Multi-Asset Trading in Focus
With Paul Squires, Head of EMEA Equity and Henley Fixed Income Trading, Invesco
Briefly describe Invesco and its trading profile as a buy-side institution.
Invesco is an independent global Asset Manager with U$1.3trn AUM and a global trading team of 82 professionals across 12 different desks in 7 countries. With that scale it’s able to have dedicated specialists by both region and asset class. For EMEA instruments we have trading teams based in both London and, of course, Henley on Thames.
Multi-asset is a commonly used term to describe a trading desk — what exactly does it mean to be multi-asset?
We would describe our organisational set up as ‘multi-asset’ because the execution responsibilities of the traders – segregated from the investment decisions of the Portfolio Managers – are not solely in equities (which can sometimes be the case) but across all asset classes: additionally fixed income, FX and derivatives (called ‘alternatives’ at Invesco).
Are all large global investment managers necessarily multi-asset?
A multi-asset trading team is more likely to be found at a large global asset Manager where the investment teams themselves may be organised by asset type, with further specialisation within each asset class. For example, Henley has a dedicated UK equities investment team and a separate (Continental) European equities team, as well as a fixed interest investment team, each responsible for specific products. The size of the trading team – and how many traders cover each asset class – therefore often reflects the size and amount of turnover of funds managed in those areas.
Some smaller boutique Managers may only have client mandates to run equities hence their trading requirements would be more simple, a factor of both the single asset class and (likely) lower turnover.
The relatively high fixed costs of employing a dedicated trading team in those circumstances (minimum 2 traders) might mean that there is spare capacity for them to trade other instruments as required, even if to a lesser extent. For example, listed futures or index options might be traded in conjunction with a basket of stocks, giving rise to the concept of cross-asset trading (traders who execute orders in more than one instrument type where the execution has some contingency). Other common examples would be the equities traders executing ETFs even if the underlying asset class is fixed income or commodity or a straightforward asset allocation change being implemented by a single trader selling futures of one asset class (bonds) and switching into futures of another (equities).
What has been the institutional buy side’s path to multi asset trading, i.e. where was it 10 years ago or five years ago, compared with where it is now?
My own professional trading history is at odds with the usual experience of buy-side dealers in that having traded equities (initially as a specialist on UK and then European stocks) for approximately 10 years, I then switched to cover fixed income (again exclusively). In more recent years however these once alien groups have increasingly come to resemble each other. The modern trader not only needs a strong understanding of other instruments and how they affect each other (for example single name CDS spreads vs the stock or corporate bond), but the convergence of operational methods to trade all asset classes, which has cultivated the culture of automation, means that even large asset managers may now choose to segment their trading teams more by the execution method (‘electronic’ vs voice or ‘high touch’ vs ‘low touch’) than simply by asset class (bonds vs equities).
The optimal set up of the trading team depends on the role given to that function and where their value is seen. To make some sweeping generalisations to illustrate the point, a more systematic investment style is likely to value a more automated, low cost execution approach with a trading team characterised by ‘quants’ whose expertise is agnostic of the instruments they are trading, their skills applied to the most efficient execution outcomes based on the order profiles and the channels available to accomplish that. In such situations the trader’s value is not manifested in a deep understanding of the stock for example (the sector, shareholders, research views) nor are they as likely to proactively suggest opportunistic trading ideas that arise from a more specialised focus on a smaller universe of instruments.
Can an individual trader be truly multi-asset, or is it more of a descriptor for a trading desk? Why is the distinction important (assuming it is important)?
Where an individual trader is categorised as multi-asset then, the likelihood is that this is in more of an automated capacity – with innovative auto-ex workflows across FX, bonds and equities increasingly prevalent. By contrast traders who cover subsets of a single asset class (e.g. HY bonds, UK small caps) add value more readily by fully knowing the instruments held by their PMs and advising on how to buy or sell positions that might represent months of average liquidity without signalling this to the market.
Regarding technology, what do technology solutions providers do well in supporting multi-asset trading, and conversely what areas remain pain points for multi-asset trading desks?
While the benefit of having traders with distinct specialised knowledge is clear, there are also natural efficiencies from harmonising operational and governance aspects that surround that expertise. Order Management Systems (OMSs) have long supported multi-asset instruments but there are few Execution Management Systems (EMSs) that provide that flexibility.
Invesco is not unusual in using its EMS for some, but not all, instrument types. Where the harmonisation benefits are leveraged it is by customising some of those workflows to deliver data across all of our trading universe to a proprietary database where results can be analysed to improve future outcomes for clients and evidence controls required for robust risk management.
What is the future of multi-asset trading?
Going back to multi-asset trading and its future: the adoption of execution channels away from their historic ‘owners’ (order books for equities, RFQ for bonds, streamed prices for FX) has begun – the result of which lends itself to the growth of composite pre-trade data that can, in turn, create the inputs necessary for transformational use of AI and machine learning.
If that prediction sounds, well… predictable, it comes with an interesting observation: during last year’s volatility, caused by the pandemic, there was a shift to more ‘traditional’ methods of trading. ‘Smart’ algorithms often rely heavily on historic, stable pricing trends in benign market conditions.
The ‘human’ skills that come with experience became more important at a time when the variance of the execution outcome shot up. The easy forecast is to say that a balance of automation and ‘fundamental’ traders is optimal, just as we would all like a post Covid working environment that balances the best of being in an office and WFH. What we don’t know of course, is how much of each will be best nor how long it will be before we get there.
The value of investments and any income will fluctuate (this may partly be the result of exchange rate fluctuations) and investors may not get back the full amount invested.
This placed article is not for consumer use.
Where individuals or the business have expressed opinions, they are based on current market conditions, they may differ from those of other investment professionals and are subject to change without notice.
Issued by Invesco Asset Management Limited, Perpetual Park, Perpetual Park Drive, Henley-on-Thames, Oxfordshire RG9 1HH, UK. Authorised and regulated by the Financial Conduct Authority.
Multi-Asset Trading in Focus first appeared in the Q1 2021 issue of GlobalTrading.
The strategies are the second launch of Northern Trust Asset Management’s ETF offerings in Europe.
With Thejas Nalval, Co-Founder and Chief Investment Officer, Parataxis Capital
Corporate Sustainability Reporting Directive elevates sustainability information to same level as financial.
Essentia analyses data to create behavorial “nudges” for fund managers' investment decisions.
With Adam Conn, Head of Trading, Baillie Gifford