One of the key benefits of the use of artificial intelligence (AI) tools for trading is that it can massively enhance human capabilities, explains Andrej Rusakov, CEO of Data Capital Management.
“The way I see it is that AI can really put human ingenuity on steroids,” he says. “What I mean by that is that it really allows you to take way more data points into account and find structures in data sources that are impossible for the human eye to spot.”
Rather than displacing humans, Rusakov explains that this technology is most effective when it is deployed in tandem with a human understanding of how markets work. When building strategies, his firm uses this understanding of markets and then codifies and enhances them by using AI, and in particular machine learning, tools to find new patterns in different data sets.
Momtchil Pojarliev, deputy head of currencies at BNP Paribas Asset Management, talks about some of the misconceptions that exist amongst institutional investors regarding currency hedging.
For example, he explains that in the past, some firms have been unclear on the exact difference between absolute return strategies and active hedging.
In the former, the aim is to produce risk-adjusted returns that are as high as possible for a given volatility. The currency manager is allocated a notional amount of funds and can invest in any given currency to try and produce the maximum amount of returns possible.
David Mercer, CEO of LMAX Exchange, talks about why a lack of credit, rather than custody solutions, is the biggest single challenge facing institutional market participants wanting to trade cryptoassets.
LMAX offers a crypto custody solution through LMAX Digital, and Mercer concedes that having platforms provide custody services is not necessarily ideal from a market structure perspective.
However, he quickly adds: If you look at LMAX Exchange’s business model I’ve always been regulated as a broker-dealer and I’ve alway been regulated as an MTF and there’s Chinese Walls between the two.
Charles Ellis, a trader and quantitative strategist at Mediolanum Asset Management, explains how data can be used to help generate alpha signals.
The first thing that Ellis points out is how trading firms can most effectively use data is dependent on their investment process and the type of research questions they are trying to use the data to answer.
For starters, he says, firms need to consider what investment time frame they are working towards.
“Then you have to ask which of these time frames can we add the most value to? What data do we have access to? And then it goes into what sort of questions can we answer using this data over these time frames?” comments Ellis.
Philippe Bonnefoy, founder of Eleuthera Capital, explains why the FX industry suffers due to a lack of an effective industry benchmark.
Bonnefoy discusses why the 4pm Fix can be beneficial, but points out that it also suffers from potential gaming. He then adds that benchmarking remains a huge issue for investors trying to work out whether they should consider FX as an asset class or not.
“With an equity benchmark, you know what the index is doing, for fixed income you know what the composite bond or the bond benchmark in 10-year Treasury is. For FX, is it cash? Is it a three-month yield? Is it overnight pricing? How do I say that you created value for me in trading FX other than just saying whether you were positive or negative?,” asks Bonnefoy.
Adrian Lee, president and CIO at Adrian Lee & Partners, explains why combining currency hedging with alpha generating strategies can benefit investors.
When questioned about whether clients are looking for hedging or alpha from currency managers, Lee responds that many clients actually need both simultaneously.
He continues: “The challenge of risk management is that currencies are a biggish risk – there’s no long-run return really, so on paper it makes sense to reduce it. But when you start to do these hedges after you’ve got the international assets, you’ve got to get the currency exposure back… with that [you have] really strong cash flows because if you hedge half your 20% international, it’s 10% of your whole portfolio. If that goes against you [the impact on] performance in a quarter could be massive.”
Although there are clear drivers pushing more FX products into central clearing, this is unlikely to have a significant impact on market structure, says Paddy Boyle, the head of ForexClear, LCH.
“The pressure to clear for banks that are subject to bilateral initial margin rules is very, very high and we have banks who tell us they’ve been cut off by other banks because they weren’t clearing,” he says.
That, explains Boyle, is one of the negative drivers towards central clearing, while on the positive side there are lower capital costs, lower initial margin requirements and fewer credit line restrictions for firms that choose to use clearing services. As a result, Boyle predicts that cleared FX volumes will increase “pretty significantly” going forward.
Hasan Amjad, head of algorithmic trading at GAM Systematic Cantab, explains how machine learning tools and techniques have enabled his firm to improve almost every aspect of its trading capabilities.
“It goes all the way really,” he says, “Starting with portfolio construction, all the way to the final trade and the post-trade analytics.”
For example, Amjad points out that machine learning can be used to improve pre-trade analytics by more effectively identifying what kind of trading the firm should be engaging in during current market conditions. He concedes that there are other techniques that enable firms to determine market conditions, but that “machine learning just takes it that one step further by being able to ingest a lot more data and give you the answer”.
Philippe Bonnefoy, the founder of Eleuthera Capital, explains how his firm has evolved over the years in response to changes in the FX market.
“Over the last 20 or 30 years we’ve evolved massively, starting as discretionary macro traders, then using more and more quant models to manage positions and then finally using the quant models to actually do the trading and become a quant portfolio manager,” he says.
Part of the reason for this, explains Bonnefoy, is that the price behaviour of the FX market has changed significantly as market making has become overwhelming conducted electronically. Even now, he points out, FX trading firms need to be cognisant of these changes and how they’ve impacted liquidity when they screen and look at data to test their models.
Uncertainty about regulations, a lack of trusted custodians and concerns about security are key factors that continue to deter many large financial institutions from trading cryptoassets, says Kevin Beardsley, a managing partner at B2C2.
Amongst these three factors, Beardsley cited the lack of regulatory clarity around cryptoassets as the biggest issue for these firms right now, pointing out that no major bank wants to clash with their regulators for trading in what is, relatively speaking, still a small marketplace.
“The large institutions are all waiting for the regulations to become clear, which is a very rational approach,” he says.