Eric Falkenstein: It’s All Relative

Academics and practitioners are no longer surprised by the existence of the low volatility anomaly. Many papers have been published in credible journals describing the effect and several explanations have been proposed. But most of the explanations seek to preserve the traditional relationship between risk and return that serves as the fundamental basis of modern economics.

Eric Falkenstein turns this concept on its head.

Eric wrote his thesis on the low volatility effect long before it was acceptable to talk about in polite company. Despite the size of the effect and the depth and breadth of Eric’s analysis, it violated the critical “equilibrium” theory of the day and was rejected by every journal. Eric learned some valuable lessons from this experience that listeners would do well to pay attention to.

We were most intrigued with Eric’s research into an alternative equilibrium model, rooted in aversion to relative rather than absolute wealth. If investors are more concerned with relative status rather than absolute wealth then the low volatility phenomenon is a legitimate risk factor.

Eric’s work covers far more than just low volatility investing and risk models. Our discussion branches into politics, social policy, and eventually into his new pet project – cryptocurrencies. This was an all-around incredible conversation that listeners won’t want to miss.

Listen on

Apple Podcasts

Subscribe on


Subscribe on

Google Podcasts

Eric Falkenstein
Portfolio Manager, Pine River Capital Management

To help inform investors about the passive investment approach, he was among the first authors to publish a book that explained passive investing in layman’s terms — The Only Guide to a Winning Investment Strategy You’ll Ever Need. He has authored seven more books: What Wall Street Doesn’t Want You to Know (2001), Rational Investing in Irrational Times (2002), The Successful Investor Today (2003), Wise Investing Made Simple (2007), Wise Investing Made Simpler (2010), The Quest for Alpha (2011), and Think, Act, and Invest Like Warren Buffett (2012). He also co-authored seven books: The Only Guide to a Winning Bond Strategy You’ll Ever Need (2006, with Joe Hempen), The Only Guide to Alternative Investments You’ll Ever Need (2008, with Jared Kizer) and The Only Guide You’ll Ever Need for the Right Financial Plan (2010, with Tiya Lim and Kevin Grogan), Investment Mistakes Even Smart Investors Make (2011, with RC Balaban), Reducing the Risk of Black Swans (2013 with Kevin Grogan), The Incredible Shrinking Alpha(2015 with Andrew Berkin) and Your Complete Guide to Factor-Based Investing(2016 with Andrew Berkin). He writes a blog for and you can follow him on Twitter.


Adam:00:00:02Hello everyone. Thanks for joining us for today’s episode of the Resolve Podcast series. I am really excited to have Eric Falkenstein on the show today. Eric received his economics PhD from Northwesten in 1994 and wrote his dissertation on the low return to high volatility stocks. As such, Eric is one of the first academics to document the so-called low volatility anomaly, along with practitioners like Bob Hogan and Jim Himes. Early in his career, Eric built an enterprise risk system for trading operators to keep … and eventually went on to create the RiskCalc private firm default probability model at Moody’s, which is still one of the most popular product form default models in the world. Eric’s been an equity portfolio manager and currently works on trading algorithms for Walleye Software. He’s been published in several journals including the Journal of Finance, the Journal of Fixed Income, Derivatives Quarterly, and others.

He’s also the author of two books, “Finding Alpha” published in 2009 and then “Missing Risk Premium” in 2012. He blogs, albeit infrequently, at, and you could sometimes find him on Twitter @ egfalcon. Eric, welcome. It’s a pleasure to have you.

Eric Falkenstein:00:01:19Hey. Thanks, Adam. Good to be with you. Just to clarify, I stopped working at Walleye about six years ago, because then I left there and went to Pine River for like three years. Unfortunately, they had a tough patch and I got there at the peak and they were like five billion and now … And then that all went away, your big multi-strat. So for the last basically two years, I’ve been on my own and I’m creating a fund in the crypto space and I can’t talk about it too much because it’s qualified investors but that’s what I’m doing now, and so just to clarify.

Adam:00:01:59Thanks for that, yeah. That will teach me to grab your bio from Amazon where you probably haven’t updated it.

Eric Falkenstein:00:02:06Yeah. Right.

Adam:00:02:07A number of years, so thanks for clarifying, and we should chat afterwards about what you’re doing in crypto. I’m really trying to climb the …  in that space and man, there’s a lot of misinformation.

Eric Falkenstein:00:02:24Well yeah, it’s fun for me because I’m a big libertarian and like the whole cipher punk angle and then just the math of it and the game theory is really fun. But it’s kind of what, diagonal, and it’s very high risk so I’ve moved over as most people do. It’s okay to be for high volume I think if you know what you’re doing. But as a general strategy, it doesn’t make any sense, and that’s the problem.

Adam:00:02:54Right. Yeah. So are you thinking about applying some sort of factor overlays or some sort of systematic strategies to try and put together portfolios of crypto-currencies, or what’s the general thesis?

Eric Falkenstein:00:03:10No, I’m not going to do … No. They really don’t have any factors that I’ve identified and it’s not liquid enough to do that kind of trading. So it’s more of an institutional … stuff you do, but unfortunately, I can’t talk about it much but-

Adam:00:03:29No. Fair enough.

Eric Falkenstein:00:03:30You can’t do … A year ago, they had so many different coins you might be able to find a factor, but basically you’ve really only got five that trade now and they’re all so correlated. They basically all are one factor models now.

Adam:00:03:47Yeah. Well, fair point, fair point. Eric, I’ve been following your career for over 10 years. I’d stumbled on your blog which led me to the missing risk premium, which led me to some of your papers that we’re going to talk about today. You’ve had a really interesting career trajectory in my observation. I’m just wondering, are there any facets of your professional journey that you feel are not very well captured in your biography but have been really uniquely formative for you? Many experiences don’t really fit into a bio but are instrumental in shaping our thinking. You want to fill any gaps there, if there are any?

Eric Falkenstein:00:04:34Well, I guess I’ve always been wanting to do it on my own. So when I wrote my dissertation, I didn’t have a lot of buy-in from the finance guys. I had two game theorists and a …  And if you want to get a good job, you need somebody from the finance department who’s well known to push you, and I didn’t make any friends there because my stuff didn’t make sense to them. So I’ve always been unconventional. I was TA for Hyman Minsky, and what I liked about Hyman Minsky was that he thought everyone was wrong. And to a certain extent, everybody is wrong all the time. The trick is you’ve got to find something better. But I miss our way wrong. And so I thought that was really cool and I thought I could figure out business cycles and … But then when I published my papers, I don’t know if you know this, I don’t thank a lot of people.

I do them by myself, and I think looking back I would have been a lot more successful if I would have tried to reach out and get more … I don’t know, compromise more with big names, because you can’t do anything by yourself. So when I tried to create my own novel fund back in ’96 or so, one of the main reasons it failed was because I’d tried to do it myself. A good friend of mine, Pim van Vliet  over at Robeco , he worked within the system. He had a guy at Robeco and he was a young guy out of school and he partnered with somebody and … but that’s what you got to do. You got to go out and make friends and you can’t be the lone genius creating great things. You got to work with other people to create great things. So I think, looking back, I wish I would have done that more but-

Adam:00:06:40That’s a good life lesson. We’ve had Pim on for a webinar. He’s been extremely generous with his time and he’s such an incredible, humble, so incredibly talented individual. I’m hoping to have him on again for a podcast chat. I know he’s been working on this paper. He had gone back and extended these multi-asset factor premiums back a couple of hundred years, which obviously was an enormous effort just in terms of data collection alone, and he’s getting the paper, or at least the research in shipshape so they can submit it to some-

Eric Falkenstein:00:07:19I thought they did submit it like a couple of months ago, they sent it out.

Adam:00:07:22Yeah. Okay. Maybe they’re doing revisions now, but in chatting with him, he said he had a bunch of work to do and hoped to …

Eric Falkenstein:00:07:27Yeah. I told him he should just focus on … He’s got a really unique data set because most data sets, like the Fharma  – French data in 1926 in the U.S., and then he’s got … Well, the trick is, he’s got world data going back to 1800 but he doesn’t have cross-sectional. So, his factors are analogous to equity factors, but when we think of a value factor, it’s really like a cross-sectional factor, and if all you have is the Japanese or Dutch stock market return, you got to say, “Well, this is analogous to the value of the Dutch stock market, but it’s not really.” But anyway, it’s a unique data set so it’s very interesting.

Risk and Return

Adam:00:08:13Yeah. No, I agree. Okay. So, I want to get right into what I consider to be the meat of your life’s work, right? And you can correct me if I’m wrong but I thought this excerpt from a paper that you wrote in 2010, the paper is called” Risk and Return in General Theory in Evidence”, and it presents an alternative model for risking utility in financial markets. By the way, it’s a very approachable paper. I highly recommend it to practitioners and academics alike. It takes an extremely orthogonal view to the traditional models of risk and how risk is compensated in markets, and I just want to read this extract because I think it really frames what we’re going to talk about for the rest of the conversation.

So I’m going to … This is an excerpt.” People strictly prefer a certain outcome to an uncertain outcome with the same mean payoff, and so demand payoff premium to be indifferent. To the degree risk is not diversifiable, as in market risk, someone must hold it, and because it is disliked, those who do hold it must be compensated via a risk premium relative to risk-free securities. Yet it is striking that a first approximation to risk via volatility or beta against the market return generates no positive risk premiums. This paper argues a more radical but much simpler solution: There is generally no empirical risk-reward relation, and that the seemingly obvious examples are exceptions to the general rule, explainable as liquidity premiums and measurement error. I present a model that explains the null risk-return result as an equilibrium where people internalize risky decisions by comparing themselves to others, as opposed to the standard approach to risk based on the absolute volatility of their wealth. If utility is a status function, specifically the value of wealth relative to one’s peers, only deviations from the consensus are risky. Risk can be avoided in this context by everyone holding an identical market portfolio, making it similar to diversifiable risk in a world of absolute returns, avoidable, and so un-priced”.

Maybe take a minute to unpack what this excerpt is talking about in your own words and maybe bring to bear some of the experience that you’ve had, and deep thinking that you’ve had over the 10 years or eight years since writing it.

Eric Falkenstein:00:10:47Well, when I came out in my dissertation and which I published in ’94, I discovered that there was low volatility actually slightly higher return. It was like 2% higher. And I didn’t have a good theory at the time, so I tried to document that mutual funds tended to disproportionately hold low volatility stocks and I documented that, and that paper got in the journal finance. But then … so that wasn’t an equilibrium theory because back when I did this, it didn’t work to say the Freakonomics behavior of finance stuff wasn’t really popular. So you couldn’t come out and just say well, you have this ad hoc partial equilibrium explanation for this result. You can do that now. You can do that since like 2000. But you couldn’t do that in the early 90’s. And so it just didn’t make any sense so I didn’t come on to the relative volatility stuff until later, and then I figured out oh, if it’s relative volatility then everything makes sense.

Because intuitively we don’t like risks. I’m not going to … You have to pay me to take on reducing credit risk. But reducing credit risk is the same and unlikable whether you’re a relative risk guy or an absolute risk guy, because you deviate from the zero or you deviate from the mean. It’s the same thing. But the question was, well, clearly beta doesn’t work within stock markets. And it just gets more clear all the time. And it’s never worked. It’s not like it used to work and it went away. It’s never, never worked. And then I found all these other markets, like 20 of them. Financial markets where it doesn’t work where it should work. And then they’re all these things outside finance where it clearly doesn’t make any sense that … with this way. And so that’s why it’s common myth with the relative risk and I came up with that later in the mid 2000’s because I wrote that one book.

That was the theme of my book, “Finding Alpha”, and when I wrote that because I was … Well, mainly because I was in this silly little lawsuit and I was … I don’t know, you ever watch Silicon Valley?

Adam:00:13:16I’ve seen it, yeah.

Eric Falkenstein:00:13:17You know the Julio lawsuit? Saw that?

Adam:00:13:17Mm-hmm (affirmative).

Eric Falkenstein:00:13:20That was the kind of thing. I left the hedge fund, I was going to start my own thing. I thought, I was like, “Well,  I can do this myself,” and I had this long shot equity strategy based on low volume and it worked well, and it generated nice little low one Sharpe and thought it would be great, and my ex employer found out about it and sued me. And he said basically he owned everything related to low volatility and, and so while I was in probation for that two years, that’s when I wrote the book because I couldn’t work. And I just got into it, it just seemed like …well, it’s obvious that we were more relative than absolute risk minded. The theory I’ve started with about the marginal revolution of 1870’s where you have the first guys that say why is it that diamonds are worth more than water? And you could explain … no, nobody else could explain it, right? And Mark had this … he had the value of use and then you had the value of exchange.

And so I would say the value of use of water is high but the value of exchanging water is low. And they had this kind of silly compartmentalization. But then guys like Jevons, and I don’t know who the other two guys were, came up within five years, they all came up with this theory of utility which is your first ice-cream gives you one utile, and then your second ice-cream gives you a half a utile, and if you have diminishing utility, that implies you’re risk averse. So there’s like an if and only if relationship between risk aversion and decreasing marginal utility, mathematically. And, I don’t know, mathematically the utility theory is great, and economists love it and it works really well at the micro level in explaining all sorts of things, because like I said, it explains relative prices and stuff like that. But then in the 40’s they figured out, well, these guys …

I think it was Friedman actually, Milton Friedman, and some other guy did a study of games right around the time they are doing all that game theory stuff and they said, “Well, let’s look at the risk premium. Let’s just assume wealth is treated like ice-cream or something and use that same diminishing marginal utility framework.” And if so, then you have risk aversion. And of course Markowitz worked under Friedman so he picked up on that and then we get the development of the risk premium, because it all just comes out mathematically about it, and that’s why we’re so beautiful. But the thing is it never worked, and it has all these other absurd implications that don’t work but mathematically it’s nice because it just makes so many things in growth theory and microeconomics from that perspective, work great. But it’s just that-

Adam:00:16:29It just doesn’t explain anything in real life.

Eric Falkenstein:00:16:31Right. It’s great for modeling the length, because if you’re a good theorist if you buy this relative risk hypothesis, if you think we’re more relatively oriented, economists really can’t say much about making the world better. Because in some sense, well, a good world is one where everyone has the same income at $1,000 rather than one where we have a distribution-

Adam:00:16:55… higher average in wealth but-

Eric Falkenstein:00:16:57Yeah. Yeah. Obviously that’s not good but then it gets into how do you value quality versus liberty and then those get into questions that aren’t mathematizable. And then economists become not relevant and we wanted stuff that was mathematizable, model-able, and so no one wants to go that way. But it’s still … it just doesn’t work at all and so here we are. And fortunately, when I figured out the relative risk thing back in the mid 2000s, I wrote the book because you don’t have a … you’re not going to get rejected for writing a book and Wyle wrote the book. But I did try to send it out to some places and then they all said, “Well, obviously that doesn’t make any sense because well, it’s just too radical.” And the big counter example was that the equity was premium. That that’s a pretty big data point to … that I couldn’t explain.

And when it kind of remains, but like I said you can explain some of these things with liquidity premiums. There’s obviously a risk premium from going to cash to like one year of debt. But think about it, you can use t-bills as collateral. That’s like money. But you can’t use t-bonds as collateral’s money. Right?

Adam:00:18:27Mm-hmm (affirmative).

Eric Falkenstein:00:18:29And the same thing’s true for triplicated Triple-B. There’s a risk premium, there’s return premium going from triplicated triple-b. But again, you can’t really pose triple-b bonds as … You can’t use those to collateralize all sorts of things, where you can Triple-A. So that’s kind of an institutional liquidity thing. There’s a big difference between going from certainty to non-certainty but after that it doesn’t extrapolate and so … And then the equity premium though I think that’s a real puzzle because … the crazy thing about equities is most people think the equity risk premium is something like 5, 6%, right? So how do you explain that? Weird thing is, overnight returns are like 100% of the equity risk premium. If you look at close-open- last like 30 years, that’s all the return in the stock market. It’s not open to close. But open to close to close is two thirds the risk.

So if you think you are getting for equities for taking risk, well, why aren’t you getting two-thirds returns in a day when you have two-thirds of the risk?

Adam:00:19:40You make a really good, deep conversation of the ERP in your “Missing Risk Premium” book if I recall and once you back out, all of these other explanatory variables, you’re are not left with much, if I recall?

Eric Falkenstein:00:19:51Yeah. Your average investor does really poorly. You ever seen surveys of the institutional, I don’t know, there’s some group. Whatever the top line-

Adam:00:20:04The DALBAR?

Eric Falkenstein:00:20:05Yeah, the AMR something. The average investor makes like 5% less than the top line, even if he’s an equity investor because of all the fees and bad timing they do. They have all. I forget who the guy was. He’s a guy at Michigan. Your average retail investor is just bad timing and they pay a lot of costs, and of course then there’s taxes. And when you take all that out, your average widow and orphan is not making the equity risk premium. Institutions are. But so … it’s a weird thing but, those are the three anomalies. You’ve got the Triple A to Triple B, your risk premium. You got the yield curve risk premium going from like cash to three years or so. And then you’ve got the equity risk premium. And all those I think are the first two are I think liquidity, institutional collateralization issues and an equity one. Well, the equity one’s weird. I don’t know.

Adam:00:21:16More of a puzzle. And also to review, if you look at the equity risk premium more from a median perspective across all markets through history, then that premium is nowhere near as large as it is. If you exclusively look at the U.S premium.

Eric Falkenstein:00:21:36Yeah. Right, right, right. Yeah. Because you have a lot of markets that have gone to zero like in China and Russia and Germany and Argentina and you have a bunch of them. I think Israel actually went to zero once. Don’t take many of those too, but put a negative 100% compound return stream and it wipes everything out.

Adam:00:21:56Exactly. Exactly. So I want to go back to the mid 1990s, you’re doing your PhD, you’ve identified this incredible anomaly. It is robust to everything you throw at it. It is eminently treatable as you demonstrate a little later on. But you can’t get this comprehensive thesis published. What was the climate back then that prevented you from being able to make progress academically with this concept of low volatility?

Eric Falkenstein:00:22:27Well, like I said, that was before behavioral finance and Freakonomics made it reasonable for somebody to come up with an ad hoc, partial equilibrium solution. So, a general equilibrium solution requires that people can arbitrage whatever little effects. So today you can publish a paper and say, well, because people really like companies with these characteristics. Because a lot of people like them. It pushes up the price and so they have lower than average returns. And you can say that like in Frazzini & Pederson, right? So Frazzini & Pederson from AQR had this paper out where they say fund managers, they want more equity exposure because they want more of the risk premium. And so they all reach for the High Beta stocks. And so that’s why they have lower returns than expected. Fine, but then if you introduce a couple of agents in that model who aren’t constrained then they just get rid of that result entirely.


Eric Falkenstein:00:23:39So they have an ad hoc constraint on the entire system that wouldn’t pass muster in the 90s, but it works now.

Adam:00:23:47You’re not assuming macro consistency now or-

Eric Falkenstein:00:23:50Yeah. Right.

Adam:00:23:50… It’s not a …

Eric Falkenstein:00:23:53You have a solution that says, “Well, people overpay for … ” And this is the way it was, like Ed Miller came out in ’77. He was the first one to point out that hey, high volatility actually should have lower returns because if you have two stocks and they’re both … let’s say mean value is a hundred, and one’s got a really large standard deviation in terms of private valuations. Well, the long owners or are in the top tail, right? Then there are the top 5% of people who liked the stock. Well that tail is further out, the higher the volatility. And he came out with this paper in ’77 and in the70’s economics was still not super mathematical and you got away with that. But, it was becoming very uncool around that time and nobody really picked up on it. But then later on in the 2000s, it’s referenced quite a bit. Because there are models that implicitly basically use that kind of idea and actually some explicitly point to the Ed Miller model. But it didn’t sell at all.

And no one ever hears about Ed Miller. And he’s actually the first guy to say in an academic journal, I think it was in 2000 or 90, he came out and said, you should buy low volatility stocks because high volatility stocks are overpriced because of this reason. And he was the first guy to actually say that. And so anyway, I had this personal equilibrium result, which was people liked it because it was … Low volatility stocks are … they’re sexy. Another thing I pointed out was if you look at the inflows to fund’s and they’re convex, so if you’re in the top decile, you get a ton of inflows and then, it’s very nonlinear and then it’s flat. It’s increasing as you go from the first percentile to the 90th percentile, but then it kicks up from 90 to a 100. So that’s like a convex payoff of a co-option. Right? So what do you want to do? Well, if you just hue to mean, you’re never going to get up there. You have a higher expected inflow if you have a high volatility strategy. That was one of the things I pointed out in my-

Adam:00:26:19So that destabilizes the taking of … that have lottery payoffs for the mutual funds because … the opportunity to get those kind of flows?

Eric Falkenstein:00:26:30Yes. But that was … So that didn’t work. So I remember I sent my low volatility paper into Journal of Finance and they’re like, “Oh, this is interesting why don’t you revise and resubmit?” And then I was doing that. I was also sending it to famous academics and they were all like telling me it was … Actually since then I was working at a bank they were especially dismissive and, just saying, I wouldn’t recommend you do this. This is dumb. As a young guy, it’s really discouraging.

Adam:00:27:05Of course.

Eric Falkenstein:00:27:07So I pivoted and I tried to say, well, instead of saying this is the low volatility anomaly, I’m going to emphasize the fact that this really proves that the CAPM doesn’t work because, you can look at low volatility stocks and statistically prove that there’s no way you can explain this within the CAPM at all. And then when I sent that in, they said, “No, no. Okay, now you’re just going crazy.” And so that killed my Journal of Finance paper.

Adam:00:27:41So was the specific … that security market line is flat or were you making the assertion that it was at a negative slope?

Eric Falkenstein:00:27:49I was saying it actually had a negative slope, but it was so negative and the statistics were so powerful. You could reject the hypothesis that P value of 0.001, that it was positive.


Eric Falkenstein:00:28:05But I didn’t have a good general theory for why, but I just said well, this just clearly proves that this doesn’t work. And because of the feedback I was getting about my crappy ad hoc theory, I thought, well, they like that, but they like that even less. And so then yeah … but I didn’t really care, because I was, I was in the private sector, I was actually quite happy to do this on my own. And I set up my own fund, I created a C-Corp and I pulled in some … my family’s money and I thought I’ll just seed it and then I go around and sell it to like investors and then and then I discovered it was a marketing nightmare because my idea was so simple that people would either say, well if that works, why should I pay you for that? And if, if I went to an institution, they’re like, well, we’re not going to let some kid come here with his own model because he’s going to try to own it.

And then if they understood it, they were like well, you told me everything I need to know. I don’t have to pay you. And then …

Adam:00:29:14The innovator is a lamb in the asset management space …

Eric Falkenstein:00:29:17Yeah so it was … I should have sexed it up a little bit. The initial guys that got some real traction on this thing all came to it obliquely. So you had Cam Harvey and Siddique came out with this conditional skew model in 2000. And they found that low volatility stocks had lower than average returns, but they emphasized. But that’s because they have co-skewness with the market.

Adam:00:29:49Right. So there’s a risk explanation finally.

Eric Falkenstein:00:29:52Right.

Adam:00:29:53So now it’s legitimate.

Eric Falkenstein:00:29:53Right. Yeah. Yeah. And that got published in the Journal of Finance. Campbell Harvey’s a very well respected academic, but it was a very convoluted , bizarre explanation. Wasn’t robust. It’s the same, torture the data long enough. It’ll tell you what you want. Just like today when you try to explain a little volatility with 27 factors, you can say oh, low balls easily explained by these five factors. Okay, five factors versus one. But anyway, so Harvey and Siddique were the first guys that get an academic paper published, but then the big low volatility economic paper to first get published was Ang, Hodrick, Xing, and Zhang in 2006.

Idiosyncratic Volatility

Adam:00:30:37They use idiosyncratic volatility

Eric Falkenstein:00:30:38Yeah, and they came at it with … First they had some … They actually investigated first not volatility. I think they were emphasizing some other wacky aspect of it. And they-

Adam:00:30:54Idiosyncratic volatility, right?

Eric Falkenstein:00:30:55Well, they use it using idiosyncratic volatility, but they wanted … The first part was they were looking at the co-variance of volatility innovations with returns. And that was the main part of their paper. But then the latter half was all documenting, hey, volatility per se does horribly. High volatility stocks have the worst returns. And then after it was published, everyone forgot about the first half, which is what they thought was their big contribution to science. And they just said, oh, this is the first true reputable journal that’s documented, the low volatility effect. Although you could see pieces of it and other papers, but that was the first one that was clear. But even that was, it wasn’t the main point. And you had other papers like that. So, and it wasn’t until these guys started these funds and the funds did well, that everyone started to say, hey, low volatility is like a real thing. It’s got …

Actually low ball in a Sharpe Ratio perspective is attractive. We don’t know why, but from the time I found it in ’92, and by the time you could actually say that directly is your … when you’re in your abstract that whole thing took the industry 16 years. It wasn’t me, it was everybody.

Adam:00:32:27Right. It just wasn’t in the Overton window of finance.

Eric Falkenstein:00:32:31Right. Yeah, true. That’s true. There those things. What do you do?

Adam:00:32:37And so …paid obviously, enormously popular paper. That seems to be an acceptable interpretation but it seems like the results are subsumed by low vol.

Eric Falkenstein:00:32:53Yeah. Right, right. Well, I don’t think it would matter whether it was idiosyncratic, beta or vol so much. I think total volatility is probably the best if you’re looking to explain returns, but if you’re constructing your portfolio and you want to like have it hedged, right idiosyncratic would risk diversifies away, you might just use beta. But yeah, their paper I think is silly because like I said, all you take as one rational agent who’s not constrained and the thing goes away. And also their model predicts it. It doesn’t predict that you have a negative sloped security market line where high beta has low returns than average beta. It predicts a lower than lower than expected. So high Beta stocks should still have higher than average returns. And the crazy thing about low vol is … low vol stocks have a slightly higher than average return. 1, 2%, whatever. It’s the high vol stocks that have the crazy return.

They have horrible returns. The top 20% of stocks in volatility over time, just have a base mark. You want to avoid those like the plague because they’re two-faced in terms of badness, they have horrible returns and they have super high volatility. So betting against beta doesn’t say that. And so it doesn’t make any sense because all these people, all these fund managers are reaching for the high beta stocks, but they’re too stupid to know that the high beta stocks actually have lower than average returns. And so the equity premium they’re trying to grab for via this beta characteristic, doesn’t work. So, it’s the old Keynesian problem of if you assume everyone’s acting in a certain way where the implications of their actions kind of counter their beliefs, it just assumes that everyone’s just really stupid. And for me who was struggling with trying to make my model rational, I find it interesting that this crazy irrational model could be out there.

But they get a nice result, it’s mathematically pretty, and then they get a single metric of its … whatever they’ve got, some high-low return to the metric that they think helps predict stuff. And I don’t think it really does much of anything, but if you can base … if you can crystallize your model down like one little thing, one little equation that definitely sells a lot better, than a messy result that has more than one thing.


Eric Falkenstein:00:35:46And they get a lot of mileage out of that. But I think anybody who goes down that path is wasting time.

Adam:00:35:55Yeah, and the general thesis, right. It’s just avoid high risk stocks, right? High risk stocks are massively under compensated in the cross section and really if you examine the excess return to low risk stocks, the statistical properties are marginal. It’s really, the major effect is the extreme under performance of high risk stocks. Right?

Eric Falkenstein:00:36:25Yeah, on a return perspective. Yeah, but the cool thing is, I think in practice you noticed that brokerages never sell like a stock saying, listen, I’ll give you the same return as the next guy, but it’ll be like two thirds volatility. They do it now because of low volatility stocks and I know Pim van Vliet sells that, and rationally people should buy that. But it’s not sexy. A broker who goes to your average investor, they’re going to say, listen, I can make you an extra 5, 10% because if you buy the new Uber IPO or were, or something or, Tesla, it’s going to double. And I have this reason why. Nobody sells the idea of “I’ll give you the same return at lower risk”, but you should because that’s why I think if you just focus on like these low volatility funds, they’re great because you’ll do like 1 or 2% better than average and you’ll have two thirds of risk. That’s awesome. And for most people for whom investing is not a day job that’s pretty good.

And so just try to be humble and take that. It’s pretty, pretty damn good.

Relative Utility

Adam:00:37:44Yeah, absolutely. I was wondering whether or not you’ve given some thought to whether your Relative Utility model might help to explain some other widely documented anomalies? I’m thinking momentum, or trend following? It seems to me that relative utility might be linked to informational cascades or return chasing behaviors, and that you could quickly intuit how that might translate into these types of continuation effects. If you give me a thought to that?

Eric Falkenstein:00:38:20Yeah, it’s really difficult to model but I think there’s something there. Obviously you remember the Internet bubble, In late ’99, if you weren’t into internet stocks, you were a loser. And there were a couple of really big smart guys who got kicked out of the market because they thought it was all bunk. And it was … say about the market can be irrational longer than you can be liquid. If you’re just going to stand behind, you have to jump on. If everybody’s jumping on to that asset class and you’re not and it goes up, you might not be around anymore. So, when everyone just started jumping to crypto in 2017, a lot of it was just people saying, hey, I don’t want to miss out. And so, you do see a lot of that but it is hard to model mathematically because it’s a dynamic game of … you get a lot of weird stuff going on. I wrote a paper actually on … or I wrote a blog post on baiting mimicry and business cycles.

And baiting mimicry is where you have the snake that looks like the poison of snake, but it’s not poisonous. And so what you have, is in ecological systems, you have there’s an equilibrium number of non-poisonous snakes that look exactly like the poisonous ones. Because otherwise is a snake you can just … I can look like that guy, but I don’t have to make the poison. So I can use those calories for other things. And they just find the qualitative results but they don’t model it because it’s just too darn hard. And so, qualitatively, I think it does help explain why we get into some of these excesses. It’s beyond me to model, but I do think maybe someone smart would be able to do that.

Adam:00:40:18Yeah, that makes sense. I’m wondering whether or not there are other anomalies or things, characteristics in markets, inefficiencies, inconsistencies that you or that practitioners in general are aware of intuitively, but that again, just having … aren’t yet ready for open discussion in academic circles. They are in, as we were saying, the Overton window for finance at the moment. Does just anything else occur to you that’s sort of in this same category that you stumbled across?

Eric Falkenstein:00:40:53Well, big ones are things like options. Since I worked at Walleye for a couple of years, and that was after my lawsuit, and so I just got out of my lawsuit. No one would touch me because I had this weird … We settled and so it wasn’t like I had a free bill of health and no one wanted to hire me. So I was a quant for, and did high frequency strategies for an equity options market maker and learned a lot there about high frequency stuff and options. But the out of the money options, puts and calls, just have horrible returns if you price them at the median. If you price them where retail option buyers are, they’re just insanely low. And of course, they have huge risk. And so, that whole option market is just … In terms of, it’s horrible for your average retail investor. And I think that should get a lot more interest in terms of you’re not helping people by …

It kills me when the Nigerian brothers get on there on CNBC and talk about, promote this stuff, because they’re promoting all sorts of really costly strategies that have really low … I mean, not really low, super-negative returns, and they’re using the imprimatur of CNBC to sell that garbage. They can be used, but in general they’re horrible. I don’t know if you remember Miller Modigliani. That’s like a foundational financial result. Miller Modigliani says, “Well, it doesn’t matter if you leverage up the firm because you’re sure the debt cost will increase, but debt is charged less than equity, but the equity charge will go up so much because of the volatility in terms of expected returns.” Actually, no. So, there’s no evidence for that foundational result either. A lot of people said that the foundations of finance or basically Miller Modigliani, and rational expectations, and the CAPM.

And, well, Miller Modigliani hasn’t worked, CAPM doesn’t work. I believe in rational expectations in the sense of, to a first approximation, it is hard to make money in markets. So, I like that one. But yeah, everything in funds, it doesn’t work. It doesn’t work on intra-day returns, it doesn’t work for real estate, emerging markets, it doesn’t work over time, it doesn’t work in currencies, it doesn’t work in sports betting. Most of these things, it actually goes the wrong way. So it’s just a nightmare of a predictor. And then outside of economics, I think is really interesting is, consider we’re, I don’t know, about seven times wealthier than our great-grandparents probably. So we’re all insanely rich relative to kings of 200 years ago in terms of the warmth I can get, the indoor plumbing and all this stuff, and I get Google, but we whine all the time. Our life, we’re not happier.

So clearly, we’re not getting happier. That’s the Easterlin paradox. They’ve documented this everywhere that … And obviously, that makes a lot more sense if you look at it from a relative utility point of view. And so, the only way we can get the crazy utility that generates that weird result is this CARA … , constant apps to risk aversion, and it’s this weird math function where I care as much about a 10% fluctuation in wealth, whether I’m a billionaire or I have $1,000. And I think on a practical level, that’s only going to matter if I’m judging myself relatively. And so, if that’s the case, I should just junk the mathematics of the CARA utility and just look at it and say, “Yo, relative maximizer,” and biologically, it makes a lot more sense because we have to be in evolutionarily stable strategies and we’re all competing for jobs and …

Yeah, so we’re all competing for mates and jobs and lake front property and there’s only a certain amount of it, no matter how rich society is. …

Adam:00:45:14So you’ve also given a huge amount of thought to this, right?

Eric Falkenstein:00:45:20They found genetically that only 40% of men procreate over time and whereas 80% of women do. So if you’re the median male, you’re like … Over a couple of generations, your genes are going to be dead.

Adam:00:45:34Right. So, deviating away from finance a little bit. I know you’re a libertarian.


Eric Falkenstein:00:45:40

Adam:00:45:40Oh, are you there?

Eric Falkenstein:00:45:46Yeah. Okay, back.

Adam:00:45:47Okay. Yep. Sorry. I’m just saying, deviating a little way up from finance directly-

Eric Falkenstein:00:45:53Lost again.

Adam:00:45:55… you’re a stated libertarian and … Are you there?

Eric Falkenstein:00:46:01No, you’re going in and out.

Adam:00:46:02I wonder if that’s your end or my end. It’s okay, we can edit this out, but-

Eric Falkenstein:00:46:10I wonder if it’s me or you.

Adam:00:46:11Are we continuing to go in and out?

Eric Falkenstein:00:46:18I hear you. Okay, now you’re continuous.


Eric Falkenstein:00:46:23All right, yeah. For a while you were freezing up, like …

Adam:00:46:27Okay, no worries.

Eric Falkenstein:00:46:29Oh, now you’re … Now it’s …

Adam:00:46:30That’s a reference that …

Eric Falkenstein:00:46:31You’re freezing again.

Adam:00:46:32Am I?

Eric Falkenstein:00:46:34I don’t know if it’s my end. Am I freezing?

Adam:00:46:38No, you’re not freezing. No.

Eric Falkenstein:00:46:41Okay. All right. I figure you can cut this out if-

Adam:00:46:46Yeah, we can absolutely cut this out. And keep in mind too that it records locally, so even if you can’t hear me or I can’t hear you, it’s recording. So, if you can get the gist of what I said, you can still respond and it will-

Eric Falkenstein:00:47:01Oh, shoot!

Adam:00:47:02… sound consistent.

Eric Falkenstein:00:47:03I can’t even hear you.

Adam:00:47:07Okay. Just one second.

Eric Falkenstein:00:47:12I can see you.

Adam:00:47:21Why don’t we try-

Eric Falkenstein:00:47:25Now you’re fine.


Eric Falkenstein:00:47:28I wonder how long this will last. I don’t know.

Adam:00:47:30Just as a heads up, let me know if you run into this issue again, but the audio is recording directly and on your machine, so even if you can’t hear me, or I can’t hear you, it will still record fluently, so then the podcast listeners won’t know.

Eric Falkenstein:00:47:50Okay. But like there, I couldn’t even hear you.

Adam:00:47:53Oh, really? Okay. Well, why don’t we try to log back in to this thing and see if it’s any better?

Eric Falkenstein:00:48:03Shoot! I don’t know what’s going on. Once you start talking, it just stops … If you don’t say anything, you come back, but then if you start talking, then it freezes.

Adam:00:48:17Okay. Well, I’m going to log out and I’m going to send you a new link.

Eric Falkenstein:00:48:21I can’t hear. Okay, …

Adam:00:48:34Great, Eric. So yeah, I wanted to just take a minute to take a detour from finance for a second. I know you’re a libertarian, you’re a deep thinker about the fundamental principles of politics and human rights, and I’m just wondering, given … What are the potential policy implications of some of the things that you just talked about in terms of people’s preferences, in terms of relative versus absolute wealth and the Easterlin paradox? From a policy standpoint, what are we doing wrong? What changes can we make? Is there a solution to that, or is this just a problem that we’re going to have to live with?

Eric Falkenstein:00:49:20I just think it’s a sad fact of humanity, that basically … The nice thing about when I was a libertarian and believed in absolute risk, was that a profit maximizing rational, long-term person was for all the libertarian policies that I liked of basically growth. It’s neo-liberalism. You have growth is consistent with liberty, and it’s consistent with maximizing happiness, but it turns out that’s not really the case, that … and that’s scary because I think liberty is good. Liberalism started on the idea of individual property rights, and basically that the king or the sovereign has his authority from the individuals. So, it all starts with the individual, and I think that generates all sorts of good things for flourishing societies relative to free thought, it gave us the enlightenment. Unlike Steven Pinker, who thinks the enlightenment led to the industrial revolution.

I like to think that individualism gave rise to the industrial revolution. It was property rights, full stop. It wasn’t Bacon figuring out science. All the great early scientists were … they were crazy Bible thumpers, like Newton thought … He was in numerology, and all those guys who believed in six-day creation of earth and stuff. So, property rights, and that leads to free thought, it leads into great art, it leads into technical innovation. But unfortunately, if we’re just going to be grubby little, fighting over … Today, see, people aren’t happy in the U.S., and nobody looks and says, “Well, I’m poor, but I’m a lot wealthier than I would be if I lived in the Sudan.” No one says that, and they don’t because it’s not hardwired into us. And so, it’s really depressing, and I don’t have a good solution for it other than to try to convince people that, “If you try to enforce equality by taking away liberty, you’ll have neither,” as Milton Friedman said.

“But if you focus on liberty, you’ll get more equality, actually.” But some people are going to be unequal, they’re going to be able to leverage. It’s hard to say, “Well, in the long run, it’s going to be that way.” That’s just like a Dystopian nightmare, right?

Adam:00:51:59Well, I’ll send you this. I don’t know if you saw it already, but there’s a really neat and short paper by Ole Peterson and I forget who his coauthor is, but they modeled the wealth distribution of a nation, or of a, obviously very simple nation as a function of some sort of growth dynamic, but also assuming no scale. And they varied two or three different variables, and then they had also a feedback mechanism where some of the aggregate wealth is fed back into the system, right, from the individual.

Eric Falkenstein:00:51:59Right.

Adam:00:52:34And the conclusion was that, assuming no difference in skill among the agents, that the system will trend to unlimited disequilibrium unless you feed some factor back into the system, right? There’s some sort of redistribution mechanism, so you don’t even need to have an expectation of a distribution of skill to expect an intermediate to long-term outcome that results in an almost infinite Pareto distribution of wealth.

Eric Falkenstein:00:53:12Well, what’s the mechanism that is making the rich people get richer?

Adam:00:53:15Well, good luck compounds, right? So you’ve got this-

Eric Falkenstein:00:53:19Why … compounds?

Adam:00:53:21Well, you’ve got this … You’ve already accumulated some wealth, and by virtue of accumulating wealth, then you’ve had access to greater opportunity, and that greater opportunity provides for a higher probability of accumulating further wealth, and that compounds.

Eric Falkenstein:00:53:36Yeah, yeah.

Adam:00:53:37But I’m not doing the paper justice.

Eric Falkenstein:00:53:38Yeah, right.

Adam:00:53:38I’ll kick it over to you and you can read it and let me know your thoughts on it. But I thought it was an interesting and simple model.

Eric Falkenstein:00:53:45Yeah. No, I’m a real pessimist in terms of … I’m not an optimist like those people who think, “Oh well, we’re going to solve all our problems,” and I just think humanity has always just been wicked, and nasty, and stupid. And the academics of the day always thought, “Oh, well, the guys in the past were all wrong, but we’ve got it figured out now.” And some of the past, I mean Sam Harris sounds exactly like the humanist circa 1900 who thought, “Well we’re going to go back, we’re going to get rid of all the stupid biases that cause us to be a sub-optimal society and we’re going to fix everything,” and this is in 1900. And obviously, they were way wrong, and we look back and Sam Harris and those guys would say, “Well, that was dumb,” because he was a racist and whatever. But today they like, “But now I’ve got it figured out.” And it’s like, “No, you don’t.” And so-

Adam:00:54:40Yeah. And by virtue of knowing your biases, unfortunately, …  and all of the experts are the first to admit that knowledge of your own biases does not help you to avoid them …

Eric Falkenstein:00:54:51I actually read that it makes it worse actually, because you can-


Eric Falkenstein:00:54:55It’s easier for you to rationalize it, because you’re more … Right.

Adam:00:54:59Yeah. You can convince yourself that you’re not being … My goodness, susceptible to them because you’re aware of them.

Eric Falkenstein:00:55:06Yeah. You’re like, “Oh, I’m aware of them, so therefore they’re not a problem.”

Adam:00:55:12Yeah, exactly.

Eric Falkenstein:00:55:12Like, “Okay.” But yeah, that’s where it just doesn’t work at all.


Eric Falkenstein:00:55:14And so, life is going to be the same. It’s going to be always just … I just think of like my grandpa and the crappy little house he lived in and the bad beer that he had to drink, and he wasn’t any happier or … He wasn’t less happy than me, and I think that’s going to be the case, and we’re going to always have problems, and people are always going to be stupid, and whatever.

Adam:00:55:38Yeah. Agreed. All right, well let’s loop back to the main thematic thread of the discussion. I’m curious, if you were to write a book today, what would it be about? Would you cover some of the same themes, or have you have stumbled into new ideas that you’re curious to explore and share?

The Future

Eric Falkenstein:00:55:59Well, professionally, I’m working on stuff that I can’t talk about, unfortunately. And I’ve really taken a direction … I became a Christian a couple … like three years ago and so that’s a big thing for me, and I really find that interesting. I came about it through actually intelligent design. So I came about it through my head, I didn’t have a crisis. This thing, it logically makes a lot of sense, but that’s just like outside. But then in finance, everybody wants Frazzing & Pedersen thing. It’s like, I don’t know, that Kruger economist, he died recently. Curtin. Kruger came out with this test and they had this one experiment with one equation that proved that raising the minimum wage is a good thing. And then Levitt had this one test that showed that abortion lowers crime, and the sky … this once … Everyone likes these things in a …

Those are really powerful in terms of using academics to prove some point. But none of them work though, but that’s what people want. My explanation for the persistence of the low volatility effect is, well we’re relative risk-oriented, and then people like low volatility for a bunch of reasons. Basically, there’s like six of them, that article I did with Blitz and van Vliet from … goes over on this. There’s like seven reasons to like low volatility just on its own. And the fact that you can’t arbitrage it because you do have the low volatility is not going to be linear to the S&P 500. You have some residual risk there, that gets rid of it, but that’s not pretty at all. So, I don’t think anyone would find that interesting. So, in finance stuff, I just think I don’t really get jazzed about anything that I think is really cool because all I have are these stupid no results.

Like in risk management, risk management I started my career doing value risk and capital allocations and default models. Optimal risk management is good, but it’s not an offensive weapon. It’s defensive, and it’s a lot of common sense, but mainly it’s just a bunch of sophisticated apologetics for whatever your company strategy is. And so-

Adam:00:58:34And it’s not sexy and it doesn’t sell. It’s like the accounting department.

Eric Falkenstein:00:58:38Yeah, right. So the things that sell are like, “Hey, I’ve got this great new tool and it’s going to help you do great things.” The things that I’ve learned that are really profound are actually like just useful, but it’s not going to promise to make you rich. Just like telling an investor, “Hey, you can make 2% more with your money with two thirds of risk.” Well, most people find that not very appealing. So, man, I’m okay with that.


Eric Falkenstein:00:59:06So, whatever.

Adam:00:59:07Right. How much do you squat? You like to-

Eric Falkenstein:00:59:15Yeah, I work out a lot. I do a lot of Jujitsu now. It’s a great workout. We work weights a lot, but I had to control my movements because I had a micro-disectomy on my back, and I’m 53, so I try not to … I don’t want to hit my maxes ever again. But yeah, I do a lot of the machines. That’s how you still can get hurt.


Eric Falkenstein:00:59:39You stay away. Yeah, so I don’t do straight on benches anymore. When I do the squats, they’re usually in these wacky … I don’t know, they’ve got crazy machines now, but I’m still pretty strong. My daughter’s 12, so I figure I’ve got to be pretty tough for the next 15 years until she gets married.

Adam:01:00:02Absolutely. …

Eric Falkenstein:01:00:03Yeah. I can accommodate all of her quarters, her dates for the next 15 years. So that’s my goal.

Adam:01:00:11That’s good motivation. I like that. Okay, well let’s wrap it up. I’m just wondering what the nod … Did I miss asking about anything that you’d hoped to have a chance to talk about?

Low Volatility

Eric Falkenstein:01:00:20Well, just the one thing is that, whether that’s low volatility is explained by a multiplicity of factors, I would say no, just because if I have a model that has one factor that explains stuff as well as a model that explains with five factors, I would say the model with one factor is a better explanation.


Eric Falkenstein:01:00:43So, you can throw … When I was when I was at Pine River, we had the equity risk model and it’s … They now have like, I don’t know, 15 or 20 factors they look at. It’s ridiculous, and you can explain everything with them but you explain everything and nothing. I think it’s much better to be … Simpler is always better. When I was at Moody’s and tried to model default risk, it was much better to find one metric of leverage than to use five metrics, take the average, and all sorts of things that went into the model that way. And the same thing is true for a stock. I think, everyone thinks, “Oh, well if five things, and I average them, it’ll be better.” It’s like, “No.” It’s better to have some faith in one thing and then stick with it, but it takes a lot of faith because if you find something that works, you’re going to get a better Sharpe by 0.2 or something.

And you’re not going to see evidence of that, statistically for 10 years, but that’s the riskiness of investing. But I think as a general prejudice, I would go in with, if you think you can get the same result with fewer factors, choose that.

Adam:01:02:04Yeah, this is often a really confusing subject for … Even among practitioners, it’s confusing, right? So, for example, imagine you’ve got your value manager and you’ve got a variety of different ways that you can measure value. Your systematic value manager, right? So you’re running screens, and so you do a horse race and you see that over the horizon, that you’re able to measure that ranking on price earnings outperforms ranking on price to cash-flow and the Sharpe ratio is 0.52 versus 0.48, and you know that the standard error of the Sharpe ratio is somewhere on the order of 0.15. So they’re statistically indistinguishable. What’s the right move there? Is it to form a portfolio by sorting on PE and then form a different portfolio by sorting on price to cash-flow and then hold all the stocks that rank highly by PE and hold all the stocks that rank highly by price to cash-flow and just divide it up like that?

Because sometimes PE outperforms for a decade at a time, and then sometimes price cash-flow performs a decade at a time. And so you … The objective ends up to being, “Well, let’s just avoid being wrong.” Right? “Avoid over-specifying and being wrong.” Right?

Eric Falkenstein:01:03:34Yeah.

Adam:01:03:34But that’s a different question from whether or not you should use a combination of factors to rank, right? So, you’ve got price to cash-flow, and PE, and price to book, and enterprise value, McDonald’s kind of stuff, and you’re just going to sort on all of those five factors and then you’re going to take the stocks with the highest sum of the ranks across all those five factors.

Eric Falkenstein:01:04:00Right.


Adam:01:04:00Well, that ends up being really fragile, whereas the first ensembling approach ends up just, really, you’re just trying to minimize the potential for bad luck. How do you think about that?

Eric Falkenstein:01:04:11No, it’s tricky because … And plus, when you have a lot of factors, you have … I don’t know how many value metrics you have, probably at least a dozen reputable ones. You can find a subset of those that outperform everything. It’s really easy to over fit that and convince yourself that you didn’t over-fit it. I see lots of people do this stupid thing where they go, “Well, first we test and then we look at it in sample, and then we do it out of sample. And we do that again and again until we get this great result.” It’s like, “Well, if you do it iteratively, there’s nothing is out of sample.”


Eric Falkenstein:01:04:58And so, if you’re sitting there and your job as a quant is to find stuff, nothing is out of sample, absolutely, and first the equities where the relevant returns are monthly, they’re just not accruing quickly enough. You can’t test things out of sample. So, I think you just have to … You actually need some humility, and I think … I don’t know. There’s probably a good paper in there where you can show that if you tried an approach to look at, whatever; five metrics for something, it’s much better to glom on to one metric, and that’s where it takes a lot of common sense. Like when I was at Moody’s and we found out that the best metric of earnings for private firms was actually net income. And you might think, “Well, shouldn’t use EBIT, EBITDA,” all sorts of reasons why, but those are easy to gain, kind of. And it was better to just use simple net income and then ignore all those other ones.

So, you look at theory and make sure the denominator can’t go below zero and try to think, “Well, what one’s easier to gain?” So, you use your institutional knowledge of how these factors are constructed as opposed to-

Adam:01:06:19I don’t know. I know I’ve chatted with value managers who have made the case that net income is easy to gain, or-

Eric Falkenstein:01:06:27Sure.

Adam:01:06:27And all these, it really ends up just being a theology more than a science in the end. Right? I don’t know.

Eric Falkenstein:01:06:35Yeah, well … I think it was Kahneman who said that the key is to choose good prejudices.

Adam:01:06:43I like that. I like that. All right, great. Well, I think we hit everything then. This has been really neat. I’ve been looking forward to this in one form or another for many years, so really appreciate you offering your time to chat today. We’ve covered a lot of topics and I think this is going to be a really popular episode with listeners, so thanks again.

Eric Falkenstein:01:07:09Thanks … man. All right. We’ll be in touch. I’ll talk to you some other time. Get Pim on there again, he’s a great guy.

Adam:01:07:15Oh, absolutely. I will. I’m making every effort.

Eric Falkenstein:01:07:18Okay.

Adam:01:07:18All right. Thanks, Eric. We’ll chat soon.

Eric Falkenstein:01:07:20Yeah, bye.

Adam:01:07:21See you.

Show more