Ep. 380: Alex Edmans on Market Bubbles, Investor Biases, and the Madness of Markets

Welcome to the Macrihyde Conversations Podcast. I'm Bilal Hafiz, head of strategy at Macro-Hive. Before we dive in, a quick update following Macrihyde's acquisition by the BGC Group, BGC has launched a new regulated business called Macrihyde Markets. For the first time, onboarded clients can also access execution services via Macrihyde Markets. This new workflow will allow macro institutional investors to benefit from strategy and quant insights alongside access to global liquidity. Please contact Andrew Simon or Gail Mozibrianne on Bloomberg or click the link in the description below for more details on Macrihyde Markets and its service offering. So onto our podcast show. In this episode, we have Professor Alex Edwin's from the London Business School. He's one of the world's leading academics on company's purpose, social value and profit. So onto our conversation. Greetings and welcome Alex. It's fantastic to have you back on the podcast show. It's great to be back, Bilal. Thank you so much for the invitation. I have to say every time I have you on, you've just written a book. So is this that you're just a glutton for punishment? Or what's this motivation for writing this latest book that you've just published? I actually love the process of writing. So why do I do it? There's lots of great academic research out there, which has lots of relevance for a real world audience, but often it's buried. So it sits in academic journals and it's rather technical. And so why write is similar to why I post on LinkedIn frequently is just to share the findings of research with the general audience. And out of all the books that I've written, this is the one is the most fun. So it's about how emotions affect the stock market, what causes the market to saw one day and crush the next. But hopefully it's not just entertaining. It's also useful because nowadays many more people invest in in the past. We now have the tools to invest in anybody's pocket. You don't even need to log on to a computer. You can just thumbs up your way to Robin Hood. So this is something where the stakes are high. So hopefully this is something both engaging, but also practically useful. And this book, you know, you kind of look a lot at how investors engage with the market directly in some of the kind of recurring errors they make. Like that topic and not, you know, not something else, you know, around other, you know, you have a number of different fields of research that you have. Why this particular subject? Two things. Number one, because the evidence suggests that these errors are actually quite pronounced. So you might think, okay, it might only be amateurs who make mistakes in the market, but even professionals who are paid millions to invest billions, they can suffer from overconfidence, over reaction and under reaction. And so this matters for the people that we trust to manage our pension, they might make mistakes. And then what do you do where somebody investing for the future? Are you going to trust these people or go into an index fund instead? But the second reason is the market is just a laboratory for decision making in general. So the same mistakes that we make in the stock market, such as overconfidence and over reaction, we exhibit in other fields as well. But the market is such a great laboratory because you have loads of data, you can see the investment performance of an investor or a fund manager. And by having data and showing that we overreact and under react to certain things in the market that will also suggest that in other fields, we're also misreacting to information. Yeah, and the book, I forgot to mention, it's a madness of markets and it's available, you know, everywhere, which will talk more, more around towards the end. But I like the way you structured the book, you know, you basically have kind of three broad sections. One is kind of a set of chapters linked to overreactions, how we overreact is as investors under reaction and then misreaction. And then you have kind of a concluding part in terms of takeaways that we have. So on the overreaction side, you go straight forward and you talk about bubbles. And, you know, there's a chapter, I think the chapter one, I think at his bubble trouble, why we all go crazy at the top. So let's start with that one. And, you know, at the moment, we're an interesting time of markets at the moment. Many people think we're an AI bubble. But if we kind of look at the broader sweep of history and the academic work on this, what's your reasoning behind kind of why bubbles happen and how it's linked to overreaction. So what is a bubble? So this is when a particular market or sector can get hugely inflated. So maybe there's a tulip bubble a couple of centuries ago, the tech bubble in the late 1990s. People suggest there might be an AI bubble right now at the start of this decade. There was an electric vehicle bubble. So here you have some sectors where the valuations are too high. So why can really smart people make some incorrect decisions and over inflate their value. Well, behind any irrational behavior, there is a grain of rationality behind it, which is why such behavior can keep persisting. And in the markets, you think, well, let's respond to information. Don't just sit there, do something, you snooze, you lose. And there are trends in the real economy. So the internet did start taking off in the 1990s. Electric vehicles are absolutely the future of transport given climate change and artificial intelligence that has such potential that we are actually scared of what the potential could be. However, what the market might not realize is that there often gets the direction right, but the speed wrong. So let's give an example. So in 2000, Cisco became the most valuable company in the world. And you might say, well, that makes sense. They made routers and switches. That is the foundation for an internet economy. But the valuation that it had, which was a price earnings multiple of 190, that only made sense if Cisco could grow sixfold within the next five years. Now Cisco did grow sixfold, but it took them 25 years. And that's what I mean by the market gets the direction right, but the speed wrong, the market was correct that the internet was the future, but maybe the speed of internet adoption was not as fast as people thought we might say the same for electric vehicles that will be the future of transport. But we don't yet have the charging infrastructure or the battery technology. And with artificial intelligence, there might be some slowdown in terms of regulation and some pause before we keep advancing. So people will think, okay, something will be the future. They get excited about it. They do this for good reasons. They're reacting to information and trying to be current, but they may get overly excited. And as I say, we see this in all areas of life, so markets are just a laboratory. If you go down to any football stadium over the weekend, the manager loses three games in a row. You call for him to be fired, even if he's had five great seasons, anybody who manages a fantasy football team, if a player does well, you transfer him in, if a player does badly, you transfer him out. Again, we think we are doing something useful. We're acting on information, not realizing this might have been one good or bad game. You know, one of the things that kind of comes to me when I was reading your book and, you know, this is kind of me throughout the whole book is, I immediately when I hear that, I think, okay, how can I implement this now? And so on the one hand, when I hear that, you know, the price has gone too far away from some measure of fundamentals, when you're there in real time, you know, often it's hard to discern what is the right fundamental value. So, you know, perhaps the PE ratio, say in the case of Cisco, you know, 50, you thought, okay, this is crazy. So it should come down and it doesn't, you know, the PE goes to 75, 120, so there's this kind of overshoot that happens. So is this a case of just understanding these over reactions for the sake of like understanding your psychology, know yourself and so on, or, you know, can you actually implement this in your portfolio? You can implement it with some caveat, so let me discuss the implementation and let's then discuss the caveat and who did just the caveat applied to most. So Dick Taylor, who won the Nobel Prize about 10 years ago, one of his most famous studies looked at the profitability of a contrary investment strategy. So what is that? Well, if you take all stocks, let's say on the flip seat and look at how they performed over the past three years. The ones that did the worst will call them the losers. The ones that did the best, we're going to call them the winners. And if we buy the losers and sell the winners and hold them for another three years, we find reversal. So recent losers now become winners and recent winners now become losers. The idea is that a winner is a stock that has a moderately good news, but the market overreacted, it got too excited, so the future path is down. So that suggests a simple strategy or being contrarian buying what's done poorly and selling what's done well. So where is the caveat? And if it's as simple as doing that, just looking at the past three years returns, why don't the smartest investors in the world put this into practice? Well, one smart investor did so and his name is Julian Robertson and he managed Tiger Global asset management, a very respected hedge fund in the 1990s. And he looked at tech and just as you were suggesting, he saw the price earnings ratios work quite crazy. He did the seemingly sensible action of shorting tech. However, whatever craziness and irrationality and hype caused tech already to be overvalued, that got even worse in the short term and the price earnings ratios inflated even more. So this go hit 190. And so what was happening was that he was his fund was bleeding losses and his investors were saying, well, you're just losing me money. Your competitors like George Soros is staying in tech, so I'm going to move to him. And obviously Robertson a plead with his investors saying, please stay with me. Investing is about being patient and looking for the long term, but they would rationally respond to the losses and think, well, maybe he's just lost his neck. Maybe he was a great investor in the old days, he just doesn't understand the value of the internet economy. And so his fund got liquidated in March 2000 and almost right on cue, the tech bubble collapsed. So Robertson was right, but he was not around to enjoy the victory. So the complexity here is that if you are a professional money manager with lighting. capital, then you might not be able to invest and take advantage of overreaction, because the overreaction could get even worse before it got better. But then who can take advantage of it? It might be amateur investors, like me or like the household saving for the time. We often think that investing is a reality game, that it's all about having inside information which amateur doesn't have. But one thing that you do have is patience and a long runway, because if I'm investing my own money, not other people's money, I might have a 40 year horizon if I'm investing for my retirement. And therefore, even if I don't know that tech has reached a peak, I might be able to sell out now, because as long as in the long term, the future path is down, I can withstand any short and volatility. And that's well articulated there. Another form of overreaction you talk about is what you call mood music, how feelings cloud finance. That was a really fun chapter I found in your book. So perhaps I'll let you explain what you mean by all of this, but it's kind of not what you think investors or professional investors would be subject to, but it turns out they are. So if you could just elaborate. Absolutely, this is how I got into behavioral finance myself. So I never set out to do a PhD in psychology or market emotions, but it was the evidence that led me to this. So my PhD was at MIT in the US. It was a great privilege to study there, NMIT being MIT, it argued that the stock price was dependent on quantitative mathematical factors, you project future dividends, you estimate the discount rate and you plug this all into a spreadsheet. And that is true on the whole, but I think it misses an important piece of the picture, which is emotions and sentiment, and I've seen this myself working at Morgan Stanley in investment banking in London, but particularly on the trading floor in New York City. And what I wanted to do is to show that emotions affect the stock market. So what I looked at was the effect of World Cup elimination. So the idea is that in England, get knocked out of the World Cup. This causes the whole living to get depressed and it may well be that the market goes down. Now you can't just look at one country and one World Cup because that could just be luck, so my causes and I studied 1,150 football matches played by 39 countries. And what we found was systematically, after a country is eliminated by the World Cup, the market falls by about half a percent the next day. And that is after controlling for other factors, like movements in the broad global index or what happened yesterday in case there's autocorrelation. And half a percent that is 15 billion pounds wiped off the market on a single day. Now what I find is so surprising is you might think, yes, my mood is affected by emotions. I am a long-suffering football fan myself, but I know how hard it is to, when I was start going to school on Monday morning and my team lost and my friend's school's teams won, then that was really painful. But you might think, okay, now I'm professional, I am going to put my game face on. So if I'm an investor, I'm going to just set aside my emotions and I'm going to be rational in how I evaluate a company, but you're human. And as a human, it is hard to compartmentalize other parts of your life. So it doesn't matter whether your emotions are affected by a football defeat or your kid being sick or an argument with your wife. If you are at work and you're evaluating a subordinate for the one year review, you might not be as positive or if you're hiring somebody, you might be harsh in the interview. And what are you doing as an investor, you're evaluating a company, you might just be more skeptical about the new strategy that they've announced. And this is why we're finding the effect feeds through into something as seemingly rational as the stock market. Yeah, it's kind of echo some of the studies I've seen in terms of the time of day you get interviewed for a job or something or the time of day you get sentenced by a judge, that can affect the outcome, even for identical cases. Now I was just wondering, does it work the other way as well? The winning team gets a boost in the stock market afterwards. Sadly not. So sports only have a negative effect on your emotion. So a loss causes a significant decline in the national index. But afterwards country wins. We don't find anything positive. So this is a bit bizarre because why isn't this leading to national jibolation? There could be a couple of reasons. So number one is that for many games when you win, you are just through to the next round and you could still get eliminated later, so England beat Mexico, but then lose to Argentina. And also the other reason is that supporters are very optimistic about their team's chances of winning. So for 60 years, England have shown up to every men's world cup, convinced this is going to be their year. And even if you have say a pretty successful manager like Gareth Southgate, people will still say he's massively underperform. So your expectations are so high, even if you achieve a great victory, people might have said, well, that's what we expect it anyway. Yeah, understood. You know, another thing you also highlight in your book is this idea of news that should not really affect investors, but does, and you talk about names and other sort of forms of news that shouldn't really affect investors. And can you sort of explain more what you're trying to identify here? Absolutely. And this is a nice connection to the football papers. You might think, okay, this football paper is fun and it's entertaining to know that football matches affect the stock market, but why is this relevant? Because nobody's going to start a hedge fund based on this. But what it highlights is how the market reacts to irrelevant stuff that should not drive dividends and profits and discount rates and yet still prices move. And so given that the market can respond to something as irrelevant as a football match, what are the irrelevant things might it respond to? And these are factors such as name changes that you're mentioning. So earlier this year in April and all birds, the trainer company may be made of sustainable wool. They announced a rebrand to new bird AR, they were going to move from shoes to artificial intelligence. I kid you not. And the market just bought it, the stock price went up 582%. Even though a shoe company has no expertise in artificial intelligence, so this was just a massive overaction to something which was not really news because it was just the rebrand. And this was not the one time thing because it's happened time and again, so in the internet bubble, if you change your name and your new name had a dot com on it or a dot net, the stock price went up on average by 74%. Again, even if there was no real change in your business strategy or any substantive difference. So in all of these cases, the market will overact to something flashy and loud and salient, often forgetting to do the analysis of has something fundamentally changed. And in those cases, is it a situation where the market rallies and then it dissipates unwinds the rally very quickly or does it persist for a period of time? It does unwind. So with all birds, the stock price has gone all the way back down to before the rebrand level, even though they actually did subsequently appoint a CEO with artificial intelligence expertise, they felt well, the CEO has no even if they're on an expert that what they're working with is just a shoe company. Also, this was the case with dot coms, except actually if you drop dot com from your name after the bubble burst, you're also got another boost. So if you're always able to keep it up with the market, then you are able to fool people for quite a lot of the time, also this game is played with fun. So if you are in a time and where growth investing is really popular, then just call yourself an adventurous fund or a aggressive strategy and then in value is doing well, call yourself cautious and and similar study found that if you did this, even if your portfolio holdings did not change, investors go by the label and we went laugh about this, but we actually see, well, there is some kind of logic to it. We have scandals like the green washing scandal where funds will call themselves sustainable and the reason why regulators had to intervene is that people look at labels and there is some rationality behind it in a world in which we have limited attention. We're not able to scrutinize the investment process and the holdings. We will trust the label and sometimes that trust is is warranted, but then unstrupulous people may exploit that and give themselves a force label or name or name. One thing I guess connected to that is this whole notion of virality. If you believe in hurting, or hurting can cause markets to move in a certain way. The hurting could just happen from anecdotes you hear from your network and then you act on that. So you're not necessarily doing the digging around underneath. Now how does hurting actually happen in markets? I mean, is it quite prevalent and is it linked to the bubble side as well that we talked about at the beginning? Yes. The hurting is a very important force in markets and one that contributes to the sow's reaction. Why? So how will defenders of efficient markets state their case? So efficient markets is the idea that the market is not affected by emotions. It is purely driven by fundamentals. What they will say is they will acknowledge that investors make mistakes, but they will argue that these mistakes are in different directions. So maybe I am an Elon Musk fanboy and I'm going to buy Tesla and you don't like his politics or you're never going to touch Tesla, we're going to cancel each other out. However, if there is hurting, what it means is that when we make mistakes, we all make mistakes in the same direction. Why? for me. Job there. If I'm into crypto, then I do. tell you, then you think, oh, well, there's this great new asset which my friend has made money on. Let me get into this myself. So why do we do this? Are we just like lemmings who follow each other blindly? No, there is some sense to this. They behind again, any irrational decision. There is some grain of rationality underneath it. And it may be that we heard because we want to learn. We are open-minded. And if there are new assets which are available, I want to hear about this. And I will then follow somebody I trust and this might be my friend. But what you might not realise is, well, what crypto returned last year, that might not be relevant for me this year because past performance is not going to necessarily predict the future. You might not also not realise that you are hearing a selected sample. So maybe I made money on crypto and I'm going to tell you about it. But there's other friends who traded crypto. They lost and they're obviously not going to admit it to you down the pub. So you actually are seeing some selected information. And so what we end up doing is we are mimicking others rather than looking at the large scale data on where the crypto is popular. And so why is this problematic? Well, there are studies which find that even if professionals just to copy other professionals, it doesn't improve their returns. If we listen to what friends we have from our networks, again copying them does not enhance our returns. Now this is not to say that in all cases, every time we listen to other people, it is bad and we should just blink ourselves, it depends on the relevance of the information. So I mentioned that what I made last year on crypto is not relevant for your decision to invest today. But let's say you're learning about something else in terms of finance. I just refinanced my mortgage and I got a rate of 4.9% hard to do probably nowadays. But then you learn about this and that is relevant to you because maybe that 4.9% rate is also available to you if you are in a similar situation with your loan to value. And so what I studied looked at was school teachers just passing on information about mortgage refinancing to their colleagues. These are colleagues who are not investors for in their profession. They might not be paying attention to interest rates every day. So actually listening to somebody who's a bit more savvy than them, that could be valuable. So think about well, what are you learning? Are they an expert in this issue? And it may well be that if you're a teacher, not of economics, then just learning from somebody who knows a little bit more about you could be useful. And is this information relevant for me today? Or is it something that just happened in the past? OK, no, that's great. So we've covered a bunch of stuff on the other reaction side, you know, prices of shooting, that's kind of extrapolating price too far, effects of mood sort of news that we shouldn't really affect us like name changes and then this kind of herding type of mentality that we have. On the flip side, and this is probably not as appreciated as much as you have a whole bunch of chapters on under reaction, how we underreact to relevant information, you know, the first sort of chapter in that section is slow on the uptake when markets snooze on the news. You've got great knack for titles here. So, you know, markets again, you know, we're sort of imprinted to our efficient. So everything should jump immediately. So what are you talking about here, like when do prices move too slowly after news? Sure, so on the one hand, we do have the market overreacting to information that it should not. And on the other hand, the market under reacts to other information, which is highly relevant, but it doesn't fully recognize its relevance. So how can that be? Well, this is linked to confirmation bias, which I've looked at in the prior book. So confirmation bias is the idea that we have a view of the world. And if we see something that contradicts that view, then we tend to downwait it. So an example is in 2006, Amazon released S3 and EC2, which were the first building blocks of what later became Amazon web services. And the market shrugged because the market thought that Amazon is just this online retailer of books and CDs, they didn't really know what cloud computing was or that it would have any impact. And so we'd ignored this and it wasn't until nine years later in 2015 that Amazon released separate line items for its web services cloud computing that the market finally caught and don't. So it suggests that even if there was news and even we know about it because it is salient, we might not take it into account if it contradicts our world view, we might just downwait it because we underappreciate its relevance. Now, also, we might have something which we underact to because it is just not salient to begin with, it might be hidden information. And this is some of my early work on intangibles that you and I have talked about in the past. So something like corporate culture, if a company treats its workers really well to the highly motivated and highly productive and they're willing to express diverse viewpoints without fear of failure, this is really good for a company, but because there's no big press release about it, unlike a rebrand, it may well be that investors are unaware and if they're not aware about it, then it's not going to be priced in for a long time. And on the intangibles point, I mean, this kind of goes back to the, you know, chapter one, which is like, you know, you want to always have some kind of sense of valuations. So you look at price earnings or price to book and if you want capturing intangibles correctly, you might be too early to say the stock is overvalued. So do you often find the market actually is capturing intangibles before investors are? Yeah. So actually, the market is quite slow to value intangibles. So what I looked at an employee satisfaction is that it takes the market about four to five years before it fully incorporates the value of employee satisfaction into the stock price. So even though this might be public information, you can look at things like the 100 best companies to work for in a marathon list, it does take several years for the market to fully appreciate this. And this can be true for other measures of intangibles. So something as simple as R and D expenditure. So how much does the company spend on research and development? This is something which is visible, but it is expensive. It is typically not capitalized and added to the balance sheet. So many investors just think, well, this is a cost it's going to reduce the bottom line, but if you did the very basic strategy of capitalizing R and D, so treating it as if it were an investment, non-expense and investing in the companies with a lot of accumulated R and D capital, this would also have significant outperformance over a couple of decades. And another thing you talk about is a C-suite secrets. And this is kind of information you can gather from management, you know, in whose disclos information in non-conventional ways. So what have you found there? Yeah, so one big factor that the market under-reacts to is information about the chief executives. So this really matters because the CEO is in charge of the company and you can get quite good measures of the CEO. However, the market might underestimate just how good those measures are. So when I say measures of the CEO, what are we trying to measure? So I think there's two things that you can measure. The first is the CEO's information. So the CEO knows more about their company than anybody else. They know if the firm has skeletons in the cupboard or the firm is about to hit the jackpot. Now it's hard to look at some public statements because the CEO will typically put on a positive spin. So if they are on an analyst's call, they will be pretty optimistic. So what you want is the equivalent of a poker health. So this is a small signal just to show is the CEO truly confident or actually bluffing. And one good tell is the location of the annual general meeting. So why is that useful? So every year, a company has an AGM and most of this is routine such as the votes on auditors. But at the end, there is an open Q&A session. And in some cases, the Q&A can be quite aggressive. So recently with Shell, they had some climate protesters who said go to hell, Shell. They all got up and started charging this to the tune or hit the road jack. Now, you can't stop these people attending the meeting because it's a relatively shareholder that they're allowed to attend it. And maybe you don't stop them. Because if you're a CEO and you're truly confident, you want negative questions because this gives you the chance to set the record straight. You could say, well, actually, you may not know this, but we cut our emissions by 50% over the last three years. So only if you know that there's problems in the company, will you want to get away from your shareholders? And so there was a company in Detroit, Michigan, a car company, which held at shareholder meeting in MacAllen. Where is that? Well, this is the southernmost tip of Texas. You cannot fly there. You have to fight a Houston and then drive for 300 miles. So this is really painful for the CEO. So why would he or she want to do this if they just didn't want shareholders to attend? And so a strategy finds that if you were to sell a company after it holds its meeting in a remote location, the stock price typically falls by 7%. Not over the next year, over the next six months. So this is significant under performance around 15% per year because this is a poker tell about the CEO's information. Now, the second thing that you might want to know about the CEO is not their information, their confidence, but their character. So there are many scandals of CEOs doing bad things like the title of CEO who charged a million dollar birthday party to the company, but often you only hear about these scandals after the fact. So can we predict them before the fact? And one thing that people looked at was the use of the corporate jet. So this on the face of it. may not be a bad thing because a corporate jet allows you to go to a meeting and negotiate a full throttle because you're fresh, but other times it could be used for corporate excess. And what I've studied found was that companies with a CEO use as a corporate jet this leads to underperformance of we $100 million per year. So this is massive. When the cost of a jet is much smaller, in particular, even if you were to just rent a jet for $50,000, you have to disclose it, and so it's in the sample. So how can something which costs just $50,000, lead to $300 million per pound dollars of underperformance? Because it's the tip of the iceberg. Instead of CEOs who are using the corporate jet, are also perhaps the CEOs who's plenzu on the board and not monitoring him or her properly, they might be overpaid, engaging in empire building acquisitions. So this is a subtle signal as clever as the shared meeting location which tells you the character of the CEO. And have there been any studies now in the age of AI where you get AI to try to read facial expressions and the CEOs sweating in all those sorts of things? Not yet. And so I think this would be a really exciting frontier for AI. So what I know is something similar. So what people have tried to look at is your vocal tone. So there's something called layered voice analysis, which is a bit like what a lie detector would do. And so what it looked at was not the positivity of what a CEO says because anybody can put on a positive spin, but the tone. And in particular, if you were almost trying to hard to be positive, you were straining. It's a sign of cognitive dissonance that you're positive when you know deep down that you are actually not deserving of it. A bit like trying to hard to convince somebody that you're telling the truth and you're lying, then that was something which was linked to future earnings restatements. The idea there being that the CEO is hiding something which is truly problematic. But in the future, you can look at things better than voice. It could be facial expressions as you suggest. It could be something as simple as in an annual general meeting if the CEO answers one way and the CFO just doesn't look him a herb in the eye. Maybe they're not actually singing from the same song sheet. It could be body language. So lots of these things are useful. But the message here is general read the person. Don't just read the numbers. So this is what I want people to take away from the book is not just the specific trading strategies of looking at the shelter meeting locations or the corporate jet, but in general, how to evaluate a company is to see what other things can we look at, which gives away what the CEO's information is or what the CEO is like as a person. Great. Now, the third part of your book is called misreaction. And one of the things you start with there is how markets add up things incorrectly. I mean, this kind of seems wild in some ways in terms of, you know, surely the market can kind of get simple things right and you're talking about how investors or markets make simple arithmetic errors. So what's going on here? Yes, let me start with an example. So I started my career at Morgan Stanley in 2001 and at the time the palm pilot was all the rage. So you had them on your desk and you'd bring them to the meeting not because they were any useful, but because they were signed that you were technologically sophisticated. And so this was owned by a company called Threecom, a conglomerate and it decided to float a palm on the market. And because of the huge enthusiasm of palm, the stock price sawed so much that palm itself was worth more than Threecom as a whole. And this is crazy. The whole was worth less than the sum of its parts. If you were to buy Threecom, you would get palm, not for free, you get palm for net, you get the other businesses for negative value because when you're buying Threecom, you're getting palm and all of these other businesses and actually, you're buying palm for much cheaper than if you bought it outright. And so this is a simple market mistake. So how can the whole be less than the sum of its parts? It was again because of enthusiasm. And we see the failure to add up in many other areas, so not just at the single company level, we see this at the sector level. So in early 2021, if you were to sum up the price of all the electric vehicle companies, this led to an implied valuation of the EV industry, which dwarfed even the traditional car manufacturer such as Toyota and GM. And this paid both cents in 2021, why? Because the EV industry was just in its infancy. So what is going on here? So why can people make such big mistakes? It is narrow frame and we focus on individual things. So in palm, it was the individual company. We're so excited about palm pilots. We're not realizing, well, maybe there's a better way to buy this, which is to look at Threecom. And similarly, when we're looking at electric vehicles, we might fixate on, say, neo, and we might think, well, this is going to be the winner in the future. We don't realize what there's lots of other electric vehicle companies. And we think on all the winners in the future, maybe the industry will shake out and only three of them will survive. But every car company, every electric vehicle company, was priced as if it would be the ultimate winner, even though not the industry would not be able to sustain so many champions. On car one, I mean, maybe it's not the perfect sort of analogy. I mean, is there a case we made that when you get some new type of product, like an electric car, there's a risk that we may be, you know, lumping it with a traditional sector, whereas it could actually be a category breaker, like, you know, I'm thinking about phones, you know, the iPhone was actually not a phone. It was actually a computer with a phone. And so we got kind of, there was a category error in which case the valuation should be different. You know, how would you think about something like that? Yeah, so that is true. So if there was a truly new sector, which is going to achieve much more than what that sector has done in the past, then you should not limit the valuation by the valuation of the traditional industry. But for cars, it's not clear to me how much greater this will be is that we all need transport. But given that maybe we have more remote and telecommunications, maybe the future, we're going in the metaphor as we don't even need to go anywhere because we're going to be putting on our our metaglasses. Then it's difficult for me to know what else a car can do other than move people around on microphone, which has now become a computer. And so I do think that the valuation of the traditional car industry was a useful benchmark while the tradition, the value of the old dumb phone was not a good benchmark for smartphones. Yeah, that makes sense. Yeah. Another thing you talk about is how we can often look at wrong targets. And then you know, a classic one is in the entry level that you anchor yourself to what you bought the stock ads or things like the one-year highs or 200-day moving averages. There's all these sort of things of round numbers. In FX markets, there's often the case, you know, with Dalian goes above 160, that's significant for some reason. You know, I think you call it irrelevant, I think in the book or something. So what's the psychology behind this? Yeah, so this is a strong psychological fact and one that I find even myself really difficult to break, which is we anchor on wrong things. So with the stock, you're always anchoring on what you bought it at. So if I bought a stock at a hundred and it goes up to 120, there's a tendency to sell our winners. We want to take a profit because when we do that, it feels good. Then we are happy with our decision to have bought stock at a hundred. A while ago, even if it might be going up even higher, we decide to sell. But on the flip side, we're very reluctant to take a loss if we buy at a hundred and the stock goes down to 80. Even if we are worried it could go down even further, we are not wanting to sell because we want it to bounce back. If we do sell, this is just admitting to ourselves that we made a bad decision a few months ago. And so what we end up doing is we end up selling our winners and running our losers, which is a bit like cutting our flowers and watering our wheat. And why this is particularly problematic is that in the short term, you have momentum, which is the opposite of reversal. So short term winners continue to outperform and short term losers continue to underperform. But it's really difficult for us to shake off our behavioral bias of what we entered at that we are still exerting this behavior. So what I do in the end of the book is I give 20 tips on how to try to overcome these biases and put the insights into practice. And one of them is just to imagine your entire portfolio was cash. And then to ask yourself, where would you invest today? And don't cheat. They don't look at your portfolio at the moment. And chances are that you would not be in the same investments. Maybe you will not be in that losing stock. The only reason you're in this stock is not because you think it's a great investment, but you just refuse to get rid of it because you are anchored onto what you paid for it in the past. That's great. I mean, before we go on to your checklist, you do also talk about overconfidence, which kind of seems like the fundamental floor of humanity in some ways. So what's the evidence around overconfidence? Yes. So what is the root of overconfidence is that when you are investing in the market, it has to be that you have some unique insight, which allows you to beat the other average investors. So often investors will think, well, let me invest in artificial intelligence because I know this is the future. I've used it myself and can see how transformational it is. But everybody else knows this. It may well already be priced in. So you need to say, I'm going to sell out of tobacco because I know that this is an industry in decline. Again, most people know that and therefore the price may already have fallen. But often people think we have some unique insight that nobody else has and allows us to beat even the professionals who trade for a living. So the question is, well, when and retail investors, their amateurs, like you and I trade, are we trading truly on insights or are we trading on overconfidence? And what a study found is it managed to get unique access to 78,000 brokerage accounts. And so it looked at all the trades that Investor did. Not the self-reported ones, like the crypto example earlier where you have the problem of people only report their winning trades. He looked at all their trades and he was very clever. So if he found that after selling a company, the stock price went up. That doesn't mean it was a bad decision to sell because maybe you sold to send your child to university or put on a deposit for a house. So he looked at a round trip trade where you sold in order to buy something else. And what he found was the stocks that were bought systematically underperformed, the ones that you sold by about 3% per year. So you would have just been better off doing nothing. So how is this linked to overconfidence? We think we're trading on great insight. I should sell this company and buy the next one. And yet we might not actually have any insight at all. Or even if the insight was relevant, it's already priced into the stock. - That's great. And you're round off the book. You really alluded to this with 20 practical guardrails. I mean, do you want to kind of highlight some of them that we could put in place to reduce some of the negative effects either from over-reaction, under-reaction or misreaction? - Absolutely, and maybe I'll just focus on one which is most related to over-confidence given we just discussed this. And this is the tip to know your edge. So what I mean by this is when you're trying to trade and if you're doing something over, then just holding a passive index fund, then ask yourself, well, what is your competitive edge which might allow you to beat the market? So for many people, they think, well, my edge might be knowledge. You might think, oh, I'm a doctor. And if I'm a doctor, I understand that this pharmaceuticals company makes beta blockers. And I understand what beta blockers are. They were a drug to address hypertension. And I can see that high blood pressure is going to be an even greater problem in the future. I see this in my patients. I can see trends in lifestyle. So you might decide to buy this pharmaceuticals company, but you actually don't have a knowledge advantage because you have no idea on the production costs of this drug, on the marketing expenditure, on what competitors they're doing, on whether there's going to be regulation, on prescription drug pricing, and so you only see a small piece of the picture. So a little bit of knowledge is a dangerous thing. It can lead to you being overconfident, not realizing that there's many other pieces of the picture that you were just not seeing. So I would say for most investors, we do not have a knowledge edge. And therefore, trading individual stocks might be quite dangerous because you're trading against professional investors who have their team of analysts who look at the stock every day, they might have direct access to the CEO, or at least the investor relations team, and so they're more informed than us. But then does this mean there's no hope for amateur investors? And absolutely not, because our edge may well be our longer horizon, as I alluded to at the start of our conversation, if we are investing for a 30-year horizon, and we are not concerned about short-term turbulence or outside money bolting at the first hurdle, then we can take longer-term positions and be contrarian. And this is one thing that I did. So at the start of 2009, I sent an email to my students, which probably would get me fired nowadays because it was investment advice. I said, well, I'm gonna buy lots of equities. I'm gonna increase my equity waiting by 20%. Why? Because we are in the financial crisis. And we may not have hit bottom yet. Maybe things can go worse before they get better. But I have a 30 to 40-year investment horizon, so I don't worry if they're short-term turbulence. And it may well be that professional investors are worried, so this is why stocks may still be underpriced. And this was a direct application of something I taught in class, behavioral finance, and the limits to arbitrage. And that has turned out to be a good bet because until 2009, at the following years, equity markets did rally significantly. Then I had no special stock picking inside. It was just greater endurance and deep pockets. - No, that's fantastic. Okay, so with that, actually, while I have you actually, let me put you on the spot and ask you a question about AI and education, 'cause your day job is education. I often get so many questions from people on the impact of AI on their own industries. And so one area people are talking a lot about is what are universities gonna do? What is the natural academic research in the face of AI? And so do you have a take on this? - Yeah, so I think AI is a substantial threat. And I think universities are not responding anything like they should to it. And not just universities, but professional bodies. So I'm also the president of the Western Finance Association, which is one of our, we organize one of the largest conferences. So why is AI problematic? First, the in the generation of research is that people can turn out papers really, really quickly. So it was a famous Chicago researcher who's written 200 papers this year. They may nearly always be AI assisted. And why is that problematic? Is he might think, well, shouldn't we use the best tools available? Well, not necessarily because what this may do is it just expands the reviewing resources. So in order to get paper published in the academic journal, it needs to go past peer review. And if I was just to produce 200 papers, one or two of them might just get lucky, even if they're bad papers. Peer review systems are not perfect. I can just play the numbers game. So that actually bad papers will get in just because we don't have enough peer review resources. On the flip side, you could use artificial intelligence for peer review. And again, why is that a problem? Because you might think, well, doesn't this enhance the quality of a peer review? But it might not. Because why do I ask a particular expert to review a paper? Because I really trust their opinion. And that's often a subjective opinion as to whether this paper will be impactful in the future. It may well be with 2011. And my paper on sustainability on corporate culture was published then, even though sustainability was not a big thing, you need to be able to make that judgment call. But if we're just outsourcing it to AI, then actually, we might just have very regression to the mean type of responses into truly innovative research, which AI cannot understand will get turned down. So I've actually seen this in a conference that I've organized, which is going to take based next week, where there are many reviews, which were clearly AI generated. Because there were several pages long. Nobody's going to spend so much time writing a review for a conference, not in that kind of journal. And then I proposed this on the board agenda. This is an organization I'm not yet present of. I will be in a couple of years time. I said, we need to have a policy for AI. And then the response was, well, we might not be able to enforce the policy. It's debatable, whether it's going to have an effect. And I would like to say, it's debatable. Well, that's the point. Have a debate about it. Don't just deny it's going to exist. So I think people may well either underestimate the effect of AI, or they might think, well, it's not my problem. I'm only on the board of this organization for another two years. It's going to be somebody else's problem. Or they just don't want to envisage your world, which is different from the world that has led to them having a great career for the last 30 years. So the under-reaction that we referred to early in the discussion, I think we do see this in terms of AI. And what advice would you give to recent graduates, then? Because one thing we are hearing, and I'm just fine with saying it dirty, is lots of people have graduated. They're looking for jobs. They're struggling. You're entry-level jobs, kind of hearing the sorts of everywhere. There's kind of a dirt that there's a lack of opportunities. So what advice would you give to people like that? They spent all this time studying, they enter the job market, whether it's the academic job market, or the private sector. What advice would you give them? So I might then try to apply my own advice of no-your-edge to myself when I answer your question. So I think you are hoping for an answer in terms of providing career advice to people who are not able to get a job and watch what they be doing. I don't really know because I've not been in that position and I'm not a career advisor. But what I do-- That's a good point. That's very self-aware there. I'm impressed. But what I can more advise on is the use of AI in teaching and education and learning, because that's more directly related to my job, is that if you're a young person, just to try to resist the temptation to use AI as much as possible. So yes, you could use AI to write an essay, but then you're just not developing the critical thinking skills. So the other approach is to write the essay entirely yourself, maybe use AI to polish it afterwards, but resist the temptation is a bit like getting somebody else to do your homework, do it yourself, because what you learn, the whole point of going to university is the process of learning and critical thinking and not the outcome. And yes, in the short term, I get my essay in. Maybe I get an A for the class. But maybe why they ask some people not getting jobs right now is that when it gets to the interview, then the interviewer realizes that without the AI, well, this person actually doesn't know how to answer the questions of a bit like a CEO who wants to have the AGM in McCallan Texas. So to have the skill of being able to think for yourself to respond to challenges, if indeed in a class, you have the opportunity to present a trade idea. It does so. I give students the opportunity in my class. It is not graded. So if your goal is just to maximize your grade, don't do this because it's a waste of your time. But if your goal is to be employable in the future, this is a unique opportunity. You can get up, present a trade idea to the rest of your classmates and your professor. I will give feedback on your presentation skills privately afterwards. And that idea to present into something which I don't think I'm going to be able to. be outsourced by AI, so if you're pushing yourself outside your comfort zone and developing these skills, critical thinking, presenting, negotiation, forming relationships, these are things which will do you well, I think, for the next couple of decades, even if AI becomes more powerful. Yeah, it's fantastic advice there. Now, just around off, tell us how people can get hold of the book and if they did want to reach out to you as well to learn more about the work that you're doing as well, what's the best way for them to do that? Thanks so much for asking. The book is called The Madness of Markets, why smart investors make crazy decisions and how to exploit them. And yes, as I mentioned earlier, out of all the books I've written, this is the one that I had most fun writing because the stories are very engaging, the studies, the academic research on things such as football and corporate jets, but it's also important and actionable so it's not just entertaining, but hopefully useful. And beside that, I'm very active on LinkedIn and under AI demands, AED, M-A-M-S, I post pretty much every day and I try to post not just my own research, but research by other people which I find interesting and relevant. And indeed, it was the reaction to LinkedIn posts about research that led me to writing books so that I can bring more systematic and more detail about all of the great research which has done out there. I'm also an ex on AI admins, but I spend more time on LinkedIn just because it allows more for longer-form posts. That's fantastic. Well, with that, thanks a lot, Alex. Keep up the good work, and hopefully I'll have you back on with your next book in a couple of years as well. Always a pleasure, but I'll thank you so much for interviewing me. [Music] This audio and video is made available to you for general information purposes only and does not constitute the recommendation of any investment product to act or not to act in any way whatsoever and does not represent an offer or the solicitation offer to buy or sell any securities, financial products, or related financial services, or to adopt an investment strategy. To the fullest extent, permitted by applicable law, Macohive excludes all representations or warranties of any kind, including any implied, warranty, of merchantability, satisfactory quality of fitness, or particular purpose. To the maximum extent, permitted by applicable law, Macohive excludes all liability for any losses, whether direct or indirect, that may be suffered as a result of reliance on this audio or video. 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