Ben Carlson (2:42)

Management written all over him. And so we get into all that, and I think that's the. I think the pros and cons of a quantitative strategy is that you just have to kind of let go of the steering wheel and let God take control. Right. It's like, because you have to trust that this signal or this strategy or this move is not always going to work, but most of the time it's going to work. And that's a hard thing for a lot of people, right? Yes. Trusting the process and not always the outcome. So fun conversation. We get into all this stuff, how the strategies work, the pros and cons, the situations where it won't work, why other tactical strategies haven't worked as well. So here's our conversation with Dan Russo from Potomac Funds.

Michael Batnik (3:24)

Dan, what's up, man? It's good to see you.

Dan Russo (3:26)

Good to see you. Thanks for having me.

Michael Batnik (3:28)

All right. I'm excited for this conversation. Let me give you a proper intro. Dan, you are the co chief investment officer at Potomac Funds. You've been there for how long now?

Dan Russo (3:35)

Coming on five years. March will be five years.

Michael Batnik (3:38)

Okay. I'm pretty sure I could be wrong, but I'm pretty sure that you are one of the. This could be one of the first conversations we've had with a truly tactical manager. There might have been one more, but either way, it's been a minute. And the reason why is because doing tactical well. And when I say well, I'm just talking about performance. It's really hard. If you look at the Morningstar category of tactical, it really sucks. What is unique about you guys is that your numbers don't. Don't suck. And we're going to get into all of that today. Maybe let's just start there. Like, why is tactical? And I'm. There's a million answers. Why do you think tactical has been such a difficult category for investors?

Dan Russo (4:22)

I mean, I think you can start right from the beginning by saying it's hard to define tactical. I think people look at tactical a lot of different ways. You know, I mean, in theory, if somebody can move from, say, fully invested to, say, 75% to 50%, that's kind of tactical, Right? At Potomac, we can will and do move our portfolios 100% to cash. If our composite model tells us that that's the right move, and we'll obviously get into that a little further. I think that we are one of the few firms that do that actually take the portfolio 100% cash and kind of happy to let the market play out and then let probability dictate for us when it makes sense to get back in. So, you know, at its core, I think it's hard to define tactical. There's so many. There's a lot of different definitions and, you know, a lot of different ways to implement tactical. And I think one of the things that helps us is the fact that we have this willingness and ability to go to cash.

Michael Batnik (5:20)

Well, here's how, here's how I think about it or define it. A tactical model or a tactical strategy is effectively a market timing strategy. Now, within that, within that, there's a million different variations, definitions, and timing the market is really difficult. I'm not going to say it's impossible, but it is certainly difficult. It's impossible if you're, if you're winging it. It's impossible if you're using your intuition. I know that a lot of the work that you do is leaning on not intuition, not how you feel, but probabilities, quantitative inputs. So how does. And listen, I think that investors want their cake and want to have their cake and eat it, too. They want a tactical strategy that gets a lot of the upside and doesn't have to deal with a lot of the downside, which is obviously, I mean.

Dan Russo (6:09)

That'S what we're trying to deliver.

Michael Batnik (6:10)

Yeah, I know you're. That's what you're trying to deliver. So just that premise, like, is. What are you talking about? How is that possible? So what, what are you trying to deliver? I know you have four strategies and we'll get into them, but how are you trying to create this alchemy?

Dan Russo (6:25)

So we're doing it with quantitative technical analysis. We have a composite model that is made up of individual trading systems.

Michael Batnik (6:36)

Right.

Dan Russo (6:36)

We kind of view it as almost like we are the general manager of a sports team. Right. And we kind of date ourselves a little bit when we, when we talk to people and use, you know, the 90s Chicago Bulls. Right. And I'm not even a basketball fan. I don't know why we do this, but we do. And, but you've kind of looked at the 90s Chicago Bulls. First of all, Jordan was there for what, about seven years before they really did anything, right? So you have this kind of, you have his superstar, but you need the players around him, right? You need Scottie Pippen, you need Dennis Rodman, and that's the extent of my basketball knowledge.

Michael Batnik (7:08)

I'll throw in Ron Harper.

Dan Russo (7:09)

Fair. So that's kind of how we view it, right? So each of the different trading systems is a player and the composite model is the team. And as I said, all quantitative technical analysis. So we're doing technical analysis, but it's not lines on charts and randomly attaching fib retracements somewhere. All of the individual systems are tested on their own and then in combination with each other. And then we take the systems and we combine them to create a composite. And the composite basically answers the question, do you want to be invested? And if the answer to the question is yes, we have four individual 40 actors, mutual funds, which are used as the vehicle to buy and sell our investments. And each one of those funds is run to a specific risk profile as measured by drawdown. And then we take those four funds, combine them in different weights to create strategies which are available to financial advisors.

Ben Carlson (8:04)

So you say you have your composite. Does that mean that it's one rule you're looking at, or do you have multiple rules within each fund where you could be invested, like you're 60% risk on and 40% risk off, or is it, Is it all or nothing?

Dan Russo (8:16)

The composite model is all or nothing. Now, in fairness and in practice, we have more than one composite model, so a fund could be kind of 50% invested and 50% out of the market, depending on what the different composite models are doing. But what's important to understand, I think, is that we do not have one rule that gets us in, one rule that gets us out, and that's it. Right. It's kind of the theory that when all you have is a hammer, everything looks like a nail. For instance, I like to use trend following and I love trend following. I think it's you. I think it's an interesting strategy. But if you're a trend follower, what do you do in a market that's not trending right, that's moving sideways? Your strategy is going to get death by a thousand cuts, you're going to get chopped up, market's going to go nowhere, maybe plus or minus 3%, and all of a sudden you look up and you're down 15 or 20.

Michael Batnik (9:04)

Right.

Dan Russo (9:04)

Because your trend model got cut up.

Michael Batnik (9:06)

Likewise, 2022 was a really difficult year for trend following because there was a lot of bear market rallies. Where the market fell, you sold the market bounce, you bought back in. Oh, shit, it rolled over again.

Dan Russo (9:17)

Yeah. So 2022 is an interesting year, and it's one that we actually use a lot in examples in our composite for our composite model. Because, you know, our composite is designed, like I said, it's a lot of different inputs. The trading systems, the individual systems themselves tend to be uncorrelated with each other. So it's designed to be regime aware. So we have this concept of a base system and then trigger systems. And if we think of the base system. Think of the base system is Jordan. Right. The base system kind of dictates the market environment that you're in. If the base system is on a buy signal, you're probably in a pretty bullish environment. And if the base system is on a cell signal, you're probably in a bearish environment. Now, our base system was mostly on a sell signal in 2022, but we recognize that markets don't go down in a straight line. We recognize that you want to have different ways to get in and out of the market. So we have these counter trend trading systems that are designed to fire in a bearish type environment. So we actually were able to take advantage of a lot of those bear market rallies throughout 2022. So even though the environment was weak, the individual trading systems are designed to recognize opportunities across different regimes.

Michael Batnik (10:29)

So I'm curious how advisors are using you. So let's just look at. I'm calling this your flagship, but you could correct me if I'm wrong. The strategy or the mutual fund with the most assets is the Potomac Defensive Bull Fund. Correct.

Dan Russo (10:46)

Right.

Michael Batnik (10:47)

So this is just one of your strategies and we'll get into it. But what's remarkable about what you've been able to do in this, and I want to hear how you combine it with the, with the other strategies for advisors, is you've been able to not only keep pace with the market, and I'm talking about the S and P, because that's when people say the market. I know, unfair or fair, that's what people measure. That's fair. Over the last five years and three years, you've outperformed the S and P. And that's incredibly difficult, not just for tactical, for anybody in this type of market where the leadership has been narrow, it has all been in tech and communications. And you've been doing that in a way in which you're not, you're not fully invested. So there have been periods of time where you've been 100% out of the market. So the fact that you've been able to keep up is remarkable. Now within that particular strategy, there have been drawdowns, and that's fine. It's beaten the market. So how does, how does that strategy fit into the overall strategy? And how the hell have you been in the market?

Dan Russo (11:51)

All right, so I guess we'll start with how the strategy works and how it's implemented. So I said earlier, our composite model answers the question, do you want to be invested? Right. And then each fund has a specific profile for that fund. In particular, if the composite model fires a buy signal, we have concentrated exposure to a broad index such as the S&P 500. So that fund will run when it's invested. That fund will run at about a 1.6 beta to the S and P. Now obviously, when it's not invested, we'll move into money market or cash like products. So the beta drops to zero. So what that allows us to do is actually de risk the model because when we run the fund at about a 1.6 beta, we are able to spend more time in cash. Our composite model on average is in the market about 60% of the time, give or take the year. So by spending roughly 40% of our time in cash, we can wait until probability dictates via our model that it's a good time to be invested. And then once we get in, that concentrated exposure at about a 1.6 beta allows us to outperform if the trend persists, but it also allows us to give the trend time to develop. We're not trying to catch the bottom, we're not trying to catch sell the top. By getting in at about a 1.6 beta, we are able to let the trend develop, let our signals tell us that this is a healthy trend confirmed by Breathwork and confirmed by Intermarket analysis. Now we can get in with that concentrated exposure and catch up and hopefully get ahead of the broad index pretty quickly.

Ben Carlson (13:38)

So you're getting that 1.6 beta through leverage, obviously through different products.

Dan Russo (13:44)

Right. So it's a combination of futures and ETFs that allow us to get that beta in a cash efficient manner. Right. So by, by using futures, we don't have to tie up massive amounts of capital to get the exposure we want. And then adding in ETFs brings us to that, that 1:6 beta. So I call it leveraged exposure. We're not borrowing money. Right? It's not a, it's not a $2 billion fund where we go out and put three turns on it so that we could put, you know, $6 billion to work a la a lot of hedge funds, we're actually putting less money to work in the market, pure capital to obtain the exposure we want than we would if we were doing everything with individual equities or even all with ETFs.

Michael Batnik (14:33)

So this is obviously a quantitative strategy.

Dan Russo (14:35)

Yep.

Michael Batnik (14:36)

How much of it is rules based versus like your discretion to say, all right, in this environment, this input is not really working or it's out of favor or whatever, like how much, how much manager overlay is there?

Dan Russo (14:50)

So the discretion comes in the research process. Right. When we're designing the individual training trading systems, when we're thinking about how to combine them, that's where the discretion comes in. Once we've kind of done all of the testing and we're confident that what we have is going to add value, there is zero discretion. And again, I, you know, I hate 2022 is another great example because I'm kind of known as, I'm not a perma bear, but a hater. And so you're like 2022, I'm super happy. Right. The market's getting wrecked. The NASDAQ's down 40%. We can go through the psychological reasons of why I am the way I am. We've discussed it. But in that environment, as I said earlier, our base system was mostly bearish. But we're getting these counter trend signals. We're looking at things like the VIX to tell us, hey, we've gone down too far too fast and that fires a buy signal. So we come in, we run the models either at night or early in the morning. And our CEO, who's also co CIO Manish Khada and I, we'd be going back and forth with each other, you know, like, hey, we have a buy signal here. I hate buying here, but we don't ignore the signal. Right. And I think there were six or seven of those in 2022 and all but one was, was actually a winning trade. Now, those trades in that environment are going to be different than the trades that you see in a bullish environment.

Michael Batnik (16:10)

Right.

Dan Russo (16:10)

In a bullish environment that the triggers that get us in are likely to keep us in longer. Right. The market does have a natural upside bias, which leads me to believe that I should not be a hater, but I just am. So the signals that get you in, in a bearish environment are going to be kind of these quick hit trades. Maybe you're in for, for three or four days at a time and then you get out of the way again. But we do not override the signals. You know, if, if we have a signal, we don't override it. Because honestly, you know, we, we pitch ourselves as quantitative managers, systematic and rules based. The second we override a signal with our own discretion, we've stopped delivering what we promised our clients we would deliver.

Michael Batnik (16:48)

Dan, in 2014, Josh and I took a meeting and I highly doubt this manager is still around. They had like 32 different inputs, and Josh and I were like, all right, so it's rules based. He goes, yeah, but like, you know, if, we'll do what we have to do, if we, you know, like, if we have to. And I was like, wait, what?

Dan Russo (17:06)

Look, yeah, listen, I think, you know, at the end of the day, you know, we all have our experiences and we all, you know, if you've done this long enough, you have your view, right? And I certainly do. But that doesn't mean we're going to override the signals. Right? We're big believers in data over feelings. Right. Probability over prediction. These are all, you know, taglines that you'll see on our website. But we don't override it. You know, I mean, if you think about it, if we were able to do that, we wouldn't have made one of those trades in 2022 because, you know, Dan the hater hates the market. The market was clearly in a downtrend, right? You could make every argument to not take the signal, but, but you do, right? Because that's, that's the, the product we're delivering. And because we believe in the data and we believe that we, we've built a robust system so we don't ignore it.

Ben Carlson (17:51)

You mentioned that you, you have some like, drawdown limits on each of these funds. I'm curious what your risk parameters are and like, what you're comfortable with and what's the range of outcomes you're willing to accept? Do you have certain drawdown thresholds that, like, listen, below this level, like there's, there's something wrong or the portfolio gets out. Like, what are your risk profile? What's your risk guidelines?

Dan Russo (18:08)

Yeah, no, that's a great question. So, I mean, we test all the individual trading systems, like I said, on their own as well as in combination with each other. And the key metric that we look at for any of the different systems, as well as for the composite model in general, is maximum drawdown. Right. If an individual system or the composite model starts to approach its maximum drawdown, we'll take a look at it and try to understand what's going on. Did something really change in the Market has. Does the data that we're using no longer make sense for the current market environment? Does the data we're using no longer exist? So max drawdown is our key risk metric. Right. To just have a hard and fast number. Say if a system is down 10%, we're going to pull it. Or a system is down 15%, we're going to pull it. Doesn't make a lot of sense because volatilities change over time. It's similar to the concept of using stop orders. People use stop orders and they arbitrarily pick 5%. Well, why 5%? You just kind of pulled that number out of thin air. Right. Volatilities change over time. Sometimes 5% might be a lot, sometimes it might be a little. So maximum drawdown is the key metric that we focus on.

Michael Batnik (19:14)

The, the strategies and the strategies that you're running have a lot of moving parts. They require a lot of education, a lot of handholding, a lot of communicating. You guys have had a tremendous amount of success working with advisors to deliver these strategies to end clients. What, what's your, what's your AUM up to? And how have you been so successful in translating these strategies to advisors and their clients?

Dan Russo (19:39)

Yeah. So we are over 3 billion in AUM across the, across the funds and strategies. And just as a frame of reference, I joined here in March of 21. We were just under 500 million. So that growth has been fun. It's been, it's been a lot of fun to be on this ride. You're right, though. It is a handheld sale. Right? Right. I think anytime you willingly choose to look different from the benchmark, you are going to spend a lot of time explaining yourself. So we have in the past couple of years really been diligent and focused on building out our sales and education team, both out in the field and here internally. Like you all, we're big believers in content. Our, our new home office here in Bethesda, Maryland has a studio in it where we do a lot of, where we do a lot of content. We just, we believe in education, you know, however people want consumer. Whether it's written, whether it's video, whether it's, you know, audio such as this. But it's really just been kind of getting out there telling the story, making people see that the way that we're doing things makes sense and that it adds value to, you know, strategic portfolios that a lot of people are currently using. Like, we're not going in there and saying, hey, you should rip out your strategic Asset allocation portfolio and, and just. And add us. We kind of show people how we're a complement to what they're currently using by, you know, trying to maintain the upside of the S&P 500 while delivering an experience that has a lot lower drawdown.

Ben Carlson (21:11)

In one of your research pieces you sent us that you talked about the bear market and diversification. I'm just curious how you frame that for advisors and how you try to position your funds in those. In, within to complement those strategic allocations.

Michael Batnik (21:22)

Dan wants the AI bubble to pop so badly.

Ben Carlson (21:27)

Maybe he's not alone. He's not alone. I don't think.

Dan Russo (21:31)

I honestly. Well, before I answer Ben's question, I am actually, I go on record as saying I don't think there's an AI bubble as measured by the MAG 7, because if you look at the MAG 7 relative to the S&P 500 over the past 12 months, it's an inline performer. Right? So I would think of that. If. I mean massive runoff, the April lows, fair, but.

Ben Carlson (21:49)

So you're not a hater, Dan?

Dan Russo (21:50)

I'm not a hater. I'm not a fool. The data doesn't point to me being a hater right now. See, data over feelings. But Ben, to answer your question, as it relates to a bear market and diversification, you know, we just think that the traditional diversifiers that people go to to diversify their equity exposure, they all have their limitations, right? Number one. Number two is they all work at different times, right? And if we think about things like whether it's bonds, whether it's gold, whether it's commodities broadly, whether it's a balance allocation like a 60, 40 portfolio or managed futures, none of them is perfect. But what you have to give up in all of these to us, the juice is not worth the squeeze. Number one. Number two is, as I said, they all work at different times, right? 20, 22, we keep coming back to it is a great example. For the first time in what, 20 years, bonds failed to diversify your equity exposure. Now, based on our work, we think the key differentiator as it relates to when correlations are going to shift is, Is inflation. Now, if you think you can get the inflation call right, by all means, rotate amongst the different diversifiers. You're a better person than me and you're a better person than the Fed because the Fed can't even get the inflation call right. So that's number one. Number two is if you want some level of return, a 60, 40, 70, 30 portfolio, that kind of gives You a decent return. The drawdowns there are still pretty steep and a 6040 portfolio runs at about a 97 correlation to the S and P. So are you really diversified there? Probably not. And then so as you go down the correlation scale to things like the AG, roughly 23% correlation, but 10 year annualized return of about 1.3%. Okay, fine, you go a little bit further out on the risk spectrum in the bond space to something like 20 plus year treasuries via an ETF. Well, the TLT has a drawdown, a max drawdown of about 45%. So an equity like drawdown for your kind of your risk off diversifying asset. Right. Commodities broadly, almost no return over the past 10 years, about 3% with a 76% drawdown. Right. So there are these trade offs, right. The things that give you a little bit of return still have decent drawdowns and are highly correlated to the S and P. Right. Look at like say the ACWI, you know, 55% drawdown with a 98% correlation to the S and P. Right. So to us, the bear market and diversification is these massive trade offs. And what you have to give up to get true diversification, then you have to have the ability to time which product to use. So and then to top it all off, you know, you've had this kind of just set it and forget it bull run in the market for the most part, you know, diverse. A true diversifier has kind of been a drag to portfolios. So we add all that up, we think that there's this bear market and diversification and we think that that sets us up because of how we're investing. We're trying to give you that return profile while running lower correlation over time. If you look at our composite model, the amount of time it's invested, the amount of time it's in cash and you blend that out, we get to about a 0.5 beta, a 0.5 correlation. Equity like returns with drawdown mitigation.

Michael Batnik (25:16)

So when, when advisors are work with you, like all right, I get the story. I like that it's rules based. I see that it has a place in my portfolio for clients. We'll take some from stocks, we'll take some from bonds, we'll put it in, in this sleeve over here. How does it work in terms of like, all right, so you've got four different funds, they all have different risk parameters. Are you helping them come up with. All right, we think it should be 60% this fund, 20% this fund, 10 to 10. Like how does that process work?

Dan Russo (25:42)

So traditionally what we've done is We've taken the four funds that we have and we rolled out the four funds about five years ago. They all just hit their five year track record on June 30th of this year. Our longest running strategy has a track record going back to 2002. But in order to give everybody the same experience, five years ago Manish made the decision to roll out the 40 ACT funds so that all of the trading is done inside of the funds. And then what we do is we take those funds, we combine them in different weights to create strategies. And the strategies are available to advisors and you know, the strategies are delivered as an sma. They all have their individual characteristics and statistics around them. So you know, we'll try to be helpful where we can. If we have that kind of hands on consultative type relationship, we'll try to be helpful with, with what strategy we makes the most sense. But you know, we know advisors, they know their clients better than we know their end client. Right. So ultimately that decision does fall on them. But what we're delivering inside of the strategies is the four funds at different weights, again trying to fit a specific drawdown profile.

Michael Batnik (26:46)

All right, so these, so these advisors then have to take your strategy and communicate it to their clients. And they might not have the visibility obvious that you as the co CIO does. What sort of collateral or messaging are you giving them to give to their clients? Especially in times of market dislocation of performance under strategy underperformance. Like what do they get to share with their clients?

Dan Russo (27:09)

Yeah, so I mean, look, again we, we believe in transparency. It's one of the core values of, of our firm. So we do a lot of content. I write a weekly market commentary that goes out to our clients more recently taking advantage of the studio here in the office that we just opened in July. I take that commentary and we, we do a video version of it. So you know, however you want to consume the content. At a minimum, we do monthly updates where we kind of walk through the key inputs to our trading systems and the composite model to help advisors understand why we're positioned the way we're positioned. You know, what's kind of driving the market right now, whether it's things that are more of a trend following nature or signals that are more of a mean reversion nature and kind of walk them through broadly how the funds are positioned. Obviously at mutual funds we disclose our holdings quarterly. Right. So we obviously intra quarter, we can't, we can't really talk about that. But broadly speaking, on a monthly basis, we try to help our clients understand what we're seeing within the models and what that means for how we're positioned.

Ben Carlson (28:20)

All right, so your, your strategy, it's one of those that it sounds too good to be true. Like, hey, we're trying to get match the S and P or beat it. Lower volatility, lower drawdowns, what's the risk in bad case scenario? Like what's the worst case scenario for your strategy? When does it not work?

Dan Russo (28:35)

So I think worst case scenario can be defined in two ways. Number one, as I said, if we are invested, we run that largest Fund at about a 1, 6 beta to the S and P. And the strategy of in which that fund is the largest holding runs at about a 1.5beta to the S&P. So draconian scenario number one is we're invested and the market quickly tanks. Right. As I said earlier, we're not trying to catch tops, we're not trying to catch bottoms. Right. We're looking for levels of confirmation. So if you get a really fast drawdown in the market, a momentum type crash situation where you just down hard over a short period of time and we're invested well, the strategy is going to be in there at about a 15 beta. The biggest fund is going to be in there at about a 1, 6 beta. And we're probably not going to sidestep that right now. If that turns into something more prolonged, our inputs will start to catch up and the model will likely get out. Right. Again, even a year like this year, the market started to roll over in February. Right. And culminating in the April, you know, tariff tantrum. And then, and then rebound. Did were we getting out in February? No. Right. It was more like early second week of March where our composite model kind of got out of the way. Right. So we're not going to catch that. We're not likely to catch that turn at the top. And a hardened fast move to the downside while we're invested is going to have an impact. I think the other situation that's adverse to us is a slow grind higher for the S&P 500 or some other broad index that is not supported by market breadth. We are big believers in market breath. Right. We view the market through three lenses. What's the trend up, down, sideways? How healthy is the trend? We measure that through breath. Right. In a healthy bull market, you expect to see a lot of stocks going up, a lot of volume trading in those stocks and then the third leg of the stool is confirmation through intermarket themes. So if you get into a situation where the S and P is slowly grinding higher because of, you know, the mag seven or the top five or 10 names, while the other 493 names are starting to roll over, that breadth is going to show up negatively within our signals and could keep us out of the market. And then as the S and P drifts higher because Meta and Google and Nvidia are pulling it higher, we could miss upside there.

Michael Batnik (31:13)

Dan, last question for me. When we were talking about the portfolio, I don't think we got into this part of it. You're not favoring stocks, individual stocks, individual sectors, or are you? Is it at the index level or do you drill down to sectors and stocks?

Dan Russo (31:27)

It's predominantly at the index level. We will drill down to sectors, not individual stocks.

Michael Batnik (31:34)

Yeah, because you'd be shorting them all.

Dan Russo (31:36)

I would be short everything. No, I'm just kidding. We don't go down to the individual stock level, but as I said, we have the four funds. The main fund is purely at the index level. Two of the other funds that focus on equities, basically the composite model fires a buy signal. So do you want to be invested? Yes. Then those two funds. The next question is where do you want to be invested? So we will look at sector and industry ETFs. We've created a trend in momentum scoring system. So if the composite model says you want to be invested, the next question is where do you want to be invested? We use that trend in momentum scoring system, apply it to the sector and industry ETFs to determine which ones kind of have the trend and the momentum in their favor. And we will own those and then rotate them periodically while we're still on a buy signal.

Michael Batnik (32:27)

All right, Dan, you are, like I said at the top of the show, one of the few tactical fund families that has actually delivered results to their clients and not just over a six month period. Like the strategies have a five year track record. So kudos to you and the whole team. For advisors that are listening, that want to learn more about your services and strategies, where do we send them?

Dan Russo (32:47)

To our website, Potomac.com all the information, all of the information is there, including information on regional contacts on our sales team, both internally and externally. That's the best place. The Conquer Risk podcast and YouTube channel is a good place to see video content and listen to audio content as well. But I would start with the website.

Michael Batnik (33:08)

Potomac.com all right, Dan, great job. Thanks, man.

Dan Russo (33:11)

Thanks guys.

Ben Carlson (33:14)

Okay, thanks to Dan. Remember, check out Potomac.com to learn more about their four funds. Email us animalspiritscompoundnews.com.