An In Depth Look at Low Volatility Investing

[00:00:00] Welcome to Two Quants and a Financial Planner where we bridge the worlds of investing in financial planning to help investors achieve their long-term goals.

[00:00:05] Join Matt Zeigler, Jack Forehand and me, Justin Carbonneau as we cover a wide range of investing and planning topics that impact all of us and discuss how we can apply them in the real world to achieve the best outcomes in our financial lives.

[00:00:15] Justin Carbonneau and Jack Forehand are principals at Validia Capital Management.

[00:00:18] Matt Zeigler is managing director at Sunpoint Investments.

[00:00:21] The opinions expressed in this podcast do not necessarily reflect the opinions of Validia Capital or Sunpoint Investments.

[00:00:25] No information on this podcast should be construed as investment advice.

[00:00:28] Securities discussed in the podcast may be holdings of clients of Validia Capital or Sunpoint Investments.

[00:00:33] All right, gentlemen, how are you?

[00:00:35] Today we're going to kind of get into back to factor investing a little bit and talk about the low volatility factor.

[00:00:46] And I think today's discussion will kind of start from the ground up.

[00:00:52] We'll talk about what low volatility is.

[00:00:55] Some of the academic research behind the factor why it might work from a risk and behavioral based perspective.

[00:01:03] And then get into some of the strategies that are on Validia, what goes into them, talk about maybe the pluses and minuses of low volatility investing, how it can be used in building multi-asset investment strategies.

[00:01:16] And then Matt will sprinkle in, of course, how he thinks about low volatility and working with clients that he does planning for.

[00:01:25] And so let's just start with, if we were to try and define low volatility, how would we go about doing that?

[00:01:36] I think a lot of investors might think like when they think about low volatility, they might think like, well, that might mean utility stocks or maybe large consumers.

[00:01:46] Or stable stocks or stocks like that.

[00:01:48] But it's not really done on a industry or sector basis.

[00:01:52] It's more done based on some measures around a stock's variability.

[00:02:01] So maybe Jack, why don't you take sort of walking us through what the definition actually is?

[00:02:07] Well, this is like a perfect factor for me to do because as you guys know, I'm a pretty boring guy.

[00:02:12] And as the viewers have probably learned as well, so I like to implement the principles of low volatility throughout my life.

[00:02:17] I'm not just doing this on the on the on the podcast or in my factor investing career.

[00:02:22] You know, I'm trying to keep things down, keep things under control and I'm also trying to get a better risk adjusted return while doing it in my life as well.

[00:02:28] So this works out really well for me.

[00:02:31] But yeah, in terms of the definition, it's basically its easiest factor to define, I think, because there's not that many ways to measure it.

[00:02:37] And it is what it says it is low volatility.

[00:02:40] So, you know, I'm investing in things that are less volatile and, you know, there's typically two ways to measure it that are primarily used.

[00:02:47] You know, one is beta and one is standard deviation.

[00:02:49] And so standard deviation would be any asset, the volatility on its own.

[00:02:54] I don't consider anything else but the asset beta.

[00:02:56] I bring in covariance.

[00:02:58] So basically I'm bringing in like how does this asset play into a, you know, an overall portfolio rather than just how is it volatile on its own?

[00:03:06] So you can do it either way and it's been shown in research to work either way.

[00:03:09] But the general idea is I'm just buying stuff that's not volatile.

[00:03:13] And, you know, in theory, and we'll talk about this in a second, in theory, I should be getting a less return by doing that.

[00:03:18] But in reality, I'm not.

[00:03:19] So that's a basic introduction to it.

[00:03:23] I think in those terms too, it's like whenever we talk about beta, we're ultimately just talking about slope and just understanding how steep is the pitch versus how like flat is the pitch relative to whatever else.

[00:03:34] We're talking about variance.

[00:03:35] We're talking about volatility or standard deviation, how much stuff zooms up and down.

[00:03:40] I think about this a lot in terms of like min vol is basically the dentist office music of investment strategies.

[00:03:50] It's basically the stuff in design that should be the least offensive, the least jolt you out of the chair.

[00:03:57] The most stinging singing fields of gold while they're drilling your molar that you'll just be like, I can deal with this.

[00:04:04] I can accept this.

[00:04:05] And that's a wonderful thing.

[00:04:07] You could still have a chart topping smash hit.

[00:04:10] You can still have hero by Mariah Carey.

[00:04:13] And yes, I do have a waiting room dentist office Spotify playlist that I found on the screen in front of me, which may ruin this entire podcast.

[00:04:21] But the idea is you could still have a hit song.

[00:04:25] You could still have something you'd still put a whole playlist together of stuff.

[00:04:28] That's basically on the offensive is there gets the job done and plows forward without rocking the boat too much.

[00:04:36] And that we were joking the other day, this is like the smooth jazz of investing to some degree.

[00:04:40] Like I was hoping you would do the smooth jazz DJ life for the whole episode and just keep things nice and calm.

[00:04:45] But I mean, that's basically what this is.

[00:04:47] But I would just be like ragging on Kenny G or whatever the whole time.

[00:04:51] And I realized like that's not right when we have like there are smash hits.

[00:04:55] Like they're just so many smash hits here and now Luther Vandross.

[00:04:59] I have nothing Whitney Houston.

[00:05:01] There are great dentist office songs.

[00:05:03] I'll admit this and I won't just rag on smooth jazz and I won't also take you down the other path that I woke up this morning thinking of, which was explaining the cool jazz moment of the post world war two era and telling you about Lenny Tristano or something.

[00:05:18] So this is what you get.

[00:05:20] We're talking Celine Dion and Linda Ronstadt probably for the rest of this episode.

[00:05:25] And just to put some numbers behind beta and standard deviation.

[00:05:29] So a beta, the market has a beta of one.

[00:05:31] So something has a beta of above one.

[00:05:34] It tends to be looked at as riskier than the market below one less risky in general.

[00:05:41] And then on the standard deviation side, I think the S&P has like an annualized standard deviation of I think it's something like 16% give or take somewhere in the future.

[00:05:49] And there, you know, and so that's the type of variability you'll have around any years.

[00:06:01] Any year return within one standard deviation, it can be plus or minus 16% the average return.

[00:06:07] You know, when you start looking at specific stocks, especially from a standard deviation standpoint, they can vary significantly.

[00:06:17] I think there's something out there that shows that, you know, your average stock may have like a 30 or 40% move in any given year up or down based on what's happening.

[00:06:28] So just to kind of put some numbers behind those definitions for reference points.

[00:06:34] But let me ask you guys, why do you think, why shouldn't investors really care about this?

[00:06:41] Well, this is basically the holy grail of investing.

[00:06:44] I mean, like, what am I trying to do when I invest?

[00:06:46] I'm trying to get the best return I can and I'm trying to do it with the least risk possible.

[00:06:51] So this basically plays into what is most important in investing.

[00:06:54] And if I can buy something that is less risky and I can get a better return or I can get the same return, then I have just created a much better portfolio than what I already had.

[00:07:04] And so that's why this is so important, I think, and why it's so appealing to investors, this idea.

[00:07:09] And also when behavior comes into this, that's really important too.

[00:07:13] Like we know high volatility creates bad behavior.

[00:07:16] Lower volatility leads to better behavior.

[00:07:18] So when you put those two things together, this is a really important thing, I think, when you think about it in the way investors actually act in the real world.

[00:07:25] The risk and return balance, especially when you're designing financial plans, when you're picking investments, however you fit this together.

[00:07:32] It's a lot like the speed limit too.

[00:07:36] It's like we know, like you drive too fast.

[00:07:39] You go Sammy Hagar, you hear I can't drive 55 in that dentist chair.

[00:07:43] Everybody's in for trouble.

[00:07:45] But this idea of can I still get to the destination?

[00:07:48] Can I still, can I take the back roads and avoid the traffic jam on the highway or can I take the highway and avoid the headaches on the side streets?

[00:07:55] Like these metaphors are all useful because what they're trying to do is say, how do I get to the return to the destination, whatever, with the least amount of units of risk?

[00:08:04] And to talk about this quantitatively is to talk about how do we define those units of risk?

[00:08:09] Are we pairing speed limit against Sammy Hagar and can't drive 55 and whatever very slow speed we assume Michael Bolton drives?

[00:08:19] So, you know, this idea isn't like original to us, obviously.

[00:08:23] This is a factor that's they didn't just invent this right now.

[00:08:25] No, yeah.

[00:08:26] Well, this is like on the fly.

[00:08:27] I saw Matt's white paper before this and I thought like this is this was us.

[00:08:31] Matt tweeted his I tweeted my way.

[00:08:34] I tweeted my way.

[00:08:35] My white paper.

[00:08:39] But let's, let's, you know, we've talked in the past about what makes a factor a factor and there are really five different criteria.

[00:08:49] And we've had Larry Svedro and Andrew Birkin on the podcast to talk about this.

[00:08:55] But let's just quickly walk through what those characteristics are in terms of making a factor, something that, you know, investors should believe in.

[00:09:04] Yeah.

[00:09:05] And I would highly recommend that book a complete guide to factor investing is really, really good.

[00:09:08] And it's written in a pretty accessible way.

[00:09:10] Like some of the factor investing stuff can get a little bit too deep, but it's pretty accessible.

[00:09:13] So I think that's a great book to read.

[00:09:15] But yeah, to your question, the criteria they outlined in that book are persistent, pervasive, robust, intuitive and investable.

[00:09:23] And so let's go through each one individually as we think about this.

[00:09:26] And in this discussion, we're going to reference a lot of the work of Pinvon Vliet.

[00:09:29] Like his paper he wrote with David Blitz, the volatility effect lower risk of that lower return and he has got a lot of other papers that we'll talk about as well.

[00:09:37] But so we're going to use some of that as well as it relates to low volatility.

[00:09:40] But so what we want in a factor is we want it to be persistent, which means we want to work over time.

[00:09:44] We don't want it just to work in five years or 10 years or, you know, we want to see very long track record that it's worth.

[00:09:50] We want it to be pervasive in that we want it to work across different asset classes.

[00:09:54] And interestingly enough, and we won't get into this in detail, but this is the low volatility effect works in bonds as well.

[00:09:59] So you do see this working not just in stocks, but you see this working across asset classes.

[00:10:05] Robust meaning it holds up to different definitions and we just talked about that.

[00:10:08] We talked about beta and we talked about standard deviation.

[00:10:10] So if you define this one way and it works and you define it in a very similar way and it stops working, then I have to question, you know, whether this works.

[00:10:18] Intuitive, which is we've kind of had some podcast episodes calling this a new question a little bit.

[00:10:22] But the idea is these things should make sense.

[00:10:24] There should be some reason why it works and this is probably and we'll get into that later.

[00:10:28] This is probably the hardest factor to explain from an intuitive standpoint because just think at a high level like taking less risk.

[00:10:34] Why should I get a better or the same return?

[00:10:36] Like that doesn't make any sense.

[00:10:37] And we can explain later why it does make a little bit more sense than you think.

[00:10:40] But so a factor should be intuitive.

[00:10:42] And I think this does meet that definition.

[00:10:44] It's just a little bit more indirect than some of the other ones and investible.

[00:10:47] I should be able to buy it.

[00:10:48] It should be something I can invest in.

[00:10:49] It should be something that I am not like impacting dramatically while I invest in it.

[00:10:53] So if this only exists in like one million dollar market cap companies, then what I can't really do a lot about that as an investment manager because I'm in buying them.

[00:11:00] I'm going to basically get rid of any of the positive things that are going on.

[00:11:03] But so this meets all of those definition.

[00:11:05] If you look at Swedger and Burkows, Birkin's criteria, low the low volatility factor meets all.

[00:11:10] Yeah.

[00:11:11] So that's that's good.

[00:11:12] Those are important things when you're thinking about what makes a factor a factor.

[00:11:16] Those those characteristics and qualities talk about a little bit.

[00:11:20] I know in doing some work for this, you know, you were able to pull some of the risk and return data of low volatility stocks versus the market.

[00:11:30] So just talk to those numbers a little bit to put it in some sort of some context here.

[00:11:36] Yeah, it's interesting.

[00:11:37] So you look at basically what they do in these papers.

[00:11:39] A lot of times they break things into deciles.

[00:11:41] So 10% like take 10% of stocks ranked using the factor and look at like typically they'll look at the same thing.

[00:11:45] Typically they'll look at the top desk on the lowest desk.

[00:11:47] And so the top desk out, which they call D1 of the least volatile stocks is only about two thirds of the volatility of the market.

[00:11:55] And it has a point seven to sharp ratio versus a point four sharp ratio for the market.

[00:12:00] So what is that telling us?

[00:12:01] That's basically telling us I'm getting a much better risk adjusted return by investing in that top desk out of low volatility stocks than I am by investing in the market or investing in the other deciles.

[00:12:11] And so that's kind of the holy grail of investing in some ways because if I'm getting a better return, I'm getting a better risk.

[00:12:17] I'm getting at least the same return if not better, I'm getting a better risk adjusted return.

[00:12:22] Like it would be no brainer for me to invest in those types of stocks versus something like the market portfolio.

[00:12:27] And also by the way, just to look at the other side of it, like the other part of this, the worst decile has just terrible metrics on everything you could judge.

[00:12:35] It has worse performance than the market.

[00:12:37] It has much higher volatility than the market.

[00:12:39] Unless you're like in the ultimate contrarian who thinks like everything of investing is going to flip in the future.

[00:12:44] And basically my goal is going to be get the highest volatility with the lowest return.

[00:12:47] You probably want to be avoiding that part of it.

[00:12:49] Can you, I think this is really important.

[00:12:52] And I think this is something that I struggled to understand way early on in my career and getting drawn to this stuff.

[00:12:58] The top decil versus the bottom and then the value of like the long short portfolio composition to prove this out.

[00:13:06] Just comment on why we do that.

[00:13:08] Yeah, so and that's kind of separates this from the real world to some degree because your standard factory ETFs are not doing it this way.

[00:13:14] But when you want to test a factor, you want to find out, do the best stocks outperform in the way I want them to and also do the worst stocks underperform?

[00:13:22] Because if only the best stocks outperform and then as you move down the deciles, you don't really see any evidence one way or the other of anything.

[00:13:27] It's not as strong of a factor.

[00:13:29] You know, you want things that are bad with the factor to do poorly.

[00:13:32] And so that's what they did with low volatility.

[00:13:34] And it works.

[00:13:35] And what's interesting is in some factors, you'll see like one of those dominate.

[00:13:39] So basically what I do is I'm long the top decil and I'm short the bottom decil.

[00:13:44] In some factors, you'll see that like the long or the short side dominate.

[00:13:47] So you'll see like most of my returns are from the long side.

[00:13:50] And where this is important for your average investor is you don't want to see the ones where most of the return is from the short side because in the real world, I'm investing in the long side.

[00:13:57] But in this case, they're both they're both good.

[00:13:59] You know, you're getting a better risk adjusted return from that top decil and you're getting basically terrible performance with high volatility out of that bottom decil.

[00:14:07] And so the academic research backs up this factor when you think about it in a long short framework.

[00:14:12] Probably one of the most to me one of the most interesting parts about this and this is beyond low vol but this understanding of what you just laid out.

[00:14:20] It's not just the persistent pervasive robust intuitive investable piece in that top decil.

[00:14:28] It's can we basically see the opposite also playing out and then map it against these two things.

[00:14:33] So we take the whole S&P 500, we chop it up into the deciles and we look at top versus bottom and we look for that long short proving and say, can I prove it also on the long side?

[00:14:45] And then that's kind of like a long walk to get to building a mutual fund or an ETF out of this thing.

[00:14:50] I've always thought.

[00:14:52] Yeah, no, it is.

[00:14:53] And, you know, it's academics look at this stuff very differently than we kind of do in the real world.

[00:14:59] Like academics want this stuff to stand up, you know that they're looking at T statistics and all this stuff that they want to really prove that this is solid, you know, and they do that in a lot of different ways to try to prove that it's solid.

[00:15:10] And then those of us in the real world take that and say, alright, here's how I manage a portfolio in the real world.

[00:15:15] Well, I'm not going to, you know, my average ETF is not going to be out here shorting stocks.

[00:15:20] And most people want, you know, when you're running a long only portfolio, you're also getting exposure to the market going up over time.

[00:15:25] You're getting exposure to the beta of the market.

[00:15:27] You know, most people want that exposure.

[00:15:29] So a lot of people would prefer not to have, you know, the long short low volatility ETF versus the long only.

[00:15:35] So in the real world, we have to think about what are we trying to accomplish?

[00:15:38] We're trying to benefit when the market goes up over time, but we're also trying to find factors that give us a bit better risk adjusted returns.

[00:15:44] So we take that academic research and we spin it around and we say, alright, we only want, you know, we're only going to use the long side of this.

[00:15:50] But we also have to keep in mind, like I said before, that if it mostly works on the short side, then I may not be getting the benefit, I think, of using the factor.

[00:15:58] Yeah, it's so interesting because when we approach it academically and I'm thinking of, I know this is in the Daniel Kahneman episode we just recorded too,

[00:16:07] but that whole the exposure to noise and correlation and the reality of like causal bias when we're looking at this stuff too.

[00:16:15] And understanding when you're building products or you're building investment strategies around this stuff, the academic theory gets you up to a point and you have to understand that,

[00:16:25] but then you can step away from it.

[00:16:27] It's in the truest sense of the word.

[00:16:29] This is like how like boys to men isn't just slow jams.

[00:16:32] You got Motown Philly and I'll make love to you side by side with each other.

[00:16:36] It's really interesting.

[00:16:38] Like there's no long short portfolio that proves out by those things can exist in the real world.

[00:16:43] Those anomalies can exist in academic factor land.

[00:16:47] This is the way we think through it and try to then go and test these strategies in the real world.

[00:16:52] Yeah, and it's also important to think in the real world both from the respective of like how is things different than the academic research?

[00:16:57] Like academics do try to account for transaction costs and stuff, but it's hard to do.

[00:17:01] I mean that could be a little bit different in the real world and also going forward we have to understand.

[00:17:05] And this is something that's come up a lot with Fama French's work.

[00:17:08] Like once this stuff is out in the public and it's available in the real world and a lot of people start to follow it,

[00:17:13] it might not do as well.

[00:17:14] And so you can't keep referencing the academic research from 20 years ago.

[00:17:18] If it shows that in the real world everybody's followed this academic research and it's not working anymore.

[00:17:23] So there's this transition from the academic research.

[00:17:26] We always have to take it, you know, we know the academic research is typically done well,

[00:17:30] but that doesn't mean that it's going to work for the next 50 years no matter what.

[00:17:34] I mean, we have to look at it in the real world and see what evidence we're seeing post the academic research

[00:17:38] and also what was in it and say like does this make sense in light of what I know today?

[00:17:43] Yeah.

[00:17:44] And what's changed right?

[00:17:45] Like that's that's the reality of it is different things change.

[00:17:49] Different things come in and out of flavor in markets in realities and whatever else.

[00:17:53] So these things we hope they're enduring and pervasive in all the ways we're describing

[00:17:58] what the reality is stuff like it's not just look at any stock market index over time

[00:18:04] and consider the ways these companies have inevitably changed.

[00:18:07] And just reading your white paper this morning, I've already adjusted my investment strategy.

[00:18:10] So I mean, this is how quickly the academic research can come out and change things.

[00:18:14] Exactly.

[00:18:16] Exactly.

[00:18:17] And how durable it's translated to crypto markets as well.

[00:18:21] So one of the things with all of these factors is we like to try to think about them through both

[00:18:27] the risk based explanation as to why they work and then the behavioral based explanation.

[00:18:33] And I think some factors at least to me are a little bit easier when you're trying to look at them through that framework.

[00:18:41] They're easier to explain in terms of how they would fit into either of those buckets.

[00:18:48] But with Lowval obviously the risk based you can't really make well, I mean maybe there is

[00:18:56] but we'll talk about it.

[00:18:57] But the behavioral tend to be a little bit more clear to me and there's really three different sort of behavioral reasons

[00:19:07] or arguments as to why Lowval utility works.

[00:19:09] I don't know if either of you guys want to comment on the risk based thing

[00:19:11] and then we can kind of work into the behavioral points.

[00:19:13] Yeah, if you define risk in a standard way this doesn't make sense

[00:19:16] because obviously the way we're defining risk is actually what this factor is all about.

[00:19:20] So we're defining this, we're defining risk as beta or standard deviation

[00:19:24] and we're investing in low standard deviation stocks.

[00:19:27] So how are we going to make a risk based argument that this should work?

[00:19:30] It doesn't exist but there are behavioral arguments and the idea a lot of it is like investors seeking out better returns by doing a bunch of things.

[00:19:37] Wait, hold on.

[00:19:39] I do have to say the risk based argument for this thing is back to that the analogy on like speed like and driving speed.

[00:19:47] So extra Sammy Hagar like if I get in my.

[00:19:52] Justin you tell me what car do you think Sammy Hagar was driving in the I can't drive 55 video.

[00:19:57] Any Mustang or something must have been like a Mustang or like a Lambo.

[00:20:02] You would know this Matt you don't know this is like a type of thing you always know.

[00:20:05] I left this out of my white paper but it's the idea of theoretically a risk based model of like low variants basically says like can Sammy Hagar jump in his Mustang and drive as fast as possible on whatever substances he may or may not be on to the location and get there

[00:20:21] and the reality is like yeah, yeah if you go super super fast you can get there faster.

[00:20:27] The problem is that opens you up to getting pulled over getting through a difficult scenario of lamenting to the police officer or you just can't drive 55 all these things which means like the grandma cruising along at like 40 miles an hour or whatever is still might beat him to the destination.

[00:20:45] The risk based explanation includes a tortoise and hare reality of trying to get from a to b and it's useful at least to me to help remember that sometimes the fastest way is not the best way sometimes the slow and steady way actually beats the fastest way because the fast gets mucked up.

[00:21:03] Don't know how this relates this my wife actually got pulled over for going 40 once on the highway.

[00:21:08] Not the strongest driver and like she was just she just cruising along at 40 in the right lane and like the cop pulled her over like what are you doing while you're going this slowly.

[00:21:15] Yeah, the min vol speed limit there reverse Sammy Hagar is adopting like a min vol strategy in terms of driving on the highway.

[00:21:23] It was a 1984 Ferrari GTO by the way.

[00:21:26] It was a GTO look at that.

[00:21:29] So anyway back to what I was so the behavioral side of this.

[00:21:32] So it comes back to the idea that people are typically trying to generate better returns in a variety of ways and you know so for instance investors can't use leverage.

[00:21:43] If you assume there's limitations on losing leverage then one way I might want to get better returns is by investing in high volatility stocks that overprices the high volatility stocks.

[00:21:52] I know Matt you're a big person seeking out the lottery stocks you know the call options and all that kind of stuff.

[00:21:57] A lot of people like you doing that kind of stuff driving up the lottery stocks you know unfairly so you got you've got an opportunity when those stocks are driven up unfairly you've got a nice you know opportunity in the lower volatility stocks investor over confidence same type of thing.

[00:22:10] So yeah a lot of those behavioral explanations work a lot better than the risk based explanation but there is some interesting and we'll get into a second there is some interesting research from Cliff Asnes and a bunch of people whose names I can't pronounce that I would embarrass myself.

[00:22:21] I attempted to that like is it sort of looks tried to break this thing down and look at why it works which is I think is interesting.

[00:22:30] I'd really fascinating to think about why this can work and why it can exist outside of those crazy examples I'm really curious what are the what are the behavioral pieces from the asness piece.

[00:22:41] So this is paper paper.

[00:22:43] Yeah 2017 which actually in terms of the academic research is a fairly new paper but is yeah not it's not that recent because there aren't too many people writing about this like on a yearly basis with like groundbreaking papers.

[00:22:56] But anyway yeah the papers called betting against correlation testing theories of low risk effect and I'll just read if the low risk effect is driven by leverage constraints risk should be measured using systemic risk beta on the other hand if the low risk effect is driven by behavioral effects then risk should be measured using idiosyncratic risk volatility.

[00:23:13] Stocks with low idiosyncratic risk outperform stocks with higher idiosyncratic risk that's what they're explaining the thing.

[00:23:19] So what they're trying to do is they basically made two and I'll read another thing in a second they basically broke the factor in two and looked at it individually and said like does it hold up in both cases.

[00:23:29] And I'll read just one more part from it the challenge with the existing literature is that it seeks to run a horse race between factors that are by construction highly correlated since risky stocks are usually risky in many ways.

[00:23:38] Hence the most powerful way to credibly distinguish these theories is to construct a new factor that captures one theory while the same while at the same being relatively unrelated to factors capturing the alternative theory to accomplish this we just just decompose BAB which is just a low volatility factor into two factors

[00:23:53] betting against correlation BAC and betting against volatility BAB.

[00:23:57] BAC goes long stocks that have low correlation to the market is short and shorts those with high correlation while seeking to match the volatility of the stocks that are bought and sold so basically what they're doing is trying to isolate them while holding the other thing constant.

[00:24:08] And what they find to summarize it briefly is they both work.

[00:24:13] So there is an explanation kind of on both sides of things, but both factors hold up when tested individually and I think look pretty similar to each other.

[00:24:21] So that would kind of say like there are multiple explanations going on here that can be used to explain why this works.

[00:24:28] And it's interesting because this evolves over time in that sense too.

[00:24:32] So like different companies with different levels of perceived idiosyncratic risk at different points of time are going to pull and push further and further away and closer to the underlying benchmark like is that another piece to take out of this.

[00:24:46] I think the way it the way the leverage is important on a company specific level.

[00:24:51] So that makes a lot of sense.

[00:24:53] So and so over time, you know, a company different types of companies in their life cycles rely more or less on outside financing.

[00:25:05] And so that's an important I think thing here just to recognize.

[00:25:10] I mean, I was kind of thinking as we were talking about this and maybe I'm going off a little bit.

[00:25:15] But if you think about at the end of 2001, and I think this is a good example to try to think about what was going on in the market.

[00:25:22] So you had, you know, all these unprofitable growth stocks that, you know, pretty much were relying on outside.

[00:25:32] Well, they weren't profitable.

[00:25:34] They weren't generating cash flow and you had, you know, all that sort of speculation and risk in the market.

[00:25:39] And then that all kind of came apart in 2002.

[00:25:44] And that's sort of a good example, I think of like the behavioral side of why low volatility might work in some instances because, you know, to Jack your point earlier with investors kind of looking for these lottery stocks and, you know,

[00:25:59] sort of investing in those these types of like higher risk companies which those companies were higher risk in both cases.

[00:26:05] And they were higher risk because the fundamental quality of a lot of those businesses just wasn't good.

[00:26:12] And also they were higher volatility because, you know, investors were in a lot of cases chasing those types of stocks and, you know, they were more probably volatile just overall from a beta perspective.

[00:26:25] And then that all obviously came crashing down in 2022.

[00:26:29] And I think, I don't have the numbers in front of me, but I think like low volatility stocks that weren't really participating that didn't require as much like outside potential financing.

[00:26:38] You know, those are the types of stocks that held up better in what was, you know, that bear market.

[00:26:44] So just trying to put like some context with something that we've been through recently as investors and trying to think about it from this risk standpoint.

[00:26:52] And even in like the last few years before it all kind of fell apart, like if you think of the Carvanas of the world, like when you're seeing like the massive hundreds of hundreds of percent return and that, you know, people do tend to chase that type of thing.

[00:27:02] You know, you tend to want to put your money in that and be like, oh, everybody else is getting these hundreds percent return. I want to get that too.

[00:27:07] Like you put your money in it. And so systematically, you know, those those stocks end up getting overpriced relative to where they should be.

[00:27:13] And you know, that might be the person who's just sitting there with their low vol portfolio is not participating in that.

[00:27:18] But over time, you know, they're going to probably win the race against those types of things.

[00:27:22] And again, going back to the academic long short framework, shorting those companies that have the highest volatility, you know, tends to be a good bet.

[00:27:30] Although you can get, you know, trying to do that in the real world, which is something we didn't talk about Matt and we talked about the long short thing is like it's great to look at these factors and be like, oh, the long short portfolio does really well over time.

[00:27:40] Like you're going to destroy yourself at different points with that.

[00:27:43] Like think about being long low volatility stocks and in short, the Carvana type stuff like in 19 or 2020 year 21, like, you know, maybe not 21 because I think it turned then.

[00:27:54] But like some of those periods, you would just be if you don't manage your risk properly and you don't size it properly and everything, you're going to be completely ripped to shreds.

[00:28:01] Because when you do long short, it can go against you on both sides.

[00:28:03] So not something you're averaging best rest of worry about because they're not investing that way.

[00:28:07] But it is like, it's easy to look at these long short returns in an academic paper and look at them over, you know, 50 years or something to be like, oh yeah, that sounds great.

[00:28:14] You know, you get out performance that way.

[00:28:16] But when you look at it in the real world, like you probably would have blown up a couple of times along the way too.

[00:28:20] Now I want to make sure I had my timing right just for clarification standpoint.

[00:28:23] So was the big run up in growth end of was that 2020 or was that 2020?

[00:28:27] Yeah, I mean, I think it ended 2020.

[00:28:29] Okay, I think like the arcs of the world peaked in early 21 is what I was.

[00:28:33] Okay. So I was off a year. But anyways, the point still. Yeah.

[00:28:37] But within that, I think that's part of what makes like the like Cliff as this paper so interesting here because we can take the academic realities of the long short portfolio and why that is hard to do in reality.

[00:28:51] But we can still look at some of the stuff and that I didn't get that gets to the heart of the theory behind betting against is betting against correlation and betting against volatility.

[00:29:02] So on the long side of these things, like being long stocks that have low correlation to the market and also being long stocks that have low volatility relative to the market and looking at this subset of stuff that just says like simmer down for me.

[00:29:19] You know, all you low ball, you're coming back to me now.

[00:29:25] It's also interesting just going back to that long short thing is like you have to like in the real world, you can't you end up having to like beta neutralize these things because think about it.

[00:29:33] Like if I'm if I'm basically short high volatility, high beta stocks and I'm long low volatility stocks, what am I also I'm effectively short the market as well.

[00:29:42] And so like you have to be very that can blow up on you and like very, very bad ways at different times.

[00:29:47] So like people will actually neutralize a lot of this stuff to neutralize some of the other stuff out of there and try to get your core exposure to what actually trying to be long and what you're trying to actually be short.

[00:29:57] I think we're going to look at some ETFs here in a minute that incorporate low volatility, but one of the I think interesting things here is that, you know, oftentimes this is coupled with other factors.

[00:30:09] So, you know, you might and to some extent, you know, like I talked about at the beginning, like low volatility stocks tend to they aren't always from a specific sector or area of the market.

[00:30:23] But you do tend to find them, you know, the types of stocks you would think you would find in a low volatility portfolio are kind of what you get.

[00:30:32] But a lot of times it's coupled with other strategies or other other fundamental criteria like value or quality and things like that.

[00:30:40] It's just not buying like low low volatility stocks only there's often other factors that are basically being incorporated in there and like our model that we run one of the interesting things that I think with our Penn Van Ville model which we base on his book.

[00:30:57] What's the conservative?

[00:30:59] Yeah, conservative. Yeah, so he I believe this is true.

[00:31:04] Jack you might not have it right up in front of you but I don't think he's using anything off of the financial statements.

[00:31:11] I don't believe I believe his whole deal is that this is like everything that he's using is actually just either price based or I know shareholder yield is in there.

[00:31:23] But I think you can kind of get at that. He made the point before that it's you know you don't have to dig into these financial statements to run this strategy.

[00:31:31] It's a pretty simple straightforward strategy but I think for that one, you know there is no quality.

[00:31:39] Well I guess, no is it net buyback yield or is it shareholder yield?

[00:31:44] Yeah so it's the criteria market cap standard deviation 12 minus 1 momentum net payout yield and then a rank.

[00:31:52] Yeah so I mean it's using the balance sheet in that it's using net payout yield but you know yeah it basically gets at this idea.

[00:31:58] You know first I want to go back to that other thing you talked about because it's so important is the fact that this is not always the same sectors.

[00:32:04] I mean in the short term it can tend to be the same sectors like if you look at it right now your consumer staples and those types of things are in there but if you look at it over time it could be different than that.

[00:32:13] So I remember we had a guest on and I forget it was PIM or someone else but who talked about like back in the day I think it was like energy was in like the low volatility basket a lot.

[00:32:21] Now you would never find you know you're not going to find energy in the low volatility basket and what's also interesting is as the Facebooks and the Microsoft mature you're probably not there yet but those as they become proven companies you're probably going to start to see them in the low volatility basket

[00:32:36] and they are basically tech companies or you know I don't know what their class is now some of them are different sectors but they generally are tech companies so companies you never would have thought would have been in there years ago.

[00:32:44] So it does it's pretty consistent I think in the short term in terms of the sector allocations but it can change a lot as the world changes and the economy changes over time.

[00:32:53] Which goes right back to why those five factors are so important as we break these things down because the tech companies mature to your point into stuff that might not be the sexy fast driving far market beating things they turn into more boring businesses over time like you know we're still a ways off probably from Amazon being

[00:33:13] our grocery store in mall but at the same time it's like we're converging on something that's adding all these new things and features to it to something that's much more recognizable as a conglomerate of of things of yesterday and that's really interesting.

[00:33:28] Also totally amazed by I know we'll talk about inside of some of the ETFs and strategies but like I distinct distinctly remember when I think it was like like the utility sector was like 60% of one of the most

[00:33:42] involved strategies and there is a bunch of people who are like maybe not exactly betting against but it's a sector that's historically like sub 5% of the S&P 500 that's all of a sudden 50% of a strategy and at some point how does this crack on the

[00:33:57] rebalance into the flows matter and well yeah to that point too like so yeah you're you're in a low ball strategy at 60% utilities and then rates rise and what why do people buy utilities they buy utilities because of the dividend payments

[00:34:13] and well when rates are increasing or where they are now you know if you can get 5% if you can get a 5% yield risk free you know you're going to take that and you're and you're buying a utility with like a 5% yield and that's really what why you're buying it

[00:34:27] you know it you can see how a different market regimes and different things that are happening how those low volatility stocks could actually turn into maybe high volatility stocks to some extent.

[00:34:37] Yeah it's kind of like it's the when friendly looking pets attack of like her whatever right because it's what when the low ball becomes the high ball thing and that can happen here too which is important to acknowledge that idea of like the risk sitting beneath the servers that we haven't seen in a long time is such an important

[00:34:54] when to think about like I mean the example people give now a lot is the idea of stocks and bonds you know stocks and bonds you don't need anything else in your portfolio because you didn't need anything else for 40 years but to your point about utilities the same type of thing could exist

[00:35:05] like if if somebody's running a low volatility strategy and they don't have constraints around something like utilities and then something happens that hasn't happened in 30 or 40 years you might see it not being a low volatility strategy even though you thought it was a low volatility

[00:35:19] strategy and we'll get into the factor tool in a second which will help us kind of look at some of this stuff but that's an important thing to keep in mind and also to go back to your question which I again went on my tangent which got away from this idea of using low volatility with other factors like it's a great

[00:35:32] factor to do that with it works and you know when we we listen you know listed with the pin vom bleats that strategy he was using that payout yield and momentum with it but it works really great you know and that payout yield is kind of a value thing it's it works great with

[00:35:45] value it works great with momentum quality it tends to be somewhat similar I mean still can work okay with quality but it tends to be a little bit similar because quality companies tend to be lower volatility but it's a great factor and that it's very flexible like

[00:35:57] that it can you can couple it with the other factors and you can kind of get a lot of benefit from doing that so this is this is one of the biggest minimum volatility ETFs and we did do this earlier but we should have defined the difference between minimum volatility

[00:36:11] and low volatility so low volatility is really more about the individual assets so when I'm running a low volatility strategy I'm looking at the volatility whether it be the beta or the standard deviation of the individual assets the stocks and I'm putting them together I'm not really thinking in a portfolio

[00:36:25] context when I'm doing minimum volatility I'm thinking in a portfolio context I'm trying to minimize the overall portfolio volatility so I actually can add higher volatility assets to my portfolio if they reduce the volatility of the portfolio as a whole if they are like very

[00:36:39] uncorrelated so it's just you'll see both of them out there in the real world so it's important to distinguish those two because it just it's a nuance behind the scenes that sort of gets at how they're constructing the portfolio and and this is

[00:36:49] the biggest minimum slash low volatility ETF out there which is usmv so we can look at I'm just interested to look at like I want to look at some of the factor profile here as we scroll down and you know the first thing you look at is like low volatility you've got a very

[00:37:02] very high score here so even though this is minimum volatility versus low volatility you're seeing this is this is definitely investing in you know low volatility stocks that score very highly with our low volatility factor and the other thing that I think is important that we talked about before

[00:37:16] is this correlation with quality so you've also got you've got a quality score at 86 year you've got a very high quality portfolio because again low volatility stocks tend to be high quality companies know Karvana is probably not going to show up in your

[00:37:31] you know your low volatility screen so so there's there's a correlation between those two metrics and the other thing I would point out is just over time on the other factors value and momentum you know just like momentum as a chameleon you

[00:37:42] know low volatility to some degree can be a chameleon as well there was a point and I don't know what it was like a few years ago where or maybe a little bit more now where low volatility stocks just were the rage of everything and they got really really expensive so they had very low

[00:37:55] volatility to value and then there's times where they're out of favor where they might have high exposure to value and the same thing with momentum note if low volatility is doing well as a factor you'll have high momentum exposure it just all depends on kind of what's going

[00:38:07] on in the market at any given time so quality and low volatility tend to be high in unison a lot but the other stuff can vary a lot depending on what's going on and the only other thing I've mentioned on this is just going down to that sector

[00:38:17] exposure thing you know this gets at what Justin was talking about before this is a good way to look at some of these just to see you know this one is pretty balanced like it's not that based on our second definition at least it's not that different than the market does not

[00:38:29] huge bets and it's a pretty diversified ETF or ETF so it shouldn't be but this is where you would see what Justin was talking about before like if this thing was all utilities or something you'd see a huge you know excess exposure relative to the market of utilities

[00:38:41] so it's just a quick way to look and see like if what I'm getting is fairly similar to the market in terms of the sector exposure or if it's really really different

[00:38:49] so just from a performance perspective to you know when you so in 2022 the market was down about almost 20% the this fund was down 9.4% so certainly held up better in 2022 but then on the flip side in 2023 when the S&P was up you know 26.8%

[00:39:09] this fund was up 10.3% year to date it's up 7.5% versus about 10% for I think the market if I have the quarterly numbers correct so it's just it is kind of an interesting you know that is from an investor standpoint certainly

[00:39:27] and we know that you know a lot of times investors make mistakes when the performance is bad you know a 10% loss is you know tolerable by a lot of investors but then you know the downside of it is when the market rips and you have all those growth stocks coming back which is what you had last year

[00:39:43] you know this this fund trail by 16% and so if you're the type of investor that's you know sort of the fear of missing out and that would be sort of maybe the flip side of where you know the other downside to it

[00:39:59] so which is it's not going to keep up with the market when it rips like that. Yeah if you look at like O'Shaughnessy's two points of failure for investors you're kind of trading one for the other with this to some degree

[00:40:07] right with these you know you're saying basically all right I want less losses so you're minimizing losses but you're maximizing the other one which is I can have those periods where the market's ripping and I'm underperforming

[00:40:16] and so it depends on every like we've been working with a lot of investors we've kind of learned every investor looks at that kind of stuff differently some investors are more averse to losses some investors are more averse to like I can't underperform the market

[00:40:26] I'm judging you know people at the cocktail party so it's just an important to think about that trade off when you invest in this kind of stuff because you are getting less volatility you are getting less downside but you also are going to have those years where the market rips and you just trail by a lot.

[00:40:38] Now let's do this let's switch it to SPLV which is the and then I want to do one other thing which is the investment.

[00:40:44] S&P 500 low volatility so this looks like they're taking the hundred stocks in the S&P 500 with the lowest amount of volatility.

[00:40:54] Yeah so this is as opposed to the minval when we looked at last time which was looking at it more in a portfolio context this is a low volume ETF so this is looking more at the individual assets.

[00:41:01] And like you said this is a large cap low volatility ETF and as it turns out you'll find like a lot of the low volatility companies in the large cap space anyway.

[00:41:09] You know you won't find that as many of them in the small cap so it's not that big of a difference here but yeah so you'll see like this has 100% active share versus the Russell 2000 meaning that it's obviously all large cap companies.

[00:41:20] So so yeah moving down to the factors you know we'll see kind of a similar picture to what we saw the other one in this case instead of I think 97 it's 99 on low volatility.

[00:41:30] But again you're seeing high exposure to quality because you typically will always see that with these low volatility ETFs and you're kind of seeing similar things on the on the value of momentum side as well.

[00:41:39] You know these stocks haven't done as well recently so the momentum is is a little bit lower you know we've been having a big market run like we talked about before when you're having a big market run sometimes these things are trailing so that they don't have as high momentum.

[00:41:49] But you're seeing a lot of the same stuff you saw before and then you are seeing a little bit bigger sector bets on this one than you did in the other one so you've got some of these.

[00:41:57] You are seeing a bigger utility bet like you referenced before Justin like 12% ahead of the S&P 500 in terms of its its weight to utilities.

[00:42:05] You know and way way way underweight technology.

[00:42:08] So yeah again it gets into the details are always really important in this stuff and you can look at how the exposure to factors but you can also look at like what they're doing on the sector side.

[00:42:17] And you can learn a lot about how they're constructing the portfolio and what the end result looks like.

[00:42:23] So what's interesting is yeah I mean the the MSCI USA min volatility is benchmark to the large blend index whereas this ETF is benchmark to the large value.

[00:42:44] Interestingly because it's value current value exposure at least through our thing is not really you know high on value.

[00:42:52] That's for morning star.

[00:42:54] Yeah this is from morning to morning star and the reason that I was kind of I'm interested in that is because just again from when we look at the just the return profile of this specific fund to compare it in 2022 this fund was down only 4.8%

[00:43:11] But it has the index only down 6.9% and then in 2023 this was up half of a percent versus the cat versus the index of the large value morning star index of 14.3%.

[00:43:25] So you know very different return profile when you look at those kind of two years versus versus the first one we looked at.

[00:43:34] Thankfully Justin as opposed to morning star like Validia has a very very talented programmer who makes their categorization of this so we have both categorized as large cap low volatility.

[00:43:44] So our my extensive system that looked at the holdings behind the scenes and classifies them based on their holdings is it looks like is actually properly classified these two.

[00:43:52] Now one of the things that you can do here by the way is you can compare.

[00:43:57] Let's say let's compare SPLV versus.

[00:44:03] And you can see then the then we start comparing the differences in the factor exposures which you know that's that's kind of very useful so you kind of know what you're getting right like if you're if you're looking at 2 ETS and you're like what am I I want to seek the most low volatility or the most value and you know you're being presented with two different options.

[00:44:23] This comparison feature is is pretty pretty useful.

[00:44:28] Yeah what's cool too is you can see the difference you see below the difference in the sector allocations to right kind of see what what one has in terms of a sector allocation relative to the other.

[00:44:36] So if you're comparing the two and I want to I'm looking at buying one or the other.

[00:44:39] I can see like what I'm getting from a sector perspective in both of them and the factor things you talked about right so this basically saying good that it's largest overweights.

[00:44:49] In SPLV versus USMV is you know consumer non cyclicals utilities and then capital goods and the biggest underweight right is is technology which is what we showed before so before the chart looked at before was comparing it to the S&P 500.

[00:45:04] Now this is comparing them to each other.

[00:45:06] So you know SPLV had a significant underweight relative to the S&P 500 it also has a significant you know underweight of technology relative to USMV.

[00:45:15] So it's just an interesting way I mean it's not that you have to draw any conclusions from this but it's just an interesting way to understand what you're getting when you look behind the scenes of this stuff.

[00:45:22] Well you have two different recipes to get to the end result right they both have a different thing they're aiming for but two different ways of building it from the bottom up or the top down and it's really interesting to think about how again back to that initial idea both of these things actually work in practice they've both been proven out to do what they're supposed to do but they're solving it from two very different ways as the tools suggest.

[00:45:45] Do we want to we're kind of getting towards the end here but do we want to talk about I know we're all sort of fans of Nomadic Samuel he's pretty widely followed on Twitter he has a site picture perfect portfolios I think it is and he you know different he writes about different investment strategies.

[00:46:03] Managers contribute and explain their strategies on that site but one of the things that he does a lot of work on is these building and testing of multi asset portfolios and sort of trying to get at like you know portfolios that are very robust and that work over all different almost like all weather and work over all different market environments.

[00:46:29] Let's just I think we had a couple thoughts on the importance of well how he's incorporating low volatility in those multi asset portfolios and what some of his research is finding.

[00:46:42] Yeah well first of all I would definitely endorse you know picture perfect portfolios is a great site and you know what he does he does a lot of different things there but one of the things he tries to do is build these optimal portfolios from a risk adjusted return standpoint and also build optimal portfolios in terms of minimizing drawdowns.

[00:46:56] So because that's sort of the holy grail of investing for a lot of people is I want to build like a consistent portfolio that minimizes drawdowns how do I do that and you know the answer to that on at a high level is a lot of you know multi asset portfolio that takes into account things other than stocks and bonds.

[00:47:12] And there's so many tools you know we've talked about what Corey Hofstein is doing with the return stacking stuff.

[00:47:16] There's so much stuff that's available today that wasn't available in the past and so there's so many ways you can construct these portfolios like thoughtful ways of combining all these ETFs together into optimal portfolios and he does tons of it there.

[00:47:29] There's tons of different ways he looks at that but one of the interesting things that I've kind of learned from looking at his stuff is when you look at trying to build a portfolio that minimizes volatility that minimizes drawdowns.

[00:47:39] A lot of people will look at like all these other asset classes and like let's take my stocks and let's put all these other asset classes in here but it's also important to pay attention to what's actually going on in the stock sleeve of that.

[00:47:49] And that's what he uses he uses these types of things like I think he uses USMV a decent amount he uses it there because if you're trying to build a portfolio to minimize drawdowns like don't just look at all these other asset classes but also look at minimizing drawdowns and stocks and using minimum volatility or low volatility can help you do that.

[00:48:04] And so I think that's a thoughtful way he took something like this.

[00:48:08] So for an investor who cares a lot about this for an investor who's really trying to minimize like the drawdowns of their portfolio and still get a decent return over time these can be a great tool to incorporate into a multi asset portfolio.

[00:48:19] This multi asset piece of this is huge too because how to think about this cross asset classes how to think about how it applies and then how to space that out depending on what you need the portfolio to do.

[00:48:31] There's lots of advantages in understanding these variables so you can dial that risk exposure up and down.

[00:48:38] Matt talk a little bit about how you kind of approach this from planning sort of perspective and and you know do you do you incorporate any of these types of strategies in your client portfolios I mean I could certainly like I think like to me it seems like these are like.

[00:48:57] I'm going to steal from them out of here but picture perfect sort of strategies for sort of retirees like people that need to make their money grow but they don't want to get blown up.

[00:49:08] They're not really I mean you know when you're in retirement hopefully you're not really trying to beat the S&P year in and year out you know like you guys do it's just you know are you meeting your goals are you on track like the stuff that you know that you advise clients day in and day out.

[00:49:23] But how do you know how do you and your team think about like these types of you know lower volatility strategies and do you incorporate them or what's how do you guys look at it.

[00:49:33] So we do incorporate them thinking about correlations and overall contribution to volatility when we're building portfolios is a big part of it.

[00:49:42] I'll say two places this type of stuff shows up and I'll give you the very financial example and then I'll give you the more planning oriented example.

[00:49:49] And the purely like financial example it's all the risk tolerance type questions you just had how risk averse are you at what phase of life are you in.

[00:49:58] The big difference between you know like I'm thinking of like Eric Clapton like when he does the unplugged album versus I don't know cream or whatever like there's just different phases of life where different things are more appealing and knowing there are tools

[00:50:13] and methods to say you don't need to hit as high on the upside you just need to reduce that downside you might be at a point in life we just you need to tears in heaven it and that's okay you can do that.

[00:50:26] And that's useful that's useful for us to know about a client across the table from us to build that thing for them.

[00:50:32] The more advanced version of that looks like to clients who come to us who are aware of some of these quantity strategies and thinking about this stuff.

[00:50:41] It might also look like very real conversation from just in the last week where somebody understands some of this stuff we're getting towards that pre retirement phase which is a really important one where the window of retirement is about to open up markets keep surging it might happen sooner markets take a dive they might work a little bit more

[00:51:01] a little bit later. But as we're building the the after tax portfolio so the taxable savings that are still invested stuff like low vol can make a lot of sense because it might be well what if I what if I lose my job need access to this money and whatever else in this window of time and that can guide some of those decisions to just say how can I stay invested but just with less downside risk.

[00:51:24] I'm okay with less upside risk but I really need less downside risk to get through this next chapter in my life.

[00:51:33] And that might shift again actually at a meeting already this morning with somebody else who's older but there are some Roth assets that are definitely going to the kids that we're not taking distributions from and despite the age it's like yeah let's go make money with this press the risk all the way down let's see where it goes.

[00:51:50] On the financial planning side. These ideas really represent how to think about stuff where you're willing to accept upside or or you're willing to mitigate your downside.

[00:52:03] So something I learned from when I used to be at Merrill from Savita Subramanian from Nigel Tupper from some of the people that department was think about variance think about volatility think about beta is everywhere.

[00:52:15] So you can look at your job. You can look at your spending patterns you can look at your debt and you could say where are the places I'm willing to accept volatility and where are the places I'm looking to minimize it.

[00:52:29] And you can think about that from the top down so I could think about it from the approach of the the minval where I'm thinking about it how it aggregates or other people are wired to think about it from the bottom up each individual holding.

[00:52:41] How do I have the minimum amount of volatility or variance across all these parts of my life. Understanding how you're wired how you're aggregating that together inside of your plan and what what those choke points might look like.

[00:52:55] This is intensely useful logic and that's part of why I love having these conversations because like low ball in itself that maps over so many strategies for how we think about real life and way more so in a way than how we think about stuff like momentum so often.

[00:53:09] So I'm going to put you on the spot here. So which one of these five songs best in bodies. The concept of low volatility ready. This is good. This is good.

[00:53:21] Take it easy from the Eagles don't worry be happy with or without you the waiting by Tom Petty or everybody wants to rule the world by tears and fears tears for fierce.

[00:53:37] Well it was the first one again. Take it easy.

[00:53:41] Man so take it easy you have the whole like hell freezes over thing the Eagles skull and I mean fantastic song. Take it easy originally Jackson Brown I think I might confirm this or he might or he might at least written it.

[00:53:55] I'm pretty sure he wrote it. I'm pretty sure that's his sock. So that's that's definitely scoring high. I think Bob Marley is a sleeper Bob Marley is not what I want to hear in the dentist chair. Let's just say there's other implications of substances that make me perhaps worried about the person doing the procedure.

[00:54:11] I'm in that camp maybe that dates me.

[00:54:13] I do might have been Bobby McMick Fern Bobby McFerrin. Yeah it was Bobby.

[00:54:18] Don't worry. Don't worry. Don't worry. Don't worry.

[00:54:21] Oh yeah we stumped the you did. You know what I actually like this is like Penn Jennings on Jeopardy getting a question wrong it doesn't happen.

[00:54:30] Bobby McFerrin. I do love that song. I love that video. That's a weird one to hear in the dentist's office. I had Bob Marley on my mind because I saw like three little birds and something else on this playlist.

[00:54:41] And I was like if my friggin dentist is stoned and drilling me. I'm not gonna feel good about this situation.

[00:54:47] And what was the last one on your list to the last last few were sorry to keep on like it's definitely not Tom Petty Tom Petty in that whole like I can't remember if that was full moon fever which which cassette tape I had that on great variation inside of Tom Petty's music.

[00:55:06] Same thing with the Eagles. That's a hard one. Who is the last one on that list Bobby McFerrin. I mean wonderful thinking about your body live.

[00:55:13] Everybody wants to rule the world tears for tears for tears. I don't know that wasn't a great one. I assume this is chat G.P.T. Justin you're asking it like low volatility songs.

[00:55:22] This is right. This is real time chat G.P.T. But you know hey it's I mean I got to sit like it's somewhere between.

[00:55:29] It's probably like Michael Bolton because even like Celine Dion gets to chess pounding glorious in many places like Michael Bolton might be the ultimate low vol strategy where it just it never gets carried away.

[00:55:44] It's a luscious perm that never devolves into nickel back. You got the sax solos I think there's a couple Kenny G. partnerships like Michael Bolton feels like he embodies it in a way like Genesis got too lively Phil Collins would get too dancing like Michael Bolton is in that lane.

[00:56:03] If I'm investing my funds in the ultimate low or min vol dentist seat chair. Give me the Michael Bolton playlist and I have no fears a low volatility strategy could also be your sole provider.

[00:56:18] If it's in that way to do it.

[00:56:20] That's amazing. That is amazing.

[00:56:24] All right guys good stuff. Thank you everyone for listening and we'll see you next time.

[00:56:30] Hi guys this is Justin again.

[00:56:32] Thanks so much for tuning into this episode.

[00:56:35] You can follow Jack on Twitter at practical quant you can follow me on Twitter at JJ carbon and follow Matt on Twitter at cultish creative.

[00:56:44] If you found this discussion interesting and valuable please subscribe in either iTunes or on YouTube or leave a review or a comment.

[00:56:52] Also if you have any ideas for topics you'd like us to cover in the future please email us at access returns pod at gmail.com.

[00:56:58] We would like this to be a listener driven podcast and would appreciate any suggestions. Thank you.