What feedback are you receiving from investors you are currently meeting in the region regarding protection strategies?
We organised a similar road show here on hedging solutions at the beginning of this year, and it’s interesting to notice how much stronger the interest from investors now is. This is certainly related to the wake-up call we had in February/March, when global equity markets hit a succession of air pockets. Before that, and for the past five to six years, portfolio risk management was clearly not a priority in investors’ approach, as risk-on assets were carrying positively and smoothly. The situation is now starting to change, with investors remaining constructive; however, adding a line of defence to their portfolios is now moving to the top of their list of priorities. This is a trend we are seeing not only in this region, but also in Asia and Europe.
What is UBP’s approach to protection strategies? How do you implement them?
A key driver when designing a protection strategy is about striking the right balance between minimising the cost of holding a hedge while maximising its ability to react when stress arises.
Based on our experience of running live mandates, we believe that one size does not fit all, i.e. a single hedging strategy may struggle to capture the majority of the sequences occurring during a sell-off. This is why we have been running two complementary strategies since 2012. The first strategy is designed to protect against standard market corrections and answers the question of minimising the cost of holding the hedge; the second strategy is designed to protect against more extreme markets corrections, and answers the question of the reactivity of the hedge.
A robust, final implementation would then consist of combining both sub-strategies and adding this blend as an overlay to the existing long equities portfolio.
Are you focusing essentially on DM equities? What about EM equities?
Let me give you a brief overview of the ingredients we are using for both sub-strategies. The first strategy uses listed equity futures and listed options that we systematically roll. The second strategy uses listed volatility futures, for example, VIX futures.
There is ample liquidity in these listed instruments when it comes to US or European equities, hence our ability to deliver solutions for both individual markets and sizeable portfolios.
When looking at EM equities, there’s a lack of instruments for the second sub-strategy, i.e. there is basically no equivalent of VIX for, let’s say, China or Brazil. Hence we would be able for certain EM regions to implement the first sub-strategy but not the second one, and, as a result, a hedging strategy on EM equities could be delivered but it would remain only partial in terms of construction.
However, when looking at an EM investor’s generic portfolio, the bulk of the allocation to listed equities will be made up of US equities and to a lesser extent European equities. Hence our current toolkit may well represent a credible solution for the majority of an investor’s listed equities bucket.
Away from protection strategies, do you see other topics raising interest with the clients you are meeting?
Our team is also focusing on investment themes. Here, we want to think thematically, i.e. identify megatrends that carry significant long-term growth opportunities for investors; however, access to these may currently be suboptimal.
Megatrends are those powerful and disruptive forces that are increasingly reshaping how certain industries have been traditionally run. With this in mind, the artificial intelligence (AI) theme represents an attractive avenue for us to explore. Indeed, we believe that AI is one of those structural shifts with irreversible consequences for the global economy and society. However, there are currently only a few investment vehicles offering a liquid exposure to it, and most of the time the AI allocation will be diluted by other themes, such as robotics.
This is why we decided to offer simple access to AI that would be pure while remaining liquid and cost-efficient.
What is the investment process?
The first thing to do was to analyse and explain in simple terms the greater ‘AI trade’. When you decide to look beyond buzzwords like “machine learning” or “natural language processing” that may add confusion to the discussion, you quickly realise that the key driver of AI development is data. Simply put, data are to AI what food is to humans: the quantity and the quality of the data you feed your machine will determine how “intelligent” it will be.
Looking at today’s status of the data ecosystem is quite instructive. 90 per cent of the data currently available have only been generated over the past two years, and that quantity is projected to double every two years, meaning we are in a truly exponential growth phase. However, when looking at the quality of these data, you realise that only 20 per cent is currently being structured—in other words made usable—and, more interestingly, only 1 per cent of it is being analysed.
To us, this vast untapped resource represents the key hidden value to be monetised in the AI trade, i.e. the entire process of transforming data from “volume” to “value”. As data is sometimes described as “the world’s new oil”, our portfolio invests in companies involved in the “refining” process of the data: companies that will store data, structure it and ultimately analyse it.
Providing private investors with quick and easy access to the theme was essential, therefore we wrapped the strategy as an open-ended certificate that offers daily liquidity and an ISIN code. We started promoting the strategy in Switzerland first, positioning the certificate as a long-term satellite investment in a typical equity allocation. Interest from private investors there has been strong, and we believe that, going forward, we may have traction in the region based on the meetings we are currently having.
Are there other themes you are exploring?
The ‘smart data’ theme is another one where we see value for private investors but there is still very limited access to it. In a sense, it’s an extension of what we discussed earlier, as its final objective is to create investment strategies using AI. So, for example, instead of selecting stocks based on traditional fundamental factors like earnings growth, you could select stocks based on AI techniques that would, for example, create a sentiment index based on website activities.
Coming back to our initial discussion on protection strategies, do you see parallel avenues to yours that investors are exploring to reach similar objectives? How have they been evolving recently?
If you step back for a minute, you realise that our objective with hedging strategies is essentially to introduce some asymmetry to traditional portfolios, i.e. be able to come up with an overall solution that would allow a majority of the upside to be captured but that would also only be impacted by a minority of the downside. From that prospective, there are indeed other tools that can help generate this type of asymmetry, and structured products are one of them. Flows on the structured products side have continued to be sustained and are growing; however, depending on the region, there has been a slight shift in terms of product design. While the focus in recent years has essentially been on the hunt for yield with a certain tolerance for capital being put at risk, there has recently been increasing interest in structures with a high level of capital protection that still provide exposure to any upside should markets continue to rally. That may reflect the fact that we are gradually shifting from a zero-interest-rate world actively supported by central banks to a phase that is still constructive but which is approaching the end of a cycle.
Small box out: Philippe Henry joined UBP in July 2017. Before that, he ran the global structuring team at Deutsche Bank in London, covering structured products and systematic strategies for private clients. Previously he was head of financial engineering for Europe at Morgan Stanley, where his work covered both private and institutional investors in equity and hybrid investments. He started his career at Société Générale in Paris before moving to Barclays Capital in London, where he ran the pricing and new product development team for Europe. Philippe is a graduate of the French engineering school École Spéciale des Travaux Publics and holds a postgraduate diploma in finance from HEC Paris.