In terms of foreign exchange trading volume, Germany might be dwarfed by the UK and US, with only 1.8% of global turnover at the last official count in 2016, but when it comes to buy-side demand, trading infrastructure and algorithmic execution, Frankfurt can certainly rival some of the world’s largest FX hubs.
As Europe’s largest economy by some distance, Germany hosts a wide range of large and medium-sized corporates with complex currency hedging needs as well as a large number of institutional asset managers. They are served by two of Europe’s biggest banks, both of which have invested heavily in e-FX and algorithmic execution over the years, as well as one of the world’s fastest growing FX trading platforms, 360T.
Deutsche Bank, Commerzbank and 360T are all active in international markets, of course, but Germany remains the jewel in their respective crowns, while for large global FX operators, the country is recognised as a land of opportunity, with significant institutional and corporate demand for FX liquidity and advanced technology.
“Germany has a number of large asset managers with in-depth understanding of the intricacies of the FX market, including liquidity fragmentation and the importance of timing. When trading large sizes, they are embracing algos as a tool to achieve and demonstrate best execution for their clients while minimising market impact in a repeatable and quantitative way,” says Tod Van Name, global head of foreign exchange electronic trading at Bloomberg.
Reducing market impact
The use of execution algos is still in its infancy in FX when compared to equity markets, but banks have been investing in the technology for some time now and those buy-side firms that do tap algos generally do so to minimise market impact and increase execution efficiency.
In current market conditions, when liquidity and volatility can be unpredictable, corporate treasurers with large hedging books might find they can achieve better execution without revealing their hand by using an algo that splits the order up and executes it in slices, rather than by sending it straight out to the public market.
“Algo trading is becoming an increasing part of the toolset for clients to trade away their currency positions. While it is commonly thought to be a tool only for large nominal volume transactions, the reality is that clients – corporates, institutionals and banks – are also using this method to place smaller amounts,” says Jeremy Carvell, head of global liquidity sales at 360T, which was acquired by Deutsche Börse in 2015.
Standard risk transfer could be compared to the throwing of a large stone into a pond – from the moment of impact, the trade creates ripples that are felt by the rest of the pond, meaning other banks see the trade and can alter their prices and adjust their positions accordingly. For the firm that placed the trade, there ensues a period of uncertainty and potential loss as it continues to work the order in the market. Algo execution offers an attractive alternative for large orders.
“By placing the trade with a single bank, the selected bank can gently and passively break the ‘stone’ into smaller pieces which are then thrown into the pond, which in turn creates a much smaller impression. This is known as market impact and has a direct correlation to the yield on a single trade. For this reason, most clients are content and seek to use passive algos,” says Carvell.
Lifting the mystery from algos
Not all algo users will be confined to passive strategies, however, and some providers have developed beguiling numbers of algos with wide ranges of aggression and passivity, often tagged with colourful names that seek to reflect the underlying strategy. But some buy-side users have said they would prefer a smaller selection of simple strategies that are easy to customise without necessarily being too sophisticated.
Germany’s Commerzbank, which has a long history of investing in eFX, took this feedback onboard when it began to take the algos it had used internally and pitch them to clients. It deliberately narrowed the toolset to just three strategies – a time-weighted average price (TWAP) that can be set to different levels of aggression, a peg-based strategy known as Tracer, and a limit-based strategy known as Hunter.
“We have sought to tailor our algo offering to the specific needs of German corporates and financial institutions. Offering a large number of strategies with only minimal difference between each can be very confusing and inefficient, so we have kept it very simple, with three basic strategies that can be customised to suit client needs,” says Nickolas Congdon, Head of Electronic Trading Services, FICC, Commerzbank.
Of the three strategies offered by Commerzbank, TWAP is perhaps the most ubiquitous as it is a tried-and-tested algo that looks to achieve the average price over a certain time period from order submission to completion. But while TWAP clearly has its merits, Congdon believes there is a need for greater innovation than simple replication of a well-worn strategy.
“TWAP is still a popular strategy but we have encountered corporates in Germany that are inundated with TWAP algos and have been much more interested in our passive peg-based strategy that enables users to capture the spread. Financial institutions often prefer the limit-based strategy, which accesses liquidity more aggressively,” he explains.
But while Commerzbank has sought to keep its algo offering relatively straightforward, that does not preclude more ambitious users from tailoring the strategies to be more sophisticated, so that they will respond to certain market conditions and become more passive or aggressive as demanded.
“While our three strategies are designed to operate independently, they can also be combined so that particular tools are triggered during certain pre-determined market conditions. This can all be configured to create a very dynamic execution strategy that moves from passive to aggressive when required,” says John Juer, Head Interest Rates, Currency & Commodities Trading eProducts, FICC, Commerzbank.
Regulation drives transparency
The prevailing regulatory environment has served to increase demand for algo trading and transaction cost analysis (TCA) in Germany, with both corporates and asset managers running ahead of the curve in seeking to ensure compliance with new demands for best execution enshrined in the second Markets in Financial Instruments Directive (MiFID II).
The FX Global Code, published in final form in May 2017, has also raised the bar on transparency and order management, creating a global set of acceptable standards to which market participants must adhere. German practitioners have been rigorous in their adoption of both MiFID II and the FX Global Code, with many trading desks and portfolio managers now keeping a much closer watch on execution costs and practices.
“We have internal broker lists that we review very closely and will speak to individual liquidity providers if we are not getting satisfactory rates. It is beneficial for the overall market to have asset managers using TCA and taking a greater interest in execution quality,” says Harwig Wild, senior risk manager on the currency management desk at Metzler in Frankfurt.
As an overlay manager, Metzler has not yet seen a need to use algos to execute its FX business but it maintains relationships with a large pool of liquidity providers and seeks to keep market impact as low as possible. In the pursuit of best execution, Metzler contracted New Change FX last year to provide its independent mid-point pricing as a benchmark.
“It is important for us to avoid market impact and leave a minimum footprint when we trade, but we have found so far that we can achieve this without the use of algos,” says Wild. “We closely monitor how our orders are being executed, making sure the traders are getting the best rates and there is no slippage. Using New Change FX has helped us to independently benchmark our execution and we are very satisfied with our current arrangements for the sizes we are trading.”
Beyond Metzler, however, other buy-side firms in Germany have leveraged algo tools as well as TCA to keep on top of their execution requirements. As in other jurisdictions, a key requirement for many users is that algos should be made available through independent platforms so that connecting up to every bank provider is not always necessary.
Bloomberg offers access to 18 algo providers and more than 100 algo strategies, with access fully integrated into the FXGO workflow, from order generation to confirmation and settlement. Although FX spot is outside of the scope for the MiFID II regulation, Van Name reports that many asset managers and corporations are applying the same rules to all FX instruments. This has led to increased use of algos as a way to demonstrate best execution.
“Bloomberg is expanding its algo execution framework in several areas, including workflow and analytics,” he says. “We’re also planning to onboard new bank algo providers and strategies. The workflow aspect is critical to ensure that algo execution is part of the established execution cycle, from order generation and netting to allocation, confirmation and settlement.”
It’s a theme that resonates with 360T, which has witnessed at first hand the surge of interest in algos in its home market. For many users this has been a sea change as they have come to recognise the benefits of algo execution in delivering best execution.
“Initially it seemed that algo trading was not going to prove very popular,” says Carvell. “After all it captured flow into just one bank without the need to compete against other price makers, but clients did not want to use it – it took away the apparent fair market practices of transparency and competitive bidding.”
“And yet, the desire to use algo orders has increased,” he adds. “As this requirement from clients became clear, 360T began to offer algo order functionality via the 360T network. Over the last two years, the market’s acceptance of this form of execution has grown and there is a selected interest from corporate clients and asset managers, in particular.”
Traditional risk transfer still remains a well-used channel, of course, and few firms would look to transition entirely to algo execution at this stage, but it seems that algos will play a growing role in Germany’s FX industry in the future. Commerzbank has undertaken an analysis of execution costs incurred when using TWAP or risk transfer which shows there is a role for both methods of execution.
“Algos offer tighter spreads on average but there is increased risk and we do therefore see users reverting to risk transfer during times of higher volatility and market stress. Hunter is suited to a volatile environment because it is a more active traders’ strategy that will continuously sweep multiple liquidity pools and seek price improvement from all of the available interest,” says Juer.
Congdon adds that algos should be seen as a complimentary offering to risk transfer, and providers have a responsibility to educate their clients on how different strategies should be deployed and in what market conditions they will work best. Many large German corporates have been tapping algos for some time, but demand is gradually spreading to treasurers at the smaller Mittelstand companies seeking to reduce costs and increase transparency, he says.
“Corporate treasurers are increasingly sophisticated and are sharing advanced execution strategies, so this is driving increased use of algos to reduce costs and market impact. We have differentiated our algo offering by not buying off the shelf and white labelling but rather by investing and building the tools ourselves, taking input from users about what features they want to see,” Congdon explains.
For end users, combining intuitive features with clarity on how strategies can be customised and fine-tuned to suit their requirements could be a very powerful offering. While some providers have historically marketed their algos with little accompanying explanation beyond the promise of alpha, this approach is unlikely to succeed in the current environment when asset managers have become so much more discerning.
“If our order size were to increase significantly, we might need to consider the use of algos for a small number of trades. We generally use quantitative dynamic trading models and wouldn’t want to hand our orders over to a black box algo if we have no control and don’t understand exactly how the strategy is structured,” says Metzler’s Wild.