November 19, 2020

Expected Returns, Active Management, Advanced Topics, Technological Revolutions

Episode 125: (Rationally) Investing in Technological Revolutions, Human Capital, and Asset Allocation

November 19, 2020

Expected Returns, Active Management, Advanced Topics, Technological Revolutions

On today’s show, we explore rational explanations for pricing bubbles, how the concept of human capital relates to financial decisions, and a whole lot more! We kick things off with a discussion of Ashley Whillans’ book Time Smart, which explores proven strategies for improving your ‘time affluence’. Diving into this week’s portfolio topic, we use a previous discussion about Carlota Perez’s model for technological revolutions as a springboard to introduce Lubos Pastor and Pietro Veronesi’s mathematical arguments that present a rational explanation for pricing bubbles. Perez maintains that prices get bid up too high during technological revolutions due to ‘frenzy’ but we unpack two papers by Pastor and Veronesi where they argue differently, drawing on the concepts of uncertainty and discount rates. From there, we dive into the relationship between human capital, life insurance and asset allocation for our planning topic. We provide some definitions for the term ‘human capital’ and discuss how it differs from other forms of capital. A key idea we explore here is that the more risky your human capital is, the less life insurance you should take out. Along with this, you’ll hear a few quick suggestions for how you should approach life insurance and bonds depending on age, financial wealth, risk aversion, and other factors. Tune in today!

Key Points From This Episode:

Talking COVID, next week’s guests and Rational Reminder Community updates. [0:0:18]
Book of the week: Rethinking conventional notions of time well spent in Time Smart. [0:04:07]
News updates: Stories about Bitcoin, marijuana stocks, and more. [0:08:56]
Portfolio Topic: Whether pricing bubbles are caused by rational behaviour. [0:14:19]
Unpacking Pastor and Veronesi’s paper connecting uncertainty to high prices. [0:18:25]
Pricing bubbles as caused by discount rates; a second Pastor and Veronesi paper. [0:27:48]
‘IPO waves’ connected to the bubble discussion in a third Pastor and Veronesi paper. [0:37:58]
Planning topic: How the concept of human capital relates to financial decisions. [0:44:45]
The importance of considering asset allocation decisions and life insurance needs together. [0:54:46]
Bad advice of the week: ‘The Market’s Invisible Guardrails Are Missing’. [1:01:16]

Read the Transcript

Ben Felix: This is The Rational Reminder Podcast, a weekly reality check on sensible investing and financial decision-making for Canadians. We are hosted by me Benjamin Felix, and Cameron Passmore.

Cameron Passmore: Before we kick off this week just a little bit of a timestamp. I was thinking if we'd go back and listen to prior episodes, you don't really remember what was going on at the time. I know we've mentioned the pandemic in a few episodes, so we [taped 00:00:28] this on Monday the 16th, but this morning we learned about the Moderna vaccine and the fact that the initial trials are showing over 94% efficacy. And last Monday was a Pfizer vaccine came public, had 90% efficacy. So it's certainly unbelievably interesting times we live in.

Ben Felix: I was thinking about that this morning. It's something, I guess you're always living through history, but we're living through what could very likely be a big part of history when people look back on this time in the future. It's weird. It's just weird. No one's going to the office, everyone is starting to adapt to this new life. Yeah. It's something.

Cameron Passmore: It's something. For the podcast coming up next week we have Brian Portnoy and Josh Brown joining us, and they're going to be talking about their new book which was actually just released. It's called How I Invest my Money. So it's worth it to check it out ahead of the discussion next week and then in three weeks we have Morgan Housel, author of Psychology of Money joining us. Something really cool in our community I wanted to tell everyone about is that an avid listener to the podcast reached out to me probably six weeks or so ago and said, "I'm so taken by what you guys are doing. And the fact that you got this merchandise shop set up." He said, "I'm in the sock business and I've designed these really cool rash reminders socks and I'm willing to give you guys a break on the price." And he was just so nice and generous that we decided to pass a straight on to our community.

So if you order anything on the RR merch site, The Rational Reminder merch site, you're going to get a free pair of these custom socks. They're pretty cool. We're going to have them up on the website soon. I think I posted on Twitter last week, so a free pair of socks to any order while supplies last.

Ben Felix: Cool. And The Rational Reminder community, the actual community discussion site is up to when I checked this morning 618 users which is awesome. And there's so much I can't keep up with the discussion. So I'd love to reply to all the posts and jump in all the discussions, but there's just so much going on. Every time I open the app there's five or 10 new posts so I can't keep up, but the discussion that is going on and the things that I am checking into and reading for are really interesting. And there's some thought provoking threads going on in there a lot of it's making me take time and think about things that I hadn't necessarily thought about before. So it's really good. And it's continued to be a very positive community which I think is great. You always worry about stuff like that when you're managing an online community, but everyone's been excellent so far.

And if you want to discuss this episode we're still getting a fair amount of comments on the YouTube channel which is fine. But if you think of it, and if you can take the time to go over to the community and ask your questions in the episode thread over there that's the ideal place. Because it's nice to have everything centralized and there's so much good discussion going on there that maybe somebody else as opposed to one of us will be able to answer any questions or comments.

Cameron Passmore: I got a kick out of the comment on YouTube was it last week. They said that video is so clear that you can see our hair grow, which is mortifying for someone my age.

Ben Felix: It's good though, we've been tweaking trying to improve things over time. I think we're in a good place with our podcast technology set up at this point.

Cameron Passmore: Learning a lot that's for sure. All right. Anything else to add?

Ben Felix: I don't know, let's go to the episode. Welcome to episode 125 of The Rational Reminder Podcast.

Cameron Passmore: There is a book of the week this week it's called Time Smart. How to reclaim your life and live a happier life by Ashley Whillans. So Ashley is an assistant professor at Harvard Business School in Negotiations, Organizations and Markets. And she described as she basically studies help people navigate trade-offs between time and money. And this was a book that our friend Brian Portnoy recommended to us. And hopefully one day we can have Professor Whillans join us on the podcast in the new year. Interesting that she actually got her PhD in social psych from UBC. So I believe she's Canadian by looking at her background. And I'm probably two thirds of the way through the book, but her main point is that the focus on work is really a time trap and it contributes to what she calls your time poverty.

And in the book she's actually shows models to value the economic value of your increase happiness from making changes in how you focus on time and making time as opposed to making money in your life which is really interesting. So for example, she demonstrates it just by shifting your mindset from money to time, just that one thing alone increases your annual happiness value by $2,200. So as she explains the magnitude of that doesn't really matter, it's more the point that you can increase your happiness just by making this simple shift. She also shows if you take eight more days of vacation per year, that increases your happiness by $4,000.

Another example she gave is that if you save her meals is what she calls a satisfier as opposed to being a planner of a nice meal out, which many people in North America spend more time planning the meal and where to go as opposed to enjoying it once you're there, that alone can add $1,800 of satisfaction to your life. The biggest example I've seen so far is as she says, if you can outsource what you dislike in your life the most, that adds happiness valuable for $12,000. So our point in the book is all of these small decisions by focusing on time instead of money will actually add to more happiness. Which has value as opposed to just being work and money focused, which she would argue as a never-ending treadmill.

Ben Felix: Wow. I don't think I've mentioned this on the podcast but I did earlier this year, I'm reading this book too I'm not two thirds of the way done yet though. I think I started got really excited about it, told you about it, and then you powered through more…

But before reading this book I found that I was spending too much time in the kitchen cooking and cleaning up and then spend my last half hour of the day in the kitchen cleaning up and doing the dishes. I know I've told you this Cameron, but I don't think I've talked on the podcast. We started getting all of our meals delivered but we found a service in Ottawa that does not just the prep, there's all those different meal box where it's a kit where you still have to cook and stuff. We found a service that's doing the type of healthy cooking that we like to eat, but it's like they give you a pre-portioned serving. You-

Cameron Passmore: Cook it, ready to serve, ready to eat.

Ben Felix: Yeah. You heat it up and eat it and that's it. And that's been awesome in terms of just feeling good about the way that I'm spending my time. Her number there seems big $12,800 but I can totally see it.

Cameron Passmore: But notice you focus on the happiness and not on the cost of it. And you've mentioned this a number of times, so I know the impact this has had on you and Susan.

Ben Felix: Yeah. I don't say it lightly it's been life-changing for us because cooking and cleaning is one thing, but then planning what to buy and going to the grocery store to get it. you combine all that together it's a huge chunk of time. And it's not cheap to have all these meals delivered from this service but it's worth it.

Cameron Passmore: But I think that experience back to what she says are the three main steps to success. Convince yourself that time is at least as important as money, number one. So that's certainly applies to your example. Remind yourself of your values when faced with a critical decision. So you value the time as opposed to the prep work. And then number three, make deliberate decisions that allow you to have more time, this is a perfect example.

Ben Felix: I think there's a lot to be said for this topic. I think maybe we can cover it again once I've actually read the book but I bet this could be a whole planning topic.

Cameron Passmore: I agree. In other news, we talked a couple of weeks ago about the Ant Group IPO. That was going to be the largest IPO in history, while that ended up being stalled did not go as planned at all. And quote, new regulations could force Ant to raise more capital to back lending and seek national licenses to operate, which may actually reduce the firm's valuation by about half. Someone's stories in the news on the weekend about apparently Jack Ma made a speech or presentation somewhere that is now being scrutinized by the Chinese government. So I don't know the whole story, but suffice say it's been delayed likely at least six months, and the valuation could drop by about $140 billion to a level below its level two years ago in the last raise money.

Ben Felix: I just thought since we mentioned it two weeks ago I'd just do a quick follow-up on that.

Cameron Passmore: This one quickly, did you see this story The Wall Street Journal from Jason's Zweig last week called Cash is Trash so let's bet $425 million on Bitcoin. Do you read this story?

Ben Felix: No.

Cameron Passmore: I know you can always read the stories I put in here. This one just blew me away. So there's a company publicly traded called MicroStrategy, Inc. which recently had half a billion dollars of excess cash on its balance sheet. Total market cap is at that point around $1.5 billion U.S.. So with that cash of course, it could have paid a dividend, done a share buyback, expanded the business, but instead invested half of the cash into Bitcoin. So those who have invested for a while might remember MicroStrategy it was a really popular stock back in late '90s. And you look at the price chart has got this massive spike up into like the two to $3,000 range. And now it's way, way less in the hundreds of dollar range, because this big spike 20 plus years ago, and has been basically flat ever since. It has had very little return since that spike. They have a technology that enables businesses to analyze internal and external data is highly profitable and they keep building up this cash.

But anyways, in August when they announced that they had invested $250 million in Bitcoin, the stock jumped 9% in a day. A month later the company declared that it would continue to put most of this excess cash into Bitcoin. The stock then was 23% in two days. So Bitcoin of course is rallied since they bought in and now the cryptocurrency they own is worth more than a third of the total market cap of the company. So the CEO when he was asked if he was nervous about putting so much cash into Bitcoin here was his response. This is Michael Saylor responded, "What would it be nervous about if I had $500 million in cash that would make me nervous because I think it would go to zero in purchasing power over five years. What's my choice? I think Bitcoin is better than gold as a store of value. He added, it's not perfect there's risks, but I can't find anything better and the option of doing nothing is more risky."

Ben Felix: Are we in the bad advice section or no? This is-

Cameron Passmore: No, no. This is the news section.

Ben Felix: Okay. I was confused for a second.

Cameron Passmore: But it's interesting. A publicly traded company takes cash and now the share value is going up because of cash have introverted to Bitcoin.

Ben Felix: Yeah. For all my trashing of dividends from a corporate finance perspective this seems like a pretty ideal case for the company that pay dividend. If people want to invest in Bitcoin they can do that after they've received their dividend in cash.

Cameron Passmore: Anyway, in other news marijuana. So Jeremy Gee asked a question on the community board that got me wondering about marijuana. And I don't know about you, but if you noticed how quiet it is for marijuana stocks that related ETFs compared to two years ago when they were all over the place.

Ben Felix: Yeah. The price falls to the floor and then nobody wants to talk about it anymore.

Cameron Passmore: Jimmy Canopy Shares which was a big company that everybody was talking about, those shares peaked around 60 bucks now they're in the $30 range. HMMJ, the Marijuana Life Sciences Index ETF Horizons peaked around 25 bucks in the fall of 2018 and now it's in the 750 range. It's still a huge ETF at $400 million but it's amazing how it was the rage back then and now you don't hear marijuana. I haven't had someone to raise marijuana and I can't remember the last time.

Ben Felix: No, no. In terms of the people that we talked to about their actual investments, yeah, for sure. When the price was skyrocketing people were asking about it and yeah, you're right now it's... Yeah.

Cameron Passmore: And last bit of news. Can you name the largest five ETFs by AUM? I know it's that our notes here, but I just wondered that on the weekend I looked it up.

Ben Felix: Largest ETF by assets, the Spider SPY $316 billion U.S. ETF, the S&P 501 IVV it's the BlackRock version of the SB-500 219 billion, Vanguard Total U.S. Market 172 billion, Vanguard S&P 500 options VOO 166 billion and then the QQQ's at 142 billion. Those five ETFs have almost a quarter of all ETF assets-

Cameron Passmore: Unreal.

Ben Felix: ... and negligible MERs, all those.

Cameron Passmore: Right. Is cool so many assets linked to the broad S&P 500 or Total Market Index. Incredible.

Ben Felix: It is. It is incredible.

Cameron Passmore: Anyways, we'll jump into the portfolio topic.

Ben Felix: Yeah. So last time when it was just you and I Cameron, we talked about technological revolutions. I think it was important to go through the full model of Carlota Perez for how technological revolutions tend to play out. But there's one piece of her model that from the framework that we like to use to think about market just doesn't make sense, which is the idea that there are price bubbles. So throughout the whole technological revolutions concept laid out by Perez, one of the key points from the per perspective of investment returns is that the prices get bid up way too high.

So she calls it an irrational frenzy. Robert Shiller calls it irrational exuberance. Actually, I don't know if Perez called it an irrational friends and they should just call it a frenzy. I think irrationality is implied in frenzy, but in either case we're talking about prices being detached from the fundamental values of the actual businesses. And I think that concept and this is probably one of the reasons that it's such a popular concept and it's so easy to say, oh, well that was a bubble or we are in a bubble, which gets thrown around a ton. And I think the reason is it's just really easy to think about, especially in hindsight is easy to look back and say, oh yeah, technology stocks, that was a bubble because we know the prices went up, we know they went down. It's very easy to say in hindsight that was a bubble.

And I think it's very easy to say when prices are high on anything, even if we don't know if they're going to come down, it's very easy to say that we're in a bubble. I don't know the exact psychology around why that's so easy to say and think about, but it's a lot easier to say that than it is to try and figure out the rational pricing story for why something has those pricing characteristics. Now, I don't think it makes a whole lot of sense to base an entire theory on investor irrationality. And that's not to say that investors are perfectly rational. We know that's not true, but I think assuming perfect irrationality, assuming that all of these past technological revolutions and the stock price performance throughout them has been based on irrationality, I think that's a bigger assumption than it is to say the prices are rational.

Now that may sound confusing because of course, that's not rational for prices to get as high as they have in those past technological revolutions, but it is possible. And there's actually some pretty succinct explanations for why prices could get that high without being irrational. And so again, this isn't to say that irrationality doesn't play a role when we see those bubble light characteristics and stock prices or an asset prices, but I think that it's important for people to know that there is a rational pricing story for why this can happen.

Cameron Passmore: So there's a rational story for why prices could be irrational.

Ben Felix: There's a rational story for why prices could be high and look like a bubble after the fact. Which is important because we're not going to know it's a bubble while we're in them. So a lot of this research came from Lubos Pastor who obviously we had on the podcast last week. And we didn't cover this in our conversation with Lubos. I ran a by him as a potential topic and his feedback was basically that it's a really complicated topic and didn't think that was the best allocation of our time with him as a guest. But it is a complicated topic, but we're going to try and tackle it today.

We were able to chat with Lubos a little bit about this after recording and get some of his insight and feedback. Actually I think all of it is based on three different papers that he's done on this. And Perez actually in a 2009 paper where she updated some of her research, she references Pastor and Veronesi and paper to say that there's potentially irrational pricing story for why these bubble like characteristics happen.

Cameron Passmore: Isn't that an interesting just to think about. Love it.

Ben Felix: It is really cool. So there's a 2004 paper by Lubos Pastor and Pietro Veronesi who's Lubos's colleague at Chicago. The paper was called, Was There a Nasdaq Bubble in the Late 1990s. And this one I find fascinating. So they show in this paper mathematically using an inequality that we'll talk more about in a second, that higher uncertainty about average profitability of the companies creating new technologies leads to higher prices all else equal. Now that's going to sound beyond the counter-intuitive. Why would a higher uncertainty lead to higher prices. And I'll explain why-

Cameron Passmore: Okay. I want to ask a question.

Ben Felix: What's the question?

Cameron Passmore: No, I don't want to derail where you're going keep going-

Ben Felix: No, ask it, ask it, ask it.

Cameron Passmore: I'm just wondering if there's a upward skewness in hopes on profitability. Is that what is driving it?

Ben Felix: Yeah. So when there's a wider range of potential outcomes on growth, a wider range of potential growth trajectories that all else equal increases the fundamental value of firm. And the way that you can explain it using English as opposed to math is maybe it's the next Microsoft and maybe it's not, which makes something valuable. And now there's a much more mathematically rigorous way to explain that, which is what we're going to talk about. So in the paper to explain the concept they use the Gordon Growth Model for stock valuation. Now this is not a comprehensive stock valuation model, and it's been I guess shifted around over the years to be more reflective of how stocks are actually priced, but it's also a very simple model. And so they use it to illustrate the concept but in the actual analysis in their model, they use a better valuation model. But we're going to talk about the Gordon Growth Model just because it's got a relatively small number of variables.

It's just important to know though that this concept can be expanded to a more complex valuation model. We're just using this as a proxy to talk about it. So if we use the Gordon Growth Model where stock price is equal to expected dividends divided by the discount rate minus the growth rate, that's just classic finance 101 Gordon Growth Model. The price and this is really important here. The price has a convex response to changes in the dividend growth rate. So price equals D1 dividend in the next period over R minus G, over the discount rate minus dividend growth rate. So changes in the dividend growth rate have a convex relationship with price. And one of the things we're going to try and it should be good to go, but hopefully it is. We've got an animation that we're working on that we're going to use for our common sense investing video on the same topic. And we're hoping that in the YouTube version of this podcast episode we're going to have that animation ready. So people should be able to take a look at that to help think through this.

Cameron Passmore: What do you mean by a convex response?

Ben Felix: Let me just think about an XY axis chart. My linear response would just be a line up into the right-

Cameron Passmore: Straight line?

Ben Felix: Yeah. A convex responses is like a curve.

Cameron Passmore: Sloping upwards, like an exponential growth curve?

Ben Felix: Effectively, yeah. Yeah. That's what it's going to look like. Now, the convexity is really important. So it's a function that is convex in the growth rate of dividends. And there's a special case in mathematics for convex function specifically called Jensen's inequality or Jensen's inequality. I don't know Johan Jensen is probably Jensen, Johann Jensen I don't think would make sense. And so for the Gordon Growth Model, that what this inequality implies is that when dividend growth rates are modeled as uncertain as opposed to no one, the expected growth rate required to explain a given price, the expected growth rate. So you can have a huge range and it's going to have one expected growth rate, the probability weighted average of all the possible outcomes I guess, the expected growth rate to explain a given price decreases.

Cameron Passmore: Okay, I can just hear listeners scratching their heads.

Ben Felix: It's a bit of a head-scratcher, which is why we want to have the animation, but I'll try and talk through some numbers too. So the larger the uncertainty what the dividend growth rate the larger the drop in the expected growth rate required to justify given price. Now you got to think about this, you can have one expected growth rate, 6% or whatever, and that's 6% is two possible growth rates equally weighted. So to get to the 6% you can have a 2% and a 10% possible outcome equal chance of getting those. Your expected growth rate of 6%. Now you've got the two in the 10% as the possible outcomes, but you can make that distribution wider. I don't have the math in my head, but it could be 0.1% up to whatever the opposite end of that would be to get to expect that of 6%.

So your expected growth rate stays the same that case, but the uncertainty about it increases. So here's a numerical example. If we assume a discount rate of 11%. So that's the R and an expected dividend of $1. If we take a stock trading at $56, the implied no one dividend growth rate or the expected dividend growth rate is 9.2% which is high. That's a high growth rate for dividends. And actually in the Gordon Growth Model the assumption is that dividend policy and investment policy are the same thing, meaning that the dividend growth rate in this case has to be tied to the growth and profits. So that's a pretty aggressive profit growth rate in perpetuity. So 9.2% that's the no one growth rate.

Now, if instead we allow for two possible growth rates, 2% and 10%, and that's why I use those numbers because I had them in my example, with equal probabilities and take the expected value of the function. So we're looking at price equals D1 over R minus G the expected value of that function meaning the average price at 2% and 10% needed to justify the $56 price, so the expected value. In that case, the expected growth rate to satisfy the equation is only 6%.

Cameron Passmore: Wow. Therefore justifies a higher price.

Ben Felix: Correct. It justifies a higher price with a lower expected growth rate, because of the uncertainty about the growth rate. It's not that 6%, that's not as crazy as 9.2% which is what they're getting at in the paper is just that, even if the no one expected dividend growth rate might look really high, if we include uncertainty in the model because of Jensen's inequality, the actual expected growth rate could be a lot lower. And therefore it wasn't a rational to expect that there was just a lot of uncertainty around it which caused prices to be higher.

Cameron Passmore: Wow.

Ben Felix: I hope that made sense to people. And I am hoping that we can have an animation showing the relationship, but it's like you have this convex price function and you've got two different points, like the 2% and the 10% on this curve. And you've also got the expected value. So we've got a price of $56 and we know we would need a 9.2% growth rate to satisfy that price. But if we instead take the expected value of the function in our easy example, two equally likely possible outcomes take the expected value of the function in those two spots using the mathematical term, you're going to find the expected growth rate is going to be the middle of the line running across the convex curve.

You've got two points on the curve. The no one growth rate would be 9.2%, which is at the bottom of the convex curve. And then you've got the C can line, the straight line that's running between the two points and the point on that line which is always going to be above the curve that's going to be the expected growth rate required to satisfy the function.

Cameron Passmore: So this is basically a mathematical proof or argument that what now looks like a bubble back in the late '90s was actually mathematically justifiable?

Ben Felix: Yeah. All it's saying is that when you include uncertainty in the pricing equation, the growth rates implied by the historical prices were actually not that crazy. And they use volatility as a proxy for uncertainty. And they looked at the prices in the 1990s and they find in the paper that the level of uncertainty implied by their model to justify the high prices and the dot-com bubble matched up really well with the realized volatility of technology stocks over that time period. So when you take that into account, when you take that high uncertainty, which they're using volatility as a proxy for the implied growth rates were actually not that crazy. They were just highly uncertain which counter-intuitively based on Jensen's inequality results in higher prices. But it's pretty crazy, right? And I know that was a lot of math to talk there, so I hope people feel okay. So that's one of the reasons that this can happen in a rational pricing situation.

The other one is equally fascinating. So they had another paper called technological revolutions in stock prices. And in this case, instead of being about uncertainty it's about discount rates. And that's important to actually. In the other one in the growth rate one the model we just talked about, the discount rate doesn't change. So that idea of value versus growth we always talk about it in the context of discount rates, but in that case it had nothing to do with discount rates. In our example, the discount rate remained at 11%. The risk of those stocks remained unchanged, but the uncertainty about their future profitability is what affected their valuation in that case. So it wasn't a discount rate story. In this case so that was a more of a profit uncertainty story.

And then the second paper focuses on discount rates. So in this one they built a model where there's a new economy and an old economy, and the new economy is small and experimental until it becomes no one that it could meaningfully increase productivity in the old economy. So at some point in their model the old economy realizes that this experimental new technology could actually increase productivity. Now, before the technology in the new economy as adopted by the old economy, the risk of the new economy is primarily idiosyncratic specific to the new economy. It's not really attached to the broader old economy, the old economy being like everything else except for this experimental technology.

Now, if the new economy starts to become profitable... And this is really interesting, so it starts to become profitable there's a point where the combination of profits because there's new technology sector is realizing real profits, but it also has a relatively low discount rate being applied because it's still primarily idiosyncratic risk that's affecting its prices. You end up with this big shoot up in prices because we have these increasing profits that aren't being discounted based on risk. Make sense so far?

Cameron Passmore: Mm-hmm (affirmative).

Ben Felix: And then as the chances of the new economy being adopted by the old economy, like instead of just a little bit of profits and uptake full on adoption in the old economy, the rise in systematic risk in both the old and new economies. And this is happening because the new economy is starting to become part of the market and therefore its discount rates are starting to reflect systematic risk, but at the same time the old economy is increasing its overall risk because it's about to undertake this massive project of integrating this new technology to it itself. So we're increasing systematic risk in the new economy, which was previously mostly idiosyncratic, but we're also increasing the risk of the old economy.

And so what happens when this integration starts happening is that the new economy stock prices drop and the old economy stock prices drop. But the new economy stock price has drop more than the overall market and they're more volatile. You think recent example of the tech situation in 2000 that's what happened. Tech stocks were highly volatile, they increased in price at time, they dropped a ton so to the market, but tech stocks dropped a lot more. So they tested the predictions of this model against the dot-com bubble and the railroad mania of the 1800s which was pretty interesting to see the two examples so far apart. So they found in the dot-com bubble the bubble pattern was much stronger than the Nasdaq Index which is what they used as a proxy for the new economy than it was in the old economy, which they use the NYC Amex as a proxy.

The Nasdaq's beta doubled between 1997 and 2002, the volatility of the old and new economies increased, but the new economies volatility always exceeded the old economy over that time period. And then Nasdaq's beta and both the volatility of the old and new economies of the Nasdaq and the NYC peaked in 2002 followed by a massive acceleration in productivity growth and the U.S. economy. So basically their model did a really good job predicting the outcomes that we actually saw in the dot-com boom and bust.

Cameron Passmore: And then likewise in the 1830s and '40s, there was a ton of uncertainty about whether railroad technology would be adopted on a large scale. I mentioned that the book I read a long time ago about the Vanderbilt family, that the narratives around what it was like when railroads are being deployed. Yeah. It just speaks to the uncertainty. Just tons of people throwing ideas and rail lines, wherever nobody knew if there's any large-scale uptake so that they found in their research Pastor and Veronesi that all stocks fell before and during the year 1857, but railroad stocks fell more than non railroad stocks. They found that railroad stock volatility and relative prices consistently exceeded their non railroad counterparts and volatility of all stocks rose in 1857, which is again in line with what the model would predict. The railroad stock beta increased sharply in the 1850s and then fell right after 1857. And then soon after that railroads did begin their large-scale adoption.

It's fascinating to think about just the relationship between systematic risk and new technologies, which is not a strong relationship when there are new technologies that are not integrated into the economy, but then as they become integrated, the discount rates changed to reflect the fact they become part of the broader economy.

Ben Felix: Wild.

Cameron Passmore: The crazy thing about, so there's two different mechanisms. There's a discount rate mechanism and the profit uncertainty mechanism that can both cause prices to shoot up and they can be happening at the same time too. That's the other fascinating part about it. They can work together to create the bubble like characteristics that we see in stock prices. One of the important things that they note is that all of this is only no one in hindsight, we're more likely to study technological revolutions. We're only going to study technological revolutions once they've taken place. There's a whole lot of stuff out there that was never a technological revolution and therefore we don't study stock price behavior during that period. But the investors living through each of the, what we know on hindsight to be technological revolutions they don't know at the time whether the new technologies are going to be adopted by the old economy or if they're going to continue as being small and experimental.

But you can see how it would be easy to explain this using irrational pricing, but you can also see there are two completely separate cases where the bubble lake behavior that we see in prices can be explained rationally. Now, I think one of the really important practical takeaways from the models that we just talked about is that stock prices that are associated with a new technology they're going to rise. And this is specific to this second. No, it's both models. Stock prices are going to rise as their profitability potential becomes no one or as they start generating actual profits. But if you believe that a technology is going to be adopted on a broad scale into the economy, but it's still experimental if you believe. So if I'm going to make a bet, I'm going to bet that this technology is going to take off and it's going to become integrated into the economy that's actually a bet that the prices will decline at least theoretically and historically that's what has happened.

So if you bet on, okay, I see railways they're becoming profitable, I can see this is going to change the economy, I can see they're going to get adopted on a larger scale, that is a bet that their prices are going to decline for two reasons. As the market knows more about their profitability, as their profits become less uncertain, prices drop. And as they become adopted into the economy their risk becomes systematic as opposed to idiosyncratic and their discount rates increase. Two different mechanisms both causing the price to drop on large-scale adoption.

Ben Felix: A lot of head-scratching in there, it's crazy.

Cameron Passmore: Head-Scratching but does it makes sense?

Ben Felix: It makes sense, but still a lot of head scratching.

Cameron Passmore: Yeah. I get it because there's an uncertainty of growth rates which was your first model. So is that uncertainty narrows, right? That's what's driving a lower share price from the first model. Still has scratcher I get it but it's a head-scratcher.

Ben Felix: Yeah. So when you take those two together, if the technology does revolutionize the old economy the two things that happen are the market learns about its profitability. Like you just said, reducing uncertainty and stock prices because of the convexity on growth rates and valuation theory. And the risk and the new economy transitions from idiosyncratic to systematic, which further reduces prices on the discount rates at this time.

Cameron Passmore: But you're making the argument based on mathematical theory not behavioral finance for example.

Ben Felix: That's exactly it. This is a way that we can explain what has happened in technological revolutions using rational pricing theory. Not relying on people being in crazy and irrational and borrowing to invest their life savings in Tesla. Now it's probably both really and we can't definitively say either way what it is. I read that there was another paper on the bicycle bubble in England which is just as part of this research that I was doing and they actually explicitly argued against the theories that we just talked about, because they said that the betas didn't increase in that case. And so they said that this one had to be a irrational pricing story, but you can find arguments and support for either story. I just think when you're thinking about pricing and technological revolutions it's important not to have that hinge on irrational behavior.

So we still have the overall model for technological revolutions but specific to asset prices throughout them we have the behavioral story, which is pretty easy to think about, but now we also have some tools to think about it from a rational pricing-

Cameron Passmore: Precisely.

Ben Felix: And then there's one more piece that I wanted to tack on here, which is another paper from Pastor and Veronesi that uses... And this is why I wanted to talk about it, it uses the models that we just talked about to explain another phenomenon that we know exist in markets which is IPO waves. And I think you could probably say that we're having one in 2020. There tend to be these big clusters of IPO's or a bunch of companies go public around the same time. Now we know also that IPO returns tend to be awful and there are different ways that you can explain why that happens and we're going to talk about some of them here. We did talk about that in episode 42 of this podcast and there's also a CSI video on IPO's. So if you want more detail on the empirical side of how badly they attended it you can go check those out.

Yeah. So the late '90s had a big cluster IPOs, 2020s had a big cluster and Pastor and Veronesi argue in this paper that the number of firms going public changes over time in response to time variation and market conditions. So in economic spread they're saying that IPO timing is endogenous. It happens based on conditions within the economy. So they developed a model of optimal IPO timing where IPO waves are caused by... And this is the endogenous piece, caused by declines and expected market return. So expected returns go down, discount rates go down, prices go up-

Cameron Passmore: Go up.

Ben Felix: ... companies go public. Increases in expected aggregate profitability. So the economy's good, expect the profits are high prices are high, companies go public at a high valuation or increases in prior uncertainty which is their language for about what we were just talking about with uncertain future…

So increases in prior uncertainty about the average profitability of future IPO's, which again causes high prices. So they test this model empirically and they found that IPO waves do tend to be proceeded by high market returns and followed by low market returns which may be helps explain some of the reason that IPOs tend to do so poorly. Time variation and expected market returns is consistent with empirical evidence on return predictability which isn't really what it sounds like, but that idea comes from a farm on French paper in 1989, where they found that... This is a quote from the paper, "The general message is that expected returns are lower when economic conditions are strong and higher when economic conditions are weak." So it's not really like predicting future returns more of a discount rate.

Pastor and Veronesi talked about how the time variation expected aggregate profitability is related to business cycles. Time variation, and prior uncertainty is related to technological revolutions which are likely to be accompanied by high prior uncertainty like we've been talking about, because they make the prospects of new firms highly uncertain. So they show theoretically and empirically that IPO volume responds to time variation in all three dimensions of those market conditions that I just described. And their model implies that IPO waves should be proceeded by high market returns and followed by low market returns, which is exactly what we see empirically, and that they should be accompanied by increases in aggregate profitability, which again, lines up with the empirical experience.

And then another interesting point is that IPO waves in their models should be proceeded by an increased disparity between new firms and old firms in terms of their valuations and return volatilities, which is again exactly what we see. So they build this model, build other predictions and then confirm that it all exists in the data. Now, they also mentioned in this part was quite interesting too, that this could be explained by behavioral story, that firms go public when they're overvalued. And Pastor and Veronesi don't deny that, that's part of it, but they do share a couple of empirical findings that suggest that the rational pricing pieces is the dominant force here. So they say that behavioral argument does not predict that IPO volumes should be related to recent changes in market returns the volatility, or positively related to changes in aggregate profitability. Whereas that's what the empirical experience shows.

And then they tie it back to their previous paper on whether not past bubbles were actually irrational, which we've already talked about. And they say there's actually a rational explanation for this too. We can only call it a bubble in hindsight. And this again, helps to explain their relatively poor returns IPO valuations tend to be high and this is for the combination of reasons that we've already mentioned. So IPO timing is endogenous, meaning that IPO has happened when conditions are good, which doesn't mean they're overpriced. It just means that's when valuations are high and expected returns are low and it's partly due. So that's the expected return side of it but it's also partly due to a high prior uncertainty about average profitability which is again, if you win that bet, if the certainty decreases and the market realizes, hey, this thing actually really is profitable by decreasing that spread of possible outcomes you're actually going to decrease the valuations of those firms.

And they also note that according to the proxies that they're talking about in this paper prior uncertainty was very high in the late 1990s and that may be one of the reasons that so many firms went public.

Cameron Passmore: That is wild.

Ben Felix: Pretty cool, right?

Cameron Passmore: Just wild counterintuitive thinking backed up by math. Crazy.

Ben Felix: Yeah. The fascinating part about it is that when we were talking to Lubos about this, one of the things he said was that for irrational pricing for that behavior behavior-based story, you have to have a model with a lot of degrees of freedom. You have to have a model with a lot of moving parts to explain the phenomenon using behavior. Whereas if you have a... What did he call it? A single agent economic model where there's one actor with perfect information, which is theoretical it's not reality but if you make that assumption, that's a much simpler model. So you're making you're not making as many assumptions and there are less moving parts. Using a simple rational model with less degrees of freedom if you can explain a phenomenon with that, you can definitely explain it with a more complex model too, but being able to explain it with a simple rational model is I think useful and also important.

Cameron Passmore: Amazing. That's pretty cool. Onto the next topic. So this week's planning topic is something that came up in our recent conversation with Professor Milevsky three weeks ago in episode 122, and that is human capital and how it relates to making financial planning decisions. So we go back to the basics, what is human capital? And I guess in its simplest form is basically your ability to earn and save money. And effectively becomes a present value of all future expected income, wages, pensions, social security, Canada pension plan old age security, et cetera, present value of your lifetime of income. One definition I came across was from Roger Ibbotson, who called it total economic wealth is financial capital which is your savings and investments plus human capital.

Interesting in our work that we mentioned actually ended up coming episode but on our work with Dr. Brian Portnoy he also highlights two other kinds of capital to us. One being social capitals. That's your relationships, your network, you're connecting with other people, as well as temporal or time and we just discussed that earlier in that book review. So he has those at two other kinds of capital in our lives.

Ben Felix: They're all connected. They're all connected. Totally human. I think in the economic models we talk a lot about human more like the Ibbotson idea. The total economic wealth is equal to financial capital plus human capital. I think that's a pretty basic model. And from a modeling perspective that's a good thing. I guess what we just talked about a simple model is better, but the reality is social capital and temporal capital time are directly related to financial and human capital. And you can imagine that you can shift all of these things, you can shift them all around. Financial capital lets you shift temporal capital forward and backward, which is crazy to think about.

Cameron Passmore: But that's exactly what she talked about in that book, right? Is shifting your time choices and putting monetary value to them, right? Well look what you've done with your meal decisions. You gain more time.

Ben Felix: Yeah. We're getting beyond the scope of the human capital discussion but well in future episodes we'll talk more about the four primary types of capital and how they interact with each other.

Cameron Passmore: By knowing and I'm thinking about your human capital is so critical in so many parts of financial planning. Most of us graduated with very little financial capital, but very large amounts of human capital depending of course on what career choices you make or what career do you need based on what your objectives are. Do you pick a career based on what your future financial capital needs are and often we have the largest liabilities when our youngest in our careers. So the amount of life insurance and disability insurance you need in order to protect that human capital. And then remember Professor Milevsky talked about the volatility of your human capital. Remember he's a tenured professor, therefore he said his human capital volatility is much lower than certainly someone in our field, which is connected to capital markets in large part.

So some of the big decisions you have to make are how do you make asset allocation decisions with your portfolio? How do you make insurance decisions? Should a late Professor Milevsky treat the human capital as a bond thus giving them permission there increased their ability to take a more stock market risk? Should we in the securities business have less exposure to volatile markets have more fixed income? So these are all the decision points around human capital.

Ben Felix: And it comes up too like in the conversation with Lubos last week, we talked about the idea of leverage. Actually this comes up in the whole human capital discussion too where there's a big difference between an optimal portfolio which the leverage decision plays into, because an optimal portfolio theoretically does include leverage. But the whole mean variance optimization, optimal portfolio type thinking is not designed for an individual planning for retirement, it's designed for an institution whose job is to have the ideal Sharpe ratio. But there's actually a paper from Markowitz in 1990, which was an update... I actually couldn't get the original paper, there was a reference to it and something else that I read, but he updated I think it was 1956 paper, but he's the the father of modern portfolio theory. And he points this out in his 1990 update that the whole modern portfolio thinking is not for individuals because it doesn't take into account human capital.

Cameron Passmore: So interesting.

Ben Felix: Yeah. So I dug up a pretty comprehensive book on this topic which you can find online. It's called Lifetime Financial Advice, Human Capital, Asset Allocation, and Insurance and I tried to pick out a couple of interesting points from it.

Cameron Passmore: You look at the authors of the paper, Roger Ibbotson, Moshe Milevsky, Peng Chen and Kevin Zhu.

Ben Felix: Yeah. Do you want to jump into some of the points?

Cameron Passmore: Sure. So human capital interacts with traditional investments such as stocks bonds and real estate to the correlation structure. Human capital interacts even more interesting and profitable ways with life insurance and annuities because these assets have payoffs linked to the holders longevity.

Ben Felix: Yeah. It's pretty crazy to think about.

Cameron Passmore: Pretty crazy to think about. And we've been debating this before we recorded this actually some pretty head spitting things going on in here..

Ben Felix: Oh, the how this stuff relates to insurance I find just... Again the whole idea of stuff that's counter-intuitive but then once you think of it, it makes sense. Well, talk more about that in a second.

Cameron Passmore: Yeah. You're going to have to take us through that for sure, because you got me there on the logic, but you thought the last stuff on investments was counterintuitive, this just make here.

Ben Felix: This is more counterintuitive than the-

Cameron Passmore: Make your head hurt. It really does make your head hurt.

Ben Felix: The traditional mean variance framework for asset allocation focuses on diversifying financial assets which... This is the Markowitz thing that I was just talking about, that, that makes sense if you're an institution with an infinite time horizon and with a goal of making theoretically optimal portfolios. But mean variance is not a framework that makes sense for individual investors who are working in saving for retirement, because they've got to take into account their total wealth, which for an individual consists of financial assets which is what we tend to focus on, but also human capital. Which like you mentioned early Cameron that especially early on tends to be your single biggest asset. And there's one really interesting point that they made in this book, which was that from an economic perspective, your labor income can be viewed as a dividend on your human capital. Maybe dividends are relevant to the valuation of humans in that case.

Cameron Passmore: I knew you're going to say that. So let's talk about the asset allocation considerations. So in general, typically young investor certainly would be well advised to hold an all stock portfolio (perhaps with leverage)-

Ben Felix: Yeah.

Cameron Passmore: ... because you can offset any disaster scenario by saving more going forward, by consuming less investing differently going forward.

Ben Felix: Changing your labor supply, like working more. If you take a risky gamble in the stock market and lose a bunch of money you could. I don't know if a lot of people would want to do this but you could do a second job. You could drive Uber eats or whatever.

Cameron Passmore: The second job or retool yourself for different career to make potentially more money.

Ben Felix: Yeah. Spend less, save more of your same level of income which I guess are two sides of the same. Probably, you have a real capacity to absorb financial losses when you're younger. Not just by the value of your human capital but also how you allocate it, how you allocate your financial capital going forward. You have a lot of optionality around that when you're young, right?

Cameron Passmore: Right. But as you get older and your human capital proportion reduces and total wealth increases, younger investors invest more in stocks and older investors.

Ben Felix: Yeah. Yeah. And this is where Lubos tied this into leverage decision where it's like for those reasons a younger investor might still want to use leverage depending on the characteristics of their human capital but it's not a mean variance decision. I think the way that airs and Malibus paper talk about it is more of a this gives you a better expected payoff overall, as opposed to the human capital perspective which is more of a, if you have the capacity to take this risk you may want to but that doesn't mean that it's necessarily optimal for everybody. If we generalize the younger investors can invest more in stocks and older investors, investors with safe labor income can invest more of their financial portfolio and stocks, investors with labor income that is highly correlated with stocks should invest their financial assets in less risky assets seems pretty intuitive I guess.

And if you have the ability to adjust your labor supply, higher flexibility of labor income you can increase your allocation to stocks that could be a willingness to work more, it could be a willingness or an ability to have upward mobility in your the value of your labor income. You can take more risk.

Cameron Passmore: Let's jump to the life insurance part. See if you can take us to the logic trail you had me on a couple of hours ago.

Ben Felix: Okay. So I think one of the important pieces the point that the book makes is that, you can't think about your life insurance needs and your asset allocation decisions separately. They have to be considered together, jointly, not even just at the same time, they're part of the same decision-making process. Now this is the part that you found counter-intuitive and so did I, when I first read it. All else equal as the correlation between human capital and risky assets increases. So your human capital is getting riskier or more closely correlated with stocks. The optimal allocation to risky assets in your financial portfolio decreases, which makes sense. You've got a risky human capital like us tied to the financial markets. You maybe should allocate less of your financial assets to stocks, maybe more to bonds. But the other piece, the life insurance piece, you should also decrease the optimal quantity of life insurance or the optimal quantity of life insurance does decrease. So if you have a risky human capital, you want to have less than stocks, but you also want to have, or theoretically should have less life insurance.

Now, the reason that you should theoretically have less life insurance if you have risky human capital... And again, this is going to make sense once you hear it, but you'll use a higher discount rate to value your human capital. So if you have a high income but it's a highly risky income, the discount rate that you're going to use to value your human capital is going to be higher. So a higher discount rate obviously implies a lower present value of human capital, which implies a lower insurance need to cover your human capital in the event of death.

Cameron Passmore: But you can necessarily assume that growth rate on the proceeds of the insurance, God forbid something happens that the surviving spouse and get the return on the life insurance proceeds the same discount rate that we put on your human capital.

Ben Felix: Yeah. This is the part that we were talking about before we started recording. This I find from a philosophical perspective extremely interesting, because if we're going to use a 7% discount rate on someone's human capital to find what their insurance need to replace human capital would be, that makes sense. But if the surviving spouse doesn't want to invest in something that risky as they shouldn't want to, but if they don't want to invest in something that risky tend to maintain their lifestyle, while then the implication would be that they would need more life insurance to be able to invest at a lower expected return, which that's and realistically the cost of insurance is so low that it doesn't really matter a whole lot anyway. But-

Cameron Passmore: But what if is so much hire growth rate, like say 20% or 30% is what they think they could build their career at?

Ben Felix: Yeah. I think in this literature it's talking about using... Well, it doesn't actually talk about discount rates as far as I... Well, maybe it did a bit, I think it was in the technical appendix that I didn't read. But it was all about the correlation with stocks. I guess if you have a high beta effectively human capital or labor income you could have a much higher discount rate. But the philosophical piece that I find interesting is that if you would need a larger amount of insurance to fund lifestyle at a lower expected return, it just means you should be spending less now. If your consumption is high enough that you would need more life insurance to fund your consumption at a lower discount rate in the future, you're probably spending too aggressively while you're alive.

Cameron Passmore: Or you're basically assuming the growth rate on your income will go up quickly, therefore you buy more life insurance that you can win that lottery.

Ben Felix: Yeah. Yeah. That's another way to think about it. Yeah. I called it a lottery where it's like, if you replace your human capital based on the discount rate of your human capital that's a rational income replacement thing that should sustain your family at the current level of riskiness of your overall wealth, including your human capital. But if you die and want to leave enough life insurance that your family can survive at their current lifestyle with a lower discount rate, that's effectively a death lottery. You're replacing your human capital plus a bonus for the fact that you died, which is realistically what most people do. And because insurance is so cheap.

Cameron Passmore: Because you have high confidence you're able to keep up the growth rate on your income. So just to be aware of that difference in discount rates.

Ben Felix: Yeah. I don't think that's crazy because insurance is so cheap, it's probably a lot better to be over-insured than it is to be under-insured. Now this book did touch on annuities too, but we just left up. We've talked enough about annuities and other episodes.

Cameron Passmore: So bottom line, the older the individual is the less life insurance is needed. And the more bonds included in the asset allocation, the higher the initial financial wealth, the less life insurance is needed. But the more bonds should or could be included in the asset allocation, the more risk averse investor is, the more life insurance is needed and the more bonds in the asset allocation the more desire the individual has to make bequests to beneficiaries, the more life insurance is needed, but this desire has little impact on the asset allocation. And the more an individual's earning power is sensitive to the economy and the stock market, the less life insurance is needed, but the more bonds are in the asset allocation

Ben Felix: Is needed but if you're more risk averse, then you have more life insurance.

Cameron Passmore: Anything else to add to that?

Ben Felix: No, I think that's good for that section. It's a lot to think about honestly. The relationship between life insurance, asset allocation and human capital is not something that I'd thought I guess implicitly, because when we do financial planning we would tend to use the discount rate on the portfolio that a client is investing in to calculate their insurance needs. So I guess implicitly thought about this, but I've never really thought about how all of all the pieces fit together in the way that we just talked about. So you're good to go on to the bad advice of the week?

Cameron Passmore: Yeah.

Ben Felix: So this one comes from the website RIA, which stands for Real Investment Advice in this scenario. Anyways, and here we go with another story. The market's invisible guardrails are missing. This is an article dated October 14th, 2020. So the article starts out with a comparison of driving on the Pacific Coast Highway, which... Have you ever done that before?

Cameron Passmore: Maybe the PCH, oh, what an amazing drive. I haven't done the whole thing, but I've done it from parts aren't in San Francisco and down around L.A. it's unbelievable. But when you drive it you realize that there are a lot of risks. So that's the point of this article is that they're comparing driving on the Pacific Coast Highway and the benefits of guardrails, comparing that to the capabilities of active investment strategies protecting investors. So you know where this bad advice of the week is going. Anyway is in the article they referenced a 2016 article that they wrote and I quote, "Passive index strategies are all the rage. Investors desperate for acceptable returns are investing in funds whose value is directly linked to stock market indices. Unlike active funds, index funds do not perform investment analysis, they're not looking for sectors or companies that offer greater return potential in the market. They do one thing, and that is replicate a particular equity index."

It seems accurate. Anyway, so the current article continues on saying, in 2016 passive index strategies were all the rage, they are the market. Active investors have become endangered species due to poor relative returns and short-term thinking clients, many active professionals have been forced to become less value and more growth oriented failing to adapt ultimately means business failure as clients flee to the growth passive style. Similarly, most individual active investors have similarly swapped active or passive strategies. I'm not sure it's that black and white that there's been that much of a wholesale change, but that's their opinion. Then they link how value investors, the active investors have recently fared versus growth investors who are mainly passive. The duration and magnitude of values on a performance is unprecedented. As the September, 2020 year to date returns were highest for the largest companies and lowest for the smallest. So then the S&P 500 return differentials are stunning, as the saying goes size matters. It appears that size is the bold is all that matters.

They go on, as we wrote the S&P 500 and Nasdaq market cap weighted indexes, meaning the largest companies more to the index than the smallest. Ergo, went past invested by the index, they're mainly buying the largest companies. I guess if you think back to the top five ETS you mentioned earlier, they are certainly market cap weighted and dominated by the large companies. As shown... They go on, the companies with the best fundamental ratios had the worst performance, from January to September value is left for dead. The only thing that seems to matter to investors is market cap. These results demonstrate that value investors are not a viable force in the market. The activities of those who are left are being overwhelmed by the growing preference for passive investing.

In reality active investors have many different views and opinions. They also have different strategies and vastly different evaluations on rich versus cheap. That's the more active investors there are, the more prices are grounded to historical evaluation norms. In other words, active investors reduce volatility and therefore risk. Active investors are the guardrail. The question therefore is at what point passive investors negate the ability of active investors to regulate markets. The massive surge in passive strategies popularity has pushed the market to the brink of instability. Instability can result in price surges to unprecedented valuations. It can also produce tremendous volatility and tremendous price decline as we saw in March. Volatility is here to stay as long as investor preferences remain the same.

There are no longer... Very serious here Ben, there are no longer guardrails on our winding road of wealth accumulation. Those guard rails I've been temporarily put out to pasture in favor of the laziness of passive strategies. Most troubling is so few investors many of which are heavily depending and on their best in portfolios understand there are no guardrails for their wealth. As you would drive on the PCH or the guardrails, you wouldn't drive on the PCK without guardrails, we recommend managing your wealth with the same attention. This article is not a recommendation to divest and sit in cash, whoever it should serve as a warning that the hair raising declines in March and vertical search afterwards may not have been an anomaly, but a preview of things to come.

Ben Felix: All right. So why is this bad advice?

Cameron Passmore: Well, so little of the trading is actually index investments which we've talked about many times. Very, very small part of the overall trading prices are set by active managers by large passive investors are price takers and liquidity providers. And as you've talked about with the... What do you call it? The paradox of skill and more weaker active managers have been squeezed out of the marketplace. So it was getting harder and harder to beat because the better active managers are still playing the game.

Ben Felix: Yeah. And you got to remember the size and scale, or scale and scale of, I can't remember the paper was called now, but the one that Lubos talked about when we had him on last week where as the active management industry gets larger, active managers can be getting more skilled, but the opportunities for a performance gets smaller and smaller as either their fund gets bigger or the active management industry as a whole get bigger. As they shrink though, there may be more opportunities which is actually seems very much counter to what this article is saying. As there's more of a shift toward index that should create opportunities for active managers to generate consistent alpha. Which then with the Grossman-Stiglitz Paradox should push people back to passive eventually, but the takeaway from Lubos was that we don't know how long that would take. We also don't know when it would start, we don't know when active merges would start producing persistent alpha. But in either case that goes completely against what this article is saying. Which seems to be that even for active investors the market is not a viable place based on the growth-

Cameron Passmore: Still passes so much money actively managed. My gosh, it's huge. So many people we know in the industry aren't anywhere near being passive.

Ben Felix: Well, no. Well, Canada is a small part of the overall global markets I guess, but in Canada specifically the vast majority of fund assets are still in actively managed funds. And even in the states it's more 50, 50 than it is dominated by passive. But I think the note that you made earlier Cameron, that the index is aren't the ones doing most of the trading. So even if people are putting their money into index funds they're making up a tiny proportion of the overall trades that are happening in the market and therefore they're not the ones setting prices. This is what Cliff Asness talks about people making exposed narratives to explain stuff that's happened after the fact. This seems like one of those. Because the observations are true I guess obviously, but values had a pretty rough run relative to growth, smalls had a really rough run relative to large.

You sent me a tweet earlier or last week, I guess that there's a chart showing that small cap value is trading at a 60% discount to its average valuation in the post-World War II era, 60% discount to its average valuation.

Cameron Passmore: That's right.

Ben Felix: Yeah. It makes sense to look for reasons why that's happening. I don't think that the index fund bubble concept is the explanation for that, but I understand why people would be looking for explanations. I don't have an explanation. I hope it turns around at some point.

Cameron Passmore: Anything to add to this week's episode?

Ben Felix: No, I think that's good. I think it was a relatively analytically heavy discussion. I hope that the technological revolution was okay for people to think through. And I get why Lubos didn't really want to talk about it because it wasn't that easy to talk about, but I am hoping for the episode that we'll have those animations that can help as we talked through that piece.

Cameron Passmore: Excellent. All right, everybody. Thanks for listening.