It’s 2013 already and we’re still talking about regulating high frequency trading (HFT) in the absence of data quality and standards conversations. That needs to change.
2012 seemed like the year of regulators taking a prolonged look at computer trading – defining what it might be, its potential effects, and why it may be problematic. Looking at where we are now, it is still far from clear that we have answers to these fundamental questions.
Regardless, HFT has become a national obsession, resulting in a complex and divergent landscape for those trying to move the invisible hand.
Those who are aiming to come up with a singular view will find it difficult. The Germans are pushing ahead with licensing and minimum time orders ahead of an already delayed MiFID II, apparently including circuit breakers, organised trading facilities and minimum tick sizes. The CFTC is still musing over a “concept release” of HFT regulation, with a fledgling definition and FINRA has announced in 2013 it will use “examinations and targeted investigations” to ensure firms have adequate “testing and controls” related to HFT and algos. How these controls will work without a robust set of trading workflows and identification requirements is a question which should be keeping ESMA awake at night.
The UK’s long awaited set of answers didn’t appear last year. Highlighting the controversy that follows HFT wherever it goes, the Foresight Commission’s weighty computer trading study had fewer practical suggestions than expected. Perhaps even worse, aspersions have been cast from some quarters about conflicts of interest, its highly academic nature, and its methodology and data set.
This confused regulatory space is ignoring one indisputable fact: HFT is part of the financial system and it is not going to go away. Politicians, in their drive to make markets safer without concentrating on real underlying issues, are in danger of introducing poorly conceived controls that don’t get the job – whatever that is meant to be – done. The bottom line is that trading is a technical arms race and regulators will therefore always be one step behind.
In light of this, regulators and the industry must concentrate on not only defining what exactly HFT is, but also refining data collection, aggregation and analysis to balance political demands for market safety, without stifling capital allocation. This will require examining the market infrastructures that facilitate computer trading and the trade information they produce. With many other regulatory initiatives also struggling with issues of data collection, aggregation and analysis, regulators should ensure that HFT features in the larger conversations on standards and data quality.
Shining a light onto the issue, the FSA has provided the industry with valuable insight into the depth of this problem. In its January paper, entitled ‘High Frequency Trading and the Execution Costs of Institutional Investors’, it takes a more practical approach in examining HFT by comparing 30 days of trading data. The diagnosis at the centre of the report is that regulators do not have the data required to regulate, nor the standards to make this data truly useable.
The report begins on a well-known theme: the lack of a common definition of HFT making it difficult to be sure the scope of the trading activity is adequately captured. This data was then juxtaposed to HFT data from exchanges, held by the FSA. Huge discrepancies over the course of a year are apparent, with the FSA data detailing 70-80% of HFT at the beginning of 2010 and only 40% by end 2010. The reason? Unregulated HFTs are “not observed”, and firms that have HFTs that are not regulated under MiFID do not need to report. The report concludes this is “not a fair representation of true HFT activity”.
The report does, however, identify another key roadblock to an accurate representation of HFT activity – poor data quality. Some examples include trading time inconsistencies between FSA and exchange clocks, misreporting of counterparty codes, instrument and venue data and only trades reported with BIC codes able to be identified.
Without a robust understanding of HFT, regulators and politicians will be unable to regulate effectively in both their own interests and the interests of the industry. They must begin by collecting and aggregating a robust data set, based on common units of measurement, such as tick sizes and minimum resting times. While there is potential for this to be mandated in MiFID II, and it is supported by the Foresight Commission, the lack of global agreement on these requirements will result in traders taking advantage of regulatory inconsistencies. Therefore, a more practice-based, unified definition of HFT must be crafted, that will finally allow regulators to focus on the practices they wish to control.
As supported by the FSA’s research, HFT must also be included in discussions over identifiers, a mix of which is creating a convoluted landscape today, and market conduct specialists could benefit heavily from uniform standards, such as the legal entity identifier (LEI).
The ultimate key to success for these efforts will be getting the right people around the table, including exchanges, traders, regulators and academics, to offer the right balance between theory and practice. Through this cross-industry collaboration, the confusion over what HFT is, and the problems in obtaining quality, standardised data to solve the problem can finally be addressed. To get this right, all major markets need to sitting at this table, which is still waiting to be set for the discussion.
“This article is provided for information purposes only. Nothing herein should be construed as legal or other professional advice or be relied upon as such. Text and artwork remains the copyright of JWG”
HFT: Time to talk about how?
Emerging Markets : Accessibility
CARPE DIEM.
Investor appetite for emerging markets remained buoyant during 2012 and technology enhancements aiding access to a number of developing markets will be continue to be key themes during 2013, writes Roger Aitken.
Emerging markets, which as a term was first brought into fashion in the 1980s by then World Bank economist Antoine van Agtmael, is sometimes loosely used as a replacement for emerging economies. Today the seven largest emerging and developing economies by GDP today are China, Brazil, Russia, India, Mexico, Indonesia, and Turkey.
Investment across emerging markets has been robust of late, as evidenced by emerging market hedge fund capital reaching US$121bn during Q1 2011. According to Morgan Stanley Capital International (MSCI), which launched the first Emerging Markets Index covering 21 countries in 1988, the global equity opportunity set had risen to 14% in 2010 (1988 = 1%).
Per Lovén, Head of Corporate Strategy, EMEA, Liquidnet, a global institutional trading network, says: “There is a growing desire from institutional investors in the western world, who hold 85% of all investable assets, to increase exposure towards equity markets of fast-growing economies which, historically, have been under-invested.”
Some emerging markets have even started to become hubs for other markets and a new generation of algorithms based on liquidity seeking strategies well suited to emerging market environments is helping matters.
Russian market interest has been propelled by the success of London Stock Exchange’s International Order Book (IOB), where today 34 Russian companies have their GDR’s (Global Depository Receipts) traded through an IOB universe of 127 companies. Stocks like Russia’s Gazprom recorded over US$6bn in trade value in November 2012 on the IOB.
Ben Wood, Managing Director, Head of International DMA at Otkritie Capital based in London, an FSA regulated broker, says: “Interest from investors in the Russian markets is definitely improving. With the merger of RTS Forts and Micex to form the Moscow Exchange, all asset classes – futures, derivatives, FX and equities – are now under one banner.”
The combination of Russia’s two exchanges (RTS Forts/Micex) into Moscow Exchange, originally announced in December 2011, benefits market participants by creating a single platform for issuers, traders and investors. It will reduce transaction costs, make trading easier and facilitate product innovation.
The move comes as technology access to Moscow Exchange was beefed up through its new M1 datacentre following an upgrade and relocation of its exchange matching engines in November 2012.
Otkritie’s brokerage division has diverse client base trading Russian securities spanning traditional asset managers, high frequency trading (HFT) firms and broker dealers. “All these players are trading across all asset classes in Russia,” says Wood. Firms can be engaged in arbitrage opportunities between stocks on Micex and the LSE’s IOB or be pursuing certain cross-asset strategies.
“Traditional asset managers typically require a FIX connection to route orders to a desk, while broker-dealers need Direct Market Access (DMA) due to their latency sensitivity, and hedge funds and HFT houses with extreme latency sensitivity require co-location services that Otkritie offers.”
While trading volumes for Russian equities are down this year over 2011, Wood says that the “exciting story” in 2012 has been the growth of the RTS index futures. As the ninth largest futures contract traded by volume globally (c.1.5m daily contracts), it is one of only two index contracts where volumes increased in 2012 over the previous year.
Russian market reforms
In one of the latest reforms designed to increase accessibility of the local markets for foreign investors, Euroclear Bank was granted by access to Russia’s central securities depository (CSD) on 3 October 2012.
This development, which allows Euroclear to offer post-trade settlement services in Russia and supports market stability, opened the channel for a significant uptick in foreign investor participation the country’s domestic bond market. Until this point non-resident holdings of domestic Russian government bonds (OFZs) had been at below 10% – lagging emerging world peers.
The merged exchange will act as a catalyst for continued improvements in Russia’s financial infrastructure, including settlement in T+N.” (‘N’ denoting number of days).
“Additionally a project for T+2 settlement has commenced, with a loose timetable for Q2 2013,” reveals Wood. “They intend to parallel run the top 10 liquid stocks.” The settlement period in Russia currently is T0, which requires investors to have pre-deposit in place.
“Clearly T0 is a barrier as having the stock [in Moscow] at exchange or the money to exchange means it’s difficult for non-domestic investors to have that infrastructure in place,” notes Wood. To that end Otkritie has an appetite for either lending assets or money and to brokerage the client base.
He adds: “We’re also taking it further to provide a ‘T+N’ US$-settled transaction on Micex, so market participants will be able to choose their settlement cycle. That should appeal to the wide range of investors interested in this market.” Otkritie’s acquisition of Russia’s Nomos Bank will likely provide a boost on the lending front as it ranks them number two in the country’s non-state owned private lending market.
Peter van Wely, Head of InfoReach Europe, an independent provider of multi- and cross-asset, broker-neutral solutions for electronic, algorithmic and HFT analysis and execution of global equities, derivatives and FX, says: “We’re see seeing interest from US and European buy- and sell-side institutions looking increasingly at emerging markets generally and Russia in particular.”
Back in April the Chicago-headquartered software vendor announced it had expanded its global footprint with connectivity to Russian markets through Micex/RTS. As such their clients were able to route equities, options and futures trade orders directly to the exchange using InfoReach’s electronic platform (the InfoReach FIX Network).
He adds: “The importance of Russia and Moscow as a financial centre – not just in and out – but also long term, for the growth of the financial sector there will grow proportionately more than an average market in western Europe. There is also nascent interest from among Russia institutions to invest in technology and trade markets outside their country.”
Van Wely also notes a “big problem” centres on pre-trade risk controls, where not all the checks and balances are necessarily always in place to prevent mishaps at the front end. In this regard the vendor has undertaken significant recent work in this area and counts Russian firm Nord Capital among its clients.
More markets, more asset classes
Liquidnet, which today operates in 41 markets globally has in recent years increased the pace of its expansion into emerging markets to include Turkey, the Philippines, Indonesia and Malaysia. On 23 July 2012 Liquidnet announced that institutional investors were now able to trade Turkish listed securities through its platform.
Liquidnet’s Lovén says: “Institutional investors looking to unlock value in Turkish growth companies will now be able to source large-scale liquidity in those equities, with minimal market impact, through our trading network.”
Sandy White, Emerging Markets and High-Yield Product Manager, MarketAxess, in New York commenting on fixed-income landscape in Latin America, says: “For three years in a row we have witnessed overall growth in the 30%-40% range in terms of trading volumes for our emerging market fixed-income products – both for external and locally trade debt [sovereign and corporate].” For 2012 White anticipates emerging growth for the firm will end c.35% higher than 2011 volumes.
MarketAxess’ Emerging Market trading platform [Actives screen] provides liquidity from thirty leading emerging markets dealers on sovereign and corporate debt offering dynamic trade inquiry routing to dealer trading desks based in New York, London as well as the likes of São Paulo, Mexico City, Hong Kong, Moscow and Istanbul. MarketAxess’ Request For Quote (RFQ) model has also been enhanced to offer investors a ‘Click-to-Trade’ facility.
“Brazil and Mexico are still logically where the greatest opportunities reside being as they are the largest local debt markets in the emerging world. It’s also where we have gained the most transaction,” says White. “Local debt is definitely a growing part of the story and accelerating. Close to 10% of our business now, a year ago it was below 5%.”
One impediment in Brazil facing foreign investors currently is an upfront 6% tax (IOF) on money coming into the country to investing in fixed-income securities. White says: “It’s definitely slowing down the growth of foreign investment in the local [Brazilian] debt market. However, we believe this to be a temporary situation.”
Investors can also access fixed-income products in Argentina, Colombia, Chile, Peru and Uruguay through MarketAxess, though presently only for the global debt denominated in local currency and settled in US dollars.
©BestExecution
FX Focus : Exchange trading
GAME CHANGER?
London-based LMAX Exchange, the first FSA regulated MTF for FX and metals, aims to bring market participants together in an anonymous, order-driven, and fully transparent manner. Best Execution asked David Mercer* what impact his business model has on delivering best execution in FX trading and to what degree this strategy anticipates future regulatory changes.
MiFID I attempted to define “best execution” for the equities market, but MiFID II failed to develop it further. In this context, what are the key differences between these two asset classes, and how would you define best execution in FX?
FX is the last major asset class to move to exchange trading. The regulatory proposals, such as MiFID II and Dodd Frank, are driving this change by requiring pre- and post-trade transparency and centralised clearing for standard FX derivatives.
LMAX Exchange is the first FSA regulated MTF for FX and metals. It was established based on the vision that the exchange execution model is the most efficient and cost effective way to trade liquid products, such as spot FX. The exchange execution model is at the core of an MTF concept; just as on an exchange, orders are matched in price/time priority but trading is still bi-lateral with FX trades cleared through the prime broker network.
By offering an exchange style execution for spot FX, we address key industry challenges such as the lack of transparency of the true cost of OTC traded FX, and the lack of precise, consistent & reliable execution in FX trading.
How does your business model aim to achieve best execution, and can this be improved upon?
In the context of a single platform we achieve best execution for spot FX by delivering precise, consistent execution, pre- and post-trade transparency and a level playing field for all market participants. Unlike brokers, we don’t run risk to make money but just match orders, and we are different from ECNs in that the execution is order-driven against streamed, executable limit orders supplied by the general members, who don’t have the “last look” and ability to re-quote.
In addition, as an FSA regulated MTF, LMAX Exchange complies with the following MiFID obligations:
• Pre-trade and post-trade transparency – deals are published to all members;
• Prices and charges are public and applied consistently across all members;
• Operating principles and membership rules are described in the publicly available rulebook.
Given the competitiveness of the FX market and increasing fragmentation of liquidity, we focus on continuously improving the trading experience for both clients and liquidity providers. We invest in technology to further improve execution performance and increase liquidity by adding new general members.
You have been quoted as saying that your greatest strength is technology, and that you employ “disruptive” technology. What exactly do you mean by disruptive technology and what is the competitive edge it confers?
Our technology enables reliable, ultra-low latency execution. To date, we have the fastest FX trading technology with an average trade latency of under 3 milliseconds and internal exchange latency of 500 microseconds. In-house developed ‘Disruptor’ technology, partially Open Source, refers to our ultra-low latency matching engine that has been developed to maximise performance and has been recognised by the industry’s most prestigious awards – ‘Best Trading System’ at the Financial Sector Technology (FST) Awards and Oracle’s ‘Duke’s Choice’ Innovative Programming Framework award.
The buyside have traditionally not been early adopters of new technology or new platforms. How do you intend to win them over to your offering?
We only started focusing on the institutional FX segment a year ago and now over 50% of volumes are traded by buyside institutions – represented by proprietary trading firms, money managers and broker dealers hedging risk. These volumes are rising every month. Yes, it takes longer to get institutional buyside clients on-board, but once they start trading they stay because of the transparency, precision, consistency in execution and low latency that the platform delivers. The proof is our growth momentum in the industry – for the last 12 months our overall volumes and revenues have been growing consistently at over 20% per month.
Is your business model capable of stimulating demand from the buyside, and if so how?
Absolutely. New buyside relationships can be acquired directly, or through independent corporate brokers/agents, who advise buyside clients on best execution.
Your current structure would allow you to apply to be an SEF (Swap Execution Facility in the USA) or OTF (Organised Trading Facility in Europe). Is this where you expect the regulations to take you, and if so over what time frame?
Among FX products we currently offers only spot FX, which are out of scope for Dodd-Frank and MiFID II. However, if we were to offer non-spot FX, such as FX swaps and non-deliverable forward (NDF), we can apply to become a SEF in the US. If we pursue the strategy of product diversification, this is something that we may consider.
What opportunities do you see in becoming and SEF/OTF?
The opportunity is big. In my understanding more than half of the total US$4.4 trillion in FX daily trading volumes is subject to Dodd-Frank and MiFID II.
Over the next five years, what other regulatory changes do you foresee?
We see a gradual move to exchange style execution, central clearing and greater transparency.
Where do you see LMAX Exchange in five years time?
Our goal is to become the leading FX venue with a global presence and multiple exchanges
*David Mercer, is CEO of LMAX Exchange. LMAX Exchange is the first FSA regulated MTF for spot FX. ©BestExecution 2012/13
FX Focus : TCA
TCA – NO ARGUMENT?
FX markets may lack the transparency of equity markets, but the asset class is gaining momentum. As a result attention is turning to transaction cost analysis to achieve best execution. Best Execution talks to Jim Cochrane* about the challenges.
What are the reasons that asset managers use TCA for Foreign Exchange now and will that change in the future?
Foreign Exchange TCA already has a past, present and future: compliance, best execution and process improvement. Of these three, compliance is the most basic (the past), best execution the most popular (the present) and process improvement the most advanced (the future). Peer group and pre-trade analysis will also be a greater part of the future as asset managers pay more attention to foreign exchange. The market will demand analytical systems that measure trades done electronically as well as those traded in more traditional venues such as over the phone or through custodians. Therefore, FX TCA will evolve to not only answer basic questions but will also change with advances in electronic trading such as the use of algorithms. However, the initial phase of FX TCA is still focused on compliance and best execution analysis.
Our firm plans on creating analytics for more advanced FX trading styles, as well as more sophisticated measurements for compliance, best execution and process improvement. Compliance measures can be developed in the future to include not only measures of daily weighted averages but also intraday measures of weighted averages tailored to a customer’s specific trading hours and various intraday benchmarks. It can also be flipped to measure trading performance within the daily or intraday ranges.
Asset managers rely heavily on best execution analysis, measuring trade performance using flexible benchmarks to exact timestamps. This service is extremely versatile, and is limited only by the creativity of the client and the FX TCA provider. It provides an excellent overview of trading costs by currency pair, counterparty, trade size and any other metric provided by the customer. The future of precise best execution analysis is founded in data. It is highly dependent on precise, copious, multi-source data and flexible benchmarks. As a consequence, we have invested heavily in market data to provide the best platform on which to base TCA.
Process improvement helps to measure implementation shortfall within the investment process. Once again, this is only limited by the timestamps that an asset manager can provide through their order management and execution management systems. Examples of these measurements are execution rate versus the portfolio management decision time or the order arrival time to the trader and FX broker. This analysis is the ultimate use of backward looking FX TCA. It provides the asset manager with the data necessary to make positive changes to the investment process.
With regards to pre-trade analysis, banks and trading platforms are beginning to offer this service in simple forms with very basic execution analysis. In the future, traders and portfolio managers will be provided online tools to pick the times of high liquidity and low volatility. FX TCA will help them decide which algorithm to use as well as measure the performance of that execution versus an estimate of market slippage if they had performed the trade live over the phone or in one order on a trading platform. As electronic trading reaches full penetration, algorithmic trading will become as popular in FX as it is in the stock market. Additionally, clients are demanding peer group analysis of their transaction costs. Along with pre-trade measures, these are the next logical steps in any TCA program.
On what do you base your vision of FX TCA evolution?
ITG is a market leader in equity TCA. We have been instrumental in the creation and advancement of all aspects of transaction cost analysis, working with the largest asset managers in the world. In the short time that FX TCA has been sought by the buy-side, those same steps we witnessed in the equity markets are being repeated in the FX market. Compliance review led to best execution measurement which in turn led to process improvement. At the same time, our clients demanded peer group analysis and pre-trade analytics. While we are not recreating the wheel, we are certainly following the same path to discovery. The next step in analysis will be peer group analysis and pre-trade TCA.
What is the biggest challenge to analysing foreign exchange transactions?
There are two: Accurate timestamps and precise data. Without an exchange, it is not possible to know what the official price is in the market for foreign exchange transactions, especially large or exotic transactions. Having a large set of data is the best way to overcome that handicap. The other complication is that if you do not have a precise timestamp for the trade, then the analysis will have to be directed away from precision and onto trends. Negotiated trading and custodial fills are the bane of accurate timestamps. Moving from negotiated trading over the phone to electronic and algorithmic trading can solve this challenge. Refusal to produce timestamps is the last refuge of some custodians. Client pressure on the banks, and perhaps regulation, are ways to solve that issue. The data problem is less difficult to master. We have solved it through negotiation and purchase of a very expensive set of data.
Most FX TCA products analyse spot trades. Is it possible to measure other transactions, including derivatives?
Absolutely. Prices for spot, forwards, swaps and non-deliverable forwards are available from multiple sources. Being able to analyse the data and apply it properly is the only difficulty provided you have the brains trust to develop a system to make the data match the execution, whether it is a cash trade or a derivative trade. FX TCA for options will also be available in the future but will require excellent data and a powerful option pricing engine.
What is the difference between trade cost analysis and execution analysis?
Execution analysis focuses on the trade in near-real time. It gives immediate feedback for the trader that he received the best price in the market given his pricing stream. It can also measure how much he gave away to choose another provider in order to manage liquidity and allocate trades across his board of FX providers. What it does not provide is a look at the monthly or quarterly trends across currency pairs, counterparties and trading styles. It shows you that you chose the best price among the prices that the banks on your trading platform allow you to see. A complete trade cost analysis shows you your trade executions across a long time period against all of the prices available in the market.
Do you worry that basic analysis will be overlooked?
Yes and no. In the beginning I feel that many institutions are merely asking for a “check in the box” solution to satisfy their fiduciary responsibilities. However, as I stated earlier, even basic analysis will reveal trends and raise questions. For example, a client might take satisfaction that they trade within the daily range, but question why they never outperform the daily average. That will lead them to demand better execution and they will need to measure this change in focus. Natural curiosity and a desire for higher returns will lead them to ask more penetrating questions regarding even the most basic analysis.
What market variables will real time analytics measure?
Real-time and near-real time analytics will measure volatility and liquidity in the first phase. Volume will not be possible to measure in the FX market. Liquidity will be estimated using bid/offer spreads. These measures challenge any analytical system because they are highly dependent on a system of opaque data. Once these measures are mastered, they immediately bring up the idea of predictive analysis. Will real-time measures help us predict transaction costs with great accuracy or the direction of the market? The latter has not been achieved yet in the equity market but the former has and can be attempted in the FX market.
Can you measure the difference in performance between a zero cost execution and an algorithmic trade?
Yes. That is possible if you have full depth of book in your data set and a precise timestamp. A zero cost execution would match the best available price, taking slippage into consideration. A 100mm trade in any currency pair would not get done at top of book, but a good system can account for that if the database is thorough. That adjusted price can be used as a benchmark for an algorithmic trade. A concurrent trading algo can be measured against the benchmark trade just described. Algos can be measured against a variety of benchmarks if your TCA system is flexible. It can be measured against the mid-rate at the time of execution, the best price (top of book) or the best expected price based on the depth of book. Each benchmark contains trade cost information which the client can use to evaluate their performance. ITG TCA for FX can tailor the system to meet any of the client’s analytical questions.
*Jim Cochrane is Director of Analytics at ITG. ITG is an independent research and execution broker that partners with global portfolio managers and traders to provide unique data-driven insights throughout the investment process. ©BestExecution 2012/13
FX Focus : Algo trading
ALGO TRADING IN FX.
Algorithmic trading in FX is a relatively new development but its not without its challenges. Best Execution speaks to Rob Weissman* for the inside view.
How would you characterise the FX market at present?
The FX market has been going through a unique transition in two facets: fragmentation and regulation. In the past year, the number of venues with which to trade FX and FX Options has grown dramatically, with at least five new ECNs starting up and a number of FX Option ECNs evolving. All of this growth in venues has occurred in the wake of lower overall volumes and the Dodd Frank regulation, which we expect to be enacted in the U.S. in early 2013. This will create challenges and opportunities in 2013 for most traders in finding the best destinations to trade, while adhering to regulatory requirements for FX Options, NDFs, and to a lesser extent, Forwards and Swaps.
How did algo trading develop in FX and are there parallels with its development in other asset classes such as equities?
Algo trading in FX has been growing steadily over the past few years relative to equities. Equities definitely led the way in algo trading, but because the rules of engagement are different in FX, algos have to be adapted for the specific nuances that occur in FX. An example of this is clear in trying to figure out where volume trades. As most FX destinations don’t publish trading volumes, it is not as transparent as equities. As such there is more customization required within the algos, based on the client’s liquidity sources.
What are the range and styles of algorithmic trading?
In general, the goals are to find the best liquidity sources with minimal market impact. In addition, a number of real money clients want to be able to execute against a benchmark to prove the enhancing value of their trading desk against just buying/selling at a specific time. Algos can be as simple as executing a trailing stop –with certain slippage attached – or as sophisticated as executing a multi-leg, multi-currency transaction, netted across multiple venues, based on the probability (historical standards) that you will receive better execution on one ECN versus “XYZ” bank.
How liquid an asset class is FX?
First of all, FX is a liquid asset class depending on the specific product that you are trading and when you are trading it. For instance, trying to trade one month Hungarian Forint in an Asian time zone could present some problems. When creating algos, one has to take into account the time zones they are trading, the venues in which they are trading, whether they want to be passive or aggressive and not to disrupt the individual venues, which could have a “ripple” effect on the overall market place.
What unique demands are there on algo trading technology for FX?
Algo trading technology has to take into consideration what the client wants to accomplish. Is it speed of execution, minimizing market impact, restricted broker/credit requirements, latency measurement, or multiple PB allocations across multiple funds? The algos have to be cognizant of all specific factors that the client deems important.
How would you define “Best Execution” in FX?
Best execution can be defined via TCA (Transaction Cost Analysis) tools that can analyse post trade how the client executed against the arrival price (Top of the book), arrival price (TWAP) or any other measurement based on the client’s unique liquidity pool. Due to the importance of credit, one client might have different liquidity than another client at the same time, if they have different credit profiles.
How does the FX market’s OTC nature affect algo system development?
Because of the lack of transparency in the FX market, it makes it much more difficult to build algos that are based on where volume is traded (unlike equities and futures). In addition, some liquidity pools can be more “retail-based” while others can be more “institutional-based.” This creates differences and uncorrelated flow that can be beneficial in obtaining new sources of liquidity that might not have existed a few years ago. Some platforms merge the two different liquidity pools, while others keep them separate. This creates challenges and opportunities that didn’t exist before.
Which types of clients require the greatest level of innovation to develop systems and can you give examples of their demands?
There are many types of clients that require specific demands. The most important innovation in the past year has been the push to enhance risk management as it relates to the client’s overall exposure and, if applicable, how to handle one’s clients flow.
From the sellside perspective, you want to be able to give your clients the proper tools to manage their client flows by analysing their trading behaviour. This will give them the best liquidity and allow them to internalize the flow where appropriate and have client-to-client trading, thus creating their own internal ECN.
From the buyside perspective, you want the client to be able to find the best price based on “all in” costs so you can find your best price (net of costs – ECN, Vendor, Prime Broker, etc.), and the best destinations based on probability of getting executed (reject ratios) and latency measurements. Reporting enhancements that are available now help the clients better understand where to place their trades based on size, currency pair, and time zone.
*Rob Weissman VP, FX Sales at Flextrade. Flextrade is a leading provider of broker-neutral trading systems with award winning FX trading solutions used globally by leading sell-side firms, hedge funds and asset managers. ©BestExecution | 2012/13
FX Focus : Best execution
UNBUNDLING COMES TO FX.
While investment management firms are increasingly looking at FX as an asset class, they also need to be active in the foreign exchange market to facilitate transactions in foreign securities and to manage their risk. Best Execution spoke with Chris Oulton* about the multitude of considerations when transacting in FX.
What is the impact of regulation on FX?
Increasing regulation on disclosure in the FX space should serve to benefit clients who need to execute trades. Traditionally large banks and custodians have tied in clients to using their FX services as part of the provision of their general banking requirements. Payment for these services was part of the overall package. However, due to the captive nature of some of these arrangements, banks have provided poor execution rates, taking additional profits from their clients, without disclosure or the ability for them to ameliorate those costs by having an alternative.
Increased regulation should serve to prevent the banks from garnering these additional undisclosed profits by opening up the marketplace for these trades to outside agents.
Regulations such as Dodd-Frank and Basel III are also serving to push up the internal costs that banks will have to bear. This could potentially lead to them either scaling down, or exiting this market as a maker of prices directly, or by necessity, to increase margins to cover their costs.
Those banks that choose to scale down their direct FX business may themselves opt to go down the agency execution route, by offering clearing or prime brokerage solutions, but without taking principal risk on the pricing.
How would you define best execution in FX?
Best execution in FX can be defined simply as a cost-minimising, efficient process allowing the client to manage their business needs across currency pairs and settlement dates as required.
The cost-minimising element is fairly self-explanatory, but the efficiency part is also vital in the smooth running of the business. For the client to know that all of their needs can be dealt with a simple streamlined tool, without the need for multiple individual requests, gives them comfort.
Furthermore, there is also a requirement for the clients to know that they will have access to fine pricing at all times. This cannot necessarily be achieved by having a limited number of counterparties through whom they transact. If the banks choose to push up the costs of dealing, the client must have alternative strategies in place to obviate this.
Is there an increase in outsourcing and why?
FX is a simple concept where the end product, i.e. the currency, is the same irrespective of the provider. Accordingly, some clients have realised that they have no requirement to execute through their own bank. This has lead to a growth in third party providers, executing FX trades on behalf of the client, and remitting the funds back to the client’s host bank. As more and more clients see this as an efficient model, they are moving away from the old traditional, captive model. Outsourcing, to the correct provider, can also provide access to different sources of liquidity at different times, enabling the client to achieve optimal pricing.
What models does the competition offer?
The competition is twofold. In the simpler case, clients can use a simple third party, payment services company through whom to execute their trades. Where the client has a requirement for a greater volume or more sophisticated trading, they could switch to a platform-based system.
The advent of platform-based trading for these clients has helped to streamline the actual trading process. However, for the majority of users, whilst this has helped to consolidate their day-to-day trading, it has not addressed fundamental issues concerning the counterparties that they execute their trades with.
The basis of these trading systems are still, in effect, analogous to phoning up the various desks of the banks, and asking for their prices – although this is mechanised through the platform. Each of these automated feeds, and the prices that they quote, has had to have been negotiated with each of the banks, and on a bi-lateral basis. The client will then be limited to those direct feeds that they are provided with. Furthermore, traditional platforms can suffer from the ability to be tailored for each type of business, reflecting the nature and volume of trades entered into.
Can this be improved upon?
I’d like to think so. We offer a similar platform-based trading solution, but with two significant differences. The platform we use, Liquid-X, takes multiple feeds from a large number of leading liquidity providers (up to 15 depending upon the currency pair), and using fast algorithms, offers optimal pricing in up to very large order sizes. It then uses either Rabobank or Morgan Stanley as the central clearer in each of the underlying trades between both the client and the underlying liquidity provider providing the best pricing at that time.
This benefits the client in a number of ways. In effect, the client now has access to each of the prices that all of the liquidity providers offer, but without having to engage with each of them bi-laterally. Instead, the client will just face the one central clearer, and it is for that clearer to face into the market and execute each of the underlying trades. This has the benefit of minimising settlement risk, whilst providing access to greater and deeper markets.
Additionally, the Liquid-X platform is particularly bespoke. It can be tailored on a client-by-client basis to the specific dealing requirements of each client using it, through the variation in dealing spreads, settlement options and currency pairs for each client, based upon their individual profile of volumes, trade frequency and dealing size.
What are the challenges of trading in FX today?
Given the on-going financial crises and increased regulation, there is more focus than ever on achieving best execution in the FX space on behalf of shareholders, trustees (through their fiduciary responsibility) and investors. Clients should regularly review their FX execution performance in order to prevent their current solution stagnating and, consequently, being exposed to poor execution by banks who perceive little risk in overcharging for FX services.
Accordingly, clients should have specific knowledge of their trading methodologies and the costs associated with their settlement solution. A periodic trade cost analysis of trading history should be conducted to quantify the quality of execution achieved. Where this demonstrates that the current solution offers poor execution, clients can now look to alternative providers and lower their costs.
* Chris Oulton* is managing partner at Core Treasury Solutions who offers an outsourced agency execution service to corporate and institutional clients. ©BestExecution | 2012/13FX Focus : Bob McDowall
THE INS AND OUTS OF FX.
When volumes are low and trading is directionless is FX the low correlation alternative? Bob McDowall* looks at how the buyside is trading FX and whether it can be considered an asset class in its own right.
FX is traded not through an exchange (an exception being LMAX Exchange – see p.XXX) but through multiple venues and as a result there is no single price at any given time. This would not be a problem for exchange venues, but it is difficult to look over multiple venues and trading platforms because they are not synchronous. No one knows the price at an exact moment in time.
One increasingly popular solution to this problem is the use of benchmarks, which involves referencing the price by comparison with external models, and should include external transaction costs. For a dynamic market like foreign exchange, the prices are likely to come from one of three sources: internal pricing models, interdealer brokers, and client multi-dealer electronic communications networks (ECNs), which are electronic trading systems that automatically match buy and sell orders at specified prices. Slightly different prices are issued from different providers. Should the prices be referenced to mid-market or the best bid or offer price? Should the benchmark on the reference price limit the trade price or set the trade price?
Answers to these questions can be included in the client agreement, but at some point, benchmarks will become real competitive differentiators. Investors are not making large gains from their securities investments since the crash over five years ago, they have closely scrutinised the FX execution. As more modest investment returns have had an impact, investors are looking for other ways to add to total return, including modifying the way they execute their FX trades.
The FX market ranges from highly liquid such as G10 currencies and currency pairs to the less liquid “exotic currencies” of new and emerging financial markets. However, liquidity is enhanced both in response to the increase in trade and the more sustained economic growth and prosperity as well as the scale of trade with the G10 countries. Within the G10 currencies and currency pairs, the markets are highly liquid for short-dated foreign exchange contract maturities but become less liquid beyond six months forward and illiquid beyond 15 to 18 months forward. Moreover, the G10 currencies tend to be highly liquid across a number of geographic venues simultaneously as well as in their domestic financial markets. Exotic currencies tend toward illiquidity away from spot-dated contracts although that is changing.
Plugging in
Historically, banks and financial intermediaries have provided electronic access for commercial organisations in all segments to buy and sell foreign exchange on a pre-approved basis, both spot and forward. This mode of trading has enabled commercial organisations to settle commercial transactions as well as manage their foreign exchange and their exposure to overseas transactions by hedging their risk through forward purchases and sales of foreign exchange. These facilities have been extended to financial investors, financial institutions, and retail investors that buy and sell assets denominated outside the home or base currency and wish to lock in the purchase cost or sales proceeds by conducting a simultaneous foreign exchange transaction.
Retail and institutional investors who look to benefit not only from the FX market’s liquidity but also its volatility treat it as a separate, individual asset class. When it is traded as a commodity, spot and forward, it is particularly attractive for Islamic investors because it is satisfies the requirements of Shari’ah law.
Platform-based technology is a well-trodden and defined path for improving service and bringing administrative and operational efficiencies to buyside businesses. They have gained traction in the FX space as investors continue to search for higher yields. They are being drawn into what should now be termed “emerged” markets although the execution of the FX component has to be managed closely whether or not it is regarded as a separate asset class or merely a service provision (see p.xxx). In response to end investor demand for greater granularity and transparency, when they account for and report revenue and cost components, fund managers as well as administrators and custodians and other service providers require detailed analysis on a transaction by transaction basis of their revenues and charges. A platform can provide the level of data, which is auditable and capable of multi-dimensional analysis, as part of the service.
* Bob McDowall, is consulting associate to commercial think-tank Z/Yen – www.zyen.com
©BestExecution | 2012/13
Integrating TCA
Huw Gronow, Director, Equities Trading, and Mark Nebelung, Managing Director of Principal Global Investors, make the case that TCA should be part of pre-, during, and post-trade analysis.
Transaction Cost Analysis (TCA) has evolved significantly with the advent of technology in trading, and thus the ability to capture incrementally higher quality data. Historically the preserve of compliance departments was to examine explicit costs only as a way of governing portfolio turnover; this evolution provides institutional asset managers with several opportunities: the ability to quantitatively assess the value of the trading desk, the tools to form implementation strategies to improve prioritisation to reduce trading costs, and therefore improve alpha returns to portfolios.
Cost analysis models, methods and techniques have blossomed in the environment, propagated not only by technological advancements, but also in the explosion of data available in modern computerised equity trading.
The benefits of applying cost analysis to the execution function are manifold. It empowers the traders to make informed decisions on strategy choice, risk transfer, urgency of execution and ultimately to manage the optimisation of predicted market impact and opportunity costs.
Although maturing, the TCA industry still has some way to go to fully evolve, and that is largely a function of a characteristically dynamic market environment and non-standardised reporting of trades and market data (the so-called “consolidated tape” issue). Moreover, with the advent and increase in ultra-low latency high-frequency short term alpha market participants (“HFT”), which now account for the majority of trading activity in US exchanges and who dominate the market, the exponential increase in orders being withdrawn before execution (with ratios of cancelled to executed trades regularly as high as 75:1) means that there must be an implied effect on market impact which is as yet unquantified, yet empirically must be real. Finally, fragmentation of equity markets, both in the US and Europe, provide a real and new challenge in terms of true price discovery and this must also by extension be reflected in the post-trade arena.
Nevertheless, waiting for the imperfections and inefficiencies in market data to be ironed out (and they will surely be in time, whether by the industry or by regulatory intervention) means the opportunity to control trading costs is wasted. You cannot manage what you don’t measure. Therefore, with the practitioner’s understanding allied to sound analytical principles, it is very straightforward, while avoiding the usual statistical traps of unsound inferences and false positives/negatives, to progress from an anecdotal approach to a more evidence-based process very quickly.
On the trading desk, the ability to leap forward from being a clerical adjunct of the investment process to presenting empirical evidence of implementation cost control and therefore trading strategy enhancement is presented through this new avalanche of post trade data, which of course then becomes tomorrow’s pre-trade data. The benefit of being able to enrich one’s analysis through a systematic and consistent harvest of one’s own trading data through FIX tags is well documented. The head of trading then arrives at a straight choice: is this data and its analysis solely the preserve of the execution function, or can the investment process, as a whole, benefit from extending its usage? We aim to demonstrate that both execution and portfolio construction functions can reap significant dividends in terms of enhanced performance.
PM Involvement
Portfolio managers’ involvement in transaction cost analysis tends to be a post-trade affair at many firms, on a quarterly or perhaps monthly basis, that inspires about as much excitement as a trip to the dentist. It may be viewed as purely an execution or trading issue and independent of the investment decision making process. However, there is one key reason why portfolio managers should care about transaction costs: improved portfolio performance. The retort might be that this is the traders’ area of expertise coupled with a feeling of helplessness on how they could possibly factor transaction costs in. The answer lies in including pre-trade transaction costs estimates to adjust (reduce) your expected alpha signal with some reasonable estimate of implementation costs. You can now make investment decisions based on realisable expected alphas rather than purely theoretical ones.
A key characteristic of many investment processes that make some use of a quantitative alpha signal process is that you always have more stocks (on a stock count basis) in the small and micro-cap end of the investable universe. There are simply more stocks that rank well. This is also the same part of the universe where liquidity is the lowest and implementation shortfall is the highest. If you don’t properly penalise the alpha signals with some form of estimated transaction cost, your realized alpha can be more than eroded by the implementation costs.
Proving the Point
To illustrate the impact of including transaction cost estimates in the pre-trade portfolio construction decision making process, consider the following two simulations. Both are based on exactly the same starting portfolio, alpha signals and portfolio construction constraints. The only difference is that in the TCs Reflected simulation, transaction costs were included as a penalty to alpha in the optimisation objective function whereas in the TCs Ignored simulation, pre-trade transaction cost estimates were ignored. The simulations were for a Global Growth strategy using MSCI World Growth as the benchmark, running from January 1999 through the end of June 2012 (13.5 years) with weekly rebalancing. They were based on purely objective (quantitative) alpha signals and portfolio construction (optimisation) with no judgment overlay. Transaction cost estimates were based on ITG’s ACE Neutral transaction cost model. Starting AUM was $150 million. Post-transaction cost returns reflect the impact of the transaction cost estimates for each trade.
Despite relatively conservative assumptions relating to strategy size ($150 million poses relatively few liquidity constraints) and transaction cost model (ACE Neutral is a relatively passive cost model with lower cost estimates than a more aggressive trading strategy), the portfolio reflecting transaction costs as part of the pre-trade portfolio construction outperformed the one where they weren’t by 0.86% per annum. Figure 1 illustrates the cumulative growth of $1 between the two portfolios.
At the end of the time period, the TCs Reflected portfolio had grown to $2.94 vs. $2.63 for the TCs Ignored portfolio, an additional 30% return on initial capital. The turnover of the TCs Reflected portfolio was modestly higher, averaging 69% p.a., compared to 67% p.a. for the TCs Ignored portfolio.
Annualised transaction costs for the TCs Reflected portfolio was slightly higher at 0.64% vs. 0.62% for the TCs Ignored portfolio. Tracking error and volatility of the two portfolios is very similar. The net effect of higher excess returns (after transaction costs) and similar risk profile (tracking error) was a 34% improvement in the information ratio when transaction costs were reflected as part of the portfolio construction.
It’s hard to think of many (any?) portfolio managers that wouldn’t seize an opportunity to add an additional 0.86% per annum in excess return. Transaction cost estimates will materially alter the most attractive stocks to add to a portfolio at a given point in time and the cumulative impact on performance is significant. In order to maximise realised portfolio performance, portfolio managers need to reflect some form of implementation cost-adjusted alpha signals such that the expected returns of illiquid stocks are appropriately adjusted for expected costs of buying or selling them in current market conditions.
In addition to portfolio performance improvements, portfolio managers considering pre-trade implementation cost estimates have a better basis to judge whether to reconsider a transaction if current market implementation costs are deviating significantly from the initial estimates. By having a common understanding of implementation costs between both portfolio managers and traders, communication is enhanced pre-, during and post-trade. Where the trading function was previously simply a transaction execution function, it now becomes part of the integrated investment decision making process.
Jan Jonsson : Neonet
WHY DARK IS BRIGHTER THAN GREY.
For some time now a variety of liquidity pools have been widely referred to as “dark” – from “dark pools” operated as regulated MTFs to some of the more questionable forms of broker crossing networks. This has been a recipe for confusion and misunderstanding. Jan Jonsson, VP Product Management at Neonet, shines a light on some of the different definitions and explains why “dark” is actually brighter than “grey”.
In recent years, dark pools have been frequently discussed with the term “dark” used widely; from dark pools operated as regulated MTF’s – to the more questionable forms of broker crossing networks. This causes confusion and misunderstandings since it is actually clearly different types of pools under the same name. Jan Jonsson, VP Product Management at Neonet, dives into the different definitions and explains why dark is indeed brighter than grey.
As much as we like to divide our reality into clear definitions, we are sometimes faced with mixed and overlapping terms. In the financial world, we refer to pools of liquidity as lit and dark, with the inference that they are two opposite extremes, but is it really that simple?
As markets get more complex and new forms of trading arises, the term “dark pool” needs to be split and redefined, as there is great difference in transparency between dark pools and – what many now refer to as “grey pools”.
Lit, dark, grey – how transparent are they?
A lit market is, as the name implies, illuminated – it is possible to see and understand what is going on. You can make an informed decision pre trade, and then verify what happened post trade. This means that any problem that arises can be assessed, discussed and solved.
Whereas we define dark pools as “matching engines” that don’t display any pre-trade information about resting orders to anyone. They are regulated under MiFID, with equal access and rules applicable to everyone. To obtain fair price discovery, they match on the primary exchanges’ mid-bid or offer price. Execution is transparent and easy to benchmark as dark pools have a well-functioning price discovery mechanism.
Other pools match on order price and volume limits and not on a reference price such as primary mid-bid/ask. This enables execution of a block on a price that is negotiated and not pegged to a lit reference price – a hidden price mechanism. While the customer might want to pay a premium for executing the whole block without market impact, they are at the same time exposed to the risk of someone seeing that order and using the information, or that the price mechanism is tilted in one direction or other. These pools are often referred to as grey pools, and are not transparent and therefore harder to benchmark. Basically you need to trust the provider not to make money on both commission and spreads. The networks don’t add to transparency and this erodes trust in the market. Not everyone is allowed to trade in these pools and unless you are an owner, the fees to trade will be high. For the client, an alternative would be to allow for execution over time in a lit market.
As seen in the US, retail flow is often bought by brokers and traded off-exchange in a combination of prop trading market making, crossing and other techniques. Only a fraction of the flow slips through to a regulated dark or lit market, and when it does – having been sold two or three times – no one wants to meet the remaining flow. This is a sort of “super grey” handling of orders. In the US there is an obligation to give NBBO (National Best Bid and Offer) or better. In EU this is not the case; all you need to do is to follow your own best execution policy. As for the client, it is very unclear what service you are getting and how to benchmark it.
How price discovery differs
Price discovery is all about knowing what price you will get in the micro structure of the market, i.e. before you trade (at market price). For a dark pool it is easy; look at the best bid and offer of the primary exchange. The price is totally transparent, and easy to discover. The only dark aspect is that you don’t know whether anyone will trade with you, and at what volume (the same as for passive orders in a lit book). However, after a trade is done the price can be verified by looking into historical bid/ask values. Pre and post trade transparency is therefore available for this kind of dark pool.
For grey pools, price discovery is left to the operator. You send an order to the pool – with limits in price and volume – and if you’re lucky you get a hit. The best case scenario is that you get a better price than your limit.
So, how was the price set? Pre trade you have no idea. Post trade the operator has to report the trade within reasonable time. You may see that the trade was done at your price and volume, but you don’t know whether you traded with another actual investor, or if the operator took the position, with the purpose of trading it off a premium. The uncertainty in who you meet is the same in grey as in lit and dark, but in grey pools there is neither pre- nor post- trade transparency in the price discovery mechanism.
So how can we get true price discovery?
Price discovery is not possible without market data. You need the consolidated view to make an informed decision. However, each market has a monopoly on its own data. There are no alternatives to choose from, and where there is no competition inefficiency is strong. As already mentioned, in the US you are protected by the obligation to get executed at NBBO or better, whereas in EU you are not. In Europe the situation is further exacerbated by the lack of a consolidated tape to use as a reference to validate your execution quality.
Grey is dark, dark is lit
Adding transparency to execution might not be in everyone’s interest, but as an investor it should be a top priority to know how your trades were made in terms of quality. It ranges all the way from pools to algorithms, and technology to brokers.
To trade in the dark adds liquidity, improves the price, and offers protection against small unwanted fills and pings. Dark is as bright as lit venues, and adds value for everyone, from a small retail customer to a big institution.
Blanket criticism of “dark pools” is misplaced and instead concern should be directed towards the fact that there are liquidity pools – incorrectly referred to as “dark pools” – without transparency that add to the confusion of the investor and their mistrust in the market; the so-called “grey pools”. Concern should also be raised about the fact that there is a lack of access to consolidated tapes in the EU that would help customers get a complete view of what is happening in the market. The lack of a consolidated tape, and no obligation to offer good execution at EBBO (European best bid and offer) or better is a bad combination.
At Neonet we only trade in regulated lit and dark pools, never in grey pools. We use third party benchmarking to verify each and every trade in order to deliver a truly transparent and independent execution service with an optimized balance of quality and cost. Consolidated tapes have been part of our offering for many years.
©BestExecution
Trading : Best execution
WHAT’S IN A NAME?
Best Execution still means different things to different firms. Heather McKenzie reports.
More than five years after the introduction of MiFID one of the central principles of the directive – best execution – remains ill-defined and open to interpretation. However, buyside firms are beginning to take more responsibility for ensuring whether or not they are getting the best deal from their brokers.
MiFID was put together in 2004 and implemented in 2007 – before the financial crisis hit its peak in September 2008. The original intent was to break down the barriers between trading in different countries in Europe and to make trading fairer and more transparent, particularly for retail investors. These intentions, however, were hijacked by the financial crisis, which brought the issue of systemic risk to the fore and significantly pushed back all other considerations.
In October 2011, the European Commission published proposals for a review of MiFID to take into account the changes wrought on the financial markets by the crisis and also the consequences of the original MiFID, which led to a proliferation of trading and clearing venues. When the proposals were released, Commissioner for Internal Market and Services, Michel Barnier, said: “Financial markets are there to serve the real economy – not the other way around. Markets have been transformed over the years and our legislation needs to keep pace. The crisis serves as a grim reminder of how complex and opaque some financial activities and products have become. This has to change. Today’s proposals will help lead to better, safer and more open financial markets.”
For the trading community Article 21 was of great interest as it highlighted the “obligation to execute orders on terms most favourable to the client”. Six elements of the article outline what is meant by this, without giving too much detail – Europe, unlike the US, tends to opt for ‘principle-based’ regulation, leaving it to industry practitioners to hammer out the details. Investment firms must have an order execution policy that enables them to obtain for their clients “the best possible result” in accordance with the elements listed above. The firms’ clients must agree with the policy before orders are executed.
Brad Wood, a partner at London-based consultancy GreySpark Partners, notes that best execution was never meant to be well-defined or prescriptive. “The concept of best execution is principle-based, designed to oblige firms to define what they mean by best. This was in response to reluctance from market participants for heavy-handed regulations.”
Adam Toms, chief executive Instinet Europe, agrees, adding. “I think people in the industry understand what best execution needs to be; that it is not just about price but includes many other aspects such as the quality of execution end to end. Due to there being so many different reasons for participants to trade with particular counterparties and taking into account the fact that market conditions change, best execution rules should not be too rigid.”
Chapter II
It had been thought that the review proposals would add clarity but they focus more on the additional trading platforms, new safeguards for algorithmic and high frequency trading activities, increased transparency, reinforced supervisory powers and stronger investor protection. The proposals have since been passed to the European Parliament and the Council for negotiation and adoption.
A clearer definition of best execution is unlikely. Instinet’s Toms says the MiFID Review will deliver limited change in the definition, but there are “related topics” such as treatment of dark pools, that will change as a result of the Review and will help improve execution. The individual best execution policies of market participants are unlikely to change, he says.
Rainer Riess, managing director Xetra market development at Deutsche Börse, says the current best execution regime is very suitable for Europe. However, the enforcement of the regime is inconsistent. “Approaches to best execution differ in different countries and sometimes within countries. This is an area that needs harmonisation in the regulatory and legal efforts.”
Guidelines on how the best execution principle is being applied and analysis of how banks and brokers are doing best execution would be helpful, he says. “The biggest concern for buyside firms is their ability to judge whether or not they have achieved best execution.”
Steve Grob, director of group strategy at technology vendor Fidessa, believes the main problem for firms trading in Europe is that the buyside does not have an absolute measure of best execution. “Without a way of measuring broker performance, such as a consolidated tape, buyside firms cannot get an independent view of whether their broker has executed a trade in the best possible way,” he says.
According to Grob, Fidessa’s buyside clients have three challenges. First, there is greater fragmentation of trading venues which means that money saved in execution is being lost downstream. Second, as more venues trade the same instruments and stocks, high frequency trading activity is flourishing and buyside firms are trying to prevent their flows intermingling with HFT flows. Finally, there are concerns about information leakage, making it difficult to execute large blocks of trades.
The tape
A consolidated tape that combines every execution venue and every execution on those venues would enable firms to understand at which point in time and where they achieved best execution, says Tom Riesack, managing principal at securities industry consultancy Capco. However, the sticking point is who would mandate it and who would pay for it. Such a solution would require huge amounts of data. “We need to find a better way to define best execution, but we have to take into account that it is a very individual thing. Each firm needs a better understanding of what best execution means for them.”
Large buyside firms, for example, may want to ensure there is no big movement in price when they execute a large block order, whereas hedge funds, particularly those with HFT strategies, may be more concerned about the price and latency of execution. “No single answer covers everyone when it comes to best execution,” says Riesack.
These differences spawned the growing number of transaction cost analysis (TCA) solutions. “Firms can use TCA tools to address their most pressing issues, rather than what they are being provided with by sellside firms,” he says. “The effect of using TCA is that firms will get different types of best execution policies that are specific to their processes or strategies.”
GreySpark’s Wood notes that a growing number of buyside firms are demanding more detail about their brokers’ best execution policies. “Firms want their brokers to increase the level of detail about how they consider the performance of their algorithm, for example, fits in with their definition of best execution.” The different priorities of buyside firms could eventually lead to brokers competing by providing differentiated definitions of best execution. Synthetic order types that take into account the specifics of a client’s requirements may be tuned into algorithms in order to meet that particular best execution scenario, he adds.
Jon Fatica, head of analytics at New York-based TradingScreen, believes that TCA will develop into an intraday analysis tool and eventually into a real-time monitoring solution. “Most of the challenges with best execution involve data availability. Some of the new MiFID rules will address the shortcomings of data availability.”
He agrees with Wood that buyside firms are pressing brokers to tell them more about their algorithms. “Things are getting better and people are getting closer to how they want to execute a trade. But it is a zigzag path and the markets are not very liquid, they are challenging.”
©BestExecution
