Corey Hoffstein and Ben Hunt | PNL For a Purpose

[00:00:00] Welcome to Excess Returns, where we focus on what works over the long term in the markets.

[00:00:04] Join us as we talk about the strategies and tactics that can help you become a better

[00:00:07] long-term investor. Hey guys, this is Justin. On April 30th, we interviewed 24 guests in

[00:00:22] the 12 of our live stream to raise money for Susan G. Komen in conjunction with our friends

[00:00:26] at Spot Gamma. Our guests were some of the smartest market experts we know covering topics ranging

[00:00:31] from value investing to factor investing to macro and options. We are releasing each of the

[00:00:35] interviews in pairs of two over the week following the live stream to bring our guests

[00:00:39] insights to our audience in shorter videos and to continue to raise money for a great cause.

[00:00:44] If you are able to, we encourage you to donate using the link provided alongside each video.

[00:00:49] As always, thank you for listening. Please enjoy our conversations with Corey Hoffstein

[00:00:53] and Ben Hunt. How's it going? Corey, good morning. Good morning. Thank you for joining

[00:00:58] Matt and I on this special day for P&L for a purpose. Absolutely a pleasure. Thanks for organizing it.

[00:01:04] For sure, man. Let me give you a quick intro for those that might not be familiar with

[00:01:08] VWARQs, founder of Newfound Research, quantitative investment firm and research firm,

[00:01:13] creator of the return stacking concept which is offered to investors through multiple ETFs.

[00:01:19] People can learn more about those on returnstacketfs.com. And lastly, the man that's on the

[00:01:24] sole mission to defeat the dad, Bod Crete by rowing 12,000 meters a day. Yeah, something like

[00:01:31] that. Something like that. Trying to preemptive strike at least. So just a quick reminder,

[00:01:39] today's event is to support the Susan G. Komen Foundation. Quick statistic on breast cancer.

[00:01:45] It's the most common cancer among women in the U.S., counting for 32% of newly diagnosed cancers.

[00:01:50] If you can and are able to, we really appreciate people supporting this. You can use the donate

[00:01:55] way right on YouTube and donate right through YouTube. And so it's for a great cause. And

[00:02:00] people like Corey are willing to come on and give their time. And we can learn along the

[00:02:06] way while doing something good. So appreciate that. So Corey, it's going to be a little bit

[00:02:13] rapid fire with you. Let's see if we can do it. We're using your post which is found on your

[00:02:20] website. It's blog.thinknewfound.com. It's 15 ideas, frameworks and lessons from 15 years.

[00:02:27] And what you did with this is you reflected on all of these things that you've learned over

[00:02:34] the 15 years in your career. And so we're going to have to hammer through. Hopefully,

[00:02:38] we can get through all of them. But I highly recommend people go to the

[00:02:43] blog post after and read it because there's so much really good stuff in here.

[00:02:47] 15 ideas in 30 minutes. We're rapid fire. This is going to be lightning round here.

[00:02:53] All right. So the first one, which is you're sort of known for this. Maybe not your tagline,

[00:02:59] but something that you talk about a lot. And risk cannot be destroyed, only transformed.

[00:03:03] Yeah, I love this idea. This is something that came to me in graduate school. So

[00:03:08] I went to Carnegie Mellon's master's of computational finance program. It's

[00:03:12] one of the earliest financial engineering programs ever. At that point, it was all

[00:03:16] about pricing derivatives. Eventually, Wall Street derivatives hiring fell apart and it's become

[00:03:21] more buy side. But at that point, it was all about pricing derivatives. And the constant

[00:03:26] pattern I saw in the homework and the practical work that we did was what we're

[00:03:30] effectively trying to do was, you know, identify, isolate risk, price it, package it and sell it.

[00:03:38] And when I took a step back and looked at what finance really is, it's my view that all of

[00:03:45] finance is really just risk transfer. And it's a question of are you paying the right price

[00:03:51] for that risk? Whether you're talking about investing in a seed stage company,

[00:03:55] buying a public company, going long or short futures contracts that hedge exposures,

[00:03:59] it's all about risk transfer and the price of that risk transfer. And then as I got further

[00:04:04] and further into quantitative modeling, what I saw was that those decisions of risk transfer exist

[00:04:10] in the modeling side as well. These are all trade offs that we have to make when we make

[00:04:16] decisions in our investment process. And there's almost no times that risk is truly ever

[00:04:24] destroyed. There's nothing you do that ultimately destroys that risk. It's just a trade off of

[00:04:28] the risks that you're willing to bear and those that you're not willing to bear or risks that you

[00:04:32] think you're fairly compensated for, that you want to keep or in risks that you're not

[00:04:36] that you'd like to get rid of. And so this is sort of one of those big overarching philosophical

[00:04:40] concepts that stuck with me in my career. So important. Number two and value investors

[00:04:46] can certainly identify with this one. No pain, no premium. They can hit a copy so I can

[00:04:53] get through this. Got any more of the copy there? Yeah, no pain, no premium. Very similar concept to

[00:04:59] a certain degree, which is particularly for investment concepts that get held in mutual funds

[00:05:06] or ETFs that the vast majority of people have access to. You're talking about investment

[00:05:10] strategies that aren't typically exploiting arbitrages in the market. They're exploiting

[00:05:16] hopefully mispricings, either behavioral mispricings or they're tapping into risk

[00:05:21] premia for which you are being paid for holding risk. And so at the end of the day,

[00:05:25] for you to earn that return, you have to be willing to bear that risk. And it's an expected

[00:05:31] return on an ex ante basis. And there are some times that that, you know, premium that you're

[00:05:36] going to earn is not going to offset the risk that you bear. One of the ways I like to think

[00:05:40] about this is for those lower Sharpe ratio strategies. And those are strategies that are

[00:05:44] typically packaged up in ETFs and mutual funds because that's where they can live.

[00:05:49] Point three to point six sharp. You're talking about investment strategies that have to go

[00:05:53] through periods of prolonged drawdowns in my view, to ultimately shake out the non believers

[00:05:59] for you to be able to earn that premium over time. That sort of weak hands pass

[00:06:04] the premium to the strong hands over time. It also means unfortunately there's a large degree

[00:06:09] of faith baked into this. You have to truly believe you can't rent the conviction. You have

[00:06:14] to truly believe in the process and just stick with it because from a statistical perspective,

[00:06:19] we'll all be long dead before we know whether some of these concepts actually

[00:06:24] truly played out the way we expected them to. Such an important point because if you invest

[00:06:29] in something and then you sell after a long period of underperformance, you know, you're

[00:06:33] just probably hurting yourself in most cases. So that's excellent there. What about number

[00:06:39] three? Diversifying cheap data is worth just as much as equally diversifying expensive alpha.

[00:06:44] Yeah, we love alpha in this industry and I always kind of laugh because at the end of the day,

[00:06:48] like for anyone with a mathematics background, alpha just comes from this linear regression.

[00:06:52] Right. It's just happens to be the Greek letter that was chosen. There's alphas and betas,

[00:06:56] but we love alpha even though all it really is is just the intercept term,

[00:07:01] the unexplained returns in a linear regression. At the end of the day though,

[00:07:05] when we think about building portfolios, we should be agnostic as to whether we're adding

[00:07:11] true alpha or some new form of beta to our portfolio. If that beta represents a source

[00:07:19] of return, which we're not getting anywhere else and is uncorrelated to the things we're

[00:07:24] already doing. Right. And it's probably far easier to do. So very simple example,

[00:07:29] if you're an equity investor, it's probably a lot easier for you to add bonds to your

[00:07:34] portfolio than it is for you to add alpha through security selection. Right. Or easier

[00:07:39] to add some form of commodities to your portfolio than it is to add alpha through

[00:07:43] security selection. And I think that idea gets looked down upon, right? Because our goal in

[00:07:49] active management is to always be adding alpha, but I think we shouldn't look past the low

[00:07:53] hanging fruit when it comes to portfolio construction. Diversifying beta is hugely

[00:07:58] valuable and quite often we have much higher conviction in the expected return of beta

[00:08:03] than we do of any source of alpha. This next one seems obvious, but you kind of approach it from

[00:08:09] a different lens and that is diversification has multiple forms. Yeah. So diversification

[00:08:16] is one of those things everyone learns about earlier in their finance career,

[00:08:19] but it typically takes the form of what you're investing in. Right. So we've all heard the

[00:08:22] idea, for example, you can invest in 30 stocks and that will get rid of all the

[00:08:28] idiosyncratic vol and you'll be left with sort of beta component there. And that sort of

[00:08:33] diversification is typically good and you're looking for a trade-off of getting rid of

[00:08:38] idiosyncratic risk you don't want while keeping the idiosyncratic risk that you think you're

[00:08:41] compensated through for alpha. But that's only one form of diversification. So another

[00:08:46] form of diversification might be the process by which you invest. We'll go back to the umbrella

[00:08:53] of value investors, for example. You could have a value investor who takes the very

[00:08:57] antiquated academic approach and sorts on price of the book. You could take a value

[00:09:01] investor who takes a much more modern machine learning driven approach. They are probably

[00:09:06] going to be somewhat correlated, right? Tied to the fundamental tenants of value investing,

[00:09:10] but in the short term, their returns can look very different. And if you have several

[00:09:16] approaches by which you think work and you don't have a higher conviction in one approach

[00:09:20] versus another, then you should diversify. Similarly, and this is a passion area for me

[00:09:27] and anyone who knows me knows I'm absolutely obsessed with this concept. I'm Don Quixote

[00:09:32] tilting at windmills. Diversifying when you make investment decisions is also hugely critical.

[00:09:38] It's something I call rebalance timing luck. As a very simple example here, let's say you

[00:09:43] are a value investor that refreshes your portfolio once a quarter. You might end up

[00:09:49] with a very different portfolio if you rerun your screens mid quarter than if you run them

[00:09:55] end of quarter. And you can run the exact same screens and end up with very different portfolios.

[00:10:00] And in coming up with very different portfolios, you will end up with very different returns.

[00:10:04] And so the question is, is that sort of randomness something you want to bear? Well,

[00:10:10] it's uncompensated randomness. And so why wouldn't you, for example, take half your

[00:10:16] portfolio, rebalance it mid quarter and take half your portfolio and rebalance it end of quarter

[00:10:20] and get rid of that timing luck? So that's a whole other axis of diversification that

[00:10:26] people typically don't think about but can play a profound role in the impact on long-term returns.

[00:10:34] Let's clarify. You're not the Don Quixote tilting at windmills. You're the Sancho Panza

[00:10:40] statements about the industry here. I appreciate that. Thank you.

[00:10:43] Okay, the philosophical limits of diversification. Talk about this.

[00:10:48] Yeah. So this is another one where people again, it goes back to the sort of maybe risk can't be

[00:10:52] destroyed only transform. People are constantly looking to keep diversifying their portfolio and

[00:10:58] they want that perfectly smooth lineup. And the point I like to make is if you could build

[00:11:04] a portfolio that you diversified away all the risks, you end up in one of two places. One is a

[00:11:12] very expensive risk-free rate or two, you found an arbitrage. I'll hope for you it's the latter,

[00:11:19] but that's very unlikely when you're talking about diversifying with very common investments.

[00:11:24] Right? So at a certain point, you can't create a perfectly smooth lineup. You have to have

[00:11:30] some of those peaks and valleys and some of that roughness in your P&L stream because you

[00:11:36] are for the most part again, talking about the investors who are investing in things like

[00:11:40] ETFs and public securities and mutual funds and lower sharp strategies. You are bearing risk

[00:11:45] and that risk is going to manifest in some manner, whether it's day-to-day volatility or

[00:11:51] big events that occur. And that's going to create drawdown in your P&L. And that is just

[00:11:57] a natural component of expecting to earn a return. If you don't expect to have any risk,

[00:12:03] why would you earn something higher than the risk-free rate, right? Short term T-bills.

[00:12:07] So again, we can't just manage to diversify away all the risk without also potentially hurting our

[00:12:14] return. So that's the intended bets. What about the unintended bets and why can those be the

[00:12:20] ones that blow you up? Yeah. So this is an area, again, I think when people look back on

[00:12:26] the history of financial catastrophes or manager blow-ups, it's often not the things the managers

[00:12:32] were trying to do that get them in trouble. It's the things they didn't expect. It's the

[00:12:36] unintended hidden bets in their portfolio. And that's, I don't know, I don't want to say it's a

[00:12:43] tautology because it's not maybe not technically a tautology, but it makes sense, right? It's

[00:12:47] the things you're unaware of that are ultimately going to cause the greatest catastrophe. And so

[00:12:52] I think it's our job to constantly be on the lookout for those things. So as an example,

[00:12:58] right, we talked about the different forms of diversification, that process diversification or

[00:13:03] that rebalance timing diversification can be killers to your P&L. There's a story on the

[00:13:11] timing one that I'll tell about research affiliates back in 2008, what was called the

[00:13:16] immaculate rebalance. At that time, research affiliates was only rebalancing their portfolio

[00:13:21] once a year and they happened to rebalance in March 2009, which was the perfect time for

[00:13:27] them to rebalance. And I think they created 900 bips of alpha that year. Had they rebalanced

[00:13:32] in September instead of March, right, just arbitrarily a different quarter, they would have

[00:13:38] underperformed the S&P by several hundred basis points. And that has obviously not only a

[00:13:42] profound impact on the long-term returns of that strategy, that fundamental indexing strategy,

[00:13:47] but I would argue probably would have changed the trajectory of the firm at large, right?

[00:13:52] Probably would still be a very successful firm, but maybe not as successful. And so those are

[00:13:57] some of the unintended bets that as a PM or an investor, those are small things that can really

[00:14:04] ultimately blow up your performance unless you constantly are trying to find what am I exposed

[00:14:09] to that I didn't think I was exposed to. Kind of makes me think of like if the immaculate

[00:14:14] reception hadn't happened in football, which Harry Bradshaw have gone on to have the same

[00:14:18] career. What about its long short portfolios all the way down? How very Buddhist of you.

[00:14:24] Yeah, this is one I stole what's the phrase it's turtles all the way down from philosophy.

[00:14:31] Dr. Seuss.

[00:14:32] Yeah. The concept here for me is thinking about any portfolio change can be thought of as a

[00:14:38] long short portfolio. So very simple example, if I've got say a 60-40 portfolio and I want

[00:14:45] to think about tilting that to a 70-30, that is functionally equivalent to holding my 60-40

[00:14:51] and adding in a long short portfolio that's long 10% stocks and short 10% bonds. Similarly,

[00:14:58] any active manager can be thought of the same way. An active stock picker is just the market

[00:15:04] plus a long short portfolio where you're long the things that they are above market weight and

[00:15:10] short the things that they are below market weight. And this is really important because it

[00:15:14] helps distinguish what their active bets are and the true active risk they're taking and

[00:15:20] isolate it from beta. And so thinking through portfolio changes, thinking through active

[00:15:27] managers, thinking through different exposures through this lens of well, it's all just long

[00:15:31] short portfolios that are being added together at one point in time or over time can be a

[00:15:36] really useful framework for isolating some of these effects. As an allocator, that's one

[00:15:40] of my favorite ideas you've ever explained. I appreciate it. Just for the record. I really

[00:15:45] love that idea. The more diversified a portfolio, the higher the hurdle rate for market timing.

[00:15:52] Yeah. So I will say I was a big market timer earlier in my career. And one of the things you

[00:15:58] find is that as you add more diversification to your portfolio, as you add more uncorrelated

[00:16:06] sources of return, you're the accuracy with which you have to be able to time switching

[00:16:15] between those different diversified sources of return continues to go up. And so again,

[00:16:21] when we think through this lens of what's better finding a source of alpha or finding

[00:16:25] another cheap diversifying data, what's better adding more diversifying beta or trying to come

[00:16:32] up with a more accurate market timing signal? You know, again, I think all the evidence suggests

[00:16:38] more diversification tends to work in our favor versus our ability to increasingly

[00:16:45] add accuracy. I am a lot more confident that I can find another diversifying asset class or

[00:16:51] strategy than I am in my ability to consistently improve my ability to time markets. Well, it's

[00:16:58] never too late to go try, try again. That's right. Katie Stockton was just talking about

[00:17:03] this an hour ago. Certain signals are only valuable at extremes. What's that mean?

[00:17:09] Yeah. So I think a good one here, we'll go back to value stocks, for example. When we look

[00:17:14] at value stocks, we can look at the growth, the spread, the value spread between growth stocks

[00:17:20] and value stocks. And we've seen them get to all time highs, pass all time highs. But well

[00:17:26] before that, people were starting to say, hey, it looks like value is cheap. And then we saw

[00:17:33] value get cheaper and cheaper and cheaper and cheaper. And with some of these signals,

[00:17:37] they're very coarse signals. They're not highly precise. And so there's a whole bunch of

[00:17:43] reasons that we might be able to explain why these coarse signals at one degree or two

[00:17:50] standard deviations aren't really necessarily giving us much power. They are potentially,

[00:17:58] that could be explained by noise. It could be that we haven't appropriately accounted for

[00:18:04] industry differences or measuring value in certain ways or whatever it is. But at a

[00:18:11] certain point when those values, when those measures start to get to real extremes,

[00:18:15] the probability that they are explainable by noise or explainable by a factor that we've missed

[00:18:21] starts to diminish. And it becomes much more likely that it is the true thing we're trying

[00:18:26] to measure has actually gotten out of line. So value spreads between growth and value stocks

[00:18:32] at two standard deviations, maybe not that interesting. At five or six standard deviations,

[00:18:37] suddenly you're saying, okay, this is a signal I need to pay attention to because

[00:18:40] it's no longer explainable by all these potential things that could be causing this deviation.

[00:18:47] The poet philosopher Ron Swanson once said, never half-ass something you can whole-ass.

[00:18:52] Corey Hofstein once said under strong uncertainty,

[00:18:54] Hafsies can actually be the optimal decision.

[00:18:57] Yeah, Hafsies probably doesn't sound like something a quant would say a lot.

[00:19:00] But Hafsies has been a driving factor of my career. So an example I will give here,

[00:19:06] during the smart beta wars of the early 2010s, there was a question as to whether it was better

[00:19:13] to take what was called the integrated approach or the mixed approach. The idea here being if I have

[00:19:18] a value signal and a momentum signal and a quality signal, is it better for me to

[00:19:23] find the stocks that have the highest intersectionality of those signals? Or is

[00:19:27] it better for me to build a value portfolio, a momentum portfolio, a quality portfolio,

[00:19:32] and equal weight those portfolios? And you had academic proponents and practitioner components

[00:19:38] on both sides making phenomenal arguments. Just as an example, AQR was on the integrated side,

[00:19:44] Goldman Sachs was on the mixed side. So we're talking about intellectual powerhouses here who

[00:19:49] were disagreeing. And as far as I could do my own research, rely on the practitioner and

[00:19:55] academic research of others, I could not justify one approach over the other.

[00:20:00] And so my answer was habsies. I knew I wanted the factor exposure, but I had uncertainty as to

[00:20:07] which and no high degree of confidence as to one approach over the other. And so habsies

[00:20:13] ended up being the way to go. And I think all too often we feel compelled to choose something

[00:20:19] when in reality habsies is a perfectly valid option of what we can do. If we don't have one

[00:20:25] conviction of one particular signal or one particular portfolio design approach over another,

[00:20:30] habsies is very powerful. What about always asking what is not just the next question,

[00:20:41] but what is the trade? What is the trade? So this one I am not a big lover of macro.

[00:20:50] And maybe this I'm going to show some bias here, but I get very frustrated when I see

[00:20:55] a lot of macro proponents on Twitter talking about macroeconomic signals and they say things are

[00:21:02] wrong. The world is wrong. And you hear that a lot. And what I realized was when you tried to

[00:21:08] press someone as to what was wrong, why were markets wrong or why is the world wrong?

[00:21:12] The most important question I could really ask is all right, if the world's so wrong,

[00:21:16] what's the trade? Right? Because if the world is wrong, there should be some way for me to

[00:21:20] profit from it. And if they can't tell you precisely how to profit from it,

[00:21:24] then their view isn't really worth much. So as a very concrete example of this,

[00:21:28] years ago we saw a whole bunch of people talk about Greek sovereign debt having a lower yield

[00:21:36] than US sovereign debt. Right? Sort of in the claim was, oh, isn't this crazy? US debt is

[00:21:42] now the high yield asset of the world. Right? The problem is what that misses is the fact that

[00:21:48] yield is not really the measure. You're getting paid a coupon in a certain currency. Right? So

[00:21:52] if you ask what's the trade, well, the trade would be go long. Right? Or go short the treasuries

[00:22:00] and go long Greek debt and capture the spread. But if you actually accounted for

[00:22:04] currency differences and tried to neutralize that currency exposure, you would have found

[00:22:09] actually on a currency adjusted basis, the yield of Greek debt was substantially higher.

[00:22:15] And if you measured Greek debt versus a more relevant benchmark, like what maybe German

[00:22:22] bonds or just Eurozone bonds in general, you found that there actually was a significant

[00:22:27] credit spread there. So the point is when you try to get this Macrash story that, oh,

[00:22:33] that seems wrong, when you try to dig into the trade, it can actually make the Macrash

[00:22:37] story fall apart. Number 12 is the trade-offs between type one and type two errors and how

[00:22:44] they are asymmetric in nature. Yeah. So we are obsessed, particularly in academic finance

[00:22:52] with trying to avoid false positives. Right? We want to find these alpha signals and we want

[00:22:58] to say we have 95% confidence in the signal. And I think what that misses is that there's

[00:23:05] this asymmetric trade-off that if you think about trading a strategy that doesn't actually

[00:23:12] have any output to it, what is the cost of that? Well, unless I think there's a reason

[00:23:18] that I'm finding that strategy that leads to adverse selection, I would argue it's just noise

[00:23:24] plus trading costs. Right? But on the other hand, what is the cost of missing a false

[00:23:32] positive? Like if there was something that actually has alpha, but it didn't meet my

[00:23:37] threshold, false negative, then I'm missing out on alpha. And so Marcos Lopez de Prado talks

[00:23:47] about this quite a bit that we're so obsessed with this 5% certainty threshold in financial

[00:23:53] publications. But actually if you think about relaxing that constraint because of this

[00:23:59] asymmetry, in one case we're just getting noise minus trading costs. In the other case,

[00:24:04] we're missing out on true alpha. Right? We would actually trade a lot more strategies that we have

[00:24:10] less certainty in because of that opportunity cost of missing out on the alpha. I think this next

[00:24:17] one is very important and something that we all can identify with as being in the markets

[00:24:22] and working with investors. But the point you made is behavioral time is decades longer than

[00:24:27] statistical time. Yeah, I 100% stole this one from Cliff Asness. When you work in quant finance

[00:24:35] or academic finance and you're working on these investment strategies, you build these

[00:24:41] back tests that can span decades. And often we're drawing these back tests on log charts

[00:24:47] with thick crayon lines and they look like straight lines up. And even in those decades,

[00:24:52] there are drawdowns. You go, yeah, but that's just what happens. This is a 0.4,

[00:24:56] 0.5 sharp strategy. You expect there to be a lost decade. So be it. Living through a lost decade

[00:25:04] and keeping clients through a lost decade is very, very, very different. Right? So it's easy

[00:25:09] for me to look at a back test and go, yep, that would have been tough moving on with my

[00:25:12] life. Whereas in reality, behavioral time is like dog years. Asking someone to sit with you

[00:25:19] through a three year drawdown in an active strategy, particularly if they don't have a

[00:25:24] high degree of confidence as to how the strategy truly works and they don't have the conviction

[00:25:28] to stick with it. Again, earlier I said you can't rent conviction. That's going to feel like 21

[00:25:33] years of a drawdown to them. And so I think for those of us who are not just managing money,

[00:25:39] but bringing product to market, we have to be very aware and running our businesses.

[00:25:45] A decade long drawdown might be totally possible for any active investment strategy

[00:25:50] that we're putting into an ETF or mutual fund. And yet we have to understand from a client's

[00:25:55] perspective, that is non-tenable and we will lose a tremendous number of clients. You look back at

[00:26:01] someone like Warren Buffett, right? Probably the most ingenious thing he did was not run

[00:26:05] a public fund. If Warren Buffett was running public money, he probably would have lost all

[00:26:09] of investors in the late nineties. Right? And so you just have to be very aware like these

[00:26:14] processes they go through long periods of drawdown. Behaviorally, that's really tough

[00:26:19] to stick with. So I'm going to jump to number 15 because you brought up back tests, but the point

[00:26:24] you made is a back test is just a single draw of a stochastic process. Yeah. So look, markets are

[00:26:31] random. I think Mike Green has a great quote and he might even attribute it to someone else,

[00:26:36] is all markets are is just a log book of where prices trade. Right? But there's so

[00:26:42] many things that could happen in the world. There's so many ways the world could have

[00:26:45] unfolded that when we run a single back test, all we're really doing is seeing one potential draw

[00:26:54] of a potentially infinite set of worlds that could have happened, trades that could have

[00:26:59] happened, different market prices that could have occurred. And so I think it's just a

[00:27:03] good reminder that we're trying to build certainty over time, but we're missing the

[00:27:08] breadth of all the parallel universes that could have happened. And so to me,

[00:27:11] it's a reminder not to emphasize like to me, a back test never confounds a strategy works.

[00:27:18] A back test only sort of you can't accept the null hypothesis. You only fail to reject,

[00:27:25] right? You just fail to reject it didn't work and you just need to be aware of all

[00:27:31] the randomness that could have occurred. And I think if you run a good back testing engine,

[00:27:34] you try to inject some of that randomness to see what happened if that company never

[00:27:39] went public. What happened if I didn't trade on that date? What happened if I didn't have

[00:27:43] that data in time? All those sorts of things. What happens if that whole month never existed,

[00:27:48] right? And you can start to manipulate and inject randomness in all these different ways

[00:27:52] to try to create a more stochastic view of what your return stream would have looked like.

[00:27:59] This last one was basically a bonus, but the market is usually right.

[00:28:04] Yeah, I guess over my career, I went from a very arrogant young person who says the market

[00:28:09] is wrong and there's tons of alpha to be had to saying the market is pretty efficient.

[00:28:16] There are certainly cases where it's wildly inefficient. I think we all just live through one

[00:28:20] of the post pandemic bubble in meme stocks, whereas easy to say these valuations are absurd,

[00:28:28] not easy to trade though, right? Lots of people lost a lot of money trying to short

[00:28:33] against that. And so, but in the long run, I think again, it maybe ties back a little

[00:28:37] to asking what's the trade. When you start seeing things like, oh, U.S. treasuries are trading at a

[00:28:42] yield that's higher than Greek sovereign debt, right? Like is the whole world lost its mind?

[00:28:48] Is that a rational conclusion that global capital markets are so broken that U.S.

[00:28:55] treasuries are trading at the wrong price or is it more likely that I'm missing a piece of

[00:29:01] the story? Is it likely that European stocks are trading at a discount to U.S. markets

[00:29:08] because they are profoundly cheap and the world, the entire world's capital markets has missed

[00:29:14] the opportunity? Maybe. Or is it that we're failing to adjust for things like sector

[00:29:19] differences and profitability and acknowledging regulatory differences and legal differences

[00:29:26] and cultural differences that lead to divergences in economic growth?

[00:29:33] Again, I go back to, I think where my view has changed is I've stopped looking at things

[00:29:37] and saying the market's broken and I've started looking at things and saying,

[00:29:41] what part of the story am I missing? And I think that's helped sort of reframe how

[00:29:45] I approach markets. Corey, you came ready to play,

[00:29:49] delivered in spades. Thank you very much, sir. This has been great. Really appreciate it.

[00:29:52] Really appreciate you guys having me. Ben.

[00:29:57] All right, all right, all right. All right. We got the band back together.

[00:30:01] Got the band back together. Good to see you, man.

[00:30:05] Well, this is fantastic. We're all the way through to the 3 p.m. Mark. Jack,

[00:30:08] do you believe you're still alive at 3 p.m. today? I mean, I'm still going. I actually

[00:30:12] got some, I enjoyed a nice lunch of pretzel goldfish a second ago. So I think any

[00:30:16] dieticians in the audience will appreciate that that was probably successful for me. So

[00:30:20] I'm still I'm still going to take issues right now. Yeah, nature's perfect food.

[00:30:25] Goldfish is perfect. Give a man a goldfish and he'll fish for a day.

[00:30:30] How long when did you when did you kick this off, Jack?

[00:30:34] 8 a.m. So we've been amazing. We've been going for a while now.

[00:30:37] We haven't been going the entire time. We've been rotating in and out.

[00:30:39] But yeah, we've had a couple of tech issues along the way. But for the most part,

[00:30:43] we've been able to resolve them quickly and we're still going. Ben,

[00:30:46] we'll make it to the end. Very nice. Very nice. Well, I'm here to do my part. So thanks for

[00:30:52] just Jack. Appreciate it. It's great. Just a reminder to every cause. Yeah, the wonderful

[00:30:58] cause and just a reminder, if you haven't given take a look somewhere on the page around,

[00:31:03] depending if you're watching on YouTube, Twitter or LinkedIn, there is how to give.

[00:31:08] There's a button for the Susan G. Komen Foundation that's right here on your screen.

[00:31:13] So send the donations in. We're doing this for a reason now.

[00:31:17] With us right now, founder Epsilon Theory, former hedge fund manager, all round narrative expert,

[00:31:24] best hunt brother since the hunt brothers.

[00:31:27] Mr. Ben Hunt, thank you for joining us today.

[00:31:29] It's good to be here. Good to be here. Yeah. Nelson and bunker. They were they were they

[00:31:34] were the original hunt brothers. Yeah. I always had a soul for their sister Rose, though.

[00:31:41] I think she was the smart one. She was one who did the hotels in Dallas.

[00:31:45] Well, you know, the hunt sister deserves her own her own series at some point.

[00:31:50] We're going to do a little bit of a breaking news type thing here for you today.

[00:31:53] We want to kick this off and talk a little bit about the inflation map versus the inflation

[00:32:00] territory right now, because everybody's talking about CPI PC and all those fun things. What's

[00:32:06] the difference here, Ben? What's the the map versus the territory and what's up with inflation?

[00:32:11] Yeah. Well, so so look, this distinction between the map, you know, our measurements

[00:32:18] and the like in the territory, I think is so helpful when we're thinking about

[00:32:23] issues like this, because what what we've built is not just in economics and it's not just

[00:32:29] around inflation. What we've built in our whole society, we all have our jobs and our

[00:32:39] focus and our attention. It's all on maps and very little on the actual territory. I get it.

[00:32:49] Right. I mean, you go to school, you get an advanced degree,

[00:32:56] you do a lot of research on a topic. You're trying to understand it and to understand it,

[00:33:03] to communicate it. You're looking for indicators. You're looking for measurements.

[00:33:07] Again, it's not just in economics and not just around inflation, but our whole society.

[00:33:13] We look at measurements. We don't look at the thing itself.

[00:33:18] We look at measurements about sports, right? We can rattle off, you know, winds over replacement.

[00:33:26] We can, you know, saber metrics, stats. We gamble on it. We focus on it. It's not

[00:33:34] as very different from just watching the game. We're just watching the game.

[00:33:41] We try to calculate everything in our lives. Polls on this, what is politics, what is a market?

[00:33:52] And at the, I've been thinking about different ways to talk about this and one of them is

[00:33:58] the distinction between map versus territory. You want to get from here to there. You want

[00:34:03] to understand the actual land or property. We spend all our time studying the map and we

[00:34:10] make these incredibly detailed maps. Some maps are one aspect of the territory. Some maps are

[00:34:16] of other aspects and we confuse the map for the actual territory. That's one way to think

[00:34:21] about it. The other way to think about it, I want to suggest here is we have this metaphor

[00:34:28] in our heads, our mental model of things like markets as a machine, which is a simplification

[00:34:37] of the way to think about markets. And what I mean by that and well, Ray Dalio is maybe the

[00:34:44] one who's most famously promoted this idea, but it's not Ray. It's not just Ray. It's all

[00:34:51] of us. It's everything we read about in the Wall Street Journal, everything we watch on CNBC.

[00:34:57] We talk about the economy. We talk about markets as if they were a machine with levers to pull,

[00:35:06] with gears that click in, with moving parts that function mechanistically.

[00:35:14] So how many times we talk about, well, the Federal Reserve will pull this lever we

[00:35:19] call interest rates and it'll raise it 25 basis points. And then that will impact the

[00:35:25] economy in these mechanistic ways. Or, oh, if they pull this other lever and lower interest rates,

[00:35:35] there's a mechanistic effect on the economy in XYZ. And we talk about everything that way.

[00:35:40] We talk about inflation that way. We talk about wages. We think of it as a machine,

[00:35:47] well, with these moving parts that are related in knowable ways. And that's just not true.

[00:35:54] It's another way. It's not a map of the territory, but it's another mental model

[00:36:00] we use to create abstractions of certain elements of the economy to have it make sense

[00:36:07] to us, more easily make sense to us. I get it. It's how we thought about the world,

[00:36:16] frankly, since the Industrial Revolution. When do we start talking about the world in terms

[00:36:22] of a machine, in terms of abstractions of pulling levers and if this happens then that

[00:36:28] happens. And it all happens around as you make the Industrial Revolution, when we started

[00:36:34] turning our own lives and labor into cogs of a machine. It's not just in our work,

[00:36:42] but it's also in the way we think about the world. Now, the problem with this is

[00:36:48] that's not the economy. The economy is not a machine. What the economy is in the American

[00:36:57] economy is millions of households and corporations and individuals making decisions

[00:37:07] about what they buy, what they make, how they value their labor, how they value,

[00:37:14] you know, how they price stuff, what they're willing to pay. That's the economy.

[00:37:20] That's the economy. And when we have this mental model of a machine and we have a

[00:37:28] mental model of levers and pulleys and as you just call it, a map, we think in terms of,

[00:37:34] oh, this is this module of the machine we call inflation. And here are the

[00:37:42] mechanistic aspects of this and here's how we measure the gauge. You know, what's the

[00:37:48] value on that reading, Scotty? You know, for our inflation reading as we understand

[00:37:54] the machine of the economy. And I say, I get it, we all do it. There are advantages to this,

[00:38:02] but there are enormous disadvantages to it because we lose sight of what the actual economy is.

[00:38:08] And what the actual economy is are these decisions, the behaviors of households and

[00:38:16] corporations in how they buy and sell and consume. That's what the economy is.

[00:38:23] In that world, in the real world, inflation is, I think prices of stuff is going to be higher.

[00:38:37] That's what it is. That's all it is. And once that thought, once that perception of the

[00:38:47] world that prices are going to be higher, so I need to charge more for my labor

[00:38:54] or price is going to be higher so I can charge more for whatever it is that I make.

[00:39:00] Price is going to be higher, so I need to worry about that.

[00:39:06] Once that's in our heads of actual real world decision-makers, it sticks.

[00:39:12] And we can talk about raising interest rates or lower inflation rates and what that does to the

[00:39:18] price of money, which is a really important aspect of all that decision-making. What's the

[00:39:23] price of money? But ultimately when we're talking about decisions, we're talking about

[00:39:29] inflation, the territory, the real world, it's what is in our heads. And I think that

[00:39:39] when we're talking about this measurement of inflation or that measurement of inflation,

[00:39:44] we lose sight of what is inflation really. Now again, I'm not saying anything that's

[00:39:53] crazy. When Ben Bernanke, God bless him, talks about how the most important thing for

[00:40:02] understanding inflation is inflation expectations, he's really, really wrong. He's wrong.

[00:40:09] He's right. He's 100% right. I mean, this was actually Bernanke's main academic contribution

[00:40:17] to the field that if you're going to think about inflation, we can take a monetarist approach,

[00:40:25] a Friedman-esque approach. Inflation is always a monetary phenomenon. And that's right also,

[00:40:31] but only right as a tautology, as something that is correct by definition. Yeah, of course

[00:40:38] it's a monetary phenomenon. That doesn't get you anywhere. Inflation as being our expectations,

[00:40:46] our human expectations, that gets us somewhere. It's a more accurate reflection of what inflation

[00:40:53] is, what the economy is. But then of course it goes off the rails because then you start,

[00:40:59] well how do I measure inflation expectations? And so the way you measure inflation

[00:41:05] expectations is, oh there must be a price for that somewhere. Yes, look at five-year forward,

[00:41:12] five-year tips as my measurement of inflation expectations. And that's not, it's not

[00:41:22] measurement of inflation expectations, it's measurement of the maybe inflation expectations

[00:41:29] of the people who actually trade interest rate swapshint contracts on Wall Street.

[00:41:34] Let me assure you that is not reflective of the overall economy, but this is the way we've built

[00:41:42] our world, that even if we can conceptualize what it is, which is expectations and the

[00:41:49] behaviors and decision-makings of real people, we immediately lose sight of that and start

[00:41:56] looking for a gauge or a measurement that we can actually make of that. So long introduction,

[00:42:05] but it's such an important thing because all this argument over oh is it mean-trimmed PCE

[00:42:12] or annualized three-month CPI core? It all misses the point. Inflation is expectations

[00:42:25] of households and corporations, of how they value their labor and how they value their

[00:42:35] goods and services and whether they think prices are going up. That's it.

[00:42:42] And when you think about that, you think inflation is going to be higher

[00:42:45] for longer than people expect, correct? Yes, right because I live in the real world.

[00:42:54] I live in the real world and then this is what gets so frustrating over arguments over

[00:43:00] this data series or that data series, this map, that gauge, this gauge. We live in the

[00:43:07] real world people and I think about myself, right? Do I expect the price of everything to be

[00:43:22] higher? Yes, I do and once you expect that the rational reaction is I got to get ahead of that.

[00:43:31] I got to get ahead of that. And again this is not crazy talk. This is like what Ben Bernanke

[00:43:40] was talking about when he became Fed Chair is that we need to focus on inflation expectations

[00:43:46] then we get off into academic ease about how do you measure it. But the basic idea is absolutely

[00:43:52] right and the corollary to this, he did his research because he's looking at Japan because

[00:43:59] Japan is what happens. There are two very persistent things. When you let the inflation

[00:44:09] genie out of the bottle and everyone expects prices to go higher that sticks. That really

[00:44:15] sticks. The other thing that sticks is when you think that prices are always going to go lower.

[00:44:21] That also sticks and that's what we had from the, that's what Japan had for 40 years

[00:44:28] and so their big issue was well like you know how do we break deflationary expectations

[00:44:36] and what breaks these expectations, the only thing that breaks these expectations is a really

[00:44:43] to use the technical term big ass shock. Just an enormous shock to the system. That's what it

[00:44:50] takes to break these expectations. What broke the 1970s expectations of inflation? Just a

[00:44:59] horrible recession. That's what it takes and interest rates at 15-16 percent. That's what it

[00:45:08] took. What did it take to break inflation expectations in 2007? A nationwide crash in

[00:45:23] home prices and so what that did, that big ass shock of your house is now worth half what you

[00:45:31] thought it was. That you're underwater in your home. You owe more on your home than it's worth

[00:45:39] that created enormous deflationary expectations in the United States. Enormous. We became like Japan

[00:45:50] where whatever it was that the Fed did here, here's free money. It didn't matter.

[00:45:57] We couldn't get inflation even if you're saying the price of money is nothing, is free and then

[00:46:06] we had the COVID shock and that shock was we're going to do helicopter money. We are going to

[00:46:14] rein trillions of dollars. We're going to give it away. We're going to literally give it to

[00:46:20] households and corporations. You don't have to pay it back. We're going to give away

[00:46:25] trillions of dollars and that broke the back of the deflationary expectations and now we're

[00:46:32] back to inflationary expectations and the only thing that breaks it, Jack, the only thing that

[00:46:39] changes this is a big ass shock going the other way. We're going to have to have a nasty recession

[00:46:45] and we're going to have to have the price of money a lot higher than it is today

[00:46:49] to break the expectations we all have that we need to be charging more for our stuff.

[00:46:58] Whether our stuff is our labor or whether our stuff is a good or service that we provide.

[00:47:07] I wish I had a better answer but that is the answer.

[00:47:15] Do you want to make a comment on because I think what just happened with

[00:47:18] submission, I love this.

[00:47:22] Trying to decide how much I would not derail this but take this in the

[00:47:25] what just happened with the Bank of Japan because you've been talking about this too.

[00:47:28] I see it with the ET Pro people. What just happened with Bank of Japan?

[00:47:34] Well, the Bank of Japan, they've been trying to get their cut. Japan is a different animal

[00:47:47] than the United States because Japan is dying and I mean that in the non-pejorative just

[00:47:53] clinical sense. They're dying. They're dying. I don't know any other way to say it than to say

[00:48:03] that. There is no growth from population as there is in the United States. Japan is dying.

[00:48:18] So Japanese monetary and economic policy is like it's hospice care is what it is.

[00:48:26] Over a long very long period of time but there what they've been trying to do is to try to

[00:48:37] do anything to get out of the trap of saving. They save too much. How do you

[00:48:44] how do you create some inflation and some investing?

[00:48:48] And the problem is you want to do it organically. You want to have real growth

[00:48:52] even against a backdrop of shrinking which is what they're doing.

[00:49:00] The problem is if you have inflation that comes in from the outside

[00:49:05] and you know it's one of these old stories you can it's called Triffin's Trilema or the

[00:49:10] Trilema right? You can't control everything in your economy if you're open to the

[00:49:16] rest of the world and so something yeah you know you can either try to maintain your interest rates.

[00:49:25] You can try to maintain your balance of trade or you can try to balance your currency

[00:49:33] and you can probably balance you know you can probably manage two out of those three

[00:49:38] but you can't manage all three. Can't manage all three. So Japan has said we're going to

[00:49:45] manage interest rates and we're only slowly going to let them go up but if you're doing that you

[00:49:54] can't it's hard to manage the risk and so Japan depends on being an exporter.

[00:50:01] Japan depends on keeping interest rates low and you can't manage that.

[00:50:06] Something's got to give on your currency. This was happening.

[00:50:11] That's what's happening. Yeah this happened before. The last time this happened right we got everyone

[00:50:22] together at the Plaza Hotel and basically all the you know Europe, the U.S., Japan said okay

[00:50:29] we're basically going to fix or have a loose peg of our currencies to each other and just by

[00:50:36] saying that and committing to that you kind of got them to where you wanted to be and be stable.

[00:50:42] This is mid 80s right? Yeah this is early to mid 80s.

[00:50:46] Something like that. 85. It's a you know something lasted 40 years. It's pretty good.

[00:50:54] Well all of that's breaking up now. All that's breaking up now because we're

[00:50:59] in an inflationary world particularly in the United States which is the

[00:51:03] you know the economic engine that matters. So that's the problem for Japan.

[00:51:12] They're a strong country but they're a shrinking dying country and you can't control it all

[00:51:22] and so they've got a real problem with their currency. They've got a real problem.

[00:51:27] I don't know how you get out. It's really interesting to like step back and see these

[00:51:31] kind of completing inflation story narratives, how they're playing out around the world and

[00:51:37] just even the problems on the doorstep and on the front page of the most popular paper in Japan

[00:51:45] versus the Wall Street Journal are treating these as two different same terrain,

[00:51:49] two different maps. And they're crossing in two different directions right? I mean

[00:51:56] it's they have a very different, Japan has a very different monetary and economic

[00:52:05] task ahead of them than the U.S. does. U.S. has all the advantages in the world.

[00:52:11] Big problem for the U.S. right now is politically it's impossible to generate the

[00:52:18] pain that's necessary to put the inflation genie you know well back into the bottle.

[00:52:24] And that's rough right? Because if you're not willing to take the political pain

[00:52:35] then what you end up doing is you end up papering it over which is you know it's what we're doing

[00:52:43] papering it over. It's fine I mean it's manageable right? If you're in a position

[00:52:53] where you have financial assets that can also go up in nominal price like if you're rich,

[00:53:01] the rich do fine in this inflationary environment. They do absolutely fine.

[00:53:08] The non-rich do not. The middle class does not. The retired and the old,

[00:53:18] the old non-rich do not. They do really poorly and so what the government has to do

[00:53:26] because they're doing poorly is we've got to give them more money forgive student loans

[00:53:35] do a cost of living adjustment on you know insurance retirement accounts meaning social

[00:53:42] security do all of this and there's no taxing to make up for that.

[00:53:51] Okay we've crossed that bridge we've snipped that cord so long ago there's no relationship

[00:53:57] now between taxing and spending. So taxation if there's no relationship what is taxation

[00:54:04] for? Taxation is for whatever conception of justice the ruling political party has at

[00:54:11] the time. That's what taxation is for it's for to satisfy a conception of justice

[00:54:17] and spending is to bread and circuses man and you know to keep to keep the

[00:54:25] keep the the economic pain from being felt by voters but just like Japan you can't control

[00:54:35] everything right? I mean at the same time in an open economy so right now we have a

[00:54:45] a deficit that is insurmountable and increasingly difficult to service and you'll hear a lot of

[00:54:56] it come say well that doesn't matter the the deficit doesn't matter because what you're paying

[00:55:01] on the debt you're paying to ourselves and that's exactly right but you're paying it to

[00:55:07] rich guys you're paying it to rich guys you're paying to the people who own the

[00:55:12] the debt of the United States government. It's just it's redistribution but in the way that people

[00:55:21] don't think of redistribution it's not from the rich to the poor it's from

[00:55:26] you know everyone particularly the middle class people who actually are paying taxes

[00:55:32] to the rich it's that redistribution and add the tax cuts which I'm sure will be renewed

[00:55:41] you get that and then you get other taxation proposals at least that are just used for to

[00:55:47] satisfy some sense of justice like you know a cap gains tax of 45 percent or whatever

[00:55:55] whatever bizarro proposal the White House is floating. I don't know man it's it's

[00:56:04] it's it's when these relationships get get get get snipped and cut when there's no relationship

[00:56:11] between taxation and spending when the inflation genie is totally out of the bottle but everyone

[00:56:17] says no no no it's fine that's when um enormous dislocations build and build and build until

[00:56:27] they break. Yeah I wish we could uh I wish we'd go on for a while about this because

[00:56:32] this is really interesting stuff unfortunately we're like less than less than two minutes to go

[00:56:35] and Matt will not Matt will actually not have notes this time unlike our breaking news episodes

[00:56:40] although I did threaten Matt that he may I may need him to have notes for the entire 12 hour

[00:56:43] live stream at the end um yeah sorry guys you got me you got me wound up on this I mean

[00:56:50] it was great I get I get wound up because I just I just want to well I had that one when

[00:56:56] you know like today you know wages are you know increasing by yeah I call it four and a half

[00:57:04] percent a year I mean no shit of course they are every everyone in the real economy knows that

[00:57:10] what they have to pay people has gone up around between four and five percent a year

[00:57:14] and yet we have this insane world where we're told no no no that's not true

[00:57:19] you got me round up again I will give you the 30 second cultish corner on this which is that

[00:57:27] because I keep looking at this I've got this this is the single for uh the TLC hit I Don't

[00:57:32] Want No Scrubs which the important thing extra Ben Hunt extra why am I reading this now and

[00:57:39] I'm dawning on me thinking about this inflation thing like what's so important is we get the

[00:57:42] story we get the song and what does this song do call it the Harvilla Doctrine after Rob

[00:57:47] Harville the journalist a scrub is a guy who thinks he's fly also known as a busta it tells

[00:57:51] you exactly what it is right at the beginning people are constantly trying to tell you how

[00:57:56] to think about this thing you got to step back and see if that checks out you got to step back

[00:58:00] and see like yeah what is this scrub doing on hitting on chili she is a pop star this doesn't

[00:58:06] make sense say the same thing your central bankers do we have a closing question Jeff

[00:58:12] I think we've got to wrap up Jack top that yeah I know I can't I can't top that in what other

[00:58:17] financial live stream are you going to get TLC and no scrubs um only Matt Ziegler but uh

[00:58:23] thank you so much Ben this is great we really appreciate you spend the time with us

[00:58:27] anytime Jack thanks for what you guys are doing I really appreciate it

[00:58:30] Thanks Ben bye now

[00:58:42] J.J. Carboneau if you found this discussion interesting and valuable please subscribe in

[00:58:47] either iTunes or on YouTube or leave a review or a comment we appreciate Justin Carboneau and

[00:58:52] Jack Forehand our principals at the Lydia Capital Management the opinions expressed in

[00:58:55] this podcast do not necessarily reflect the opinions of a Lydia Capital no information on

[00:58:59] this podcast should be construed as investment advice securities discussed in the podcast may be

[00:59:03] holdings of clients of Lydia Capital