Neil Azous, Rareview RSEE

BlackRock, Dimensional. And then the third one is a specialization that requires expertise or active management. I would want you to think of Rareview Capital as fitting into that third bucket. That is, we specialize in non-traditional investment strategies. We deliver model portfolios to third-party asset management providers. We implement protective strategies that require derivative expertise. We focus on customized solutions, especially anything related to interest rates. And finally, we produce our own research. We don't consume it. Regarding my background, I'm the founder, the managing member, and the chief investment officer of Rareview Capital. I head our investment team and oversee all portfolio and risk management activities. And I also serve as the portfolio manager to the four Rareview ETFs that we manage. I've been fortunate enough to have worked at some great firms

Like Goldman Sachs, Donaldson Lufkin & Generate, and UBS Investment Bank. And I've been trained in various capacities by some of the best minds of the industries that have pioneered various products that we use every day in the capital markets. And as a result, I have a multi-asset background, a global macro investing foundation. And I guess the best way to think about me is I'm not a bull or a bear. I'm either an inflationist or a deflationist. And I absolutely have no religion when it comes to contentious topics like gold or China. They're just another commodity or country to me. Ultimately, I'm agnostic to the region or the asset class or whether something is a cash or derivative instrument. And the benefit to all that is that it allows me to be process-driven

And reduce human emotion when it comes to investing.

Committee meetings, the delivery of model portfolios, helping them with marketing, consulting solutions, of that like. We also do one of our main value adds is that prior to the launching of our registered investment advisor and our funds, I owned and managed a global macro research firm. And so part of our deliverables, which we make complimentary to our investors or shareholders or prospects, is that we provide them our research. And our research focuses on three things, idea generation, risk, mitigation, and portfolio construction, most importantly. And so we're trying to fill that void between economic strategy and trading of putting it all together in a process driven framework, and then being very transparent about that, and filling in all the blanks regarding the questions around portfolio construction, what the market is doing, etc. And so we make that available as well.

Money or the income phase. And then in the fourth phase, you want to be able to transfer those assets to the next generation or some other entity. And so our portfolios are more geared towards achieving those goals. And while it's always important to consider asset allocation, style premia, all of those things that would traditionally go into that, it's less of a focus. We want to just meet that goal and find the best instruments to meet that goal. So that's the primary input to those portfolios. Regarding the security selection, they can range from passive or active. They can be low fee like a Vanguard. They can be a higher fee if they're trying to triangulate on to a particular outcome. And in terms of our case, we have one ETF that we're modeled that fits into

Each of those buckets. But they're not going to be 100% concentrated in that. They will be a measured amount. So we will certainly use other instruments in there that meet what we're trying to do in terms of that goal. But our product could be anywhere between 2% and 15% on average into those models.

It's been refined or honed over decades. And it helps us identify where the asymmetry is in various probabilistic outcomes. So keeping things simple on a scale of zero to 100, something gets between 80 and 90, we want to sell it. Something gets between zero and 10, and we want to buy it. And then rinse and repeat that as the probabilities around the path of the interest rate hiking cycle or cutting cycle start to change every six to eight weeks. So it's completely model-driven on the fixed income side around that. Secondly, on the income side, we're specialists in closed-end funds. And so that's a model that's built in Python. It identifies to us the least expensive or the cheapest security on an intrasector basis. So if we've got 10 or 11 sectors across fixed income, we will identify in our model

What we think is fundamentally the cheapest one. And then we will implement that. And as it changes in its valuation through this model, we will sell that out and buy another one. On the equity side, we've partnered with a firm called GST Management that is, in my opinion, a world-class index methodology developer of strategies. And that product is algorithmic. It's systematic. It's quantitative. There is absolutely no human emotion or discretionary override involved in it. The idea of it being long short is that it's risk mitigating by itself. it's developed that way. And so there really doesn't need to be a human to decide what it needs to do in terms of going long or short. So everything we do here in sort of that decision-making process is model-driven. There are different types of models,

Models, but that's the primary input for us. And then secondarily, we want to do everything as quantitatively as possible. And the idea of being here is that it's like money ball baseball. It's statistical. We want to play in favor of the statistics that are higher degrees of success and stay away from the ones that are human-driven or that force you to be in your seat at any given time, knowing that you're never in your seat when it matters the most.

On that from a regulatory or compliance standpoint. And then in the sense of you need to make sure that you're treating all of your investor bases equally along the way, meaning a wealth management client is treated the same as a TAMP deliverable on a model, as well as your ETF and how you do that. And my experience is that it's an important piece of the puzzle to be involved in the TAMP world and the model delivery. And it can mirror a lot of the models that you currently run. But by the time you introduce the business component in terms of GIF's performance tracking, marketing to the various TAMPs, managing those models equally as if you're running them for a wealth management client or an ETF.

So you can see the P&L in real time like it's yours is a very big challenge for me personally and for our firm. And I would just, I would be remiss to say that it hasn't been less than fruitful in my experience. And so it's not one of these exercises any longer, like it was maybe five or six years ago, you go put a model on a platform and you think somebody's going to buy it, which they used to a lot. Now, you don't just do that, you have to pay to get onto a platform. And then you have to have a body that's dedicated to that platform to market to it. And these marketplace or these platforms that have marketplaces allow this, they now have 1000 plus type of investment strategies on there. So the

Competition in that open architecture is extremely high. But you're generating probably one third to one fourth of what you normally would in some other type of revenue stream. So it's really a question of your resources. But economically, it's challenging from the business standpoint.

To understand. So the question really is, why is it important for them to have and how do you go about educating the advisor as they implement it? Sure. So to answer your first question,

Really been for the last 15 years. I don't subscribe to that philosophy. In my experience, Brad, clients or investors are accustomed to weathering a garden variety stock market correction of say 7% to 15% once every year or once every two years. And if the markets are down, they don't have that big of an issue with their financial advisor or ETF man. However, if the stock market's up 20% and you're only up 4% because you're running, quote unquote, some type of hedge product, I tend to see people fire their financial advisors or replace that ETF with another one due to that significant underperform. So what I'm saying in English is that upside capture to us is very important, if not equally as important as the downside capture. And that's really the trick. And finding a vehicle

To solve for that is not easy in the traditional long short space, because by default, they run somewhere between, depending on how conservative they are, a 0.2%, sorry, a 20% net long to on average, a 60% net long. So let's just call it 40% net long or 0.4 beta to the S&P 500. So by default, if the S&P is going to be up 10%, they should be up around 4%. They're leaving a lot on the downside. I'm sorry, leaving a lot on the upside, based on that model. In our particular case, we wanted to reimagine that. And we sat out and said to ourselves, what do we need to create?

Or what is the product? And so I came across a person, his name is Rod Jones. He runs a firm called GST Management. He worked at some of the top places in the world. He was an index methodology expert, consulted and constructed portfolios for some of the largest pools of capital in the world. And we discussed this product, which is now the strategy that drives the Rareview Systematic Equity ETF. And what we wanted to do was find a vehicle that addresses what I think is the seminal investment issue for investors, which is how do you stay invested in bull markets, avoid the catastrophic stock market sell-off and bear markets, and then minimize that time back to break even. Now, I know every product looks for that. But in our case, we made an acknowledgement or Rod's strategy

Acknowledges that in order to try to achieve that, meaning you're going to participate on the upside, you're going to avoid a catastrophic drawdown that is very difficult to recover from. catastrophic defined as something south of minus 25%, not the garden variety stuff that happens every one to two years. And then figure out a way to stay invested, minimize your time back to break even. There has to be something of a sacrifice in there. And the sacrifice is that you don't know what's going to happen tomorrow if you're long, and you don't know how much you have to give up on the downside, meaning you have to sacrifice potentially the first zero to 10% on the downside to achieve this type of goal of staying invested during bull markets for the long period of time. And that's really what we're

Talking about here. And then at the same time, you want to remove the human emotion. And so what the strategy does that drives the Rareview Systematic ETF, or RC is the symbol, R-S-E-E, is that it makes a difficult decision when to get back into the market, as opposed to the human financial advisor trying to pick the absolute bottom or make that determination overall. And it won't always be perfect. You're never going to pick a bottom. But what it will do is make that decision to get long. And then when it gets long over a period of time, it will average in or it will get longer in that episodic period.

And you will be back in the game of staying invested and help you get back to break even quicker. And so that was where this strategy fits in. And in our case, just to take a step back, we have a philosophy, not we, the strategy has a philosophy where we don't believe that markets are micro-efficient, but we believe that they're macro-efficient. So that's the old dictum from Nobel laureate Paul Samuelson. But we focus or the strategy focuses on index level exposure to add value. We find that it's possible to generate above active equity returns when you exploit the behavioral patterns on a regional basis or a different volatility regime. We don't believe that that's the case in picking single stocks, meaning the alpha generation is extremely hard and isolated to

Just a small group of the 10,000 funds that do that. And then secondly, we also find it very difficult from, quote unquote, a risk-adjusted return basis to try to focus on style premia or picking sectors. for example, being long tech versus short energy, you might be having a very good year this year, but last year you had a terrible year. And the volatility of that approach is probably two times the amount of the stock market for being compensated half those returns over the long. And so we just stay away from that. Our goal in launching this product and partnering with GST management on this strategy was to fill the void of finding a solution that can stay invested, get short when it needs to

Get short, keep it simple to index beta, and keep people in the mark as opposed to, we want to focus on factors or style premia or single stock selection. We're trying to address a long-term solution, a core solution for our investors. And that's really the trick here. And so that's how we approach it. I can talk in length about certain things about it, but in general, our goal is just to capture the upside, not just the downside, meaning we seek to beat the market

Have long-term buy signals in them. And so we're long all four of those sub-strategies. And the total exposure of that is 133% long. And that's broken down in terms of the all-country

No matter how long you hold it for one day or two years. And so we want the added benefit of that. So it makes the implementation more efficient overall. And that's why we do that.

In terms of risk-adjusted return profile. And so meaning is the optimal performance at 20% of a weighting or 10? And we'll demonstrate that in a spreadsheet so they can see what that looks like and then decide for themselves what the right weighting is. If you want to just kept it super simple and somebody had a traditional 60-40 portfolio, 60% stocks, 40% bonds, we would advocate that we should be between 15% and 20% of that 60% on the equity side. And that would increase the risk adjustment.

Ever come across where you can make money potentially three different ways. The first one is that they're an income strategy and they have a very high distribution yield. So for example, the universe right now, depending on how it's asset allocated, you could be anywhere between 8% and 10% distribution. The second component to be able to make money is that there's potential principal appreciation from the underlying holdings, hence the, or a la the NAV of that fund. And then the third one, which is very interesting as well, is the potential for alpha generation, which is the, what we call discount to net asset value capture. And so if a closed-end fund is trading at a discount to its net asset value, and you can buy that at say a minus 10% discount, and then over the next year, that discount narrows to

Minus 3%, you could lock in that 7% of discount narrowing or alpha. And when you combine that, you've got this high distribution yield that's going to pay you no matter what, unless they cut their dividend. Or, and then you've got the principal appreciation potential. And if you have a model and you know what you're doing in terms of valuation, you have the potential for benefiting from this discount to net asset value capture and rinsing and repeating it. And so for us, we just philosophically love that profile where you have the potential to make money from three different avenues. And if nothing, if you're not doing anything, if the markets aren't cooperating, or you're not doing great on the discount capture process, at a minimum, you're going to get this high distribution yield, which helps generate the income

Or provide an allowance for somebody, or mitigate potential market volatility. And so that's the background on that. In the case of the Rareview Dynamic Fixed Income ETF, or the symbol RDFI, what we've done is take in the non-traditional advantages of the closed-end funds, which are the ones that, the three return streams that I just referenced, and married that with the traditional benefits of a dynamic fixed income strategy, which is a comprehensive fixed income strategy where asset class exposure is managed more dynamically or active, and it's really driven by market opportunities and risks. So not necessarily asset allocation. So in our universe, there are 11 fixed income asset classes. We would identify the appropriate weightings to each asset class.

Based on the market opportunity and the risk in each of those asset class. And then once we've done that and determined the weightings, we have a model that would select the closed-end funds in each of those sectors, and then optimize the weightings based on a number of factors to go into that particular sector. And what we found is that blended approach of traditional benefits and of dynamic fixed income, and the non-traditional advantages of closed-end funds ends up being a vehicle that gives you the allowance that you need if you need income or you have a budget to spend. But at the same time, act as a potential total return product as well and work in various environments over the market cycle when rates are more contained or come down.

Set of instruments along those different regimes? Or you could look at it like, okay, we are entering a hiking cycle, then we're in a hiking cycle, and then the hiking cycle is over, and then we migrate to a cutting cycle. What are the best representations for each of those regimes? And they're different, meaning you could be long fixed income beta or short fixed income beta in any of those regimes. You could be taking a bet on the shape of the yield curve, not to get too wonky here, but is the yield curve flattening or steepening? Those are very big decisions. And then the third one is, do you want to make bets in the options market? Define bets, you're never naked short volatility or short options,

But define bets or long only bets on the path of interest rate policy by the Federal Reserve, and make different bets on probabilistic outcomes using options. So in theory, there's three return streams, right? You get the market beta and the regime right, you get the shape of the yield curve right. And then thirdly, you want to get the path of the Federal Reserve policy right. And in each of those three return streams will make up some type of risk budget. And theoretically, they're all supposed to act as diversifying sources of return streams, doing something different. And if you can get all three right, well, you're going to have a really good year. If you get two out of three right, you'll have a good year that likely outperforms the aggregate bond index. And if you get all three

Wrong, well, then you're probably going to underperform the aggregate index. And so what it's really designed for is that if you've got a 60-40 portfolio, and on that 40% or the risk-free portion of that 40%, that sits passive, you hand it to an active manager like us, and we're seeking to beat that rate of inflation or the loss of that purchasing power over that market cycle to try to do better than what you would get just in that passive approach of not really doing anything with your fixed income beta or