IL54: Why Smart Investors Keep Making Crazy Decisions ft. Alex Edmans

0:01 I'm not so worried about missing out on perhaps future gains by not selling at the absolute top because I know that it had a really good ride. What I want to avoid is if we are in a bubble, we are in a big market delusion, and the whole market then turns south as it did for electric vehicles in sort of 2022, 2023.

0:24 Welcome to top Traders Unplugged. In markets, success doesn't come from predicting what happen, comes from being prepared for what you can't predict. In each episode, we go deep with some of the world's most thoughtful minds in investing, economics and beyond to understand how they think, how they prepare and how they decide, and the experiences that shaped how they see the world.

0:49 No noise, no shortcuts, just real conversations to help you think better and invest with confidence. Welcome, everyone, to Top Traders Unplugged. My name is Kevin Coldiron and I'm host of the Ideas Lab series where we talk with authors of new books that help us understand and navigate the global economy.

1:29 Our guest today is Alex Edmans. He's a professor of finance at London Business School and a leading expert on market psychology. You may have read about his research in the FT or the Wall Street Journal, or you may have read one of his books. He's the author of May Contain Lies, which was an Amazon number one bestseller, and also Grow the Pie, a Financial Times book of the year.

0:58 Alex is here today to talk about his new book, just out in September, called The Madness of Markets: Why Smart Investors Make Crazy Decisions and How to Exploit Them. Alex, thanks so much for joining us and welcome to the show. Thanks so much for having me on, Kevin. It's great to be here. First of all, shout out to London Business School.

1:58 That's where I studied finance and got started using a lot of the ideas you actually talk about in your book. So, yeah, I wanted to maybe start off with what you say. You say that mood matters, that sentiment impacts markets in surprising ways. And perhaps we can start off with a couple of stories from your own research.

1:51 I mean, you became well known early in your career for a paper that looked at the impact of sporting results on markets. And then later you looked at the impact of music on markets, and you used that as kind of an illustration to show us that markets are not just driven by raw fundamentals, sentiment matters a lot.

2:37 So, I was wondering, perhaps you could tell us those stories. Certainly. So, while you learned finance at London Business School, I learned it at MIT in the US, I did my PhD there. And MIT being MIT, all the professors and my classmates, they were looking at rational quantitative factors. So, the price of a stock depends, on future dividends, on growth rates and inflation, and all of that stuff.

2:46 But I had just been in the real world. So, I was at Morgan Stanley, between undergrad and my PhD, and while people are really smart and they're able to devise big Excel spreadsheets, taking those into account, they're also human. I wanted to show that psychology, and emotions, and sentiment also matters.

2:46 Now, showing that sentiment affects the stock price is quite difficult because many factors that affect the mood will also affect fundamentals. For example, if there's a plane crash, yes, people are unhappy, but the stock market might go down not because people are unhappy, but instead because it's bad for the economy.

2:46 So, this is why I looked at crazy things such as soccer results. Why? Because if England loses, that should have no effect on profits, or dividends, or inflation, except in a few sectors like replica merchandise. But it does cause a huge effect on national mood. And what I found, long story short, is that when a country gets knocked out of the World Cup, the market falls significantly the next day.

3:33 To put some numbers on it, it's about half a percent, even when you control for the broader world market movement. And when applied to the UK stock market, that is over 10 billion pounds wiped off the market on a single day. And so why is that so profound? Because you might think, yes, emotions matter.

3:05 Yes, certain things make me happy or unhappy. But when I am trading, I become rational. I shake that off. I'm a professional who puts my emotions to one side. But what my data shows is that's not the case. You are human and you are affected by emotions even when you're in your job. And therefore, we need to be very careful when making investing decisions, not to be swayed by these extraneous factors.

4:51 What happened to the London stock market after they lost to Argentina this summer? So that actually opened about 0.5% down. And interestingly, Yahoo Finance attributed this in part to the England defeat. So, because my study was published 20 years ago now, it is, as that was somewhat well known among markets people.

5:21 And so, it was gratifying. They said, oh, it's not necessarily just due to fundamentals, but partly due to this emotional effect. And why is that interesting? Because the morning after the Argentina defeat, there was good economic news. I think the UK had the highest growth rate for the last 13 months, yet it opened lower, in part because of this negative sentiment indicator.

5:35 I wonder if people started building negative futures positions when they went into that defensive crouch in the second half of the game. Everybody I was watching with, and all my friends said, as soon as they went into that defensive crouch, then people thought, oh, England were going to lose. More seriously, when Argentina…

6:13 sorry… when Germany and Brazil, when there was that 7/1 defeat a couple of World Cups ago, you could watch in real time, when the goals went in, actually, the stock prices immediately moved. Although surprisingly, in that case, that was the one case that moved against me. Why? Because when Brazil kept conceding more and more goals, the stock market went up.

5:58 And you might think, doesn't that prove me wrong? Well, no, because actually in Brazil, the stock market was concerned about Dilma Rousseff, who was the Brazilian president, who is very left wing. And because she had spent loads of money on stadiums and she had built her identity on the Brazilian football team's success, there was thought that she would not win another election if Brazil got knocked out.

6:36 So, mood mattered, football mattered in that case, but for other reasons from what it would do normally. Did she lose the election? She did, I think. I think she did, yeah. So, this was the 2014, there was the very famous 7/1 home defeat to Germany. Okay, so you did that work with sports results or sports results impacting markets, why then did you continue to go down that path?

7:08 Because later on, I think you did some work on Spotify playlists and markets. Yes. And so that's because there are many, many things that could be affecting your emotions. So, yes, I might be upset because my sports team lost, but I might be upset because I had an argument with my wife, or because my kids are sick, or because a bird unloaded on my shirt.

8:51 But I'm not going to be able to get data on that as a researcher. So instead, I thought of something different. Rather than looking at the individual drivers of mood (sports results, arguments with spouses, kids, being sick), let me look at the effects of mood. And there is a literature on what's known as behavioral congruence.

9:00 We take actions which reflect our emotions. So, if I'm really happy, I might play Walking on Sunshine. If I'm really unhappy and I've just broken up with my partner, I might play Nothing Compares to You. And so why is music listening something that I wanted to look at? Because I can get aggregated data across the whole economy.

8:33 Why? Because Spotify has a list of the top hundred streamed songs, whereas you don't have individual data on things such as kids being sick or arguments with your spouse. And what is interesting is that you can use an algorithm to look at the happiness of a song. Notice this is happiness of the music, not the lyrics.

7:51 And that's really important because there are some songs with some quite dark lyrics like Semi Charmed Life or I Don't Like Mondays, which are still quite positive and upbeat songs. And so, what we did is we used that algorithm to look at how happy or how sad a country's playlist was as a reflector of national mood.

9:01 And what we showed was that was also significantly correlated with stock prices. Interestingly, it's also negatively correlated with government bond prices, which makes sense because when you're more optimistic, then you're going to put more money into equities, that money needs to come from somewhere and it will come out of something safer, such as UK government bonds.

9:18 That measure that you developed for kind of aggregate national mood, is that something that people now publish and track? Is that easy for me to look at? Is the national mood worse now? And is that part of the reason that the bond market is struggling? Yes. So, it's actually a measure that we didn't come up with ourselves.

9:41 So, we stood on the shoulder of sort of giants there. So, the MIT Media Lab came up with something. There was a small inner lab there called the Echo Nest. And what they did is they produced a measure of valence, which is the happiness of the song, and we downloaded it from their website, and we used that as the measure.

9:59 So, it is a measure from Echo Nest, not from us. So, that measure is out there. People could... Yes, you can look at it, although what you can't do… So, at the time, we were able to scrape that data legally and download the data for a very large time period. Now, I think you can look at it, I don't think you can scrape it in the same way, but that data is still at least publicly available.

10:23 Gotcha. Okay. So, as I'm reading the book, there's a lot of very interesting stories about the ways in which markets are, as you say, impacting my mood and sentiment, etc. And you say that the goal of your, I guess, trying to educate people shouldn't be to outwit the market with facts, but to outlast it with judgment.

11:19 And. And my question was, do you think that…? I mean, typically we imagine that professionals have an advantage over individuals, but I wondered if in this respect, perhaps the reverse is the case, because individuals have a lot more freedom in the way they can invest. They're not tied to benchmarks.

10:58 They're not being measured every quarter. They aren't going to get fired if they go to cash. Do individuals, in your mind, have certain advantages over professionals in exploiting some of these mood and sentiment related ideas? They may do. And this is quite paradoxical that actually, maybe, amateurs may have greater potential to beat the market than professionals.

13:12 So, that is a really bold and controversial statement. So how can I back this up? So, at the end of the book I have a final chapter where I give practical takeaways to improve your own investing decisions. And out of the twenty, number two is know your edge. So, what do I mean by this? Before you think about investing in the first place, think about what your competitive edge is.

11:28 So many people think their edge is knowledge. They might say, oh, I have knowledge about AI. I've used AI myself for my own planning. I think AI is going to be the future. But you really don't have edge in knowing about AI because you're going to be trading against lots of professionals who study the AI industry every single day and they have access to management and they are able to understand the power of these algorithms much better.

11:28 Similarly, I might think, oh, I'm a doctor, I understand the power of this beta blocker. But again, you're going to be trading against pharmaceuticals analysts who study this every single day. So, as an amateur investor, maybe your edge is not knowledge, it's not unique information, because professionals have that.

13:08 But instead your edge comes from a different source, which is exactly what you've identified, Kevin, which may well be the ability to be free, to be able to play a long game. So, I call this the endurance game. What do I mean by this? In the depths of the financial crisis, at the start of 2009, I put a lot of my money into equities.

12:34 Why? Because I thought the market was really undervalued because of the collapse in the financial crisis. Now, would a professional investor have done the same as me? No, because it was really difficult to call the bottom. Maybe the market would have crashed even more. And if I put my money in the equities in January 2009, and it goes down by April 2009, then I'm bleeding losses.

12:21 I might plead with my investors, trust me, it's all going to come better, just be patient, in five years' time, things will improve. But they won't wait five years. They might pull their money and say, well, I'm going to put it in with another fund manager who is going to be performing better. But for me, investing my own money, I don't have external clients who I need to be concerned about.

12:09 I'm just investing in my future or my family's future. Back then I didn't have a family, but I thought I might at some point, and so, my time horizon was 30 or 40 years. And so as long as the market was cheap and going to recover over the next five or 10 years, it didn't matter that I didn't call the bottom.

11:28 And this applies not just to individuals but some institutional investors. So, Clare College, Cambridge University, they also put a lot of money into equities in 2009. Why? Because they don't have external clients. Instead, their mandate was to fund future research and teaching for the next 30 to 40 years.

14:29 Yeah, I actually remember that. I think they issued… Did they issue…. they issued debt to do that, didn't they? They exactly did. So, they issued, I think, about £10 million of debt. And so, that £10 million, over the next 10 years, I think went up to £15 million because of interest, the equity that they invested in went to £30 million.

14:55 So, it tripled while the interest only increased it by 50%. So, you brought up something when you were explaining the answer to the last question about professionals having particular, I guess, domain-based expertise and knowledge. So, I don't know, a biotech investor, they might have these expert networks, or they might indeed have people on staff who are medical doctors, researchers, that type of thing.

15:57 And it made me think about when you are an individual investor and you're looking to invest your own money, should you be looking for specialists versus generalists? And so, I can see the advantage that specialists have in that no one knows more about a particular sector than they do. On the other hand, they are very narrowly constrained in what they can do.

15:33 And I was wondering if you could tell us the Turkish hazelnut story, because to me that's an example of where generalists might have an advantage of being able to search the entire world for opportunities. And of course, the disadvantage of generalists is that there's so much to potentially invest in that it’s very difficult to filter those ideas down.

16:27 Yeah, so, I'm going to give the typical economist's answer of it depends. So, sometimes specialists outperform and sometimes generalists outperform. I’ll allow you to do that one time during the podcast. You can say it depends once. Yes, but I'll say what it depends on. So, this is not going to be complete fence sitting.

17:53 So, what it depends on is where your expertise lies. So, there will be some investors who have genuine expertise in a specific sector. So, it may well be that it's run by some expositions and they're going to focus on pharmaceuticals because they really understand that particular sector. You don't want them to be investing in retail or textiles or something else.

16:41 Others might have expertise in a particular theme. So it might be, I'm able to understand corporate culture. And so, I'm going to invest in companies with great workplaces, be this in pharmaceuticals, or financial services, or in retail. And indeed, I invested in such a fund for many, many years. It was a fund called the Parnassus Workplace Fund.

18:20 And when Morningstar did a study, this was the best performing large cap fund over the last 1 and 3 and 5 and 10 years. So, they were using still specialist expertise, but knowing that expertise could be applied to every sector. And then how does this go into the hazelnut example? So, this is a fund called TerraNova Capital, and their expertise is just trying to find stuff which is off the beaten path, news that is clearly very useful, but because it's in the dusty corners of the market, it might be ignored by other investors.

19:05 And this is what takes us to hazelnut and Turkey. So, in April 2025, there was a huge frost which wiped out a third of the country's hazelnut crops. And maybe the listeners are not that familiar with Turkey, but hazelnuts to Turkey are what coffee is to Brazil. So, this is really big. And it was really big in Turkey, and Turkish language, local media covered it, but many Americans or Brits, they don't read Turkish.

19:04 And so, it was not exactly hitting the front page of Bloomberg. And so, the wholesale prices began climbing, but there wasn't that change in the stock price. So, this fund just noticed it. It flew to Turkey. It found the country's only listed processor sitting on a huge trove of hazelnuts. And so, knowing that the price of hazelnuts will go up because of this drought, they invested $20 million.

18:56 And when the shortage finally hit the headlines, the company's value went up by 40%. So, here their insight was, well, let's try to find relevant news. News which is ignored by the market, perhaps because it's in a different language. And I can do this in every sector, but I will still say that they are specialists in that their trading strategy is trying to find this obscure news, rather than saying, well, I believe I can run discounted cash flow models better than anybody else, which might not be so plausible.

19:30 I see. So, you don't see them as generalists, you see them as specialists in a particular type of story, almost. Yes. So, specialism can be in theme, not just industry. So, we often will think about specialist versus generalist as whether you are sector focused or sector diversified. But I would still say, well, they have a specialist theme.

19:39 I think it's very difficult for a fund to be successful without having that specialism. Because otherwise, to answer my question, what is your edge? It's not clear. So even Warren Buffett, even though he invests in lots of different sectors, he will say his edge is being able to analyze intangibles, companies with great brands.

20:06 He helps them build a moat and he helps protect them from the vagaries of the short-term stock market by taking a large stake and allowing them to invest for many years. Just going, kind of circling back to this question of performance and benchmarks, and when I think about when I started my career, I actually started in the investment management world in the UK in the mid-1990s and that world was dominated by active investors who really didn't have benchmarks or the benchmarks were very loose.

20:50 And that had evolved, I think, from the very old days of the Scottish investment trusts that were originally set up to just sort of scour the world for investment opportunities. And then we sort of (in some sense, I feel a bit bad about this), we came along and we were like, well, you're not outperforming the market.

21:15 And we went to their investors and said, you'd be better off with an index fund or better off with a risk-controlled fund that was tightly managed relative to a market benchmark. And that was novel in the 1990s. Of course, it's not novel at all today. That's how most funds are run. They're tightly benchmarked.

21:31 So, I guess my question is, have things come full circle now in that is there so much benchmarking that everyone is tightly constrained and you're better off looking for those that aren't benchmark constrained? When you think about your own personal investment, is that a consideration? Do you want people that are tightly constrained to a benchmark, or people that are looking for more absolute returns?

22:00 Out of every bad and insane practice, there's always a grain, or actually more than a grain of sensibility behind it. So, often why there are seemingly incorrect practices is that a good idea was then just misapplied. So, benchmarking at its core is fundamentally sound. Why? Because if I'm going to choose to put my money with an active manager, he or she needs to outperform a passive benchmark.

23:55 Why? Because I might be paying them fees of 75 basis points per year, whereas a passive fund may be charging just 5 basis points per year. So, I don't want to reward the manager for doing well in an up market. They need to be doing better than what an index fund would do. So, it's absolutely important to have a benchmark which is not zero.

24:00 You need to be beating what a passive index fund would have done. But where this becomes a problem is then, if active managers become so conservative, they're afraid of deviating from the benchmark because then they will underperform. And so, they might think, well, as long as I market perform, I will still keep my job.

23:15 And as a fund manager, I'm getting paid very well. And it's a lot of status to be a fund manager. I don't really need to be in the top 10 percentile as long as I'm sort of median, that's fine. I just don't want to be really underperforming. So, even if there's an AI bubble right now, and I know there's a bubble, I don't want to sell my AI stocks because if the bubble continues to inflate, I don't want to be the muppet who's still out of AI and missing out on this big boom.

23:55 And so, if you do that, then you're actually not doing what your clients are paying you to do. Your clients have chosen to buy an active fund because they don't want to just passively hold the market portfolio. So, you need to have conviction and to move away from the benchmark. Otherwise, you're just giving them the same as an index fund for a much higher fee.

22:00 So, there is a measure called active share, which was invented by some academics nearly 20 years ago. And what they found was that this active share was generally correlated with outperformance. So, funds which were having conviction to deviate from the benchmark. Why? Because they're using their specialist knowledge.

23:08 Even if that specialist knowledge is across different industries, they are still deviating from that benchmark by buying high culture firms or firms with strong intangibles. If you're using that expertise, you're going to be moving away from that benchmark. And so, the ones who are inactive, who are hugging the benchmark are the ones who are not using any expertise at all.

24:34 They're just overcharging you. So that active share is potentially a proxy that people could use when they're evaluating funds, like how much conviction these managers have, or to the extent to which they're just kind of managing their professional risk by hugging the benchmark as opposed to delivering what you're looking for as an active investor.

25:00 Absolutely. So, it highlights, well, who are the ones who are actually managing for their clients, which does involve, if you have unique insights, acting on the insight, and who are the ones who are overly conservative and just trying to manage their own career risk. Now, of course, we don't want to take this too far the other way because we know Goodhart's law.

25:26 When a measure becomes a target, it ceases to be a good measure. If you have no unique ideas, don't just be active and deviate from the benchmark just to improve your active share. And so, this is why what's really important when evaluating funds is to see, well, what is their expertise? Do their active positions reflect what they claim their expertise to be?

25:26 And if so, great. But if not, maybe they're just trading for the sake of trading. What do you think about a benchmark that's kind of more old-fashioned, that says, well, the equity risk premium is, let's call it 5% above cash. So, cash is 3%, I'm looking for 8%. And it's an absolute return fund, I'm scouring the world and don't evaluate me on performance this year or next year.

26:02 Evaluate me over long horizons on whether I can do better than the market. And is that something that you find compelling or is that something that you think people should avoid? Because that's more like what a Warren Buffett would say. Right? It depends on how you're doing better than the market. Because we know from basic finance theory you can do better than the market by just taking on more systematic risk.

27:09 So, if I am having a beta of 1.5, I should be delivering a 1.5 times greater excess return. So again, this is why benchmarking does have some sensibility behind it. We want to look at your alpha, which is your outperformance after taking risk into account, rather than just your raw unadjusted for risk outperformance.

26:19 But if, indeed, what you're doing is, you are able to capitalize on markets in which you think there is an equity premium, and that equity premium is more than what it should be, given the level of risk, then there might be a way, there might be a reason to reward you for that. So, what do I mean by this?

26:33 So, the equity premium puzzle is the following idea. So, stocks have outperformed treasury bills over any reasonable length of time. For example, if we look at the last 10 years up to December 2025, I think the T-bill average return was 2% and the S&P 500 was about 15%. So, that difference is 13%. Maybe on other time periods it might be 7%.

26:19 Now, some people will say, well, that is just due to risk, that there's no free money on the table. People don't like risk and that's why the S&P 500 needs to give you a higher return. But actually, when people run the numbers, and they put into them any reasonable number for risk aversion and risk appetite, the equity premium should be something like 3% or 4%, not 7%.

28:19 So, the stock market over any reasonable period does offer good value. And so, one argument is that, well, a fund, if it just goes for risk by buying into markets with high equity premia, that is a way that they can legitimately add value for your clients. Now, if your client was able to replicate it themselves just by buying index funds in those individual markets, then you would not be adding value.

27:36 But if your client was sort of very unsophisticated and not able to pick out foreign markets for some reason, there is an argument for maybe if you're buying a globally actively managed fund, that active fund could go into particular markets where it thinks the equity premium is particularly rich. Let's talk about some of the kind of specific effects that you go through in your book.

29:04 Momentum is one that you spend a lot of time with. Momentum is essentially trend following. And that's something that we see working through, you know, we see it in stocks, we see it in bonds, we see it kind of cross sectionally between stocks, we see it on a time series basis. It's a very strong effect.

28:46 The tricky thing, of course, with momentum is that it has periodic crashes that are very violent. And if you're a professional investor like I was, and you were running momentum strategies, you can have multiple years of performance wiped out in a very short space of time. So, the kind of holy grail with trend following strategies is can you get out before the crash?

28:46 And there's been some interesting research done over time on that. And you talk a little bit about that in your book. But I'm curious what you think the state of the art is with that and is it even possible? In other words, is the crash risk part of the reason that momentum makes money in the first place?

29:56 So, you really aren't able to separate out the two. Yeah, so this is a great question. So, what is momentum and what psychological bias does this try to exploit? The idea of under reaction. So, even if we see some news, we might discount it. Why? Because of confirmation bias. We have our view of the world and any news that challenges that view, we just down weight it because we don't like it.

30:08 So, let's just give an example. So, in 2006, Amazon quietly launched what ended up being Amazon Web Services. But back then, people never saw Amazon as being this cloud computing company. They thought, well, you buy books and CDs there. What is it doing playing in web services? So, it was only when it hit 2015, and Amazon Web Services actually reported their income separately, that people finally cottoned onto it being really valuable.

30:08 And so, if we indeed ignore information, there is a simple strategy of buying stocks that have done well over the past six months and shorting stocks that have done badly over the past six months. Why? Because a stock that has done well recently had some very good news, but the market only thought it was moderately good, and so it underreacted to it.

30:08 And over any reasonable time period, people have found that momentum typically outperforms. And interestingly, this is not just in the US, it's around the world. It's not just in equities, but it's in bonds, and currencies, and virtually any asset class. Which points to human psychology being a common driver.

32:06 Because it doesn't matter whether you're a Latin American commodities trader or an American equities trader, you're all affected by confirmation bias and under reaction. But as you say, there is a danger, which is when momentum loses, it loses really, really badly. Now, fortunately, you can foresee these momentum crashes.

30:35 And as I describe in the book, there's a really good study by two professors who also double up as investors for AQR and Goldman Sachs. What they found is that when VIX, which is the volatility index, is high, momentum is typically going to be underperforming. So, this tells you when to get out of momentum.

30:08 Now, it is not a perfect predictor. And sometimes it may well be that momentum crashes unexpectedly. And that may well be the secret to answering your question. Why, even though momentum was first discovered in 1993, is it still alive and well 33 years later? Why don't people exploit the free money on the table?

33:22 Because people are worried about these crashes. And if I go back to our early discussion on career concerns, even if it's a strategy which will make money 99% of the time, you're just weirdly worried about that 1% of the time where if it crashes you're going to be out of a job, even though it would be in your client's interest to invest in momentum.

31:52 Why? Because your client probably is not just invested in your fund, they're investing in lots of other funds. So, they don't worry so much about your fund crashing because they're diversified. You as a fund manager, you're not diversified. Your entire reputation is tied to this one fund. And so, you might be excessively conservative and not pick up the free money on the table.

30:08 And again, this is why, going back to one of our earlier conversations, why I think I can make the bold and controversial claim that perhaps sometimes amateurs might be able to beat the market more easily than professionals because if you're unconstrained and you're not worried about external clients, you might be able to exploit momentum because you don't worry so much about a crash.

33:47 Yeah, I think I agree with that. And I guess, just talking a little bit more about momentum, there was one area where I think I didn't agree with you, and that was when you talk about the notion of corner strategies, which is actually, funnily enough, what we used to call them too. But the idea that you've got momentum that works across the market.

34:56 But let's say it works particularly well if you filter down just the small caps. And then within small caps, it might work particularly well if you filter further down to, say, small caps that have negative earnings. Let's just say that's the case. And so, the more you apply these layers, you get to, “corners of the market” where momentum is potentially very strong.

34:15 And, as a professional investor, we were very well aware of these corner strategies, but they're not really exploitable in any kind of scale. It's very difficult to put a lot of money to work if you're layering on three, four, or five different types of filters because you get a small number of stocks, that's number one.

35:15 Number two is you get increasingly less statistical confidence in the result the more you narrow down the sample space. So, my thinking was, well, maybe these corners are an area that are more suited to individuals who don't need to put a lot of money to work. Now, the individuals might not have the sophistication to identify the corners, but it seemed to me that might be another area where, I don't know, sophisticated individuals or small funds could play, that big investors couldn't.

35:24 I don't know, how you think about that? Yes, you're absolutely right. So, momentum is what I call a level one strategy. So, what do I mean by this is, we find a behavioral bias and we see how to exploit it. So, if the bias is that people underreact, then we want to buy recent winners, because those are stocks to which the market has underreacted.

35:36 But then we can think about what I call a level two strategy, which is, where is that bias more prevalent? So, you think about, well, why is it that people underreact to information? Well, maybe they just don't even notice the information to begin with. Why? Because what do we see on Bloomberg, on the Wall Street Journal, we see coverage of the Magnificent Seven, or with AI stocks, or large companies like Amex and Goldman Sachs.

36:36 And so, if there's a small company which has had some great news, we're less likely to notice it because it's not hitting the headlines. And so, the level two strategy is that we play the momentum game, but particularly in small stocks and stocks with little analyst coverage. And if, indeed, it is the case that large professional investors are unable to play that level two strategy, why, because small stocks are less liquid, then there is another reason for why individual investors, who don't have so much of a constraint, they might be able to outperform.

36:57 Okay. Okay. So, it sounds like we're philosophically in agreement on that. I want to maybe talk about another area where I had a question of how maybe individuals could use one of your research findings. So, you talk about this fixation with round numbers, that we get unusual price movements when stocks move above or move below a round number, like US$50 a share or US$100 a share.

37:39 So, I was wondering if you could explain what happens around these large numbers. And then I want to ask a question about whether there's an implication for people setting limit orders when they want to buy or sell a stock for another reason. Can they use that round number effect to kind of help them be a little smarter about doing that?

37:49 Yeah, absolutely. So, let's do this with a numerical example. So, let's say I buy a stock and it's currently US$80. I might think, well, my price target is US$100. Let's sell it at US$100, and I'll put a limit order to do this. But it may well be because other people like these round numbers. It's actually difficult for it to hit this US$100 because if other people have put these limit sell orders there.

38:50 It might be that those sell orders get satisfied first and that drives the stock price down. Because of the selling pressure, it never really hits there. So, what I do with my own limit order selling is I might put the sell at say US$99.90. Why? Because it doesn't really matter to me much emotionally if I sell for US$99.90 versus US$100, once I realize that the round number is just some false barrier, and it makes it more likely that I will get my order filled.

37:49 It's also the same on the buy side. So, I've actually put a buy order in for a fund where I put it in at US$12,510, not US$12,500. Why? Because that's again a round number. So, it may well be that if the fund price goes down, it might not hit US$12,500 because other people have put the buy order. So, what I want to do is front run.

38:55 I want to get in before other people get in or get out before other people get out. Gotcha. Okay, so you do use this effect in your own...? Yes, I do it myself. And there was a fund which I had sold at US$14,000. Well, actually at US$13,990, and I think it's going to go down again. So, that's why I put a buy order at US$12,510.

39:32 Okay. Maybe one last thing to talk about is the disposition effect. And you had a… So, you explained what the disposition effect is, and then you had a fix that I really liked. So, I was wondering maybe you could walk us through that, what the disposition effect is and then what your “fix” for it is.

39:55 Absolutely. So, the disposition effect is such a common phenomenon in finance and it's such a big mistake, but it's so human and it's something where people understand why it happens. So, what is this? It's the idea that we're really reluctant to take losses and we really want to lock in winners. So, if I've bought a stock for US$80 and it bumbles around and it's now US$75, I really don't want to sell it.

40:54 Why? Because then I have to admit to myself that I've made a loss. And even if I think it's going to go down to US$60, I hold on, just hoping it's going to get above US$80. And then when it hits US$80, then I'm going to be selling. And this is exactly the same that you might do with a casino if I've lost US$50, I will keep playing, and playing, and playing, until I recover that US$50, because I want to come out at least break even if it means throwing good money after bad.

41:09 Why is this such bad behavior? Because of momentum, which we discussed earlier. If something has done poorly recently, if it's gone down from US$80 to US$75, it's likely to continue to go down in the future. And similarly, if something has gone up recently, it's likely to rise. But because I want to lock in again, I might sell the stock at US$90, even if it's heading up to US$100.

39:55 And that's bad not only because of momentum, it's also bad for tax reasons, because if I sell a winner, I'm immediately locking in a tax, capital gains tax that I need to pay today. So, what is the solution to this? Well, one solution would be to say, oh, just ignore the purchase price, ignore the disposition effect.

42:12 And if you were really strong willed, you might be able to do this, but not everybody is strong willed. It's just like to say only one Pringle, that is really hard to put into practice, even though it makes sense in theory. So, what I explore in the book is a more realistic solution, which is the idea of rolling your stocks over.

42:37 What do I mean by this? Because if I was to sell my stock in Tesco for US$75 after buying it at US$80, and immediately reinvest the proceeds in Vodafone, I actually don't view myself as exiting that position because the trade is still live. I've just rolled it into a different investment. And indeed, in my Excel spreadsheet, I would have invested, say, maybe ten thousand pounds initially.

41:54 It's gone down to nine thousand pounds. But I still know that my nine thousand pound investment is still carrying on and I'm not going to close out that position until I've sold Vodafone. So, by rolling on a stock into a new stock, I actually am able to take losses because I don't need to admit defeat to myself, because I've still kept that position going on.

41:30 And indeed, there's a really clever study by some people which found that rolling on your position is a way of overcoming the disposition effect that you might have otherwise suffered from. Yeah, I thought that was a very clear explanation both in the book and right now. And also, a fix that I think we can all put into practice.

43:34 So, while we're on that notion of fixes or things that individuals can do to take advantage of some of these ideas, I thought maybe we could focus a little bit more on that. You have a really nice summary at the end of the second chapter, which I thought maybe you could walk through. And it's really kind of three things that individuals can do to avoid some of these, avoid trading on emotion.

43:31 And one is, don't check your portfolio too much. Two is, write down the reasons you're planning a trade and write down not only what the world looks like if it works, but also what the world would look like if it doesn't. And then three, pay attention to your mood when you make a decision. So, I was wondering maybe if you just give us the rationale for those three things.

43:36 I think we actually covered some of those ideas and yeah, talk us through those three things. Absolutely. So, let's start with don't check your portfolio too much. And going back to my earlier comment that behind every bad behavior there is a grain of sensibility behind. So, we often say, oh, you snooze, you lose; the markets are fast moving, you should always be responding to information.

45:43 And so, this will encourage us to always check our portfolio and always try to read the news to see should I be increasing this position or cutting back that position. But what we don't realize is that, well, if there's news out there, such as an earnings announcement, maybe somebody else has already responded to that and it's already more than priced in.

45:12 So, if we're trading on information, it may well be that we're trading on old news. We're buying high because we're buying after the stock has already risen and we're selling low, which is the opposite of what an investor should be doing, which is buy low, sell high. So, if we are to not check our portfolio too often, which is actually advice that Warren Buffett gave, we're more likely to be investing on long-term factors such as the market being in a downturn in 2009 and I'm going to be willing to wait five or 10 years for it to recover rather than short-term things which might already be priced in.

46:01 The second bit of advice is to always try to take the opposite position to the trade that I want to make. So, if right now I wanted to say, well, let's buy into an AI fund. Why? Because AI is the future. I've seen just how powerful AI is in my own life. Well, let's try to find reasons for not investing in AI.

45:15 I could be looking at the valuation ratios and saying, well actually the price earnings ratio here is extremely high. And if I'm not able to come up with that myself, I could use AI to help me. I could ask ChatGPT, give me reasons for why I should not be investing in an AI fund right now. And this doesn't mean that we should always be inert and not taking any decision, but it does mean that when we take a decision, we will have seen both sides to it.

45:06 It's just like if I want to buy a house, I want to make sure a survey is done to see whether it's structurally sound. This is just good due diligence. And I think we should treat any investment decision with the same seriousness as you would do any decision like buying a house or buying a car. How important is it to write down both sides of it as opposed to just like, oh, I'll do a Google search, I'll do ChatGPT search.

46:47 We had Annie Duke on the show, who I know gave an endorsement to your book and she talked about this idea. And I believe, if I'm correct, she said, you really, you want to go through the exercise, but you've actually got to physically kind of write down what the world looks like both when you're right and when you're wrong, and then go back and kind of keep checking: is the world it getting closer to one of those two scenarios?

47:15 Is that bit important in your mind, or is it more just, hey, think it through both sides carefully? I think it is very important. I think it's important on a number of levels. First, at the time that you make the investment decision, writing it down is really useful to make sure that you've done that process really carefully.

47:56 So rather than just thinking in my head, oh yeah, I know that a danger might be that there's overvaluation. If I've written down, I'm concerned that AI could be overvalued. Why? Because the price earnings ratio is 50 and typically you might think it should be 30 or something else. This just makes sure that you are taking it seriously.

48:45 Also writing it down makes sure that you are actually internalizing the information and it's going to be affecting your decision. This is why when you're going to a lecture at university, see, taking notes is really useful. Even if those notes end up catching on fire, the actual act of taking notes makes sure that you're more likely to be understanding and internalizing information.

47:23 But also writing down is useful after the fact. Why? Because if the investment decision went south afterwards, then you will be able to go back to it and say, well, was this because my investment thesis was wrong? Because often what we do is we want to blame external factors. You might say, oh, my thesis was sound and it's just that the markets went crazy because Trump made a trade announcement.

47:52 But actually, if you said, oh, my view is that, well, this stock, these valuations were high, but I think there could be further AI growth and, actually, that ended up not transpiring, then you can look at the outcome and compare it with the original rationale that you made for it. You know, after I had her on the show, I started doing, I actually started doing what she recommended, which is, I rarely follow through on things like that, but I did.

49:23 And what I found was, because the process of writing down your positive thesis, your negative thesis, she also recommends you put down kill criteria, which is specific things that happen that are going to make you close that trade. That was like an involved process. And because it was so involved, I found I didn't check my portfolio as much because I didn't want to go through the whole process of thinking about a new trade in that same level of detail.

49:37 So maybe that's just my personal laziness, but I'm wondering if those two things are related. Yeah, and I think it dovetails with advice that people give for just general good behavior and good habits outside of investing. So, while my book is about investing, investing is just the setting. It's about good decision making in general.

50:45 So, when people say you want to develop a good habit, actually keeping score is really valuable. So, if my habit is to be, I'm going to check my phone less, what I used to have was a scorecard where, at the end of each day, I had to write down the number of minutes that I had been on my phone, because you can look at this on Apple screen time.

50:26 And every day I would write down that number. And if a particular day the number was 105, I think, what was I doing in all that time? And yes, I could look at the end of the day and see it was 105. But I just feel more embarrassed when I write down it was 105. And I say, well, yesterday it was only 72.

49:51 Also, you might think, oh, I want to do 30 minutes of cardiovascular exercise a day and I'm going to put a tick when I do it. But if I don't do it, I don't just leave it blank, I'm going to put a cross. Just to say that I have failed to myself. And that's something that people teach you, in terms of developing habits, is whenever you can, write it down and put feedback, you're more likely to internalize it.

51:08 Let me ask you one more question. And all this, by the way, is coming from this last section of the book, which I really like, which you call Turning Madness into Money. And I think that's one of the, I think, really valuable aspects of your book, is that you end with these, I think it's 20 kind of the tools that I think individuals can take away.

51:41 But one of them, which also goes back to what Annie Duke would recommend, is called Outsource the Ugly Decisions. And I think in her framing, it's like, hey, people tend to be better at the buy decision than the sell decision. So, you need someone external to yourself to basically pull that trigger and to do the sell.

51:08 You tell them when you want, you know, why you put the position on, and when it's going to go wrong, you set the kill criteria, and they kill it for you. Is that what you had in mind with Outsource the Ugly Decisions? And do you do that yourself? Do you have someone who makes the ugly decisions for you?

52:11 Yeah. So, this is to try to overcome the idea of the disposition effect, which is, it's difficult for you to reverse a losing position. Why? Because you are. You don't want to admit that you made a mistake. And so, it may well be that I'm going to invest in a single stock, let's say Goldman Sachs, right now, at US$100, and I will ask maybe my spouse to review it for me.

53:08 And if she thinks, oh, actually it's gone down too much and it's going to go down even further, I might not delegate it fully to her by allowing her to sell, but she is able to tell me, Alex, you need to get out. Similarly, within a company, it may well be the risk manager or the chief investment officer, who is saying, well, I'm going to be telling you when to get out of this.

52:42 So, the big question is, do I do it myself? And I might say no. And you might think, oh, this is crazy. How can I read the book of somebody who doesn't follow his own advice? But the reason why it is that I invest very little in single stocks to begin with, why? Because I believe in the power of diversification.

52:11 I invest most of my money within either passive index funds or actively managed funds, where I believe the fund manager has a lot of skills, such as talent over capital. But I do implement the principle in other areas of life, which is similar to the idea that financial markets are only a laboratory for decision making more generally.

53:44 So, whenever I write a book, I will try to send it to other people and say, just please tear it apart as much as possible. Why? Because I will review it myself many, many times, but I'm very unlikely to completely scrap a section because I've thought, well, I've spent a day of my life writing this section or this chapter.

54:19 Even though I, yes, I edit something, I might just change this word or the sentence. I'm not going to be cutting out a whole story. So, I'll send it to some people with explicit requests. Can you tell me which of these sections are just not pulling their weight completely? Get rid of this. And so those ugly decisions I will send to other people.

53:49 For my last book, (which is the first book I went with an agent because it was published with Penguin Random House, a mainstream publisher), out of all of the agents that offered me representation, I went with the most negative agent, the one who was the most critical of my proposal. There were other agents who said, oh, your proposal's great, we can send it off to publishers right now.

54:23 But I thought, well, this is the guy who will be able to improve my proposal the most. And so, he did the ugly decisions for me and said, oh, this really is not earning its weight and this needs to be improved. And so, I will try to apply this in many other areas of my life. Nice, I appreciate that. Maybe we can wrap up by just talking very briefly about the kind of current situation.

55:03 There was a number of things in your book that I think are relevant or potentially relevant for what's going on today. One of them is what you call the big market delusion. And I was wondering if you could explain to us what that is and then what's your view? Are we seeing this big market delusion in a form with the AI hyperscalers?

55:08 Are they falling victim to the big market delusion or investors in pricing the hyperscalers falling victim to that? Certainly. So, I'll first explain what the big market delusion is and then apply it to AI hyperscalers right now. So, the big market delusion is the idea that when there is excitement about a new technology, often the prices of every company within that industry will rise up significantly.

57:06 So much so that if you added all of those companies together, you'd get a valuation of the industry, which is just implausible. So, the numbers just don't add up. So, in the early 2020s, if you were to take the value of the electric vehicle industry, adding up Nio, and Tesla, and Xpeng, and so on, you got a combined valuation which was even higher than the traditional car market.

57:26 And that was about five years ago when electric vehicles were still nascent. Now it is indeed true that one of those companies may well succeed and take over the world and become extremely valuable. But the market was pricing the industry as if every single company would be a winner. And there's an adding up constraint.

57:26 Not every single company can become a winner. Not everybody can get gold medals. And so, the whole industry was being overpriced. And why might this be? It might be the fear of missing out. You don't want to just own Nio and Tesla because what if BYD ends up taking the lion's share of the market? And so, then if you apply this to AI right now, even though, yes, AI will absolutely be the future, not every AI hyperscaler will win.

56:50 It may well be that some of them end up over investing or investing in the wrong stuff. So, this is why I, myself, reduced my position in AI and tech more generally about six to nine months ago. And so, I don't know whether this will be a good decision in the long term. Certainly, I'm not unhappy that I've exited from that.

55:33 Also I know that my immediate investment objective is that I have a large mortgage coming up for refinancing about one year from now. And because the AI in my portfolio has done so well, I wanted to lock in those gains. So, I'm not so worried about missing out on perhaps future gains by not selling at the absolute top because I know that it had a really good ride.

57:12 What I want to avoid is if we are in a bubble, if we are in a big market delusion, and the whole market then turns south, as it did for electric vehicles in 2022, 2023. Cool. Well, I appreciate that and I appreciate all the stories. This is a really fun conversation. We could easily keep it going, or at least I could.

58:11 You probably have a day job to get to, but that's a good place to wrap up, Alex. Thanks so much for taking the time to join us and to share your research and we wish you the best of luck. You're very welcome. Kevin, thank you so much for having me on. I really enjoy the conversation myself. Okay. The book is called The Madness of Markets: Why Smart Investors Make Crazy Decisions and How to Exploit Them.

58:42 It's out now, so please make sure to get a copy and to follow Alex's work. As always, what we've discussed today really is just scratching the surface of what you'll learn from the book. So that's it for today. For all of us here at Top Traders Unplugged. Thanks for listening and we'll see you next time.

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