— Stavros Siokos

Stavros Siokos, head of European alternative execution, sales, Citigroup tells FTMandate about educating the buy-side in the best use of algorithmic trading technology.

FT Mandate: With algorithmic trading seemingly besieging stock markets on both sides of the Atlantic over the past year, do you think the buy-side users still need (ongoing) education about algorithmic trading techniques in order to make the most appropriate use of algorithms and reduce the fear among some over the so-called ‘black box’ and even ‘white box’ applications?

Stavros Siokos: Absolutely. We are working on new ways to help the buy-side to make the most of our algorithmic trading product. Recently, we have been using our internal traders more as coaches – these guys use our algorithms day-in, day-out and so are best placed to transfer some of their knowledge about how they work to our clients.

Our approach is very much from a white, or ‘glass’ box point of view – ‘black’ box strategies should not be used by the buy-side, as by definition if their behaviour is hidden from the user it is not clear what they are going to do.

We’re still learning as well – much of the usage of algorithms and strategies differ between buy- and sell-sides, and we work constantly with our clients to develop our algorithms to suit their needs better.

FTM: Clearly there are different tastes and reasons for using algorithms as an execution and trading tool. In terms of the perception (and reality) of algorithmic trading and DMA (direct market access), how does it vary from institution to institution on the buy-side? Has this changed over the last six-12 months and in what ways has Citigroup been responding? Are algos being used for ‘high’ as well as ‘low touch’ trades?

SS: We have seen in recent industry surveys that there is a phenomenal appetite for algorithms, but perhaps only a few per cent of overall European flow is traded via DMA and direct algorithm access in Europe. While this is growing, buy-side technology is a limiting factor in this. This tends to be the main factor in differentiating between algorithm take up among the buy-side: while some institutions are at the forefront of the technology race – with advanced order and execution management systems, others, often owing to budgetary constraints, are not yet FIX enabled. The buy-side has moved forward over the last year, but the pace has perhaps been slower than anticipated. We are seeing ‘high’ touch business increase as the comfort level goes up – our internal trades have been putting large- or mid-cap orders on our algorithms for years and we see no reason why the buy-side should be different.

FTM: With algorithmic trading accounting for around 50 per cent of trading in large caps in the US, possibly 10 per cent to 20 per cent in Europe, and Asia coming from a lower base, what can we expect from these different regions over the next 12 months in terms of growth and adoption of algos? What potential does Asia-Pacific have and which countries will be the first movers in take-up ?

SS: There’s little doubt that we will see algorithmic trading gain market share globally over the coming months, as electronic markets become more liquid and buy-side comfort level increases. This growth will be further boosted, as more and more assets flow into hedge funds, which tend to be the primary buy-side users.

This growth will be slower in the US than the rest of the world, while in Europe as buy-side technology improves we expect growth to take off over the next couple of years. Furthermore, increased scrutiny, regulation and accountability will tend to push the buy-side towards more algorithm usage owing to the transparency of their execution performance and cost effectiveness.

FTM: With so much talk about multi-asset trading and gaining arbitrage opportunities from trading across asset classes, how appropriate are algorithms for that and for trading mid- and small-cap equities, emerging market equities, FX and commodities? Is more development needed in terms of IT infrastructure and capacity of systems (connectivity, FIX) to allow this to really bloom going forward?

SS: In the equities world, algorithms can trade just about any stock, provided the right algorithm is chosen, and the model behind it is well written and tailored to the market. In respect of true ‘arbitrage’ type strategies, the sort of funds or prop desks which trade this will typically write their own algorithms and will have little demand for what brokers would offer. Outside equities, the demand for ‘execution’ type algorithms is likely to be limited in the foreseeable future, among other things many instruments are not even traded electronically and they tend to be net markets, so commission is not an issue.

FTM: Despite a plethora of algorithms and solutions being touted by various providers – from agency/brokers and sellside firms – how important is it for service providers and sellside firms to differentiate themselves in terms of product and service offering, connectivity and innovation? How does Citigroup differentiate itself and what is the current strategy across the globe?

SS: It’s vitally important – getting the right outcome from using algorithms is as much about service, support and consultancy as the algorithms themselves. Globally we have both algo development and support teams in each major hub: so that solutions are tailored for the market in which they are going to be used.

FTM: In the US, with RegNMS coming up this July (MiFID in Europe too) and the provision for ‘best execution’ (trading on an automated venues, likely fragmentation of execution), what impact will this have on institutions trading algorithmically? How important is it likely to become with RegNMS mandating use of automated trading venues and what should buy-side institutions be considering now?

SS: We expect that all these regulations will increase fragmentation of liquidity, both in the US and Europe. This can only encourage the uptake of algorithms among the buy-side – there is no way that a human being can simultaneously monitor multiple liquidity pools. We have no doubt that the smart order routing algorithms that are prevalent in the States will become a must-have in Europe for the buy- and sell-sides.

FTM: With such a focus on performance, trading costs really matter to investors and can make a significant difference in a portfolio’s overall return. What do you consider the key factors in a decision to deploy one algorithmic trading system over another – ease of use, connectivity (FIX), liquidity, best execution and transparency or a combination?

SS: Ease of use, flexibility and transparency are key differentiators for us. In some ways, ease of use and flexibility are pulling in different directions – it’s hard to have a product that can achieve a wide variety of execution objectives without a large number of parameters. The way we get around this is by working hard with our clients to ‘can’ popular parameter sets so that they can be achieved with just a single click, or even working on custom strategies. Transparency of performance is important to us – that’s why we use BECS post trade, which has a large universe and rich peer comparison to show which brokers are doing a good job for their clients.

FTM: Education, education, education – that was a key theme from the recent TradeTech event in Paris in relation to the needs of the buy side. How does Citigroup enable its clients to recognise the value the organisation brings to them as ‘execution’ consultants or specialists who dispense practical, ‘real world’ trading solutions in Europe, North America and Asia 24/7? What is your role as execution consultants to clients and various institutions?

SS: Algorithmic trading forms part of the Alternative Execution group here at Citigroup – including Program Trading, DMA and portfolio strategies. Our sales people have an outstanding feel for these products, and so we are able to help them choose the right mix of these and our cash and derivatives businesses to maximise their alpha capture.

Our Global Portfolio Trading Strategies (GPTS) team has been consistently ranked number one in a variety of surveys for their portfolio analysis service – their role is now broadening to include all aspects of the investing and execution process.

We also provide a bi-monthly marketing piece called ‘Inside the Box’ with performance statistics, news and tips to get the most out of our product.

FTM: ‘Best execution’ is a term that has many different definitions. Some say it means delivering the execution that best suits the client’s needs. How do Citigroup’s algorithmic trading solutions help in that regard? Clearly algos are not appropriate for every trade, but can help deal with the ‘noise’ on trading floors and simpler trades – freeing up traders to intellectualise over the more complex transactions. Can they help generate alpha too?

SS: Best execution is a term that gets thrown around and used for many different reasons. It’s possible to satisfy the regulators’ definitions, without providing the best execution, which is what we are always striving to achieve for our clients. Algorithms can be used to automate simple orders – but also to take advantage of fleeting opportunities that may exist for milliseconds. It’s unlikely that any broker would give out a model that ‘generated’ alpha for a few basis points – but there’s no doubt that algorithms used well preserve alpha compared to a pure manual process. We’ve seen this internally over many years – our traders have much more time to deal with their difficult trades or capital commitment.

FTM: Despite a plethora algorithmic flavours on the market, in your experience would you say clients are finding that there is a limit in terms of the number and ways in by which clients execute their algorithmic business? Is that dictated by trading style and/or
practicalities?

SS: Typically the standard strategies – VWAP, TWAP tend to dominate our flow – albeit with parameter overlays. There is a near infinite way to put these parameters together, but most clients will find a set that work for them and integrate well with their investing process. The biggest barrier to new strategies tends to be the lead time in getting OMS’s updated to include the up-to-date offering.

FTM: Where does Citigroup envisage developments in algorithmic trading strategies and execution to be heading over the remainder of 2006? And, what can we expect in non-equity algorithms – FX and futures, algorithms of algorithms, and listening or polling algorithms? Will customisation and even analogies to biological science/nature play a role in developing killer algo strategies? With that in mind, are the days of the human trader numbered or is that fantasy?

SS: Algorithm use will continue to grow, and we’ll probably see more demand from sophisticated clients for tailored algorithms. With regards to emerging markets and less liquid stocks – we’re already there, and have been trading mid-caps on algorithms for a number of years. Multi-asset class algorithms, as I mentioned earlier, are unlikely to take off in the same way as their equity counterparts. Human traders will always play a role – it’s just that the skills demanded for that role evolves. The big bang of 1986 changed the way the stock market operated in London for ever, and successful traders adapted to that change. Although it’s a gradual evolution, we’re seeing something similar here with algorithms, DMA and other technologies.

FT Mandate: Aside from the view of some institutions that not all algos do what they claim, transaction cost analysis (TCA) is key pre- and post-trade, but should such measures be agency broker TCA offerings or more independent solutions? Then there are the benchmarks - VWAP, TWAP, INLINE. What makes most sense and why when analysing trading strategies?

SS: In BECS, we are able to offer our clients a solution that offers the best of both worlds – we have a world-class impact model, developed in collaboration with academia: and an arms-length, independently audited post-trade solution. The choice of benchmark depends on what is trying to be achieved – typically we provide our clients with performance against a comprehensive list of benchmarks, so that the algorithms can be assessed from a variety of different angles – VWAP strategies should obviously be assessed primarily against VWAP, but Arrival Price (the mid-point when the order is started) should also be used to assess information leakage and impact of the strategy.

In association with CitiGroup.