Yet Another Value Podcast - The (Working) Theory of Weird Markets

Episode Date: January 15, 2026

In this solo episode of Yet Another Value Podcast, host Andrew Walker introduces and unpacks his evolving investment concept: the Theory of Weird Markets. Andrew uses analogies from sports, AI, and Rubik’s Cube competitions to argue that traditional strategies in investing are increasingly obsolete. Instead, he suggests that in an age dominated by quant funds, AI, and machine learning, alpha lies at the edges—in unique, weird, or "N of 1" investment opportunities. This episode is part rough-draft, part invitation, as Andrew seeks listener feedback to refine the theory that will underpin much of his investing outlook for 2026. ____________________________________________________[00:00:00] Introduction and sponsor mention[00:02:02] Overview of episode structure[00:03:08] Theory of Weird Markets explained[00:05:17] Stock market as ultimate competition[00:09:09] Sports performance evolution examples[00:10:00] Rubik’s Cube as improvement analogy[00:13:11] Incentives in Rubik’s vs. investing[00:15:09] Finance history proves competition[00:17:30] Counterintuitive strategies dominate at scale[00:18:42] AI and chess: new strategy insights[00:20:00] AI poker strategy looks irrational[00:21:16] Humans must embrace “weird” edge[00:22:56] AI fails with unexpected variables[00:23:26] Power demand as under-modeled opportunity[00:24:35] Spinoffs and unique events as alpha[00:25:28] Warner Bros. Discovery case study[00:26:26] Management incentives and market edges[00:27:10] Writer’s block and theory reflection[00:28:21] Call for feedback and discussionLinks:Yet Another Value Blog - https://www.yetanothervalueblog.com See our legal disclaimer here: https://www.yetanothervalueblog.com/p/legal-and-disclaimerProduction and editing by The Podcast Consultant - https://thepodcastconsultant.com/

All right, hello, and welcome to the Yet Other Value Podcast. I'm your host, Andrew Walker. If you like this podcast, we mean a lot. If you could rate, subscribe, review, wherever you're watching or listening to it. And as always, if you don't like it, forget about it, don't rate, subscribe, review, and go on your way. See you later. Today's episode, I have a slightly different episode. I'm going to introduce a theory that I kind of talked about a little bit in my December

random ramblings. I've been thinking about a lot. I'm trying to write a piece on it. And I wanted to put, let's say, a rough draft of the theory out into the world to get feedback on, basically. So I'm going to, it's not my random ramblings, but it's just me talking about this theory. I'm putting it out there because I would love to hear from you if you've got thoughts on the theory, ways I can improve the theory, weakness in the theory, because as I'll discuss, it's kind of core time thinking about the upcoming year, investing, everything I do. So

you'll hear it all once I get there. So we're going to go to that episode, but first, a word from our sponsors. Today's podcast is sponsored by fiscal.aI. Fiscal.a.i is a modern data terminal built for investors who want an institutional-grade platform without the complexity. Whether you're an individual investor or professional portfolio manager, fiscal.a.I gives you instant access to years of financials, earnings transcripts, and company-specific segment and KPI databases, all in one intuitive platform. What makes it stand out from other platforms? Speed, depth, and ease of use. Their data updates within minutes of earnings reports, not day. Segment revenue, subscriber growth, is all there, easy to chart, compare, and export. I've been using Fiscal AI for

interesting ways to chart and graph and visualize different segment KPIs, comparisons, all of that. And I think it's been really interesting, particularly it's the segment. It's really the segment data when you put it in a graph. You can get some really interesting comparisons, you know, margins from one grocery or to another, how they've evolved different times, stuff like that. Anyway, use my link, fiscal.a.ai slash yav. That's fiscal.a.m.a. for two weeks free, plus 15% off any of their paid plans. That's fiscal.com. A.I. slash YAB. All right. Hello and welcome to a special episode of the yet another value podcast. They're all special, but this one is extra special. I'm your host, Andrew Walker, and today I have a

slightly different episode for you. I'll explain to a second. Let's just start the same way we start every episode. Quick disclaimer. Nothing on this podcast that in investing advice. Can't emphasize that enough. Can't tell you how weird, how strange I am all the time. We're actually going to be talking about how weird I am. That's a funny turn and phrase. So just remember that full disclaimer at the into the podcast, it's all to financial advisor, all that sure stuff. Okay, let me explain the purpose of this episode. So this is just me hopping on rambling like a man, madman. I do that once a month in a segment I call my random ramblings, but this is not that. The reason for this podcast is every year I do a lot of annual stuff, right? I write up my annual outlook for my yet another

value empire. I write up a letter, annual letter to investors, all sorts of annual stuff, right? And I'm hitting a little bit of a frozen point right now. I'm working on all of this stuff for this years and it's getting bigger and harder and all this sort of stuff. And the central thesis of what I'm trying to write up involves a theory, a theory that I kind of alluded to on my last random ramblings. And I call this the theory of weird markets. And I do understand how hoity to and, you know, arrogant a little bit it can say to sound, I have a theory of the markets. But it is what I'm calling my theory of weird markets. And that is kind of the center of a lot of my vision for my empire for how I'm thinking about investing everything in 2006.

So I need to get this theory piece, my theory of the markets piece, out before I can write everything else because I need links to send back to that to explain, hey, here's the full theory, if you want. But I'm heading a little bit of a writer's block, building it, just finishing it. I've got the visions in my head, but I'm having trouble getting them fully onto a paper. So I thought, hey, you know, a lot of my favorite writers, they will do podcast versions of their articles where they will literally just read the articles that they wrote, right? That, hey, I could do that.

Or maybe it's because I think I'm a better talker than I am. Maybe it's because I'm a worse writer than I would like to be. But I think I could kind of talk the theory out better than I can write it right now. So I kind of wanted to talk out. I'm not going to read my rough draft fully, but I'm going to, you know, I have my notes. I'm just going to kind of talk out the rough draft and put it into the podcast form. And this will be my rough draft of the theories of the markets, and I'll put it out. And then, you know, if you've got ideas, if you're listening and it kind of spurs a wheel,

or I say something, you're like, I firmly disagree at that, or I firmly agree with this, or it should go further. You can reach out to me. You can tell me, hey, Andrew, here's so to evolve your theory. And then, you know, I'll kind of put this podcast out. And then hopefully this podcast kind of cures my writer's block and my, you know, a conversation with people. You know, 10 years ago, I used to think sitting in a room just reading was the way to invest. And increasingly, I mean, I think you need to read. I think you need to be differentiated, but the conversation I have on the podcast, the conversations

I have with friends, they really help me think and evolve. So, you know, I think putting this out there and having a conversation with the few of you who respond with thoughts and everything, I think it can help me evolve and perfect this theory I'm working on. So that is my overarching reason and overarching thought process for this podcast. Let's dive into it. And let me start with the theory of my theory of weird markets. And again, I alluded to this a little bit in the December.

random ramblings, but here is the theory as I have come to think about it. The stock market is the most competitive game in the world. And in all games, across all competitive things, as the stakes get higher and higher and things get more and more specialized, the winning strategies at the highest levels often look counterintuitive or insane to what the game looked like when it was kind of less evolved or what even less evolved players would do. But those are insane and counter-attuitive strategies do come to dominate traditional strategies as the game gets better and better, gets more competitive as the players get more skilled. I think the stock market, you know, again, I think it's the most competitive game in the world. And I think the stock

market has increasingly reached the point where the traditional strategies are just dominated. You know, there's the rise of all the money in Pod Shop. So if you were like, hey, I'm trading on credit card data or something. I'd say, hey, I think Pod Shopps can probably trade these quarters a lot better than you. If there's the rise of quantitative models, if you're saying, hey, I'm trading stuff on value multiples, exclusively I buy things that are deep value five times earnings. I'd say, hey, I think the quant models can probably do that better than you faster than you can. There's increasingly machine learning and AI. And I think if you were saying, hey, I'm doing some general trend following or rules. Say, hey, man, I think the machine learning's kind of coming out there.

So anyway, I think the stock market is the most competitive game in the world. And increasingly, I think the traditional strategies are dominated. What does that mean for you and me? I think the winning strategies for smaller investors who aren't running pod shop money, who aren't running with, you know, $100 million computer systems, I think the winning strategies, actually the only strategy is the only way to find alpha is going to be in what I am calling weird. So that is my theory of weird markets. If you want to upperform, if you want to generate alpha, if you want to be different,

you have to do something weird going forward. You have to be investing in the weird. I've described them in the past as end of ones, things that have no parallel in the market. And, you know, my favorite historical example would be Twitter, Elon Musk, right? Elon Musk, the world's richest man, not a corporation, the world's richest man, decides to buy Twitter on a whim. And then he decides to back out of it. And he claims an MAA. There's only been like five publicly traded MAA cases in history.

So right away, you have something that hasn't happened a lot. And then, you know, the MAA cases in the past have been global financial crisis causes banks to fail or the individual company, you know, really gets hit, like basically gets hit by a meteor. In this case, it was world's richest man. once the back out has cold feet thinks he's overpaying. You know, it was an extremely strange case, and you would have all sorts of things, but I would just point to that as that's a really great example I like to use of and of wants.

So that is my overall theory. Let me go through some of the things I've just been thinking about as I've evolved there. And let me start with my first contention. That was the stock market is the world's most competitive game. And before I start talking about why I believe the stock market is the most competitive game, let me back up and look,

I said, as I talked about the most competitive game, games get more competitive over time. And it's really tough to evaluate that. You know, there's always in basketball, people will always debate was Michael Jordan or LeBron James the goat. And you're comparing across eras. It's really difficult to compare things across eras. But there are a lot of sports where there's quantitative standards that we can see across eras, and that makes it very easy to compare. You know, track and field.

If you run 100 meters in 10 seconds today, we can compare that to how the grates of 10 10, 20 years were, and we can say, hey, you know, the people today are fast and the people 10, 20 years ago. No, there would also be some debate of, hey, you know, sports performance, medicine, athletic, all this is much better today. Equipment is much better, so maybe you have that. But, you know, you can say that runners generally are faster day. One example I came up with, baseball. In baseball in 2007, only 11 pitchers had average fastball velocity of 95 miles per hour.

In 2025, 300 pitchers had average fastball velocity of no. So, you know, 20 years ago, if you were throwing 95 miles plus hour plus with your fastball, you were in elite speed pitcher. Now, maybe you didn't have control or whatever, but you were one of the literally the top 10, top 11. Today, if you're throwing 95 mile per hour fastball, there's literally 300 other pitchers like you. So, you know, the fastball speed there went from elite to commonplace in just in under 20 years. You know, that's 2007 to 2025.

I've got lots of other examples in sports, but let me give you my mind. favorite example for thinking about the stock market and for comparison because it's both so out there and because it's a because it's so out there and because it's a combination mental and fiscal and that is rubix cube the rubic cube so in 1982 at the time the world's first and for 20 years only rubic's cube championship is held in hungry hungry hungary hungary i never know whatever uh the winning time is 23 seconds they never hold another world championship again or they don't hold another world championship again or they don't hold another world championship for 20 years. The next World's Championship event in Rubik's Cube is held in 2003. The winning time is 20 seconds. So that is a jump from 23 to 20 seconds. I mean, look, that's not bad. When you're talking at the elite sprinting level, you're talking, you know, tens of a second is how you separate the greats from the Allsau Rands. 2004, there's that famous photo, if you remember, of the Olympic gold where everyone's literally crossing the pitch line at the same time.

Noah Lyles, the American wins Olympic gold for the 100 meter dash with 9.79 seconds. The fourth place time is 9.82 seconds. So in that case, 300ths of a second separates I am the world's fastest man from I am not, I have as many Olympic medals as Andrew Walker does. You know, so that's 300ths of a second. In Rubber's Cube, I just told you over 20 years, 23 to 20 seconds, three full seconds. I mean, that is a lot of improvement. But that's nothing compared to what's to come.

You know, with the world championship, it gets taken place basically every. year from 2003 on, with a world's championship to kind of organize and push people and push the sport, the sport, quote-unquote, to its limit, by 2023, the winning time for Rubikis-E solving is approaching five seconds. So, you know, from 82 to 2003, you go from 23 to 20 seconds, from 2003 to the same 20 years, you go from 20 seconds to five seconds. That is just an insane amount of progression. But my favorite way to say this is actually, until 2019, the Rubik's Cube Championship doesn't, Rubik's Cube Championship actually has all sorts of things.

There's, can you solve it blindfolded? Can you solve a 3 by 3? That's the classic cube puzzle. Can you solve 4 by 4 or 5 by 5? Until 2019, they have, hey, who's the world's fastest person who can solve a Rubik's Cube with their feet? How fast can they solve it? And in 2019, the fast, this is the last year they have the with feet category,

the fastest person solves a Rubik cube in 17 seconds. So, you know, from 2003 to 2019, the sport improves so much that the fastest, person in the world is solving a Rubik's Cube with their feet faster than the fastest person in 2003 was solving with their hands. I mean, that is just crazy. And now, the other reason I like Rubik's Cube is because the stakes are really small, right? It is Rubik's Cube. It is not exactly getting the girls, you know, football, the high school quarterback gets all the girls. Rubik's Cube, I am the fastest Rubik's suh solver at my high school. Isn't exactly going to get the girls come out after you.

And it's not exactly a monetary task. The total prize pool for the Rubik's Cube championship is 36,000, $5,500. That's the total price scoob. The fastest solver of the three-by-three, the best, the best, most competitive event of Roobbibbizcube, you get $5,000 for solving that. So, I mean, we're literally talking a week, two weeks, a month, take-home pay for an average person. That incentive is enough to push humans within 20 years to solve a Rubik's cube faster with their feet than they were solving with their hands 20 years before. I mean, if that little pride and that little incentive, can push people that far with Rubik's cubes? What do you think the stock market, where the rewards for being right once, once, having one unique insight can literally turn you into the world's richest man, right? One of the richest people in the world. If you can be right more than once, you know, Buffett, his net worth is $150 billion, and that's after giving away a heck of a lot of money.

That's four times the GDP of a lot of small European countries, you know? So if a Rubik's Cube, less than $36,500, $36,500 in total, it is enough to drive this. What do you think the returns for finance where you can become the richest man in the world, one of the most respected men in the world? I mean, look, you're great at finance. You can become the Secretary of Treasury, the Secretary of Commerce. You might not even have to be great at finance to become the Secretary of Treasury, by the way, but if you can raise enough money.

So I would just contend, you know, if you can do that at Rubik's Cube, set back and look at the history of finance, you know? In finance, we, you know, you see firms investing hundreds of millions of dollars to compete for milliseconds or microseconds of speed to win in trading games. In finance, you have, you know, the Rothschilds, the rumor is that they trade on Waterloo faster than their peers, thanks to a racing pigeon network. Rooters, the news service is named after a man, who one of the ways he got his news service going was he used a pigeon network to bridge the gap in a telegram network. There was a gap.

He was a Pigeon network so that traders could get news faster by pigeon than they were getting it by training. I mean, if you think about that history of hundreds of years of competition where every edge is sought out and taken, the incentives,

the insane riches that can accrue, I would just argue if you say, hey, I don't think finance is the most competitive game of the world. I'd say you're ignoring the history. I'd say you're ignoring the stakes, the incentives. I'd say you're ignoring the competition.

So that's my point on competition. Let me go to the second thing I mentioned. As the competitive stakes get higher and games get more and more advanced, the winning strategy looks counterintuitive even insane. I mean, the first place I would just step back and point this out is basketball. If you and I are playing a game of basketball, our strategy is going to be much different than an NBA person playing the game of basketball. Why? Because NBA people can dunk and we can't.

So that means NBA strategy needs to be to revolved around, hey, the tall man who's running super fast, if he gets close enough to the rim, he'll just jump up, grab the ball, and throw it through the hoop. Whereas if you and I are playing, we don't have to worry about that kind of verticality. We will play on a horizontal level.

They will play on a vertical level. That's just a really nice example of when you're at the peak of your powers, how the dimensions of the game can change. But the strategy also, I would just say as things get more advanced, the strategy can start to look insane. Let me give you an example. Everyone knows the Olympic high jumps. It's been an event at every Olympics since the first Olympics.

It was one of the first events that women could compete in. This is an event with a long, long history. The high jump is where you literally set a limbo bar and you have to jump over it. Until the 60s, the way everyone jump over it is kind of the way most people would. You'd run up and you'd try to just like jump, normal. And then Dick Fosbury in the 1968 Olympics wins the gold medal with what becomes the Fosbury flub. He jumps backwards over the bar.

And if you've seen high jumping, now I'm sure everybody's seen high jumping once, you'll know the thing. They run up to the bar, and then they kind of turn their body to it, and they lean over and their shoulders and their head go over first, and then their legs go over less. And Dick Fosbury won't it. That was, that was, it is the best way to jump. But, you know, if you, it's before the Fosberry jump comes around, if you had kind of gone to the best electric jumper in the 50s and said, hey, why don't you jump over that bar backwards? People would have thought that was insane.

But, you know, this is a better technique. And I'm not saying that's the same at every sport. You know, obviously running the best way to run was kind of like evolved into us. But it's just interesting. Again, here's an event where as people got better and as they perfected the strategy, they discovered a way of moving that kind of seemed insane. That is the actually optimal way to do things. And if you tried anything else, you would get crushed today, right?

And again, that is a physical event. But I would point to, there are lots of examples of kind of strategies in sports that have similar things. You know, let me, one, football, going for it on fourth down. In the 80s and 90s, teams almost never went for it on fourth down unless they had to. Today, teams go out for fourth down like crazy. Watch a football game. You know, fourth and four at the 40. Teams are going for that every time. If you, that is because of analytics and people have realized that is optimal, and there's lots of reasons for that. You know, if you don't get it, you give the other team a short field. The reward for getting it versus kicking a 50-plus yard field goal, the expectations. The

expected points value is much higher, all these types of things. But, you know, if you imagine 30, 40 years ago, if you had fourth and goal, let's say, from the three and you went for it, is that the analytically correct play? Absolutely. But everyone else was not going for it. If you went for it and you missed it, you're probably going to get fired the next day, right? It was just so crazy. Baseball, money ball has this famously, right? Putting first baseman who can't really hit, but who takes lots of walks. Really is seeing that on-base percentage is much more important than and the batting average, all this sort of stuff. So across sports, you'll see lots of this type of stuff.

The optimal strategy might, it's not intuitive. It seems insane at the time. But as the game evolves, people kind of hone in on the optimal strategy, even it's crazy. You can see that as AI has started to dominate a lot of places. Chess. As AI has mastered chess, I've got this great quote from someone who says, AI master chess, and it did so not by playing like a grandmaster or a pre-eastern, existing program, it conceived and executed moves that humans and human-trained machines found

counterintuitive is sometimes even simply wrong. The games that AI chess plays looks like chess from another dimension. And again, the AI is smashing everyone else. It is so much better than everyone else, but it's making moves that at the high end, people never thought of it. They're counterintuitive. They look wrong. Poker. AI has started to solve poker. And one of the things that AI has changed in poker is if you've ever played high limit poker, you know, most of the time the bet is in relation to the pot. So if there's $100 in the pot, you know, people would think of, do I bet 50% of the bot, 1% of the pot, do I bet half the pot? Do I bet the full pot? Do I bet two outs the pot? AI started evolving and discovered AI overbets the pot way more than normal humans do you. You know,

you'd have $100 in the pot and it would put a $500 bet in or something. One friend who is a former, kind of semi-pro at poker told me, hey, if you looked at the AI models and you didn't know that the AI models had evolved to kind of win at chess, and you saw one of these play, you would think it was playing like a drunk uncle, you know, who had just come in and was kind of cloning around and throwing chips on the table. Like every time we put $50 into a $10 pot, and you'd be like, this guy's crazy. But the AI has kind of evolved and that aggressiveness as found me. So I point that out because, I guess I point that out because in finance, I think these things are evolving. They're coming to dominate humans, and I think the

ways that they're starting to win are going to look kind of strange to a lot of humans. So how does, you know, that is talking about at the high end and kind of the meta level. So if the metal level is evolving to a place where, you know, the competition is more fierce than ever, where the basics are getting dominated by all this AI, machine learning, everything, how does an individual investor, a one-man shop, someone running a small fund, someone who doesn't have access, someone who's not using this AI learning, this machine learning, these quantity funds,

how do they compete? And I would argue the way that these things, the way that you need to compete is getting weird. And the place that I would kind of point, I don't think you compete by saying, hey, you know, I'm tracking credit card data. I'm going to analyze this credit card data beta better. For a thousand reasons.

Podshops have more analytical capability. Podshops. run with Podshops, quant models, they can run with more leverage. So, you know, if the returns to getting a quarter right or modeling credit card data is right are 2%, that's not worth your time if you're not applying the same leverage. They can apply a lot of leverage and turn that 2% into 8%. Now, obviously that carries risks and reward, but it just, they're better, they do it faster, they do it more systematically, they just pressure out of it. So how, what is the winning strategy? I think you can see the winning strategy at the edges of a lot of these games that AI has played.

You know, there's a famous example when, what is it, Deep Blue versus Gary Kasparov and the 80s or 90s when IBM creates Deep Blue. He starts opening, he starts his opening moves with moves that would literally be insane because he took, unquote, out of the book, right? If you have a chess move that no one, if you have a chest opening move that no one make because it's so bad and you make it, yes, that's suboptimal, but you've taken it out of the book. The AI is experiencing weirdness and it doesn't know where to go, right? You'll see this in Starcraft, for example. In StarCraft, they introduced AIs that could beat even the top pros, but it was only under very specific controlled scenarios, one map with a lot of different things with the AI was in control of.

If you changed any of those scenarios, the AI could not evolve. As a commentator noted, the AI was the best player in the world unless there was even a minor surprise. Once there was a minor surprise, AI couldn't compete. And I think that's how stock markets are going to apply going forward. That is my theory of weird markets. If you are investing on fundamentals, you can't do it simply on fundamentals. The AI, the competition is too great.

You need to have the surprises. You need to have the weirdness. And the good news is that the world is a weird place filled with thick tails. And it's the thick tails that are going to present the opportunities for Alpha. It's where you can find a place to apply fundamental thinking in something that is kind of out there on the far tails. And, you know, I'll give one example. And again, this is kind of where I start to hit the writer's blocks, please.

But I'll give one example. A.I, speaking of AI, AI is a data, is a power pop, right? And if four years ago, you could realize that the demand for power was one of the constraints on AI, you could make a fortune. And I would argue that that was a place where AI, AI models, a lot of places did not, that was a thick tale. A lot of places did not have the capability to do this. It's not in the historical data, right?

You couldn't look at a power play and say, oh, this is trading really cheap, let's buy it, because it was the future. You couldn't see the demand in the past. A lot of times you couldn't even see the demand in the future. You just kind of had to know, hey, all this AI is coming. It's not modeled anywhere, but it's going to consume a ton of power. So I think that's one interesting example.

You know, I've said N of ones, weird situations. I'll give some others. I think spinoff are always a great place, right? You've got a company that's spinning off a division. Oftentimes, the people who own the core company don't care, don't want the spinoff company. You get a lot of force selling. You don't have a lot of historical data on it, so you can do a lot of work on that. oftentimes the management team is a new management team, so you can get views that, you know,

AI is never going to have. Podchups might have, but potchops also might have liquidity constraints and all this sort of stuff. So I think that's another interesting example. Unique event situations in the stock market. There's a few that I'm currently involved in that I won't mention now because, you know, I'm currently involved in them. I do write up a lot of these, obviously on the premium side. That's kind of the bread and butter.

But I think unique events are absolute capital. for this where, hey, the fundamentals might, oh, here's a great one. I'm Long Warner Brothers Discovery, WBD, I've written it up, all this type of stuff. So there's my disclosure. But, you know, there've only been a handful of bidding wars in history. And at WBD, you've got a lot of soft considerations. You know, you've got the Ellison's going around saying, hey, this was not our best in final bid. You've got all these other stuff. But bidding wars are very much on the edge of the markets, they're very rare. And when they happen, I think each and every one is unique. You've got the adolescents, the richest people, round to the richest people in the world,

personally guaranteeing an equity deal. You've got Netflix on the other side. You've got the Trump administration. You've got the Warner Brothers Board. You've got all these different things. But I think that would qualify as a unique one. So I'm trying to think of others off the top of my head. And again, this is where, you know, I like the first two-thirds of the theory, but then just translated into the specific market thoughts. I think as I talk through this is where I start to have the writers block that I mentioned and all that sort of stuff. So where else?

You know, I think a lot of times, I think there is still a lot of it in management incentives, you know, when this is the classic non-gap spring loading stuff. But when a management team, when you see the 8K file that says, hey, this manager has decided to take all the next five years of their equity comp up front in options this year as a reward. I think those are very interesting situations. But, you know, I do think those are increasingly picked over because if you say, hey, every time that happens, that's an opportunity. Well, then AI is eventually going to learn that and everything.

So that's one where I think there's both opportunity and risk. Yeah, that's it. So look, I'm running long. I've done this, you know, on a Friday. I've been thinking about this all week. I've got to go pick my daughter up in a second. So I'm going to have to go pick her up. But I think I've done, I hope, I've done a nice job of explaining the weird markets theory.

I feel like the first two-thirds of it, the overview, my thinking, my parallels to the sports world. I think those are very good. But I do have trouble, like, kind of once I get to this specific markets piece, really driving at home with specific examples. And maybe I just need to think of them more. Or maybe that's a sign of saying, hey, Andrew, you know, theories can be evolved. You can come up with a lot of interesting theories in your head. But sometimes it's really hard, like once you put it to paper, the reason it's hard to put it down is because the evidence doesn't back that up. So I'm still thinking about a lot.

I think we're going to wrap it up here. I appreciate you listening to me. But what I would really appreciate is if this conversation, me throwing all this out at you, it spurs a thought with you. I'd love to chat with you. If you've got, if you say, hey, Andrew, here's some other examples or here's something you're not thinking about on the weird market side or any of that. We'd love to talk. We'd love to do it because I do want to get this theory. posted in the next, I'm recording this Friday, January 9th, you know, in the next week or so

I want to get it posted because then, as I said, all of my annual stuff is kind of waiting on getting this theory out so I can link to it and mention it and build off it. So I want to get off then, but I'm going to wrap it up here, put this up. We'll get the follow-up post, but if any of this is spurring a thought for you, I would love to discuss it with you. This is a topic I've been thinking a lot about, and hopefully it did spur something with you. And look, if it didn't, hopefully you at least enjoyed me rambling.

And the Rubik's give example, I mean, come on, how much better you get than that Rubik's example. So wrap it up here. Thank you so much for listening. We will talk soon. Later. A quick disclaimer, nothing on this podcast should be considered an investment advice. Guests or the hosts may have positions in any of the stocks mentioned during this podcast.

Please do your own work and consult a financial advisor. Thanks.