The Itiviti Perspective On Current Trends In Quality Assurance

August 21, 2018

By Vaibhav Shukla, Senior Vice President, Global Services, Itiviti

Automating quality assurance across a range of procedures provides cost benefit and productivity improvements.

The financial industry is constantly evolving, driven by a mix of new business and regulatory requirements. The implementation of the Markets in Financial Instruments Directive (MiFID) II in Europe, for instance, is spurring a tectonic technology transition. With these rapid changes in the industry and the rising cost of errors in production systems, the quality assurance function is gaining importance, and is increasingly seen as a business-critical investment and not just a cost centre.

Automated testing and common use cases
Automation is a natural evolution evident in any industry, be it agriculture, vehicles or financial software. The core driver is the need is to automate “well defined, repeatable, and costly” operations. Instead of devoting efforts to manual testing, a similar effort spent on designing the test harness and automating the test executions may produce a huge cost benefit and productivity increase. A computer can run 4,000 test scenarios on a complex infrastructure system in a matter of minutes — where it would have taken days or even weeks as manual task.

As a rule of thumb: if you must do the same task twice you should automate. One area where we see clients benefit from automating quality assurance is where unit testing, integration testing, and regression testing is integrated with the automated software build systems within a continuous integration process. Other areas with strong cases for automation are change management and service virtualization.

To illustrate, imagine that you’re investing in new infrastructure software for managing client flow, but the software is still under development. Traditionally, you would wait for the software to be completed. Automated testing can save time by virtualizing the new environment for your clients to test against and validate their interfaces before going live. Additionally, you can use all the known client flows to continuously test against your software in development to ensure it will be fit for the purpose and scope.

Quality assurance in the light of MiFID II
The introduction of MiFID II was a momentous event impacting European trading operations even before it was implemented. Every aspect of trading was affected by this regulation and therefore practically all aspects of trading infrastructure software have required testing in light of the new requirements.

At Itiviti, we have supervised re-development and re-certification of nearly every client connection as well as platform changes from all venues in the FIX and native protocols. We offer venue emulators and venue simulators enabling clients to test their workflows in both FIX and native protocols using our MiFID II Certification Service and our industry leading on-boarding solution, Itiviti Conductor. We are using the same tools internally to manage and assist the quality assurance process for new Itiviti products and upgrades.

Our clients’ view on VeriFIX by Itiviti
In March 2017, Itiviti asked TechValidate, an independent third-party research firm, to survey clients who use our Quality Assurance product VeriFIX by Itiviti, to discern product usage and evolving trends in testing automation. This survey provided essential guidance, helping us design the new enterprise offering in the area of automated testing.

Clients identified the following as the most common challenges in quality assurance:

Continuous integration and regression testing.
Unit and isolation testing with multiple protocols.
Session level testing with the end points including using service virtualization.
Test harness design to catch black swans/unexpected or known race conditions.

Testing automation efforts are mainly focused on first three aspects:

Automated testing on the rise.
The proliferation of automated testing is evident from the way clients are using VeriFIX by Itiviti. Among those who use later versions of VeriFIX (6.0 or higher), nearly three quarters reported using it for regression testing while just 38% use it for manual click testing as seen in the chart below.

who-are-the-main-users-of-verifix 500–2000 or more automated test cases.
Users who perform regression testing will quickly build a critical mass of automated test cases – 61% have created 500–2000 or more. As the volume increases, test case management including re-usable framework, collaboration, and version control becomes an important element of an enterprise solution.

Quality assurance teams the main users.
VeriFIX by Itiviti is today predominantly used by quality assurance teams with nearly 72% of the user base identifying themselves as such – a change from the early days of this product when it was primarily used by support desks.

50% of the users of older versions (4.x, 5.x) identify themselves as support staff, whereas 82% of the users of newer versions (6.1, 6.3) are quality assurance. Another trend influencing product design is that quality assurance has become an integral part of the development and deployment process.

Conclusion
We expect continued strong momentum towards automated testing, driven by increasingly complex and comprehensive testing needs as well as transformative industry trends and events such as MiFID II. We envision a highly integrated continuous testing environment and are currently investing in next-level automation that will further reduce the cost of test design and management building an enterprise-level platform.

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Optimizing Trading Workflows With Agile Platforms

GlobalTrading

August 14, 2018

Buy-side trading desks have unique requirements, but all need to future-proof their platforms.

Should buy-side trading desks buy technology or build their own? How are institutional traders extracting maximum value from data? What is the potential — and what are the limitations — of automated trading?

Those were a few of the questions explored in a recent buy-side roundtable hosted by TradingScreen in New York.

On the buy-versus-build question, roundtable participants noted that every trading desk has its own unique workflow and its own unique needs for solutions, so every desk has its own unique answer. This differs from bank broker-dealers, where the universe is much smaller the suite of trading products and services is comparatively standardized.

“Unlike the sell-side, most buy-side firm have unique workflows, which require them to tailor technology and data solutions to drive performance and meet ever-growing regulatory mandates,” said Nasdaq Head of North American Equities Tal Cohen, who moderated the roundtable.

Mostly, buy-side trading desks buy systems ‘off the shelf’ and customize to their own specifications — so, some buying, and some building. But today’s increasingly complex market calls for more sophisticated, higher-horsepower products, so there is a discernible shift towards buying.

Enrico Cacciatore, Voya Investment Management.

“We’ve gone from mostly proprietary technology to mostly third-party,” said Enrico Cacciatore, Senior Quantitative Trader and Head of Market Structure & Trading Analytics at Voya Investment Management.

“We had to have the skill-set to maintain it, and our corporate model is to scale and simplify. So we asked ourselves: ‘Can’t we build this in a third-party product and maintain our edge?’”

Interoperability

For a large investment firm that trades different asset classes, with different trading protocols, multiple ‘best-of-breed’ solutions are required for specific areas of the trade lifecycle. Then the real challenge is stitching it all together so that systems are interoperable with each other and also the internal technology.

“We count on third parties but it’s also critical to have an internal team of developers to handle integration with multiple platforms,” said Alessandro Barroso, IT Manager, Investment & Wealth Management Technology at Franklin Templeton.

(L) Eric Thorson, Vanguard and (C) Alessandro Barroso, Franklin Templeton

The largest buy-side institutions with trading desks across continents face another challenge: maintaining standardized workflows while giving individual trading desks some leeway. For example if Sydney traders have a way to efficiently trade Australian securities that differs from how they do it in London, that should be accommodated.

“The utopian view is that it’s all going to be consistent,” said Eric Thorson, Senior Delivery Manager for Portfolio Management Systems at Vanguard. “But it never really is.”

Or as another roundtable participant said, it’s about “balancing between effective change management and still allowing for the ‘secret sauce’.”

Data overload

One shared pain point for institutional managers is data management. The problem isn’t a lack of data; on the contrary, the challenge is sifting through massive amounts of data, finding what’s usable, and acting on it before its usefulness expires.

“There is too much data, and most of it is bad,” said Jose Marques, CEO of Inferent Capital. “How do we make data useful in a timescale that’s relevant to the problem we’re trying to solve? Post-trade is fine, but that’s not going to add alpha.”

Roundtable participants were in consensus that almost every buy-side firm is working to optimize data management; however these is a long way to go, which presents an opportunity for technology vendors to step in with the right solution.

Institutions are either developing or shopping for more robust data-capture models, which will be overlaid by more advanced functionality such as aggregation, pattern recognition, and visualization.

One roundtable participant noted his firm is at the beginning phase of leveraging data to improve trading decisions. “We are not there yet,” this participant said. “We are collecting data and we have a data scientist looking at it. The question is, how is it going to add value to our process?”

What’s ahead?

“The question to ask is not what the buy side needs, but what will the buy side need,” TradingScreen Senior Developer Edmund Caraceni told Markets Media after the roundtable.

“For a technology provider, having a future-proof lens enables readiness for shifts driven by regulatory demands for the data aggregation and business-intelligence tools that enable best execution across asset classes.”

Regarding the trading desktop of the future, one buy-side technologist who participated on the roundtable noted a secular shift away from a closed system, and towards a more open model that can be described as a container with multiple specialist fintech tools.

Machine-based trading will continue to gain traction, especially for what one roundtable participant described as “low-risk, low-value trades.”

Trading desks “need humans — we’re the pilots of the airplane,” another participant said. “We can put things on autopilot, but we need humans. Technology is there to scale the stuff we don’t need to deal with.”

The mix may change over time, but trading will always be man plus machine, not just one or the other.

“Humans create technology to extract away all the tedious things that humans are good at the first 10 times, but then they’re terrible at,” said one participant. “Technology can run with that, and when something’s not going well, it gives the human the context they need to engage. That paradigm works.”

MiFID II’s Impact On The Trading Desk

GlobalTrading

August 14, 2018

By Fabien Oreve, Global Head of Trading, Candriam

Market fragmentation and tougher trade execution reporting requirements compel greater investment in technology and also a more stringent selection of brokers.

A major intention of the Markets in Financial Instruments Directive (MiFID) II is to improve the transparency of financial markets, and hence ensure greater justification of best execution for each major asset class. This dual objective of transparency and justification is not one that market participants always find easy to meet; one of the biggest obstacles is growing market fragmentation and another, the degree of technological investment required.

Managing market fragmentation

The Candriam trading desk began by revamping its procedures, strengthening order-execution processes by providing greater detail and case studies. It designed a more detailed execution policy with decision trees to identify best execution from pre-trade to post-trade. For example, we now describe in greater detail how pre-trade indicators feed into the broker-selection and best-execution processes. Data-driven decision-making is a key aspect of this evolution.

The desk streamlined its lists of brokers and platform providers in order to focus on key partners who know our business inside out. Naturally broker lists have been reduced, in particular for equities. In each business category, we have retained a limited and balanced number of brokers, which entails excluding those we perceive as having no added value. With more reporting obligations and justification exercises, we have tried to streamline connections, focusing on “one-stop shop” brokers and platforms that offer easy access to liquidity. The core list of brokers has been complemented by a group of specialists to cater for more specific business activities.

In keeping with the spirit of MiFID II, amid greater market fragmentation, the desk has tried to gain agility in the way it manages equity orders across markets through dynamic multi-placement. Our order and execution management system (OEMS) provides a functionality to split a single order by the number of venues and brokers it has been placed with. We can take advantage of any potential increased liquidity through the OEMS. For example, the original order placed with broker “A” on lit venues is automatically reduced in our system if a portion of the order is matched with a natural block offered by broker “B”.

With the return of market volatility, we have recently been trading more in emergency mode and relied on systematic internalisers (SIs) to reduce the timing risk. We tend to focus on our large brokers, who facilitate trading for orders in their entirety. The selected brokers are typically those who have made major upgrades to their central risk books, where they hedge positions more efficiently.

It’s uncertain as to which trading venues will benefit most from the new MiFID II rules, for instance, from dark pool restrictions, but agility for a buy-side dealing desk in executing orders across brokers and venues will certainly gain ground thanks to the OEMS.

New regulations have clearly led asset managers in general to make significant adjustments. These include upgrading their technology and gain efficiency in dealing, enhancing monitoring capabilities, sending legal entity identifiers to brokers and platforms, collecting more trade data and ensuring a more systematic approach to best execution.

We have also had to work on further automating our order dealing process in asset classes other than equities without compromising security or order execution quality. FIX connectivity, request-for-quote (RFQ) platforms for bonds, currencies and exchange traded funds as well as algorithmic trading for equities have already, to a certain extent, automated our trading desk.

However, we have never had full-scope automation as an option. Why? Because, for example, at the Candriam trading desk, sending an equity order to an algorithm is subject to strict conditions and written agreements with brokers on pre-trade constraints like maximum order value and maximum average daily volume percentages.

With today’s OEMSs, there is more room for automation and more opportunities to further streamline our trades. That is true for a portion of our futures and FX order flow. We have selected a multi-asset “algo” broker covering equities, futures and FX, and are currently working with the IT teams, legal, compliance and risk management departments to set up trading limits and to document and test new tools.

FX is an interesting large asset class where a majority of our flow is handled via electronic RFQs. For the most liquid currency pairs, our RFQ platform can be clearly complemented by other tools, such as time-weighted average price (TWAP) and by time- or price-trigger algorithms (equity-like trading mechanisms) to meet portfolio managers’ requirements. However, we do not see any interest in using electronic RFQs for cash equity, because we currently have easy access to indications of interest (IOIs) from those of our brokers who advertise reliable tradable sizes and prices.

Post-trade analysis

As a result of MIFID II, the main challenge with transaction cost analysis (TCA) lies in assessing and ranking brokers in a more rigorous, quantitative and yet non-complex fashion. Ranking brokers that have performed under similar scenarios is the first step to more easily identifying outperformers versus underperformers.

Another challenge is that of presenting meaningful post-trade data across the major asset classes: that includes fixed-income, which requires more manual analysis and verification than equities.

Candriam has been engaged in post-trade analysis for equities and fixed-income for a number of years. In the case of fixed-income, we internally built a tool that produces reports where each trade is compared against the losing quotes obtained from the RFQ process and the “composite” mid-price level at the time of execution. Of course, there are still market data issues for the most illiquid bonds, and this does not help transaction cost analysis but, we have managed to find a way to know our trading costs, business trends and outliers across different bond segments and sub-segments.

For any given bond category, our post-trade reports provide average bid-ask spreads and executed prices’ deviations versus. mid-price reference. These reports also help visualize top broker-dealers. Knowing top broker-dealers in specific segments is quite useful for fixed-income traders and helps them target counterparties.

As the scope for TCA has become far broader under MIFID II, we are also discussing potential new partnerships with multi-asset TCA providers covering equities, fixed income and FXs

Impact on trading desk organization

MiFID II promotes market transparency and greater convergence among asset classes. The new regulations are driving more order flows to electronic trading. While electronic trading technology is broadly used today, traditional trading methods still have a significant role to play. At the Candriam trading desk, traders have to work more horizontally and navigate between low-touch and high-touch trading channels, depending on order difficulty and market environment.

Having junior colleagues’ roles confined to low-touch trading only is not a satisfactory solution. Bringing together people with various backgrounds and diverse perspectives, training new employees to find the right balance between electronic and voice trading for specific orders in a particular asset class enhances professional growth and expertise.

Trading desks always need the flexibility of human traders to adapt to changing market conditions and achieve best execution. After all: “It is men who make a city, not walls or ships” (Thucydides).

Buy Side + FinTech + Big Data = ?

nicholas_greenland

August 7, 2018

By Nicholas Greenland, Managing Director, Global Head of Broker/Dealer Relations at BNY Mellon Investment Management

The rapid evolution of technology and the surging availability of datasets, means that assessing and choosing which products and firms to work with can be overwhelming, so industry cooperation is essential.

Asking people on the buy-side about Fintech – more specifically big data and machine learning – and its potential application to their business elicits a broad range of responses ranging from excitement and existing involvement, to frustration and the lack of belief that opportunities can be grasped.

I believe that the buy-side can be split into three pockets: those who believe there are great opportunities within big data and machine learning, those for whom it’s “just not in my business” and those who struggle to understand how this new technology can be relevant to them.

Summing up some of these challenges, Mahmood Noorani, founder of Quant-Insight, recently said: “We need to understand the question that we are trying to answer, not try to reverse engineer the question from the answer”. For many, such experiences have been quite the opposite, so the ability to both bridge business challenges and understand and deliver technology has never been more valuable.

Stepping back, the core belief (and at times, hope) articulated in conversations with buy-side peers is that alternative datasets and the evolving FinTech space can offer value by addressing not only our trading and investment management requirements, but also our clients’ needs. With this in mind, the broader issue is actually about identifying the right questions that need to be answered, searching for the right answers and then understanding how to execute on what is now possible.

This is against the backdrop of industry evolution, where some are now looking at whether the sell-side model of high-touch and low-touch trading makes sense for us. For the buy-side, the former is the focus for trade advisory/value creation (for example, research-led cross-asset liquidity consultancy and derivative implementation ideas) and the latter is more focussed on streamlining and scaling execution coupled with research (for example, how best to aggregate fragmented liquidity). Regardless, both approaches need to lever technology to meet their full potential.

Technology options
With these business drivers and with MiFID II stimulating changes in technology and trading processes, the question for many is: what else can we do to optimise and expand upon what we have? For example, do we need an execution management system (EMS)? If so, what is the best implementation strategy and technology solution?

The main options currently being discussed include adopting cross-asset platforms from an existing firm, an amalgamation of best of breed platforms, or leveraging container-like technology to create one’s own “trading app store”. The latter allows a bespoke cross-asset trading workstation to be delivered using components from separate providers and seems to be gaining mind-share as it promises greater levels of customisation above and beyond what is normally attainable.

It also allows for a flexible “swap in and out” of components as technology evolves and potential for faster delivery of solutions as these become available, for instance, as some sell-side firms look to expose some of their tool-sets. This is against the backdrop that few asset managers, with notable exceptions, consider building their own technology as being a true differentiator.

Regardless of the approach: do implementing new trading tools mean that all the questions will have been answered? No. The broad themes of data and tools for pre-trade and in-flight decision support (which may or may not be within an “out of the box” EMS), and other functionality to assist price formation for those wishing to be price-setters on all-to-all venues, will keep many on the buy-side focused internally for some time.
Looking externally, the question is actually what should and can we be doing together as an industry. I think there are two main areas:

Buy-side initiative
Firstly, given the rapid evolution of technology and the surging availability of datasets, assessing and choosing which products and firms to work with can be overwhelming. This is where the industry can work together through trade bodies, in partnership with specialist investment firms or with larger sell side firms, all of whom can curate such conversations for their own members, clients and partners.

By leveraging such organisations, the buy-side has the ability to hone in more rapidly on the Fintech firms that are ready to engage with sophisticated financial institutions, have correctly articulated opportunities facing our industry and have identified meaningful problems that they can help us solve.

The sell-side, for many years, has been at the vanguard of driving and paying for evolution in market structure and technology. It has had existing teams and demonstrable pedigree in collaborating with competitors to deliver mutual goals. For the cynic, this has been to support “just enough” innovation without too much disruption.

The buy-side however, has less pedigree with arguably fewer resources to do so. With some recent notable exceptions (for example, Luminex and Turquoise Plato), this has meant that we have historically relied upon the sell-side to facilitate collaboration to encourage innovation. Looking ahead, there is a real opportunity for buy-side firms to strategically collaborate and partner (including with the sell-side) to the benefit of its clients and industry.

So, secondly, I would encourage buy-side firms to articulate several problem sets, for instance around how best to enhance either high- or low touch trading, so we can actively collaborate to find the potential solutions. One recent suggestion is supporting initiatives such as OpenFin-led FDC3 to enable standardised connectivity for our industry’s desktop applications. It would then be up to the individual firms to follow their own path and add their edge through tailored implementation and use of such tools, including the input of carefully sourced and manipulated data sets.

Collaboration to foster evolution
Being part of a global multi-boutique investment management organisation, I am aware of the power of co-operation and scale that companies acting together can bring, as well as the importance of independence. The two are not mutually exclusive. I also believe members of trade bodies should utilise them as a forum for collaboration and to foster evolution in the market structure. Members are increasingly more proactive in their thoughts and feedback to the market and this is evident in the Investment Association’s position paper on “Last Look” in foreign exchange.

Long may the buy-side seek to collaborate ever more closely and proactively push for market evolution. This will help us all more clearly demonstrate that trading is a core part of the investment management process and that the industry is cooperating to act in the best interests of our clients.

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Fixed Income Trading: Big Data Boost

GlobalTrading

August 7, 2018

By Carl James, Global Head of Fixed Income Trading, Pictet Asset Management

Access to more data is improving the efficiency and raising the sophistication of the buyside fixed income trade execution process.

Fixed income buy-side firms increasingly have the capability to analyse data to achieve a better outcome for clients and to satisfy regulatory requirements. To some degree the reason is quite simple: until recently data was sparse, now it is becoming more and more abundant.

Banks make money when there is opacity, but regulators are forcing them to be more transparent about their activities, justify their fees and validate transaction pricing across asset classes. Moreover, sophisticated technology is getting cheaper which encourages disintermediation and disruption to traditional business models by new entrants. Banks and brokerages are compelled to respond, or else suffer shrinking market share.

The buy-side is in a similar position. The ineluctable rise of passive investing and the intrusion of robo-wealth advisers are piling pressure on established asset managers. Truly, the tectonic plates are shifting.

The technology needed to gather and make sense of the information and then derive recommendations is rapidly improving. Indeed, we have just launched a five-person trading technology team to take advantage of these new opportunities.

The information is generated internally and accumulated from external sources. The internal data accrues from messaging from counterparties, orders, trades and their hit ratios and a myriad other derivations and interpretations. External data, for instance, declared orders and reported trades, was previously proprietorial and therefore scarce or expensive, but is now widely available.

Although there isn’t yet a consolidated tape, measures such as the Trade Reporting and Compliance Engine (TRACE) for over-the-counter bond transactions in the US is a step in that direction. In the UK, the London Stock Exchange’s approved publication arrangement (APA) has raised the level of trade reporting in the fixed income markets, with some third party vendors now aggregating APAs. The product captures a significant part of the total market, and usually large enough to draw valid conclusions especially when used in conjunction with internal data.

Post-trade analysis is critical. As more data is available, a trader becomes better able to gauge whether they handled an order correctly (for example, a request for quote), whether they approached the best counterparty for a particular bond (through examination of hit-ratios) and whether they transacted at the optimum time in the day.

It is also worth emphasising that an important effect of the Markets in Financial Instruments Directive (MiFID) II is to ensure that a fixed income trader’s experience and intuition is underpinned by evidence. A decision to execute a trade and the process towards that decision must be seen to be rational.

Electronic and automated trading of liquid, benchmark bonds is evolving, with increasingly reliable and systematic recalibrations of constituent bond issues taking place. One obvious benefit for traders is that more bandwidth is created for them to deploy their skills and exploit their networks to concentrate on illiquid or esoteric bond issues.

Limits to machine learning effectiveness
Of course, the potential of artificial intelligence (AI) and machine learning (ML) for the trading process has attracted a lot of attention. However, despite the hype, their deployment in fund management in general is at a very early stage: there simply isn’t yet the commercial imperative for their application.

Portfolio managers might use ML to track a benchmark (either explicitly or covertly); traders might eventually find a use for ML if orders are delivered in a less sequential fashion than now. However, the fragmentary nature of the fixed income markets and, despite the proliferation of data, the still incomplete knowledge of all liquidity sources, different trading protocols, diverse instruments and partial price information inherent in an over-the-counter market limits the efficacy of ML in the trading process.

Furthermore, many bond issues trade infrequently. Although most European equities trade around 500 times a day, many bond issues rarely trade for days or even weeks. This, perhaps, is the most significant reason why ML has restricted relevance to the fixed income markets – at least, beyond the regularly traded, liquid benchmark issues which are more amenable to systematic trading.

The extensive use of algorithms caused a behavioural shift in the equities markets, by reducing the size of individual trades. Greater electronification of fixed income trading is also likely to lead to behavioural changes, as orders get focussed on more tightly defined data points and as the underlying process becomes more methodical.

The difficulty for buy-side firms is how to embrace new technologies successfully. There isn’t a standard model with an unambiguous record of success – partly because it’s too early to make an accurate assessment, and partly because many buy-side firms have historically relied (and in many cases still do) on the sell-side for technologies and systems, for instance their trading algorithms. In any case, the buy-side firms need to decide quickly – and must expect to fail as they experiment.

Ultimately, it’s only possible to solve problems and adapt to external innovations to the extent of your capabilities. As in the solution to the riddle, how do you eat an elephant? Answer: one bite at a time.

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Seizing Innovation In A New Era

GlobalTrading

August 7, 2018

By Rupert Walker, Managing Editor, GlobalTrading

The challenges and opportunities of new technologies preoccupied delegates at the recent FIX Asia Pacific Trading Summit.

The trading industry is in a race to devise and implement new technologies to gain a competitive edge, while recognising the importance of intra-firm collaboration to reduce costs and direct resources efficiently. Indeed, innovation and adapting to its consequences were major themes of the 16th FIX Asia Pacific Trading Summit held in Hong Kong on 10 May 2018.

In particular, blockchain technology and its operational functions are evolving rapidly, with new endeavours underway throughout the financial industry. Panellists in an early morning discussion shared their experiences form various projects, including the ASX Chess Replacement and Corda projects, as well as how they envisage deploying blockchain or distributed ledger technology within their business strategies.

“It was a wonderful discussion that examined blockchain based on real-world application in the financial industry,” said panel moderator Huayi Dong, Global Head of Electronic Trading Solutions at Daiwa Capital Markets.

Many firms are now moving from proof of concept to proof of value to determine whether or not to invest in the technology, and to assess the efficacy of its application. Practical issues such as interoperability and cost are central to the discussion, increasingly superseding conceptual or academic proselytising.

Elizabeth Stark, co-founder and CEO of Lightning Labs, argued in a keynote speech that the ascension of blockchain and cryptocurrencies is inexorable, and will help shape commerce in the near future. Her San Francisco-based company is tackling one the main deficiencies of digital currencies by developing an open protocol layer that leverages the power of blockchain and smart contracts to make fast, scalable transactions possible.

“Everyone is keen to see how the cryptocurrency market will evolve and institutional investing is likely to be the key factor,” said Avril Parkin, Head of Technical Relationship Management, North Asia, Thomson Reuters who introduced Ms Stark to a packed auditorium.

Operational challenges

The markets themselves are also posing challenges. For example, China’s capital markets are continuing to open up to international investors, and the inclusion of A-shares in the MSCI benchmark emerging market index has induced a sense of urgency to identify the best ways to gain exposure. China Stock Connect and the longer established QFII scheme are existing routes with respective merits as well as drawbacks, and the potential introduction of China depository receipts could offer easier access.

On the other hand, investor confidence and assurance is dulled by repeated instances of trading suspensions of A-shares by the Chinese authorities, especially when conducted in a manner that appears capricious, warned speakers on a panel assessing preparation for China’s MSCI inclusion.

In this environment, sell-side firms are experiencing greater competition while faced with increased demands from clients to adopt new technologies, implement multi-asset services and reduce and be accountable for costs.

Brokerages need to consider different ways to improve their services to clients and optimise their own operating models, concluded a panel discussing emerging trends for the sell-side.

Speakers reflected on the rate of margin compression affecting their businesses while under pressure to invest and innovate as trading complexity increases. The industry clearly needs to ascertain the appropriate payment model and pricing levels to offset the burdens of regulatory compliance and continual system upgrades.

“This panel revealed how ‘best ex’ obligations have led to a greater focus by the sell-side on the cost of providing different levels of service, and by the buy-side on who and what they want to pay for, and what it is worth to them,” said Mark Northwood, Founder, Bips Global, the panel moderator.

One solution, often proposed by buy-side firms, is the provision of utility-like entities that offer basic, essential services such as risk management and trade processing where there is a limited competitive imperative for individual brokerages to provide separate facilities.

New opportunities

Meanwhile, the buy-side is entering a new dawn, with expectations of the rapid growth of new technologies and promises of intellectual satisfaction for a younger generation entering the industry.

Indeed, “embracing data science and innovation on the trading desk is essential in order to meet the industry’s future challenges, from front office to operation and compliance,” said Stephane Loiseau, Managing Director, Head of Cash Equities & Global Execution Services – Asia Pacific, Societe Generale – Global Markets who moderated a panel that discussed “The Future of Trading”.

Traders will do more than complement automated processes, artificial intelligence and machine learning; instead they will them through the application of different, adaptive skills, expertise and initiative. It should be an exciting future for young professionals entering the trading industry.

“It was great allowing new faces on the Next Gen Leaders panel to reflect on career paths and offer intelligence on what strengths and qualities are required to be a leader in today’s electronic trading world,” said Dillon McNiven, Executive Director, Head of Electronic Trading, Asia Pacific, Instinet who moderated a discussion called “Up Next: Next Generation Leaders”, which included an impressive panel of speakers who will take the FIX Community to its next stage of development.

Viewpoint : Corporate credit : Edward Perks

Ian Rycott

August 2, 2018

REVISITING CORPORATE CREDIT AMIDST MARKET VOLATILITY.

By Edward Perks (Executive Vice President, Chief Investment Officer, Franklin Templeton Multi-Asset Solutions)

In 2018, rising inflation, higher US interest rates and escalating trade tensions have led to concerns about global economic growth and bouts of equity-market volatility. However, Ed Perks, CIO of Franklin Templeton Multi-Asset Solutions, says corporate credit has been a bright spot for fixed income investors. He gives his outlook for the global economy and explains why he still sees value in select high-yield bonds.

As we head into the latter half of 2018, rising inflation and higher US interest rates―against a backdrop of intensifying global trade tensions and widening tariffs―have begun to pose challenges for many developed and emerging-market economies. As a result, many investors could be wondering about our outlook for global growth and its influence on our investment decisions.

Despite these issues, and weakness in a number of confidence indicators, we think the balance of economic news and data remains supportive. We continue to expect positive global economic growth led by a US economy that appears to be in relatively good health.

Midsummer Outlook for Inflation and US Interest Rates

We do not see inflation as a meaningful factor just yet in the United States. What we see with inflation today is a return to normalisation after the global financial crisis.

Our view is that inflation will continue to tick up, but the increase is apt to be very gradual. The primary forces that have kept inflation muted—globalisation and technological innovation—are still in place and should continue to have a restraining influence, in our view.

In the United States, labour-market strength has continued while generating what we believe are manageable increases in labour costs as job openings have exceeded the number of unemployed. We think increasing costs, particularly wages, are likely to be only a modest drag on profit margins.

What’s more, we think US corporate profits―supported by business spending and expanding manufacturing activity―are likely to be strong and hold the potential to be conducive to further interest-rate hikes.

Will Trade Disputes Affect Global Growth?

We think it is important to acknowledge that fears of protectionism are not new and have been with us in many parts of the world during the current economic expansion. At this stage, the likelihood of a full-scale retaliatory trade war appears at least partially contained as world leaders continue to seek productive solutions, but the escalating conflicts that we saw in the spring and early summer remain a risk. On the whole, we do not see international trade coming to a standstill or the global economy toppling into recession in the near term.

We hold this view even as the US yield curve, which is a graphical representation of the difference between interest rates on short-term and long-term US government bonds, has been flattening as shorter-term rates have been rising more quickly than longer-term rates. Although we think it is perfectly normal for yields to rise along with stocks, this metric is closely watched due to its apparent predictive value—every recession in the past 60 years has been preceded by the yield curve inverting, or falling below zero.

As the chart below shows, the gap between two-year and 10-year Treasury notes narrowed to roughly 30 basis points in June, and the yield curve compressed to a level not seen since 2007.

Implications for Fixed Income Investments

Corporate credit has been resilient, even in the face of rising US interest rates. Although we have seen volatility pickup this year in equities, credit has performed pretty well, in particular below-investment-grade corporate bonds (those rated below BBB- by independent credit rating agency Standard & Poor’s).

Certainly the length of the economic cycle―now entering its tenth year of expansion in the United States alone―factors into our decision-making. Should this elongated economic cycle start to show some typical end-of-cycle signs, such as slowing earnings momentum or inverted yield curves, we would expect to see related shifts in our portfolio positioning.

In the fixed income space, we have been focusing a bit more on the shorter end of the yield curve, and hold a generally positive bias towards corporate credit because we continue to think the fundamental backdrop remains very supportive.

The yield on the two-year US Treasury note has risen from 1.89% to 2.52% in the first half of 2018. Furthermore, the gap between yields on high-yield bonds and those on US government debt has narrowed this year, even as the spread between highly rated debt and Treasuries has widened.

Within some of our income-oriented portfolios, as certain high-yield corporate bonds and equities appeared to reach our estimates of full valuation, we have established positions in short-duration US Treasuries in the one- to five-year range, given the recent increase in yields in those categories. Importantly, we believe this will provide flexibility during periods of potential volatility in the second half of 2018.

We are seeing firsthand how thriving corporate profitability has supported select corporate bonds at the fundamental level, seemingly in defiance of more aggressive US Federal Reserve policy and political and geopolitical challenges. Many such securities are closely geared towards the strength of the US economy.

Distress in the high-yield corporate bond market remains idiosyncratic, not widespread, across sectors. Moreover, based on our analysis, speculative-grade debt defaults have been trending down while being eclipsed by an uptrend in corporate bond analysts’ credit-quality upgrades, and the near-term credit outlook amongst high-yield companies is generally benign.

Looking Ahead

As in 2017, our bias so far this year has been towards shorter- and intermediate-term maturities. In general, companies continue to be highly focused on any of their upcoming maturities, and so those shorter maturities may be able to perform better even in a period of volatility.

That said, we continue to look for signs of default risk before it is priced into the corporate bond market. These warning signs would potentially surface from a deterioration in fundamentals, including the issuer’s total leverage (debt-to-cash-flow ratio) and interest coverage measured by annual cash flow generation to annual interest expense.

As investors in corporate bonds and bank loans, we want to be very particular about the types of companies that we are lending to or purchasing the debt of, and we also want to be highly targeted about where in their capital structure we are positioning ourselves.

For more comment from Franklin Templeton CLICK HERE.

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Adapting To Constant Change

GlobalTrading

July 31, 2018

By Neil Bond, Partner, Equity Dealer, Ardevora Asset Management

In an evolving trading landscape, the buy-side needs to embrace technologies to extract liquidity wherever they find it.

Exchanges have been around for a great many years and will likely be around for many more. They play a crucial role in the listing of securities, but are also secure trading places, and data vendors. They have not remained unchallenged even if the politicians seem to be aligned with their interests, and they have had to evolve. Recently we have seen IEX enter the trading, listing and data arena.

Spotify has also come to market avoiding the traditional channels. So the primary exchanges need to keep on their toes which they have been doing by way of conditional order type venues for large-in-scale (LIS) orders and periodic auctions for smaller orders.

The MiFID changes this year have been the most dramatic to the UK market since “Big Bang” in the 1980s when trading left the floor and went screen based. So, what do traders need to keep up in this constantly changing trading landscape?

I believe that new technologies and trading styles and venues need to be embraced. One thing that does seem to remain constant is a trader’s need to source liquidity. The trend toward passive investing has had a somewhat detrimental effect on liquidity, with stocks being bought and sent to the index trackers’ vaults, unlikely to see the order book again for years.

In the past, you could ask a market maker and be quoted a reasonable size (maybe “a penny out in a hundred”), but that was when balance sheets were healthy and accessible, spreads were wide and commissions were high. Market makers cannot operate like that anymore and instead of making thousands of pounds in a large trade, have to make the same amount but over thousands of trades. We need to understand what the costs are when accessing the liquidity and the price of urgency.

The resurgence of quant fund managers could also create a vein of liquidity that has been absent since the quant crisis of 2007, when some of the smartest fund managers suffered unprecedented losses. The use of artificial intelligence in stock selection is increasingly popular, but caution is needed in the form of human supervision and intervention to avoid a crash. The data available now has increased immensely and processing power has also accelerated greatly. Many of the tools that traders dreamt of are now a reality and help us not only make informed decisions but also demonstrate how we arrived at those decisions.

Where trading commissions are fully segregated from research payments, traders can freely trade where they find best execution and use sophisticated tools to aid them in their broker/venue selection analysis. At a glance now I can see a host of visuals together on a dashboard that explain the factors that determine whether or not putting a block together at current levels is the right price.

Two-tier market
We seem to be transitioning to a two-tier market place where one set of trading strategies is needed for larger orders and a completely different set for sub-LIS orders. The options for block trading are well catered for by high touch sales traders, conditional venues and the traditional block crossing venues POSIT & Liquidnet. For sub-LIS trades things get a little more complicated. It is a world frequented by high frequency traders and electronic liquidity providers who tend to have extremely short holding periods, but they are trying to convince the world that they want to trade larger sizes and hold positions for longer.

Understanding the toxicity (normally measured by market impact and reversion) has become a core requirement for traders who now have to decide between the lit market, dark pools (assuming double volume caps are not in effect), periodic auctions and systematic internalisers (SIs) for their smaller orders.

Increased transparency was one of the aims of MiFID II, and one area where this has succeeded is giving buy-side traders more granularity into the counterparties they are trading against. Some larger money managers have trading volumes big enough to gather the data in order to make educated decisions.

However, most of us do not have a large enough data set to do this and still rely on data collection and analysis from our brokers. The selection of trading venues, particularly non-bank SIs needs to be approached quantitatively – some may have strengths in small- and mid-cap stocks, others may have strengths in particular regions or sectors.

Now that all trading data has to be reported, it would be nice to think we could end up with a consolidated tape that would be beneficial to all market participants, but for that to happen data costs would need to be addressed and these revenue streams are proving to be an insurmountable hurdle.

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VWAP Trap: Volatility And The Perils Of Strategy Selection

GlobalTrading

July 31, 2018

By Erin Stanton, Managing Director, Trading Analytics, ITG

Historical performance indicates that traders should reduce their use of VWAP strategies during spikes in market volatility.

When it comes to improving trading performance, selecting the right strategy is crucial. An ITG survey of buy-side traders last year found that 85% believe strategy selection has the most potential to affect trading performance, far outstripping the importance of broker choice or venue selection. But before traders choose a strategy, they would be well served to consider prevailing market conditions.

The relationship between algorithmic trading strategies, trading costs and volatility has been well documented, including in a 2011 paper by Ian Domowitz. Domowitz found that usage of a VWAP strategy in a high-volatility environment added an eyebrow-raising 18 basis points (bp) of impact costs versus a VWAP trade executed in a low-volatility environment.

We employed a similar analytical framework leveraging ITG’s broker-neutral algo Global Peer database, focusing on two recent periods in the US with differing market conditions, as measured by ITG’s Smart Market Indicators (SMIs). Our SMIs compare current volume, volatility and spread to historical averages, allowing users to quickly identify abnormally favourable or unfavourable market conditions, and react to those conditions accordingly.

In October 2017, volatility measured by ITG’s SMIs was relatively normal at the 58th percentile, whereas in February 2018, SMI-measured volatility jumped to the 71st percentile.

Despite this observed shift in volatility, the general use of a VWAP strategy in the US remained quite consistent between the two time periods. During the more volatile period, liquidity-seeking algos were used less while implementation shortfall (IS) usage nearly doubled.

VWAP as an algo strategy is generally used to achieve two objectives: 1) to implement a trading strategy that minimizes costs against a VWAP benchmark, and 2) to take an in-line approach to implementation against an arrival benchmark. Irrespective of the driver behind the selection of a VWAP algo, during the more volatile period costs increased by two times against the VWAP benchmark and nearly three times against the IS benchmark. Recognizing that VWAP as a strategy can be affected by single outlier trades, we also reviewed the median IS costs, which increased from -1.3bps to -4bps.

Parallels in Asia Pacific trading
We took a similar look last year at the use of VWAP in Asia Pacific trading around the extreme volatility events of Brexit and the 2016 US election. We observed that VWAP use spiked from a typical level of 10% to around 30% during the high-volatility periods caused by specific market events. This increase came at a cost. Compared against a VWAP benchmark, the difference between low-volatility and high-volatility periods was a significant 2.7bps. And while the difference in cost against an IS benchmark between an implementation shortfall algo and a VWAP algo became less pronounced, the standard deviation of cost became much wider for VWAP trades in Asia Pacific trading.

Algo performance evaluation should not consider just the cost of what was executed, but should also consider the opportunity cost for what does not get completed. Without considering the number of shares left on the table, we would say that in the lower volatility environment of October, VWAP was still the most expensive strategy in US trading. But when considering the total cost of the order, including the unfilled shares, we can see that IS was the most expensive strategy, averaging 18bps of slippage (unfilled shares were priced using the trade date close and benchmarked against IS). This picture changes in the higher-volatility regime of February, though. Total costs for all strategies, except IS, increased between October and February, while VWAP spikes to -28bps of total implementation cost.

No herd immunity
It is difficult to offer a definitive reason for the continued use of underperforming VWAP strategies during periods of higher volatility. It is possible that some traders are focused on working more difficult parts of their order books and they seek to put some trades on a “participate without too much risk” setting through VWAP. It is also possible that traders looking to remain in line with their index benchmarks are hopeful that VWAP is the best way to preserve that correlation when trading conditions are unfavourable.

Even if this year doesn’t see the same return of volatility that some are predicting, traders would be well served to consider lightening up on use of VWAP strategies during any sharp spikes in volatility, because an “in-line” print can result in sub-par trading performance.

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Industry Warning: Is your Brokerage Compliant? New ESMA rules to take effect on August 1

Ian Rycott

July 31, 2018

INDUSTRY WARNING: IS YOUR BROKERAGE COMPLIANT? NEW ESMA RULES TO TAKE EFFECT ON AUGUST 1.

An industry-wide legislation set forth by the European Securities and Markets Authorities (ESMA) has called for a temporary restriction of the marketing, distribution or sale of contracts for differences (CFDs) to retail clients. The new measures which will take effect on August 1^st2018 will consist of:

leverage restrictions according to asset type
margin close-out rules
negative balance protection
a limit of CFD marketing

FOR MORE INFORMATION – CLICK HERE

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REVISITING CORPORATE CREDIT AMIDST MARKET VOLATILITY.

By Edward Perks (Executive Vice President, Chief Investment Officer, Franklin Templeton Multi-Asset Solutions)

INDUSTRY WARNING: IS YOUR BROKERAGE COMPLIANT? NEW ESMA RULES TO TAKE EFFECT ON AUGUST 1.

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