We Study Billionaires - The Investor’s Podcast Network - TIP793: Thinking Fast & Slow by Daniel Kahneman w/ Clay Finck

Starting point is 00:00:00 You're listening to TIP. On today's episode, we'll be exploring the book thinking fast and slow by Daniel Conneman. Conneman is a Nobel Prize winning psychologist whose research helps shape the field of behavioral economics and transformed how we understand decision-making. At the center of the book is the idea that our minds operate through two systems. One is fast, intuitive, and automatic, and the other is slow, deliberate, and analytical. Most of the time, we rely on the first far more than we realize, even when the stakes are at their highest. For investors, this matters deeply.

Starting point is 00:00:37 Many of the biggest mistakes in markets are not driven by a lack of information, but by cognitive biases like loss aversion, overconfidence, and our tendency to not think hard about the difficult but important questions. In this episode, we'll break down several of Conneman's most important insights and connect them directly to investing. And at the end of the episode, I'll share some of my thoughts around the recent sell-off of software companies and more recent news related to Constellation Software. So with that, I hope you enjoy today's episode. Since 2014 and through more than 190 million downloads, we break down the principles of value investing and sit down with some of the world's best asset managers. We uncover potential opportunities in the market and explore the intersection between

Starting point is 00:01:28 money, happiness, and the art of living a good life. This show is not investment advice. It's intended for informational and entertainment purposes only. All opinions expressed by hosts and guests are solely their own, and they may have investments in the securities discussed. Now for your host, Clay Fink. Hey, everybody, welcome back to The Investors Podcast. I'm your host, Clay Fink. On today's episode, I'll be discussing Daniel Kahneman's book, Thinking Fast and Slow. This book is a masterclass in explaining the inherent biases that we all have as humans, as it was based on decades of experimental psychology research, much of which was conducted by Kahneman and Amos Tversky. In their research, they relied on controlled experiments that tested how people make judgments

Starting point is 00:02:24 under uncertainty using simple problems and decision scenarios. And these experiments revealed systematic and repeatable errors in human reasoning rather than just random mistakes. Daniel Kahneman has a Nobel Prize in Economics and has popularized several ideas on the subject of behavioral finance, such as loss aversion, overconfidence, and cognitive biases. And although the book is not tailored to be read by just stock investors, I feel as if it was written just for us. So Warren Buffett once stated, success in investing does not correlate with IQ. Once you have ordinary intelligence, what you need is the temperament to control the urges

Starting point is 00:03:06 that get other people into trouble in investing." That might be a shocking statement to some, especially since Warren Buffett is probably one of the most intelligent investors to have ever lived. To help illustrate this quote, I'd like to tell a story about Buffett. Each summer, the Boutique Investment Bank, Allen & Co., they hosted a week-long conference in Sun Valley, Idaho. It might be a stretch to call it a conference. It's probably more like an extravaganza with these lavish parties and a lot of fun activities included. The event features Hollywood celebrities,

Starting point is 00:03:40 Silicon Valley's most well-known entrepreneurs, and names that everybody would know. In Alice Schroeder's excellent biography, The Snowball, she told the story of how Buffett got invited to this party in July of 1999. Buffett actually attended the event each year and brought his entire family, as it was a beautiful area and a good opportunity for him to catch up with a lot of old friends. But in 1999, the mood was different. It was the height of the tech bubble, and there were new faces at the table, such as heads of technology companies that had grown rich and powerful almost overnight, and then you had venture capitalists there too. Buffett, on the other hand, was this old-school investor who just didn't get caught up in the speculative frenzy around companies

Starting point is 00:04:25 with unclear earnings prospects. Some dismissed him as a relic of the past, but Buffett was still powerful enough to give the keynote address on the final day of the conference. During his speech, he would quickly become one of the least popular people in the room, as he explained in great detail, why the tech-fueled bull market would not last. He studied the data and the warning signs and considered what they might lead to. This was the first public forecast that Buffett had made in probably 30 years at this point. And to some, Buffett was just spoiling the party. He received a standing ovation after the speech, but in private, his ideas were dismissed, claiming that he had missed the boat. This speech of Buffett's would be kept under wraps and wouldn't be revealed until a year later.

Starting point is 00:05:13 After the dot-com bubble had burst, just as he said it would. Buffett takes pride not only in his track record, but also in following his own inner scorecard. He devised the world into people who focus on their own instincts and those who followed the hurt. Now, the Silicon Valley entrepreneurs at the time, they were likely to be smart people, but despite all of that intelligence in the room, most of them just could not resist the emotional pull of the crowd, which ties right back to the original quote I shared from Buffett. Long-term investing success is not about being the smartest person at the table. It's about having the discipline to stay steady when everyone else is losing their minds. The other part about that quote from Buffett is the part about controlling

Starting point is 00:05:59 the urges that gets other people into trouble. These comments transcend just the avoidance of unprofitable tech companies trading at ridiculous valuations, as there's a long list of things that can get people into trouble. This is where temperament comes into play. Buffett has stated, you need a temperament that neither derives great pleasure from being with the crowd or against the crowd. So investing is a field where it can be really easy to do what feels good. It feels good in the moment to buy what's hot and what's rising in price. And it doesn't feel good to buy what's unloved and distressed. But what feels good does not necessarily correlate well with success in investing.

Starting point is 00:06:43 The other thing about temperament that I wanted to highlight is how each of our investments are underpinned by some sort of story we tell ourselves. And too often, people claim to stories that they think are true because they desperately want them to be true, and not because it actually reflects reality. So Morgan Housel, he calls these appealing fictions. An appealing fiction happens when you're smart, you want to find a solution, but you face a combination of limited control and high stakes. Appealing fictions can also make you believe just about anything. Whether we like it or not, investing will always have some sort of element of forecasting to it. This element of uncertainty will always exist. So one way to think about maximizing your

Starting point is 00:07:30 odds of success is trying to align your forecast with reality as closely as possible. If your story of the future is a financial fiction and has a low likelihood of actually playing out, then you're just setting yourself up for trouble. Part of this is also recognizing that we all have an incomplete view of the world. The world is just too complicated to fully comprehend all of the moving pieces. We don't know what we don't know, and we're perceiving the world around us through a very limited set of mental models. Daniel Kahneman once said, hindsight or the ability to explain the past gives us the illusion that the world is understandable. It gives us the illusion that the world makes sense, even when it doesn't make sense. That's a big

Starting point is 00:08:16 deal in producing mistakes in many fields." In investing, that illusion can especially be dangerous, because markets have a way of humbling even the most confident narratives. We look back at what happened and we can convince ourselves that the way things played out was just obvious, when in reality, the outcome could have easily gone the other way. The best investors are the ones who stay humble about what they can't know, constantly testing their stories against reality instead of falling in love with them. And I think that's what makes this so tricky. When we run into something we don't fully understand, our brains don't like leaving that blank space there. We want an explanation and we want the world to feel coherent. So we fill in the missing pieces with a story that

Starting point is 00:09:04 makes sense to us based on our own experiences and perspectives. But those experiences are always limited. And that means our explanations often leave out things we can't see or don't even realize we're missing. In a world as complex as investing, those blind spots are everywhere. And the stories we tell ourselves can feel like clarity when they're really just comfort. So let's dig in here to some of the ideas that Connman discusses in detail in his book. One of the interesting things about behavioral economics is that when we look at other people and how they behave, it can seem obvious to us that some people are behaving irrationally, or they're just making decisions that we ourselves would not make. But when it comes to our own actions, we can have a really hard time making some of

Starting point is 00:09:51 those same decisions. When we're an outside observer, we don't have all that emotional baggage that comes with making that decision that the other person is grappling with. The irony here is that ideally we would be better off being able to make these right decisions for ourselves, because we actually have to deal with the real consequences of those decisions. Connman writes in the intro, it is much easier as well as far more enjoyable to identify and label the mistakes of others than to recognize our own, end quote. Of course, I'm no expert when it comes to this like Connman is, but I just fall for many of the same biases and mistakes as everybody else. But one helpful method of dealing with really difficult or painful decisions is to imagine

Starting point is 00:10:39 one of your close friends or siblings being in the exact same situation that you are in. And then ask yourself, what would you tell them to do? What would be the obvious decision for them to make? Sometimes if we take a step back and look at the situation as if we were an outside observer, we can see things a bit more clearly because in the moment we have all of these emotional attachments that would lead us to do things that would really look foolish from an outsider's perspective. Connman opens up the book by discussing System 1 versus System 2 thinking. System 1 thinking is your mind on automatic mode. If I said to you, what is 1 plus 1, your mind would

Starting point is 00:11:22 automatically say 2. You didn't need to consciously think about it or think through the steps. System 1 thinking is fast, intuitive, and effortless. System 2 thinking, on the other hand, requires a deeper level of thinking. If I say, what is 17 times 24? the system one part of the brain would not be able to tell you the answer immediately. We can think of system two thinking as slow thinking as it requires a sequence of steps to solve the problem. Rather than being fast and effortless, it's slow and requires deliberate effort. Hence, you can see why the book is titled, Thinking Fast and Slow. The system one part of our brain is pretty much active whenever we're awake.

Starting point is 00:12:04 Perhaps it's detecting spatial awareness of where things are at and what we're seeing, reading the words that pop up on our TV screen, or driving our car down the road. System 2 is also active while we're awake, but typically it's in a comfortable, low-effort mode. But when System 1 runs into some difficulties, it calls upon System 2 to support the tougher problems. This arrangement works well because System 1 is generally very good at what it does. Its model of familiar situations are accurate, and its initial reactions to challenges are swift and generally appropriate. However, System 1 has biases and systemic errors in specific situations. There are a couple of different examples here in the book, but to help illustrate how what is going

Starting point is 00:12:51 on in our minds might not match with the reality, he shares a classic illusion where it shows two different lines where one line has arrows that are pointing inward and the other line has the arrows pointing outward. We can obviously see that the line with the arrows pointing outward. We can obviously see that the line with the arrows pointing outward, are longer. But if we were to actually pull out a ruler, then we would see that the length of the lines is actually the exact same. The important takeaway from this isn't that there are these visual illusions that can trick our minds, it's that not all illusions are visual. We also have cognitive illusions. For example, let's say we bought a stock for 100, the stock price dropped to 50, now we're sitting on a 50% loss. It's very very very

Starting point is 00:13:37 It's very possible that we have these inherent biases telling us, I made a mistake in buying this, I'll sell when I get back to even. Or this is an amazing business. Surely it's going to recover and reach new highs. This sort of thinking can potentially prevent us from seeing reality for what it really is, such as if the investment thesis has fundamentally changed, or the future prospects of the business are considerably different than what we originally proposed. The question of cognitive illusions is whether or not they can be overcome.

Starting point is 00:14:08 Kahneman explains that the research he has seen on this is not encouraging, because System 1 thinking operates automatically and cannot be turned off at will. Errors of intuitive thought are often difficult to prevent and constantly questioning or thinking would be impossibly tedious. And System 2 thinking is too slow and inefficient to serve as a substitute to System 1 in making these routine decisions. The best we can do is compromise, learning to recognize situations in which mistakes are likely and try harder to avoid significant mistakes when the stakes are high. A somewhat remarkable aspect of our lives is that it seems that we rarely

Starting point is 00:14:51 get stumped. We occasionally face the 17 times 24 example, but these dumbfounded moments can be rare. The normal state of your mind is that you have intuitive feelings and opinions on just about everything that comes your way. You like or dislike people long before you know much about them, you trust or distrust strangers without knowing why, and you feel that a company is bound to succeed without analyzing it. Connemon explains whether you state them or not, you often have answers to questions that you do not completely understand, relying on evidence that you can neither explain nor defend. And when I read this, I feel like he's talking directly to me. So often, I form an opinion about a company in my head without actually having done the real

Starting point is 00:15:39 research behind it. And although I might not really tell anyone else what my opinion is, it's still there in my head. And I'm sure many of our listeners can resonate with that idea as well. Connman then reasons that if a satisfactory answer to a hard question is not found quickly, then our system one thinking will find a related question that is easier and will answer it. This method of answering one question in place of another is referred to as substitution. Connman pondered how people managed to make judgments of probability without knowing precisely what the actual probabilities are, and he concluded that people must somehow simplify this impossible task. When people are called upon to judge probability, they can judge the probability of something

Starting point is 00:16:25 else when faced with such a difficult question. To share some more concrete examples here, someone might ask you how happy you are with life these days. It's a tough question because your mood varies throughout the day and each day is different. Your mind might answer this question by asking itself what your mood is right now in this moment. It's a much easier question to answer and directionally would oftentimes be correct. But answering a question through substitution can also lead to some serious errors. Another example of substitution is using the classic example of why 90% of drivers believe that they're better than average. Answering the question on whether you are a better driver than average can be a difficult one because it requires

Starting point is 00:17:08 an assessment of the average quality of drivers. Instead of seriously responding to that question, respondents instead ask themselves if they are a good driver, to which 90% of them are going to say yes. The mental shotgun approach makes it easier to generate quick answers to difficult questions without imposing too much work on System 2. As of the time of writing, the market is currently experiencing a bloodbath in the software space. Most notably, I hold Constellation Software in the two spinoffs, and the market has totally given up on these names. Other software companies that are down significantly from their highs include companies like

Starting point is 00:17:46 Adobe and Salesforce. With a lot of software names selling off, I think there are plenty of angles to look at this. One might say that the market is very momentum driven at the moment, so money is flowing out of software companies into the AI names, and momentum traders are playing that momentum. Let's take a quick break and hear from today's sponsors. All right, I want you guys to imagine spending three days in Oslo at the high high of the summer. You've got long days of daylight, incredible food, floating saunas on the Oslo Fjord, and every conversation you have is with people who are actually shaping the future.

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Starting point is 00:22:34 more on this at the end of the episode. The software sell-off was also a stark reminder for me of just how volatile stocks can be and how the market has a way of testing each of us eventually. It's one thing to watch a sell-off on the sidelines, and it's a whole other thing to actually experience it for yourself with your own money on the line. Since the market can oftentimes swing like a pendulum, great companies that swing too far on the upside and become overvalued can just as easily swing back the other direction and become undervalued for a variety of reasons. As Kahneman discussed, we live in a probabilistic world. Anyone who tells you that an investment will play out a certain way with 100% certainty is lying to you.

Starting point is 00:23:19 Jumping back to the System 1, System 2 thinking, when System 1 uses substitution to simplify the problem, System 2 thinking can choose to either accept or reject this initial gut reaction. However, a lazy system too often follows the path of least resistance. Furthermore, you may not even realize that the original question or problem was difficult because the intuitive answer just came right to your mind. One of the most important ways substitution shows up in investing is when we replace a hard analytical question with a much easier emotional one.

Starting point is 00:23:55 So instead of asking, what is the intrinsic value of this business and what are the probabilities attached to the different outcomes, we can ask something much more simple. So you can ask yourself things like, do I like this company? Does this stock feel cheap after falling 50%? These substitute questions are easier for our system one to answer, but they can quietly lead us away from rational decision-making because liking a company or seeing a lower stock price tells very little about the future returns. Another common form of substitution happens when investors confuse stories with probabilities. So rather than asking, what is the statistical likelihood that this company will succeed relative to similar businesses in the past, we ask, is this a compelling

Starting point is 00:24:42 narrative? If the story is exciting, for example, the company's writing the AI wave or they're addressing a massive TAM, then our system one can supply a confident answer even when the base rates are unfavorable. This is how investors end up overpaying for growth or assuming success is a inevitable simply because the story feels convincing. Substitution can also play a role during market drawdowns. So when prices fall sharply, the difficult question is whether the long-term cash flow prospects of the business have materially changed. But instead, we often answer an easier question. How uncomfortable does this loss feel right now? That emotional discomfort can be mistaken for new information, causing investors to sell not because the investment thesis is broken, but because

Starting point is 00:25:31 the pain of seeing red numbers has become too intense. And trust me, when it comes to drawdowns in my own portfolio, I feel that discomfort just like everybody else. Having an understanding around your thesis, around a company for me, it doesn't make the drawdowns any less painful in most cases. I thought that chapter 19 in the book titled The Illusion of Understanding, it was quite relevant for investors. So in Nassim Taleb's book, The Black Swan, he gets into the idea of the narrative fallacy. This describes how flawed stories of the past shape our views of the world and our expectations of the future. Narrative fallacies inevitably rise from this continuous attempt to make sense of the world. The stories that people tend to find compelling

Starting point is 00:26:18 are simple, they're concrete rather than abstract. They assign a larger role to talent, than Tulluk, and they focus more on the few striking events that happened rather than on the countless events that failed to happen. Taleb suggests that we humans are constantly fooling ourselves by constructing flimsy accounts of the past and believing that they're true. People love a good story that helps them make sense of the world. So to help illustrate how stories can give people a false sense of the world, Kahneman discusses the story of Google. As of the time of writing, Google, now Alphabet, is one of the world's most successful companies. In September of 1998, two Stanford graduate students in the Computer Science Department

Starting point is 00:27:05 came up with the superior way of searching information on the internet. They obtained funding and made a series of decisions that worked out very well. Within just a few years, the company was one of the most valuable stocks in America. On one memorable occasion, they were lucky, which made it. makes the story even more compelling. A year after founding Google, they were willing to sell their company for less than $1 million. But the buyer said that the price was too high. So the transaction, of course, never happened. This single lucky incident, it helps showcase the multitude of ways in which luck affected where Google is today. The story of Google mostly focuses

Starting point is 00:27:46 on the founders and all of the fantastic decisions they made. And it largely ignores the companies that ended up falling by the wayside. The story of Google might tell you some things about how Google succeeded, but it doesn't necessarily tell you anything about how businesses in general succeed, because Google's competitors may have taken a very similar business approach, but had a couple of unlucky breaks that just didn't fall in their favor. What these stories tend to leave out are base rates. How many other companies pursued a similar strategy had comparable talent and still failed?

Starting point is 00:28:21 This leads us to dramatically overestimate the odds of success. Connemann writes here, the human mind does not deal well with non-events. The fact that many of the important events that did occur involve choices further tempts you to exaggerate the role of skill and underestimate the part that luck played in the outcome. Because every critical decision turned out well, the record suggests almost flawless execution. But bad luck could have disrupted any one of these successful statistics. steps, and the halo effect adds the final touches, lending an aura of invincibility to the

Starting point is 00:28:57 heroes of the story. The main takeaway from this point is that luck is likely understated in the story of any company, and the more luck is involved in an outcome, the less there really is to learn from the decisions the business people made in making that company as success. So since our minds cling to making sense of the world and crafting narratives and stories around it, the past tends to have played out in a way that makes sense to us. But at the same time, we might not be so sure of how the future will unfold at the same time. And then as the future continues to unfold, our view of the world is continually changing. And we tend to be a little

Starting point is 00:29:38 bit forgetful of how we used to view things, especially when it comes to the large, unexpected events. So think about the COVID pandemic, for example. So before and after the pandemic, I'm sure that most people's views of the world's changed pretty drastically. But we tend to be rather forgetful of what we used to believe prior to that big event. And this can lead us to underestimate the amount of surprise that we felt from those types of events. Again, this is something I can see in myself as well. A stock goes up and I'm thinking, of course the stock was going to do well. Why didn't I buy more initially?

Starting point is 00:30:14 Or when a stock goes down, I think, of course I overpaid for the business or XYZ competitor was going to steal market share. Why did I ever buy that? This is also known as hindsight bias. Everything appears obvious with the benefit of hindsight. Hindsight bias can also lead stock investors to make poor decisions because they fall prey to resulting. They might assess the quality of their decisions not by whether the process was sound, but by whether its outcome was good or bad. For example, consider a low-risk surgical intervention in which an unpredictable accident occurs, that causes the patient's death. The jury would then be prone to believe, with the benefit of hindsight, that the operation was actually risky, and the doctor who ordered it should have

Starting point is 00:30:57 known better. This hindsight or resulting bias makes it almost impossible to evaluate a decision properly. This is also a challenge for asset managers. One asset manager might make several good decisions that end up turning out poorly. This could then lead to investor outflows, and correspondingly, you might have another asset manager that made several poor decisions that happened to turn out well for them and experience significant inflows despite their average decision not being as good. These snap decisions or conclusions come from System 1 thinking. By System 1's logic, the world is more tidy, simple, predictable, and coherent than it really is. And these illusions are comforting.

Starting point is 00:31:38 They tell us that we can predict and control the future. Kahneman also has a discussion around the engine of capitalism. Many investors, myself included, have a bias toward optimism. Many of us view the world as more kind than it really is, believe our skills are better than they truly are, and the goals we set as more achievable than they're likely to be. We also tend to exaggerate our ability to forecast the future. Economen writes, in terms of its consequences for decisions, the optimistic bias may well be the most significant of the cognitive biases, because optimistic bias can be both a blessing

Starting point is 00:32:14 and a risk. You should be both happy and wary if you are temperamentally optimistic, end quote. So he explains that an optimistic attitude is largely inherited, and it's part of a general disposition for well-being, which may also include a preference for seeing the bright side of everything. Optimists tend to be happier, have more positive attitudes, they're more resilient and adapting to failures and hardships, their chances of clinical depression are reduced, their immune systems are stronger, they take better care of their health, and they're likely to live longer. They're also more prone to investing in individual stocks. Optimists also play a disproportionate role in shaping our lives. Optimists are the inventors, entrepreneurs, and are

Starting point is 00:32:56 political or military leaders, so not your average person. They seek challenges and take risks. And with success, their self-confidence and optimism is reinforced through the admiration of others. But the blessings of optimism are offered only to individuals who are only mildly by biased and don't lose sight of reality. The downside of optimism is that it can lead individuals and institutions to take significant risk, overestimating the odds of success. Because they misread the risks, optimistic entrepreneurs often believe they are prudent even when they're not. Tying this more closely to the engine of capitalism, the chances that a small business will survive for five years in the U.S. are about 35 percent, according to the book, but it looks like

Starting point is 00:33:41 the more accurate data today might be closer to 50. But as you can imagine, entrepreneurs overestimate their ability to overcome these odds, as most entrepreneurs put their odds of success at 70% or higher. And one-third of entrepreneurs shared that their chances of failing were zero. These statistics shouldn't be surprising, as entrepreneurs tend to be optimists and who would start a business if they expected it to fail within the next five years? That in itself would be setting yourself up for failure. Connman tells a story of him and his wife. They went on a vacation to Vancouver Island,

Starting point is 00:34:18 and they stayed at this attractive but deserted motel on a little traveled road in the middle of a forest. The owners were a charming young couple who needed little prompting to tell their story of how they came around to owning this motel. They had been schoolteachers in the Providence of Alberta, and they decided to change their life by using their life savings to buy this motel, which was built just 12 years earlier. Not realizing the irony at hand, the couple told Conneman that they were able to buy the motel for cheap because six or seven previous owners had failed in making it a success, and they planned to take on a loan to make the establishment more attractive by building a restaurant next to it. They felt no need to explain why they expected

Starting point is 00:35:03 to succeed while six or seven others had failed. Connman writes, a common thread of boldness and optimism links business people, from motel owners to superstar CEOs, end quote. For public company CEOs, a prime example is the leaders of large companies who sometimes make these big, splashy acquisitions, acting on the mistaken belief that they can manage the assets of another company better than the current owners do. This overconfidence leads them to potentially overpaying and overestimating potential synergies. The other thing about optimism and overconfidence is that this is the type of leadership that employees want to rally behind. For a number of years, professors at Duke University conducted a survey where they asked CFOs of large corporations what the return of the S&P 500 will be

Starting point is 00:35:51 over the next year. Their findings clearly showed that these CFOs didn't have any clue about the short-term future of the stock market, as the correlation between their estimates and the true value was negative. When they said the market would go down, it tended to go up and vice versa. This shouldn't be as surprise either for our listeners, as Buffett has shared that stock market forecasting is a fool's errand. But these CFOs did not appear to realize that their forecasts were worthless. CFOs were also asked to give a high forecast and a low forecast with 80% certainty that the index's ending value would be within that range. So it's essentially saying, without the big surprises, what range will the S&P 500 be in?

Starting point is 00:36:35 Based on historical data, the correct range is about minus 10% returns on the low end and plus 30% returns on the high end. This confidence interval was four times wider than the intervals that were shared in the study, further showcasing the CFOs overconfidence. But what shareholder base or boardroom wants to hear from the truthful manager who speaks in those terms. The wide confidence interval may seem like a confession of ignorance, which is not socially acceptable for someone who is paid to be knowledgeable in financial matters. And even if they knew how little they know, they could be penalized for admitting it.

Starting point is 00:37:15 The effects of high optimism on decision-making are likely a mixed blessing. The main benefits include its contributions to good execution and resilience when facing setbacks. You could also argue that optimism is essential in mind. business, because setbacks are inevitable, and someone who keeps going forward anyways, will be able to push through until the next success comes their way. One way to combat this optimism and overconfidence when it comes to selecting investments is by performing a premortem. A premortem is an exercise where you imagine that an investment ends up going terribly wrong

Starting point is 00:37:50 in the future, and then from there, work backward to identify all the plausible reasons why it went wrong. This exercise forces System 2 to engage by identifying potential risks and blind spots, and it helps bring base rates into the equation, which optimism would otherwise suppress. Premortems can force us to look at what could go wrong when the outcome is ultimately uncertain and help prevent us from making those costly investment mistakes. As many of our listeners know, Conneman and Terversky, they popularized the idea of loss version. Their research from 1979 found that losses hurt roughly twice as much as equivalent gains

Starting point is 00:38:29 feel good. So, for example, losing $10,000 in the market hurts far more than the joy we feel from gaining $10,000. This asymmetry and emotional impact explains why drawdowns can just feel so overwhelming, even when we know that drawdowns are expected. It also helps explain why investors often make emotional decisions at exactly the wrong time. In some sense, loss aversion is logical. A relatively large loss makes us more sensitive to similar and subsequent losses, because the subsequent loss would consume an even greater proportion of our net worth. But loss aversion is illogical if it leads us to making a bad bet. The danger for investors is when avoiding the emotional pain of losses takes priority over making decisions based on probabilities and expected

Starting point is 00:39:23 returns. When that happens, loss aversion stops protecting capital and starts actively destroying long-term performance. For example, let's say you can reasonably expect a portfolio of stocks to generate roughly an 8% return over the next 20 years. Then it would be illogical to have a majority of your portfolio in bonds over that same time period if they yield only 4%. Let's take a quick break and hear from today's sponsors. No, it's not your imagination. Risk and regulation are ramping up, and customers now expect proof of security just to do business.

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Starting point is 00:43:09 Connman also framed loss aversion in another way that I hadn't really thought about before, but I thought it was really interesting. So he frames two different scenarios here. So in the first scenario, take a second to think about which of the two options you would prefer here. So you have option A, you would get $900 for sure. Or option B, you get $1,000 with 90% probability. If you're like most people, you would probably just take option A, take the $900, because it's a sure thing, and you don't want to risk potentially getting nothing.

Starting point is 00:43:43 And then Connman flips this example on its head. Now, in this next example, for Option A, let's assume that you would lose $900 for sure. And then for Option B, you would lose $1,000 with 90% certainty. Which would you choose out of these two options? Most people in this scenario wouldn't choose Option A like they would in the previous example. they would actually select option B, meaning that they were likely to lose more money in that scenario, but have a slim chance of getting out without losing anything. To summarize the findings from this hypothetical scenario, humans tend to be risk-averse

Starting point is 00:44:22 when sitting on gains, but risk-seeking when facing losses. Now, this actually has profound implications when it comes to stock investing, because if you invest in individual stocks, you're inevitably going to find that. yourself holding a stock that is down substantially. Consider that you purchase the stock for 100, and as you're holding it, the company starts performing poorly as the economy is entering a recession. So the stock price dropped to $40. Because of loss aversion, many investors can be prone to just hang on to the stock, even if they believe it is likely to drop down to an even lower price. So theoretically, if you signed a 90% probability that the stock would drop from $40 down to 30,

Starting point is 00:45:06 due to, you know, the poor economy, then you may be better off selling the stock at 40 in reinvesting it into a stronger company. But because we're risk-seeking when faced with the loss, we'd be prone to hold onto that stock, even with the slim chance that it's going to bounce back to $100 a share. However, if a stock has fallen and you believe that the overall business fundamentals remain intact or potentially have even improved, then if that's the case, it may be justify to continue holding onto it or maybe even consider adding to it. When the fundamentals are strong and probabilities are in your favor, selling simply to relieve the discomfort of a loss can be just as damaging as holding on blindly. Now, I mentioned that humans tend to be risk-averse

Starting point is 00:45:50 when sitting on gains, but risk-seeking when facing losses, if we flip this scenario and look at what people do when a stock is up, we often see the opposite mistake. So imagine you bought a stock at 100. It quickly rises to 160 as the business executes well and the fundamentals remain strong. Many investors feel the urge to sell early to lock in gains, even if they believe there's a high probability the stock could continue compounding for the next several years. Because gains can feel fragile, investors become overly risk-averse and prioritize the certainty of profits over the larger expected value of staying investing. I can't count the number of times I've had a listener of the show tell me that they had one of today's great companies many years ago,

Starting point is 00:46:35 and they thought they were smart by locking in a 40% 50% profit in the first year of owning it. Before we get into the next topic here, I wanted to share a little thought experiment with you. Take a few seconds to consider the following question. Was Gandhi more or less than 144 years old when he died? So I'll give you a moment to think about that question, and once you have an answer here, I'll ask the second question. How old was Gandhi when he died? So you probably would guess that Gandhi was less than the age of 144.

Starting point is 00:47:09 And even if we don't consciously do this, the number in the first question likely influenced the number we would choose for the second question. So the right answer was 78, by the way. You probably didn't believe for a moment that he lived for 144 years, but your associative machinery surely generated an impression of a very ancient person. Kahneman believes that the system one part of our brain tries its best to construct a world in which the anchor matches reality. And this is something that likely happens totally subconsciously.

Starting point is 00:47:46 So he conducted a study where there were two groups of people who had to answer questions similar to the one I just asked about Gandhi. Another example was guessing the height of the tallest redwood tree in the world. So study participants who were asked if the height of the tallest redwood was more or less than 1200 feet, they had answers that were significantly different than those who weren't asked that question that anchored them. So for the participants who were anchored to the 1200 feet, their average response was 840 feet, whereas the group that wasn't anchored had an average response of just 280

Starting point is 00:48:25 fee, which is a significant difference. Similar experiments have been done with real estate agents, who are significantly influenced by the asking price of a home when determining the home's fair market value. Of course, this explains the concept of anchoring, which is a tendency for a given number to impact people's perception of an unknown value. I think one of the best examples of anchoring is how we tend to look at the stock price prior to determining the intrinsic value of a company. We know that we should calculate the value of a company without considering what the market believes the company is worth, but the stock price will almost inevitably influence our estimation of the stock's true worth. And it's for this reason that overpriced stocks look attractive and

Starting point is 00:49:11 underpriced stocks look risky. When prices are high and rising, our system one brain thinks, well, something must be going right, even if the fundamentals don't justify it. Underpriced stocks, on the other hand, feel risky because of a low or falling price, anchors are thinking towards negative narratives, making a search for reasons why the market might just be right. In both cases, the anchor distorts our judgment by reversing the proper order of analysis, letting price inform value instead of letting value inform price. I think we're all at least somewhat prone when it comes to our entry price of a stock. If we've decided that deteriorating fundamentals are a reason we want to exit, but now that the stock price is down, we don't want to sell it a big

Starting point is 00:49:56 loss. We would rather wait it out, assuming that soon the stock price will recover and get closer to our entry price, so then we can exit. The tough reality is that the market does not know and does not care what price you paid for the company. We have all these feelings and emotions related to the stocks in our portfolio, but the stock doesn't know or care we own it. When choosing to hold or sell an investment, it's best to ignore what your initial purchase

Starting point is 00:50:24 price was because your initial purchase price has no effect on the true underlying value of the company. If you realize you've made a mistake in purchasing a company, it's oftentimes best to just cut your losses and move that capital to opportunities that are more likely to compound your wealth from here. Buffett once shared the wise words that it's often a mistake to try to make your money back the way you lost it. You can think of gamblers at the roulette wheel.

Starting point is 00:50:49 gambler who's lost their money can be tempted to go back to the roulette whale to make it back the way they lost it, which is an inherent part of our human nature. So turning to another bias that I see all too often, we have the availability bias. This is the tendency to judge the likelihood of something based on how easily examples come to mind. Instead of thinking statistically, our brains rely on what feels recent or sparks an emotional response. If something is easy to recall, we assume it must be common or important, even if it has no real importance. This also reminds me of the recency bias as well. One of the most available things about a stock is, of course, the stock price. So naturally, since it's so available and tells us whether investors are making

Starting point is 00:51:36 or losing money on the day, it will be used as a proxy to judge whether the news is good or bad. So earnings reports are a perfect example of this. So after checking the headline numbers, investors tend to immediately check how the market reacted to the report instead of coming to their own conclusions. Our brains are designed to seek the path of least resistance. It takes time and it takes work to read through an earnings report, tune into the earnings call, work those into your current view of the company and how things are developing. It's much easier to just check the stock price and make an assessment of the report based on that. Connman explains that the availability bias is especially strong when events are dramatic or widely discussed. For example, after seeing

Starting point is 00:52:20 news coverage of a plane crash, people tend to overestimate how dangerous flying is, even though driving is statistically far riskier. The problem isn't that our brains are irrational, is that they're designed to respond to what grabs our attention, not exactly what's most likely. And in today's world, attention is often shaped by headlines, social media, and emotionally charged stories. This bias has huge implications for stock investing because financial markets are saturated with headlines and information. Investors constantly see breaking news, earning surprises, analyst upgrades, and volatile day-to-day price movements. When a stock is soaring, it becomes mentally available, and investors start to feel like it must be a great opportunity. When the

Starting point is 00:53:03 stock's crashing, that decline becomes salient, and people assume the business must be permanently broken. Availability bias also explains why investors tend to overweight recent events and underweight the base rates. After a market crash, people become convinced that another crash is just around the corner. After a long bull market, investors start to believe that stocks only go up. In both cases, the most recent experience dominates perception, and the future starts to feel like a continuation of whatever just happened. This is one reason why investors often buy high during euphoric periods, and sell low during fearful ones. To wrap up the episode, I wanted to talk a little bit about Constellation Software

Starting point is 00:53:45 and what is happening in the software industry overall with this AI wave. Constellation has been a company that has captured many people's attention due to its high returns. It's delivered to shareholders and its long track record of compounding capital. The company never had a significant drawdown over the past 20 years or so until just recently when there's been just massive wave of selling. Here, as the time of recording, the CSU shares that are traded on the Toronto Stock Exchange, they're down by over 50% since the high in May of 2025.

Starting point is 00:54:18 For about a year now, the software sector overall has seen declines in its share prices due to AI fears. And with each new announcement from all these AI companies, software stocks just seem to keep sliding and sliding. So the IGV index, which is a software index, it has seen significant selling pressure as there's been record volumes, and it's the most oversold. It's been in about a decade. So I first initiated a position and constellation back in early 2023, and just by happenstance, the shares were trading at a similar price back then to where they are today. This drawdown is primarily driven by two factors. So first, you have the company's founder and president,

Starting point is 00:54:59 Mark Leonard. He stepped down in recent months. And then second is the fears related to AI, which has led to many software companies selling off in recent months. On the first point, I wanted to share a line from Sequoia Capital's Year and Letter that I thought was just beautifully written and I wanted to share here. They write, Leonard is a combination of intellect, agency, diligence, humility, and decency. We are not sure we have ever found so concentrated in any individual CEO. Very few founders get a company off the ground. Very few then grow that company successfully over 30 years.

Starting point is 00:55:32 Very few CEOs truly care about the value they deliver for the common shareholder. Very few are both introspective and worldly enough to understand when and how to increase their circle of competence and to change their minds and pivot when necessary. Very few CEOs build up such capable leadership talent that they can be trusted to be CEOs of their own companies, both inside and outside of the mothership. Mark Leonard has done all of these things. Starting in January 2015, Mark has taken zero salary, bonus, or reimbursement of any kind while delivering nearly 800% returns to shareholders.

Starting point is 00:56:16 We have been honored to invest with Mark Leonard and we wish him a full and speedy recovery. Notwithstanding our admiration for Mark Leonard, we believe former CEO, Mark Miller, is eminently qualified to take the CEO reins. He was a co-founder of the very first acquisition Constellation ever made, and he grew his branch of the Constellation Tree in exemplary fashion over the subsequent 30 years. While Mark Leonard was an investor who learned the software business over those decades, Mark Miller was a developer who learned to be an investor. Mark Miller's background as a developer should give him extra depth and credibility to help

Starting point is 00:56:53 the company navigate what it means to write and maintain software in an AI-enabled era. end quote. So I'll be sure to get that letter linked in the show notes for those who are interested in checking it out. I found it to be very insightful. So Constellation's also been discussed extensively in our mastermind community. And one of our members shared a chart that I thought was really interesting. So it essentially shows the institutional flows between software stocks and more of these hardware plays like semiconductors and semiconductor equipment stocks. And over the past year, flows to software have fallen significantly, and the hardware or AI bets have increased significantly. So this highlights how momentum-driven our market can be.

Starting point is 00:57:39 Based on my experience, it seems that many institutional investors can like a stock like consolation, but if the short-term flows, like what I just mentioned, they aren't playing to their favor, then they just won't bother with the stock. Many institutional investors have this pressure to perform in the near term to try and keep their investors happy. And then I hear from some institutional investors who were some of the biggest constellation bulls I know, and they've also held the stock for years. And yet they sold out because of these momentum-based flows in order to appease shareholders.

Starting point is 00:58:15 It reminds me of the quote from Thomas Phelps in his book 101 in the stock market. He essentially said that, you shouldn't make an investment decision for a non-investment reason. So as a value investor, I interpret that as don't sell an investment for something that is unrelated to the actual business and its underlying thesis. So if you decide that constellation will get disrupted by AI, then sure, it might make sense to sell. But in this situation where these institutional investors are selling for non-investment reasons like momentum or flows, this is the type of situation where you can get these big mispricings. We have a member of our community who runs a VMS acquirer, and he's a former portfolio manager at Constellation.

Starting point is 00:59:00 And he's personally seeing a lot of opportunities for these VMS businesses to utilize AI to enhance their business. And so far, he wasn't seeing much of a threat in terms of disruption. So this member talked about how the companies he manages now have all these tools available to them that allow them to pursue new opportunities that would have been projects that would have been too cumbersome or too time-consuming to pursue, but now AI all of a sudden, it makes some of these opportunities more attractive. Now, can somebody else replicate a certain piece of software or technology and just roll it out? Of course, but it needs to be compliant with ever-changing laws and

Starting point is 00:59:40 regulations, needs to be updated as the industry evolves and customer needs change, and the customer needs it to work essentially all the time. And then one of our other members who worked at Microsoft for more than two decades, he highlighted that SaaS stands for software as a service. Part of a VMS product is the servicing of it. You need a professional vendor that understands all of the complexity that goes into a highly specialized software solution. Could the customer switch to a similar solution that's half the price or they could develop maybe a solution for themselves? Sure, but there's significant costs of switching to a new software. So part of what a customer is paying for, is it also ensuring that the solution works, and if the solution were to ever break,

Starting point is 01:00:28 then it gets fixed rather quickly. AI lowers the cost of software development, but there's much more to building a software business than just creating software. Another ingredient, for example, is distribution. You can have the best software in the world, but if you can't distribute it and acquire customers, then it might as well be useless. Since the solutions that Constellation offers are mission-critical and they're essential to their customers' operations, it would be very difficult to convince a lot of them to switch to another solution because what they have already works fine, there are switching costs and risk involved in switching, and Constellations built trust with several of these customers for decades. So there's little incentive to switch unless the

Starting point is 01:01:12 new solution was significantly better. Another part of the bowl thesis for Constellation is that with these software valuations falling, they may be able to find more opportunities for more attractive deals. So one of their recent purchases was in Japan, and based on what I was hearing, the founders sold the business because they essentially believe that AI is going to disrupt all of software. So they decided to get out before the tide fully turned. If everyone's afraid to touch software companies, then that should provide no shortage of opportunities for Constellation to do more deals. Lastly, Constellations managed VMS businesses for over 30 years now. Their new CEO, Mark Miller, was a developer who learned to be an investor after joining

Starting point is 01:01:58 Constellation, and him and the other leaders at the company have lived through multiple eras of software. Code has been updated and rewritten to adapt to ever-changing customer needs, and the rise of AI will present another opportunity for them to navigate this dynamic market environment. If Constellation is able to utilize AI to deliver more value to its customers, then, you know, it could be a tool for improving its market position. In the Sequoia letter, they wrote, Constellation's companies certainly cannot stand still. We would argue that they have never been able to stand still, that they haven't, and that they are not standing still now. Mark Miller has already revved up the company's test and learn culture to comprehend and adopt

Starting point is 01:02:44 AI. They have not found any areas where AI has hurt their businesses yet, but they are on the lookout. Mark wants Constellation's businesses to disrupt themselves if they must. He set a task for all Constellation units to try to solve new problems for their customers with AI and generate new revenue from AI, end quote. So one thing I would like to see from management is purchasing shares on the open market. So as the shares of the Constellation family of companies have declined, we haven't seen a lot of major buying from the management team, which I think could help improve investor sentiment turning the other way. So if the management team believes in the opportunities that lay ahead for the company, then I, as a shareholder, would prefer to see them

Starting point is 01:03:29 put more money behind that belief. So as of the time we're recording, Constellation trades at a high-teens multiple of 2026 earnings. So if they're able to continue this acquisition strategy and prevent their existing businesses from being disrupted, then I believe this valuation is compelling. So with that, I think we'll close out the episode there. It will be quite interesting to see how the Constellation story continues to play out. Thanks a lot for tuning in, and I hope to see you again next time. Thanks for listening to TIP. Follow We Study Billionaires on your favorite podcast app, and visit The Investorspodcast.com for show notes and educational resources. This podcast is for informational and entertainment purposes only and does not provide financial, investment, tax or legal

Starting point is 01:04:13 advice. The content is impersonal and does not consider your objectives, financial situation or needs. Investing involves risk, including possible loss of principle, and past performance is not a guarantee of future results. Listeners should do their own research and consult a qualified professional before making any financial decisions. Nothing on this show is a recommendation or solicitation to buy or sell any security or other financial product. Hosts, guests, and the Investor's Podcast Network may hold positions in securities discussed and may change those positions at any time without notice. References to any third-party products, services or advertisers do not constitute endorsements, and the Investor's Podcast Network is not responsible for any claims made by them.

We Study Billionaires - The Investor’s Podcast Network - TIP793: Thinking Fast & Slow by Daniel Kahneman w/ Clay Finck

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