Uncross within the specified time window – under half a second – and with both price and size parameters inside the minimum requirements of the service defined with input from buy-side and sell-side users. Figure 5 shows that in less than just 9% of OSRs did the respondent fail to come back within the prerequisite core time and size parameters. The key insight is that the vast majority of Turquoise Plato Block Discovery OSRs successfully firm up. Surveillance of Turquoise activity, including monitoring of price movements ahead of Turquoise Plato Uncross is undertaken by the independent London Stock Exchange Group Surveillance team. Any suspected manipulation of Reference Price will be referred to the UK Securities Regulator, FCA. A combination of robust automated reputational scoring, independent quantitative analysis evidencing quality of the LIS trading mechanism, and an independent surveillance oversight add to the integrity of Turquoise Plato Bock Discovery for the matching of undisclosed Block Indications that execute in Turquoise Plato Uncross. Turquoise Plato Block Discovery, designed in Europe and refined in partnership with buy-side and sell-side, has more than two and a half years of empirical evidence and the scale today to be the trading venue of choice for LIS electronic execution.
Figure 5: Turquoise Plato Block Discovery firm up rates into Turquoise Plato Uncross are consistently high.
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62 | FIX TRADING COMMUNITY MEMBERS
FIX Trading Community Members *Premier Global Members marked in bold
360T Asia Pacific 42 Consulting Pte Ltd Actuare AFME- Association for Financial Markets in Europe Alcova AM Algomi AllianceBernstein American Century Investments Ancoa Software Aquis Exchange ASIC Association of International Wealth Management of India Australian Securities Exchange AXA Investments Managers Ltd B2BITS EPAM Systems Company Baillie Gifford Banca IMI SpA Banco BTG Pactual S.A. Banco Itau S.A Bank of America Merrill Lynch Bank of Ireland Barclays Barings BATS Global Markets Baymarkets AB Beijing RootNet Technology Co., Ltd. Berenberg Bank BlackRock, Inc. Blitz Trading Bloomberg L.P. Bloomberg Tradebook BlueBay Asset Management BM&F BOVESPA BNP Paribas Bolsa de Valores de Colombia Bolsas y Mercados Españoles (BME) Brandes Investment Partners LP Bridline Brook Path Partners, Inc. BSE Limited BT Global Services BVI Cameron Edge Cantor Fitzgerald Capital Group Companies, Inc. Cedar Rock Capital Charles River Development CBOE Chi-X Global Inc CIMB Securities Cinnober Financial Technology AB Citi
CL&B Capital Management Clearing Corporation of India Ltd CLSA Limited CME Group Colonial First State Global Asset Management Colt Technology Services Connamara Systems LLC Cowen Corvil CQG Credit Suisse Crown Jewels Consultants Ltd Daiwa SB Investments Daiwa Securities Group Inc. Danske Bank DATAROAD DataArt Dealogic Delta Capita Deutsche Bank Deutsche Boerse Group Devexperts Dimensional Fund Advisors Drebbel DTCC DXC Technology Eastspring Investments (Singapore) Limited EBS BrokerTec EDMA Europe Egypt For Information Dissemination Emagine Consulting Equinix Esprow Pte. Ltd. ETLogic Ltd Etrading Software Ltd Eurex EuroCCP Euronext Paris SA EuroTLX Exactpro Systems Exane BNP Paribas Eze Software Group EZX Inc. Federated Investors FIA (Futures Industry Association) Fidelity Management & Research Co Fidelity International Fidessa Group First Boston Group FISD Fiserv FIS Global FIX4wards FIX Flyer LLC FIXSOL FlexTrade FpML Franklin Templeton Investments Gamma Three Trading, LLC
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GATElab GETCO Asia GMO Goldman Sachs GreySpark Guosen Securities Ltd Haitong International Securities HCL Technologies Higher Frequency Trading HM Publishing Hong Kong Exchanges & Clearing Limited Hong Kong Investment Funds Association (HKIFA) HSBC HSBC Global Asset Management ICMA (International Capital Markets Association) IG Group Ignis Asset Management Incisus Capital Partners Indata Recon LLC Indian Association of Alternative Investment Funds Informagi AB Infoware Infront AS ING Bank Instinet InstrumentiX Intercontinental Exchange (ICE) International Securities Exchange (ISE) ITG Ipreo IPC Systems IRESS ISITC ISO Itiviti Jefferies J.P. Morgan Jordan & Jordan JP Morgan Investment Management (J.P. Morgan) JSE Limited KB Tech KCG Holdings Kotak Securities LCH Linedata Liquidnet LiquidMetrix LIST Group Lloyds Banking Group LMAX London Stock Exchange Group M&G MACD Macquarie Securities MAE - Mercado Abierto Electronico S.A. MarketAxess
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Marshall Wace Asset Management Mawer Investment Management MDSL Metamako MFS Investment Management Mizuho Securities Morgan Stanley Investment Management Morgan Stanley MTS SpA Nasdaq National Physical Laboratory Newton Investments NEX Group Nikko Asset Management Nomura Asset Management Nomura Nordic Growth Market (NGM) Norges Bank Investment Management Northern Trust Global Investments Ltd OCBC Securities Private Ltd. OMERS OMG (Object Management Group) On Budget and Time Ltd Ontario Teachers’ Pension Plan Board Onix Solutions [OnixS] Options Clearing Corporation Options Technology Ltd Orbis Investment Management Limited Oslo Bors ASA OTC Exchange Pantor Engineering AB Peresys (IRESS) PFSoft PIMCO Pioneer Investments Portware Primary E Trading Principal Global Investors Putnam Investments QuantHouse Quendon Consulting R3 R Shriver Associates Rabobank International Rapid Addition Raptor Trading Systems, Inc. RBC Capital Markets RBC Global Asset Management Research Exchange Santander Global Banking & Markets SASLA (South African Securities Lending Association) Schroders Shanghai Stock Exchange SimCorp Singapore Exchange SIX Swiss Exchange Skandinaviska Enskilda Banken AB Sloane Robinson smartTradeTechnologies
Societe Generale Softsolutions! Srl Southeastern Asset Mgmt Spectracom SS&C Technologies Standard Chartered Bank Standard Life Investments State Street Global Advisors State Street Global Markets State Street Technology Zhejiang Sumitomo Mitsui Trust Bank Swedbank Robur Fonder AB SWIFT Sycamore Financial Technology Symphony Communication Services LLC Systemware Innovation Corporation (SWI) Taiwan Stock Exchange Tata Consultancy Services Technistock Telstra Global The Continuum Partners The Investment Association The London Metal Exchange The Nigerian Stock Exchange The Realization Group The Technancial Company The Vanguard Group Thomson Reuters Tokyo Stock Exchange TORA Tower Research Capital India PVT Ltd TP ICAP TradeHeader, S.L. Tradeweb Trading Technologies TradingScreen Tradition Traiana (ICAP) Transaction Network Services (TNS) Trax Turquoise TWIST UBS ULLINK UniCredit Vela Trading Technologies Velocimetrics Verne Global VOEB Warsaw Stock Exchange Wellington Management Company Wholesale Markets Brokers’ Association Winterflood Securities XBRL Xetra (Deutsche Börse) Zeopard Consulting
New Member
FIX Trading Community wishes to welcome the following companies to its growing worldwide membership. For more information, please visit: www.fixtrading.org
Berenberg Bank
www.berenberg.com
CLSA Limited www.clsa.com
HCL Technologies www.hcltech.com
Hong Kong Investment Funds Association (HKIFA) www.hkifa.org.hk
Northern Trust Global Investments Limited www.ntrs.com
Premier Global Members
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64 | LAST WORD
My City
Mumbai By Jyoti Rai, Associate Director, Business Development & Advocacy, Edelweiss Prime Brokerage Services
Best thing about your city? As an army kid, I have lived in many cities across India, but there is no city like Mumbai! It is truly a “maximum city”, embracing diversity and accepting various lifestyles without being judgmental. On the one hand it has a buzzing nightlife and on the other hand it promotes art and theatre, festivals, commerce and sports. All of these activities find their place in the city. Worst thing about your city? The low premium on human lives and the time spent by millions in commuting from home to work and back. Getting to work? Thanks to the disruption in transport
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services, Ola and Uber have made my life easy. That’s why I sold my new XUV500 after a year use and use these taxis. It takes about 25-to-30 minutes to reach the office if I leave on time.
are paramount - after all, you want the experience to say with the client. I have personally enjoyed and also had rave reviews from clients for Yauatcha in BKC and China House in the Grand Hyatt, Kalina.
View from your desk? I sit on the 12th floor and from my desk I can see the tall, glass covered buildings of the Bandra Kurla Complex (BKC), the sight of eagles flying high and effortlessly are very common.
And a relaxed spot with friends and family? About an hour’s drive from Mumbai is a place called Upper Deck in Lonavala where weekends are blissful. A quiet evening around Bandra bandstand is great way to relax too.
Where to take your clients/brokers for dinner? The ambience, quality of service and, especially, the authentic flavours that
Best tourist spot? Marine Drive, also known as the Queen’s Necklace, at night.