Structured products have significantly evolved over the past several years, and providing asset managers with greater transparency into these particular investment vehicles is essential for continued growth and adoption.
On Tuesday, June 14, the Nasdaq Fund Network (NFN), Luma Financial Technologies, and Morningstar hosted a series of in-person panels to discuss how recent innovations in technical and analytical platforms will create the right environment to ignite this industry trend into a true revolution.
For the second panel of the conference, Stephen Bodurtha, Luma board member and an adviser and instructor in Columbia University’s master’s in Wealth Management Program, moderated the discussion. The panelists included Florian Reiter, Head of Fixed Income Data and Analytics at Morningstar, Anil Varughese, head of Structuring and Origination for MLI and UNHW Solutions at Bank of America, and Brady Beals, director of Investment Solutions for Luma Financial Technology.
The following is a transcript of the second panel discussion, which has been lightly edited for clarity.
Stephen Bodurtha: Welcome to our second panel here. I am happy to be associated with such an innovative group and work with a number of folks in the audience over the years in the business. Florian, when the last panel talked about structure products for as long as anyone can remember being categorized as “other”, sort of undefined, Florian is one of the key people here who has tackled that. And Florian, if you want to talk a little bit about what makes structured products so challenging to categorize and analyze?
Florian Reiter: Happy to talk about it. The first thing I want to say, though, is that it wasn’t just me. Right. There is a great team at Morningstar who contributed to that, and you’ll see that on the paper. There’s Brian Austro, who’s contributed a lot to this, and it also originated out of discussions with our partners, so there’s been quite some collaboration going on. When we saw the challenge, we asked ourselves what our structured products are in an asset allocation because in an asset allocation, in the end, you would just have a few assets that are there. You have stocks, you have non-U.S. stocks, U.S. stocks, bonds, cash, and that sort of ugly category other that structure products unfortunately also used to fall into. So, what are structure products in this context, and you could argue that it’s whatever the underlying is because that determines the payoff. So mostly, that will be equity. You can say it’s equity, but there are others who are saying, well, technically and legally, this is debt issued by a bank. So that sounds to me like a bond. And the thing is that both of those views are right and wrong at the same time, just to a certain degree. And what we try to answer with this is quantify that degree. So how much is it a bond? How much is it actually equity at any point in time? And the way we’re doing this now and that we’ve come up with is, what you could say is a risk-based approach. Now, that’s where it could get a little technical. And I’ll try to keep this really, really short. But just, you know, the essence of it is that we’re taking the Greeks of the structured products. The sensitivities of its value with respect to one, the underlying, and two, the sensitivity with respect to changes in the interest rate. They can have those two components; we’re then scaling each of those with its respective volatility. So, the volatility of the underlying; volatility of the interest rate. And then you have these two components. And what we then do is simply assess the relative sizes of those, and that will tell you how much the price dynamics of a structured product are determined either by its underlying or by a fixed income/bond side by the interest rate side. And that gives you a fair representation of the status quo of how much this product is driven by its underlying or by fixed income. And then you can have an answer to the question, what is it? And it’s quite a general framework that will work in all kinds of products, all kinds of market conditions, and ultimately helps us to get it out of the other category.
Stephen Bodurtha: Florian, is it right to say that using a risk-based approach tells the users or tells the advisor more about how the product will behave in a client portfolio?
Florian Reiter: The answer to that is yes. That’s exactly the point of it. I think that is the essence because if one of those components dominates in the methodology, that means that it behaves more like that in your portfolio and will therefore shift your portfolio a little bit more towards that direction. And the idea is to provide insights on that basis and enable conversations between advisors and investors on that basis in a portfolio context.
Stephen Bodurtha: I’m going to pivot now for the benefit of the panel members from our carefully prepared plan. Anil, I’m going to jump to you actually and based on Florian’s answer just now about understanding the behavior better, being able to anticipate, and maybe even model the behavior of structural products in portfolios. How does that change the opportunity set? How does it change your job from a distribution standpoint?
Anil Varughese: Yes, typically the way we’ve looked at structured products, and I think we heard a little bit about that in the previous panel, is that it’s either equity or we put it in this bucket of other. And now we have a deeper lens to be able to classify it appropriately or at least a benchmark to be able to look at and reflect on and decide whether that’s the appropriate approach. But this is a much cleaner, much easier way for clients to fully appreciate what the composition of a product is within their broader portfolio context.
Stephen Bodurtha: And what do you see? Do you see the usage of structural products running the gamut from fully long equity with maybe a touch of protection to structured products that are supposed to function more like fixed income?
Anil Varughese: Traditionally, we are a heavy equity-linked, focused business. And while we’ve seen that as the predominant type of product that we do, typically, the behavior of that vehicle will change over periods of time and, therefore, should be commensurate with what’s happening in the marketplace. It’s very realistic to expect different outcomes as market conditions change.
Stephen Bodurtha: Right. How about operationally, how does it change the options you have, the capacity you have to get more products out in the right way through the right advisors to the right clients?
Anil Varughese: Yeah. And I think this stems back to some of the conversation that we were having earlier, which is, you know, effectively a lot of the data innovation and analytics that are being presented, it really gives a scale to our business. Starting from a perspective of origination, this allows us not only to expedite the delivery of new offerings into the marketplace but also creates the capacity for the team to really focus on things such as personalization. So, our job is to be able to deliver a consistent, strong menu of different product types into the workplace and to the ability for advisors and clients to adopt. And this is the technology and research that can help us deliver that.
Stephen Bodurtha: Got it. Brady, I really want to come to you now with a question, and that is, it’s hard to go to an investor presentation, listen to a business plan without data transformation–transferring business through data–without that being part of the discussion. I’d like to understand–some of those discussions, at least for me, take place at a 50,000-foot level–what’s actually going on here? What’s the connection? What’s happening between Luma and Nasdaq that is enabling some of these things? What is what’s the data, and how is the data going from here to where it’s supposed to go?
Brady Beals: Yeah, exactly. To step back, where has Luma been over the last five years? What have we been developing? It’s been very much focused on how you do certain things with structured products. So traditionally speaking, pricing notes, finding products, tracking how your note was performing–all very difficult to do. And that was very much the focus of Luma to illuminate that and make it simple, make it accessible to advisors by going on to Luma itself. Where the partnerships with Morningstar and Nasdaq become so interesting is that they already have an ecosystem where advisors are used to going in, they’re used to seeing the entire portfolio and now they’re adding on all this expertise that we have with just structure products. And so, we’re able to basically amplify everything we build into the larger ecosystems that advisors and clients can actually see a structure note next to an equity investment, next to a fixed income investment. The mechanics of how we share that data and how we work through that is very much a collaboration. We certainly have data that we’re already calculating and already have available on the platform. Morningstar has a certain methodology. They have a certain way of calling things; Nasdaq does the same thing. We certainly work with them, and as partners, I think that went very well to modify our data, massage the data, but then also amplify expanding beyond what Morningstar might just show. For example, in a report for fixed income, we’re able to incorporate very specific features of structured notes into that.
Stephen Bodurtha: Can you share an example of data that Luma has in its ecosystem that becomes very powerful as it travels to Nasdaq and then ultimately to the Morningstar Advisor Workstation?
Brady Beals: Yeah, certainly. I would go back to Florian discussing the sensitivity of notes to various factors in the market. That was a very hard thing to track, traditionally speaking. The worst of structures, for example, you’re not really sure about. Should I be tracking the one that is actually the worst performer? Should I be tracking the one that is actually the most volatile? Those are all factors that we track. So, we’re able to calculate. We’re able to display the Greeks of a structure. We’re able to kind of simulate through Monte Carlo simulations the likely path or paths a note might take from here until maturity. Morningstar is obviously able to take that in and amplify what the impact of those calculations can mean for a client’s overall portfolio.
Stephen Bodurtha: Got it. So, Florian, I’m improvising, but is it right to say one of the things you might do is test the model you’ve developed against actual experience?
Florian Reiter: Oh, yes, of course, we won’t be putting this into any of our systems if we hadn’t properly tested it. We’ve gone through various examples to see the behavior and see that it behaves as we are hoping and expecting and making sure that that’s all the case. And I’m happy to say that it is. So else, we wouldn’t be putting it out there. And that’s also going to be true; I think Kevin on an earlier panel already mentioned that asset allocation is just a starting point, right? We think the portfolio approach is the right way to go for any investment advice, clearly including structured products. So, after asset allocation, there will be all kinds of portfolio analytics that will include structured products and in the reports that you get on your own portfolios, and they will, of course, do the same kind of due diligence before we actually release it.
Stephen Bodurtha: And Anil, coming back to you. What are some of the things maybe that haven’t come up already today that this audience would benefit from knowing about what it is these advisors are looking for from this product and partnerships like the one we’re talking about here today?
Anil Varughese: I think there are a couple of things in our daily conversations with advisors that come up with some high frequency, which is first streamlining that experience. I think as more education, more training, and more knowledge about the product becomes available, we need to simplify that experience. And for them, navigating the tool set to be able to identify an appropriate product based on a client preference is really important. With the partnerships that we have with Luma and otherwise, we’re helping to deliver that modernized experience. And the second point is the combination of all the things that we’re talking about here helps to deepen the conversation that we have with clients because, ultimately, the challenge has historically always been how do you demonstrate the contribution a product has in a portfolio, like structured notes? And that’s always been a challenge. And therefore, with things like the Morningstar Analytics concept, I think the ability to actually show the contribution and the value-added and the ability for the product to meet the client preference is ultimately what’s going to propel the adoption of this product in the future.
Stephen Bodurtha: Great. I’m going to turn to Brady next with a question. But for those of you folks who want to ask questions, I’ll create a pause in just a moment for you to be able to speak up. So, Brady, in your role, you have a chance to work with larger wealth management organizations but also in increasing followership among independent wealth advisors as it relates to the use of structured products. Are there differences between those two populations? And what do you see happening with the independent advisor community compared to the larger wealth management firms?
Brady Beals: So primarily, I’m working with RAs and family offices with structured notes. My background before Luma was more on the wholesaling side to traditional retail broker-dealers. There is certainly a distinct difference in the approach. We’ve seen a tremendous amount of growth in the RA space, primarily around portfolio allocation. A lot of RAs are looking at particularly income notes, but also growth notes as well as a distinct part of the overall portfolio, almost as a sleeve of the overall investment. With that said, that necessitates going beyond just individual product tracking. You have to now calculate and show them in reports. How is this 20-note portfolio actually impacting my portfolio? If I add an additional note to this 20-note sleeve, how is that going to impact the risk-return profile of the overall investment sleeve? How is that going to impact my exposure? So, it is very much around asset allocation. They very much see structured notes as a way to either enhance yield, provide downside protection or even potentially look at it as a true alternative investment through traditional investment vehicles, if you will. And that’s very much where I’ve seen growth is when RAs have that perspective, and in working with Luma to actually have the output they need to show clients or to analyze it from an investment perspective, that makes it all the more powerful because they can actually tell what’s going on with the overall investment.
Stephen Bodurtha: Yes, and you mentioned family offices. Are you seeing both multi-family offices and single-family offices beginning to participate? And how are they the same or different?
Brady Beals: I would say a single-family office is a little bit of a hybrid between an RIA and a traditional broker-dealer. They certainly have, I would say, conviction trades. So those are trades that are tied to a single stock, traditionally speaking. They’re really looking to take advantage of market movements. The past couple of days is a good example of that, where they can get a potentially good entry point, good yield, that sort of thing. But then they do also have that overall portfolio perspective as well. Multi-family offices, I would say, are going more down the SMA or sleeve routes where they have a certain investment philosophy. They’re working with advisors at the multi-family office. And really, we partner with them to get more attention to a certain strategy or sleeve that they might want to convince other advisors at that family office to get into.
Stephen Bodurtha: You mentioned custom notes or conviction trades. I’m wondering if you, Brady or Anil, have any sense of what the average size of a structured note issuance is, say per ticker. Has that been staying the same as has been coming down given some of these scale benefits that we’re seeing?
Anil Varughese: I think we’ve definitely seen, at least within our channel, that the total issuance size is starting to come down quite a bit. I think that the concept of bespoke customized is more available and much more adopted, and therefore the traditional leverage return note that was available once a month, which was basically taking something off the menu, is now, people are realizing that there’s more optionality to it and therefore moving more to the bespoke nature of certain products.
Audience Member: I think I know the answer, but I’m just curious. When is the portfolio analytics target to be released on the Morningstar platform?
Florian Reiter: So, the asset allocation piece that we’ve been discussing will be released in Q3, and I hope Kevin is not going to kill me for mentioning a date here. But that’s what the plan is. And then there’s going to be all kinds of other things that we are currently scoping out and developing a methodology for that will follow after that. But with those, I would really not say any timeline. But there’s more to come.
Audience Member: When will the back-test on that product be available?
Florian Reiter: The back-test on the asset allocation methodology, if we put that out? That’s a good question. I mean, we’ve done, as we’re just saying, and the due diligence that I mentioned, we’ve generated a whole bunch of them. Whether or not these are actually put out there, I honestly don’t know, but I think I would be open to making these available.
Audience Member: Do you think when we get the Q3 methodology released, will you be willing to host a broader call with some networks that are considering raising value proposition?
Florian Reiter: Oh, yeah, of course. I mean, we are always happy to reach out and speak with the industry. Absolutely. No question about that.
Audience Member: Florian, what would you recommend for the regular investor out there right now with the current market environment in terms of actions–what’s the type of product, according to the analysis you’ve seen lately, that could work well for that kind of extra offer or yield that they are looking for?
Florian Reiter: Yeah. And you know, I’m going to give you an answer to this that you probably don’t want to hear. But I think that’s the way it should go. You know, we are not in the business of specifically advising on certain products, but there’s still something that I can say. And I think the advice would be not on a certain product, but the advice would be to consider the portfolio context. Don’t look at any investment, including structured products, in isolation. I think that is the right way to go. You should understand your personal situation and understand the mix of assets you have, including all kinds of exposures. And that should be the basis for your analysis. And I hope that what we’re doing is going to contribute to being able to do that. But when it comes to specific products, it’s not Morningstar; we won’t be giving any advice on that basis.
Stephen Bodurtha: Building on that, I’m wondering if you’ve seen any change since the end of last year, let’s say, with obviously big changes in the financial markets, in the types of structures that advisors, clients are interested in and may be more appropriate now than they were six months ago.
Anil Varughese: Yeah, I think there’s obviously an industry shift in terms of callable products. I would say the composition of our books has shifted slightly lower, less callable products because less are being called in there; therefore, the vol dollars being harder to achieve. But I continue to see folks that are really interested in deeper barriers [and] more downside protection as markets have been volatile. But there still remains an interest in generating yield as a play to be able to focus and navigate volatile environments.
Brady Beals: I would just add, I think that’s certainly true. The barriers have certainly become more conservative, particularly in the last two or three months. I’ve also seen a little bit more of a bias actually towards domestic indices. I think there’s just gravitation towards earning that enhanced yield by keeping it as conservative as possible.
Audience Member: Obviously, you guys covered structured products in the market; what about other products that you covered, as well, too, on Luma?
Brady Beals: Yes, we cover annuities. We cover, to my understanding, I’m not an annuity expert, but all types of annuities, so DSPs, FIAs, VAs and RILAs, which are very interesting if folks aren’t familiar with those. Those are very much like a buffer-note-type of return structure but in an insurance wrapper. That is definitely something that we’ve seen a tremendous amount of growth with. And it’s an interesting dynamic, too; as rates have come up, I think annuity products have become more attractive in and of themselves. I think structured notes also have a certain attractiveness to them in this type of market as well. It’ll be interesting to see where clients gravitate towards, but it’s something that we definitely are very excited to look at in that same portfolio context with annuities as well.
Audience Member: When you’re looking at [INAUDIBLE] that in your analysis of the … market, rising, looking at it and constructing the value of a structured annuity, the equity product seems pretty straight forward. But what are the assumptions when trying to give bonds to the issuer? What types of things do you take into consideration?
Florian Reiter: I think that’s an excellent question because that is actually a little bit the harder piece. But you know, the starting point of the analytical components here is always the pricing of a structured product because we talk about the Greeks and the sensitivity, so basically a result of the pricing engine. Now that you actually have an interest rate, you cannot price any derivative without an interest rate in the model. So that’s the bit that we are relying on. Now, admittedly, you can argue that it is an approximation, and this model is by no means, you know, in 100% detail, perfectly accurate. It is an approximation. And that’s the bit, though, that we are using to estimate the fixed income part of it. It’s an interest rate inherent in the pricing model, and that’s the one we’re using to represent the fixed income side of things. But it’s an excellent question.
Audience Member: Does that rate change with the issuer?
Florian Reiter: In the concept, it should, but in the pricing of — now, it would get really technical [because] you’re in a risk-free world in terms of pricing derivatives, and therefore, it is technically not. But of course, the degree to which interest rates have an impact on the product are relatively similar. And you will see that in, for example, the volatility component picking up when the markets will get shakier on the issuer interest rate side of things. So, you will see it reflected there. Now, there is a version of this where you could, of course, have a particular issuer occurs and so on. But it is an approximation that we think makes a lot of sense.
Stephen Bodurtha: I’m going to ask each panel member for a prediction. What does the future hold? So, Anil, this may not be fair to come to you first, but I’m wondering if you have a crystal ball out and what’s the path we’re on here, and where is it taking us?
Anil Varughese: I think we’re on a path where we’re going to continue to see more education, more transparency, [and] more awareness, which will lead us to be able to try to figure out how best to deal with that demand. And, ultimately, I see advisors and clients alike having more control and being more in the driver’s seat. So effectively, being able to manage the identification of our product and, to some extent, the execution. That’s where I see we’re eventually going as an industry of thanks.
Stephen Bodurtha: What about you, Brady?
Brady Beals: I would say just increased customization. I think that direct indexing is a good analogy for what I see happening with structured notes and that advisors will no longer struggle with the basic questions of: How do I see products? How do I customize something? How do I price something up? What does my portfolio look like if I add this note or sell this note? Those are all going to be answered and almost ubiquitous, I would say across again, just pointing to the Nasdaq Morningstar relationships. They’re going to be available for clients and advisors. That said, I think you’re going to see much more of a bias towards this– a unique investment for this specific scenario with my client, and I have the means and the ability to actually go and create that quite easily.
Stephen Bodurtha: Right. Thank you. What about you, Florian?
Florian Reiter: Well, I wouldn’t call it a prediction, more a possibility, let’s say. But our Morningstar CEO, Kunal Kapoor, recently said at the Morningstar Investment Conference that active personalization is the new active investing. And to be clear, he wasn’t specifically referring to structured products there but more generally. However, I think that applies to the structured product context because, in the end, it’s the most flexible product type that you have. And we’ve talked today about the data tech now being available to do all kinds of things. I think where this can go is that you can create structured products and propose them in an automated way based on data you have of a client’s portfolio and perhaps other client data in terms of preferences, restrictions and so on. And on that basis, you can generate structured products that fit that particular person in a personalized way. So in a way, that’s a possibility for mass customization, and that will make the lives of everybody easier in this process. I think that’s a possibility.
Stephen Bodurtha: And that might be a good note to close on as well. Thank you to our distinguished panelists here. Panel 3 will begin shortly.
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About Nasdaq Fund Network (NFN):
Nasdaq Fund Network (NFN) offers fund data services that deliver transparency to investable products to help ensure professionals and non-professionals can make more informed decisions with their assets. NFN facilitates the collection and dissemination of performance, Net Asset Value (NAV), valuation, and strategy-level reference data for over 35,000 products to 100 million+ investors.
Read more on NFN and Luma’s partnership here.