ETF Expert Corner

Tony Barchetto Spotlights the Salt truBeta High Exposure ETF (SLT)

July 3rd, 2018 by ETF Store Staff

Tony Barchetto, Founder & CIO at Salt Financial, spotlights the Salt truBeta High Exposure ETF (SLT) and offers his thoughts on the proposed ETF rule.


You can listen to our interview with Tony Barchetto by using the above media player or enjoy a full transcription of the interview below.

Nate Geraci: The ETF we're spotlighting this week is the Salt truBeta High Exposure ETF, ticker symbol SLT. This just launched back in May and joining us via phone from New York to discuss this ETF is Tony Barchetto, Founder and Chief Investment Officer at Salt Financial. Tony, a pleasure to have you on the program today.

Tony Barchetto: Thanks for having me, Nate.

Nate Geraci: Tony, let’s just jump right in. This ETF seeks to own 100 of the highest beta stocks. First, for people who are unfamiliar with beta, perhaps we can have you explain what that is, and then take us through the ETF - how holdings are selected, how they're weighted, anything else noteworthy.

Tony Barchetto: Sure. Happy to. Yeah, let's take a step back and talk about beta. We talk about beta a lot in the ETF world. Smart beta, cheap beta and really it's kind of used as a shorthand for market exposure. It has its roots back in the '50s when modern portfolio theory really came to light as a means of measuring market risks. It's really the sensitivity of a stock or a portfolio to the market, measured as beta. The way that we like to think about it, I think the easiest way when you break down the math very simply is, what's the beta of the stock? I think a lot of folks understand if something has a beta of more than one, it moves more than the market and if less than one, it's going to tend to move less than the market. When you break it down into its pieces, there's two. Number one is how much is it moving with the market? That's basically correlation. If it's a correlation of one, it's moving exactly with the market. And then how volatile the stock or the portfolio is relative to the market. Those are the two pieces. When you put them together, you get beta. If you have a beta of 1.2, you can expect it to move about 20% more than the market, but that's not precise. That's the best forecast, because prices are unknowable. So I'm trying to estimate what the risk of this stock is relative to the market. We talk a lot now about smart beta. This is kind of the original beta, one we don't talk about much. But in any equity portfolio, it's the market risk that’s still about 2/3 of the risk. Beta is still a big portion and that's why we focused on it. What we found is that the way that beta is calculated, estimated, is really off of old data. The typical way to do it is to take five years of monthly returns and estimate how that stock or portfolio is going to move with the market. If you think about it, if you're going to forecast anything using data over that long of a period, what does a stock's movement four years ago have to do with how it's going to move over the next month or next quarter? What we did was we took a look at taking more recent data from the last couple of months and using that as the forecast of how this stock is going to move with the market. Using the kind of an analogy that I think makes a lot of sense, take the weather, for example. If I wanted to forecast the weather, the temperature for tomorrow, I'd rather use today's temperature, maybe yesterday's temperature. We have a heatwave now. New York, it's like 95 degrees today. My best guess is that tomorrow it's going to be pretty hot. If I took the temperature from six months ago, that might not be a great estimate of what tomorrow will bring. So it's kind of the same concept. We're using more recent data to produce what we believe is a more accurate and consistent forecast of how is that stock going to move with the market. That's what we call truBeta. Now we take that truBeta to build our index.

Nate Geraci: Tony, what's the universe of stocks that you start with to filter down?

Tony Barchetto: Sure. We start with the top 1000 by market cap, then we further filter it by the top 500 by 30-day average trading volume. We do that for two reasons. Number one, we're looking for larger stocks that are more liquid so when the portfolio does turn over, it's cheaper to track the index. For number two, we find that the more liquid stocks have a better, more predictable beta. So we limit it to those 500 most liquid stocks. We calculate our truBeta score, which is a combination of the recent data that I mentioned over the last couple of months, along with the more traditional data. Then, we get a composite score of truBeta. We filter out the stocks that I mentioned before. There's two pieces to neta. How is the stock moving with the market and how volatile is it? If it's not moving with the market, if it has a relatively low correlation, it doesn't really tell us that much about the data, so we filter those out. We take the top 100 that meet those criteria and that becomes the index, but we also limit the number of the sector concentration. We cap the 100 stocks, but only 30 of them can come from any one sector. We didn't want this to be a sector fund. This is really designed to be broad market exposure 100 stocks that have a higher sensitivity to the market. Then, we equal weight the basket and we rebalance quarterly. That's how the index is built.

Nate Geraci: Tony, do I have it right in the process of calculating the truBeta score that you are incorporating some machine learning? If so, what does that entail?

Tony Barchetto: Sure. We are and I definitely want to make it clear and differentiate. There's some hedge funds and other index providers using AI and machine learning tools to pick stocks. To be clear, we're not doing that here. We use a machine learning process to help us get the beta score, the forecast more accurate. So we use it as an optimization tool as opposed to really picking stocks. That's a key distinction. The actual filtering of the index is a little bit more traditional in terms of those criteria I mentioned. Using the machine learning process was very helpful for us in getting a more accurate forecast of what beta is going to be over the next quarter. That's where it really helped us.

Nate Geraci: Our guest is Tony Barchetto, Founder and Chief Investment Officer at Salt Financial. We're spotlighting the Salt truBeta High Exposure ETF, ticker symbol SLT. Tony, this ETF is positioned as sort of an alternative to leveraged ETFs. I've call it a leveraged light ETF. Certainly, we've covered some of the pitfalls of leveraged ETFs on the program before, but can you maybe explain a few of those pitfalls and why SLT might be a better option here?

Tony Barchetto: Sure. With a leveraged ETF, what it's doing is it's resetting a specific multiple to an underlying index, like the S&P 500 and saying, "We're going to give you three times the return of today's return on the S&P." What that does in terms of how it works is every day it's adjusting its exposure to meet exactly the two or three times multiple. That's not a problem when markets are going in one direction, either up and down, and you're taking a position to either bet against the market or with the market. Where it becomes an issue is if it's a choppier market and if the leveraged index is resetting every day. It's kind of buying high and selling low as a part of its process. The path to get from A to B can affect what your outcome is, so it's possible to actually be right on direction, saying, "I want two times the market," but because of volatility, when you get to the other side, because of this rebalancing process, you can actually be down money or be nowhere, even though you were right. So it's path-dependent. Really, those products are meant really for day trading and short-term trading. The providers of those products do a pretty good job of disclosing that and used properly, there's nothing wrong with that. Where it becomes an issue is they tend not to be suitable for investors to use over time. What we believe is that by having something that mimics some of the effects of leverage, we don't give you a specific multiple. You have to trade off with precision, but you can hold this basket that seeks to target more volatile stocks, but return more in exchange for that risk and mimicking the effects of leverage without that daily reset. I think you said it well. It really is a potential substitute for that, but it really is meant to be held a little longer than a day or an hour or more of day trading tool. This is a little bit more for a longer term investor to get more exposure to the underlying market.

Nate Geraci: You mentioned SLT not targeting a specific return multiple of let's say, the S&P 500, but just to give listeners an idea, let's say US stocks are broadly up or down, I don't know, 1%. What would be the goal with SLT? What should investors expect?

Tony Barchetto: Sure. The average truBeta score since we've been measuring is about 1 1/2 and that can range from about 1.3 to 1.6, depending on the stocks that met the criteria. It's about 1 1/2, but like I said, it's not a precise multiple and it won't be every day or even every month. It's really designed to work over time to have a kind of magnifying effect through higher stocks that are more volatile, but also moving with the market, which swings both ways, obviously. The general experience is about 1 1/2, but not precise.

Conor Kelly: Tony, this is Conor Kelly. All we hear about on the news is about the FAANG stocks, right? They're driving the markets. Are those some of the top holdings? Give us an idea and our listeners kind of the current top holdings in the fund right now.

Tony Barchetto: Sure. Generally, technology stocks are going to be more volatile than the S&P, so we do have a heavy technology weighting. Not that much more than the S&P because we do cap it, but for example, right now in the portfolio, Netflix is in there. Amazon is in there and that's just based on the criteria. So generally, the FAANG stocks will be in there, but it's not every quarter. We do rebalance every quarter, depending on what's going on right now. The top sectors right now are technology, financials and industrials and it'll tend to be more in the same five or six sectors. For obvious reasons, not in consumer staples or utilities, for example. A higher volatility, higher beta strategy is not going to be typically in those stocks. But that's where the weighting tends to shake out.

Nate Geraci: Alright, Tony, so let's talk portfolio applications. How do you think investors should view SLT in the context of a portfolio? How should this be used?

Tony Barchetto: Sure. I think there's two kind of broad use cases that have different permutations. Number one is kind of the obvious case, which we've talked about, is using it as a leverage substitute when you're more bullish and you want to get more exposure to the market. That could be tactically, if you have a model that does that or you're just looking to increase your exposure. I think that's the simple case. Where we think it gets really interesting is... look, the trend over the last several years has been low volatility investing, which can work, but we're saying you can use a higher volatility, higher beta asset in a diversified portfolio in smaller amounts. In a diversified portfolio with rebalancing, that can actually reduce risk. What I mean by that is you can use a smaller amount of SLT, which has its magnifying effect in your portfolio. That's really why we named the company Salt. You wouldn't eat a chunk of salt, but you'd use it as an enhancer. We think it can complement other strategies like low volatility, for example. It actually has a pretty low correlation to those stocks. So overall, it can lower the volatility of the portfolio, even though it's high volatility in and of itself. So we see the combinations as really being interesting in a way as a portfolio construction tool, which is how we talk about the ETF.

Nate Geraci: I like that with Salt, that these strategies can be sort of the seasoning to a portfolio. Very well done.

Tony Barchetto: Exactly.

Nate Geraci: Tony, moving forward, do you envision launching similar strategies in other markets, say an international high exposure ETF or are there some other ideas that you have in the hopper?

Tony Barchetto: Sure. Based on this truBeta concept of what we believe is a more accurate and consistent forecast of beta - now we're using beta versus the S&P 500 or the SPDR ETF in this instance, but you really could use any base in there - so it could be a foreign stock index. It could be a sector. We're developing a series of indices right now based on sectors. We're going to explore some other market caps and definitely foreign markets. So we believe this truBeta concept is definitely portable and we look to get out more indices hopefully this year and create more tools for investors to use.

Nate Geraci: Tony, while we're on this topic of new ETF launches, we visited earlier with's Dave Nadig on the proposed ETF rule that made, boy, a lot of headlines last week. I'm just curious, any thoughts or comments on this? Is this a good thing for you?

Tony Barchetto: On the margin, yes, and there's a couple of things in there that had been talked about for years that are going to be a lot more clear, provided there's a rule that passes. Exemptive relief, we are an issuer, we already have our exemptive relief, so that doesn't help us. But the cost of that has come down so much over the last several years. It seems like most of this rule was kind of built for problems from five years ago in terms of the costs of getting in. But a couple of the other aspects, for example, the custom baskets is a big piece of it. The big change there is for active transparent ETFs to be able to use that functionality basically to maintain the tax efficiency or make it more consistent across different types of ETFs. That could be something that we potentially could explore, although we are a passive index provider and our ETF is passive index. The third part is the additional website disclosure. That's good for investors to understand more about what's in the product. That'll be a little bit more work for us to do, but those are kind of the three areas. But having gone through the process of being a new issuer, the exemptive relief is the big one and that one we checked the box on that one, so a little less than others, but overall, we think it's pretty good for the industry.

Nate Geraci: You mentioned the term “smart beta” earlier in our discussion. Do you view SLT as a smart beta ETF or what do you think about that term?

Tony Barchetto: I think it's more like the original beta, the original dumb beta, which is the market risk. We're just taking a different look at how to measure that and estimate that. That said, I think it will work well within the smart beta universe. I talked about SLT being an enhancement in your portfolio. You wouldn't put your whole IRA in a more volatile strategy, but using it with things like low volatility or dividend strategies or with small caps, other factors, we think it can play well in the sandbox of smart beta. But I wouldn't really call it a smart beta strategy since it is really key to that market risk, which was the original risk identified when modern portfolio theory really first came about.

Nate Geraci: Well Tony, with that, we'll have to leave it there. Fantastic spotlight today. Congratulations on the launch of SLT and best of luck to you moving forward.

Tony Barchetto: Thanks so much, Nate. Thanks, Conor.

Nate Geraci: That was Tony Barchetto, Founder and Chief Investment Officer at Salt Financial and you can learn more about the Salt truBeta High Exposure ETF by visiting