Total time: 11:44

Roman: Well, welcome back to the Sage Advisory podcast. This is Roman Samuels. I'm one of the regional consultants here at Sage, and today I am joined by a very special guest, Samuel Hikspoors. Sam, how are you?

Sam: I'm very fine. Thank you.

Roman: Good, good. Good. Could you tell me just a little bit about MAI in general, the overall process of what MAI actually means?

Sam: Absolutely. So MAI stands for “multi asset income.” And generally the investment process that we have adapted in designing that strategy and managing it for the last so many years is a multi asset class quantitative approach. For example, obviously we tap into the core fixed income in the U.S., which appropriately it's called the core. We tap into all the high yield U.S. sectors, including bank loans or high yield junk bonds, or muni high yield and such. And we also tap into convertible bonds and REITs as well. We classify that as a hybrid exposure because there was some component of those sectors that relate to equities. Essentially, although it's not equities, they have some component of exposure that will move in tandem with equities at times, so a highly correlated asset right. So these risk needs to be taken care of.

1:25

Roman: And then a fourth food group that we're pulling from is pure equities.

Sam: But it is not market-cap-based type of index or anything like that. It is more high dividend, high dividend stocks across the world and regions, so to keep our portfolio well diversified even in that bucket.

Roman: That’s right because we're looking for income. At the end of the day we want dividend payers here.

Sam: As long as it blends well with the rest of the portfolio and it's used in a way that reduces the volatility of the risk of the portfolio without reducing the level of income. So and in doing so, we also constrain ourselves to very liquid markets. We do not invest in, say, esoteric asset classes that potentially can offer a very high level of income but no liquidity. That are very hard to sell in times of distress and such -- we avoid those.

2:21

Roman: We want something that can be traded in both good and bad markets. So just to kind of summarize, we're talking about a portfolio that is intent on income. It's not really focusing that much on the capital appreciation of the investments you buy. We're going outside of the traditional bond market and basically for four food groups of asset classes -- core fixed income, non-core fixed income, hybrids, and then dividend equities. And we're constructing the portfolio in more of a quantitative approach to try and mitigate the risks that are associated with putting that portfolio together. So, you know, I’ve got to imagine that if I’m putting a portfolio together that is now not just bonds, is not just traditional fixed income securities -- I'm going into hybrids, like MLPs and REITS, and all types of other things. And I'm putting this portfolio together, I've got to assume that there's some risks in doing that that traditional fixed income investors are not quite familiar with. So, could you tell me what are the risks of this landscape of putting a portfolio like this together?

3:20

Sam: We have talked a little bit about it earlier, essentially the fact of having various modes you know, various asset classes that blend together without speaking the same language, so to speak. Because in fixed income, the way you measure risk and you understand your risk exposure is in composing your portfolio and duration and spread exposures, for example. In equities, it is going to be more sector allocation and/or the beta relative to the essentially capital market, you know, the broad equity index. In hybrids, or in high-yield bonds or bank loans -- it's not that simple. There's no one way to decompose the risk that combined nicely with the other asset classes, such as fixed income and equities. So essentially what we developed is a multifactor risk management approach that allows us to decompose every single one of those asset classes into their main factors of risk that essentially gives us across the portfolio from a top-down perspective, if you will, a good measure of where downside risk may come from. So for example, a certain asset class may not have a yield that is stated, for example, MLPs don't have a precise yield stated or REITs don't have a precise yield stated. So you cannot measure the risk of those sectors via duration and yield. But you can certainly decompose in terms of Treasury exposures and equity exposures and spread components, for example, that will make sense from a more mathematical perspective. It's a little bit more abstract, but then that is why it's a more quantitative, and rigorous, and data-driven approach to risk management.

5:08

Roman: So essentially, you know, if I'm, if I'm hearing you correctly, because we've got bonds and stocks and other types of asset classes inside of this portfolio -- the way that you measure risk is different in each of those, that you're looking at different metrics. So what you're talking about is a process that takes those risk factors and kind of makes them more normalized in the sense of you can really say, “okay, this is the risk factor of this, this is the risk factor this,” and then put a model together that tries to blend the different risk characteristics of these asset classes in the most advantageous way.

5:39

Roman: And talk to me about correlations. I know that that's a huge component of what you're doing. What are correlations? What does that mean, and why is that an important component of what you're doing?

Sam: Correlations are very simply part of our proprietary risk model that are used to assess the risk of various asset classes but also assess the common risks and how across asset classes and how different asset classes will move together in which period of time. For example, some asset classes may not move together in time, in a period of calm or in a bull market. But once major crisis happened, like in 2008, for example, then various asset classes tend to start to go down together with a higher correlation. So it is very important to have a good grasp of that.

6:30

Roman: What you're trying to do is trying to put together, and correct me if I’m wrong, a portfolio of things that are not going to all move in lockstep together.

Sam: That's right. To a large extent that's right. So there's a trade-off to strike there in the sense that if you are disallowing the portfolio to take any kind of risk, then you cannot generate much yield either.

Roman: So you can't get the return you're looking for.

Sam: That’s right. So there's a balance to strike there, and given that those MAI and TAMAI solutions are Sage Advisory solutions -- we have a legacy of being very conservative in our allocation and in our way to manage investment portfolios, because the founders of our firm, as you well know, started from a fixed income investment background. So these MAI and TAMAI solutions are really designed to generate high yield or high income for our clients, but within strong risk constraints. So we tend to err on the side of caution.

7:33

Roman: You know, a huge component of that is because we're not trying to grow the capital appreciation here, we're trying to get income. We're trying to do it in a in a in a smart risk approached way.

Sam: It's actually -- I did the portfolio analysis lately about precisely about that. And well over 90% of the total return of MAI in normal market situation come from income. So it is really not the intent of that portfolio to be equities on the bull markets. But over a full market cycle, it takes care of generating capital gains via income or gains via income. And it does so at the rate within that risk constraint budget that we are allowed to take. It is going to be hard to beat we believe.

8:24

Roman: Got it, and you mentioned something there called the risk budget, which I know we haven't quite got to yet. But the one thing that we've put on this portfolio is kind of a volatility constraint, some type of what we're calling a risk budget. Could you elaborate a little bit more on that?

Sam: So quickly, our main risk budget is to not exceed 150% of the Agg volatility at any given time.

Roman: And when you say Agg, you’re talking about the Barclays Aggregate Index?

Sam: Right. So basically the benchmark of MAI is 80% Agg and 20% Equity High Dividend, and so the Agg is a mainstay of -- in fixed income, the Agg is the main benchmark out there. Th index that most of our clients keep in mind and you know, bench themselves relative to. So although we are aiming at an income level that is significantly higher than the Agg, and therefore, from an income perspective, the Agg is not the best benchmark. From a risk perspective, it really gives us a bar to not exceed. So we don't want to go more than 1.5 times the level of volatility currently present in the Agg as we measure it.

9:38

Roman: Got it. So it's almost kind of like it's giving us enough juice to try and grab more income than the Agg –

Sam: It is still a risk that is totally appropriate for the vast majority of fixed income investors. And that's where we started with that product. From a risk perspective, the way I like to think about it is that MAI and TAMAI are good sources of income for fixed income investors looking for additional risk but who don't want to go all the way to equities. And they are also looking for much greater diversification than is possible in equities. Or for equity-primarily investors that have already a lot of exposure to equity, they're looking for solutions that are fixed income-ish but don't want to go all the way down to the Agg, because for them, it feels like cash or it feels a little too conservative -- so they want to keep a high level of income in that more conservative sleeve of their portfolio. MAI is a perfect fit for those kind of investors as well.

10:39

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