Do you think you’re bad at math? Who doesn’t! Whether you’re an algebra whiz or struggle with subtraction, today’s episode is for you. Join us as we dive into the exciting intersection of math and finance with Ben Orlin, author of ‘Math with Bad Drawings.’ We’ll uncover the unexpected fun in mathematics and learn how understanding concepts like statistics and standard deviation can reveal the hidden stories within numbers. Ben’s perspectives on embracing mistakes and the intrinsic link between math and finance offer a fresh look at these often daunting subjects.
In our headline segment, discover the top strategy for achieving millionaire status through consistent investment in–believe it or not–nothing fancy! Danny Noonan shares the results of Fidelity insights into the lives of ‘401k millionaires,’ spotlighting the power of patience and discipline over high-risk opportunities, underscoring sustainable financial growth.
Finally, Doug enlivens the discussion with intriguing trivia on the differences between mean and median averages. Doesn’t that sound hilarious?
Of course, there’s much more, so join us as we weave together actionable financial advice with engaging stories, making complex concepts like math and finance accessible and relatable for everyone.
RUN OF SHOW
- Monday Morning Vibes
- Financial Wisdom with a Twist
- Introducing Today’s Mentor: Ben Orlin
- Math and Bad Drawings
- The Beauty of Mathematics
- Breaking the Economy with Dice
- Statistics: Lies, Damn Lies, and More
- Tweaking the Guinea Pig Bed
- Embracing Mistakes in Learning
- The Power of Walking Away
- Unexpected Solutions in Math
- Good vs. Great Mathematicians
- Math and Mentorship
- The Collaborative Nature of Math
- Understanding Averages
- The Storytelling Power of Math
- The Importance of Consistent Investing
- Wrapping Up and Final Thoughts
Deeper dives with curated links, topics, and discussions are in our newsletter, The 201, available at https://www.stackingbenjamins.com/201
Enjoy!
Monday Mentor: Ben Orlin
Big thanks to Ben Orlin for joining us today. To learn more about Ben, visit Math with Bad Drawings – Lover of math. Bad at drawing.. Grab yourself a copy of the book Math for English Majors: A Human Take on the Universal Language.
Our Headline
- The Number One Way Americans are Becoming Millionaires (Morningstar)
Doug’s Trivia
- When we talk about average, what’s the difference between being mean and being the median?
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Tune in on Wednesday when we’re diving into a case analysis…of all things, professional sports teams, to discover how you might be able to grow your stack more quickly.
Written by: Kevin Bailey
Miss our last show? Listen here: Stacking Health or Wealth? Your Retirement Dilemma (SB1586)
Episode transcript:
[00:00:00] Joe: It’s Monday morning. Oh gee, how you doing? How are you doing?
[00:00:04] OG: I’m just excited to be here,
[00:00:06] Doug: fan. Hear it. You can hear it in his voice, can’t
[00:00:08] OG: you? How the It’s just electricity. It’s my friend Marshawn Lynch says, I’m just here so I don’t get fined
[00:00:12] Joe: starting up the week on a, just so I don’t get fined. Positive.
[00:00:16] No. On a You can do it. No haystacks. You can do it. You know what, I’m just here
[00:00:19] OG: so I don’t get fined.
[00:00:20] Joe: If OG can show up on a Monday like this, you can open a Roth IRA. It’s fantastic.
[00:00:28] OG: Just do it so you don’t get fined.
[00:00:30] Joe: Yeah. Talking about practice, your retirement
[00:00:33] OG: gets fined. That’s if you don’t. And Iversson different person.
[00:00:36] That is a different
[00:00:36] Joe: person.
[00:00:37] OG: I understand. Skittles. Skittles driving the cart. Cal
[00:00:41] Joe: just put it this way. You can either show up and not get fined or you can pull it Deshaun Watson and just Nope.
[00:00:47] OG: Like also a completely different person.
[00:00:49] Joe: Wow. But you can like half fun. Thank you. Did you know Doug,
[00:00:53] Doug: that Deshaun Watson is not Marsha ly?
[00:00:55] We could not be further sideways than we are right now.
[00:00:59] OG: Nobody needs to pull it to Sean Watson. Please God, don’t do that. Put this
[00:01:01] Doug: back on track.
[00:01:03] Joe: You can either have fun your Roth and walk off the field or you can show up and do the whole thing so you don’t get fine. Oh, look at that Mickey Mouse mug.
[00:01:11] It’s fantastic. I’ve got the Ferrari mug ’cause this is the Ferrari of opens right here on behalf of the men and women. Make a podcast of Bombs basement and the men and women at Navy Federal Credit Union. Big shout out to our troops. Thank you for all you do. Let’s go, uh, stack some s together, you know, so we don’t get fined.
[00:01:31] Cheers. I.
[00:01:33] bit – Jocko: Who’s with me? Yeah.
[00:01:39] Alright, let’s do this. People
[00:01:47] Doug: live from Joe’s mom’s basement. It’s the Stacking Benjamin Show.
[00:02:01] I’m Joe’s mom’s neighbor, Doug, and, oh God, math. Am I right? Well buckle up stacker because today we’ll introduce you to a guy who makes math a blast. Today’s mentor is the one and only Ben Orland. Plus. In our headline, we’ll share the number one way that Americans are becoming millionaires. Could you be one as well?
[00:02:23] Of course you can, and don’t you worry. Midway through today’s show, I’ll share some of my world famous trivia, and now two guys who are like the variety pack of cereals at the store. One’s kind of fruity and the other one could use more fiber. It’s Joe, oh and oh.
[00:02:50] Joe: Hey there, stackers. Happy Monday. I’m Joe Salhi, Aboriginal money on Twitter or X or whatever we call it. And you know what, Doug, I think the guy sitting across the card table from East had, uh, too much fiber. So I’m the one that hasn’t had enough fiber. So you can do the math on who? OG. Must be fruit fruitcake.
[00:03:05] How are you my friend? The coffee’s starting to sink in, so sun up a little bit. That’s good. That’s good because after the amazing open we head to this show. Wow,
[00:03:15] Doug: man. You can feel the excitement. Just settle down a little bit. og. You’re just don’t compete with my energy. You just gotta chill. Well
[00:03:24] Joe: the good news is Doug, is that, uh, we don’t really have to rely a lot on OGs energy today ’cause we got a guy that’s bringing the energy.
[00:03:30] Ben Orland’s here. He is a guy who’s a math teacher who can’t draw. He will tell you he cannot draw. And so math and bad drawings from Ben Orland. And by the way, what’s made better for drawings than a podcast, right? Take a look at this
[00:03:46] Doug: one. Everybody. Oh, that’s bad. And yet, here’s another stick figure of a guy with a calculator and look at how his arms aren’t even the same length, right?
[00:03:56] It looks like a cucumber to me, Ben.
[00:03:59] Joe: So Ben Orland is here. og, can you draw?
[00:04:01] OG: Uh, I can’t, I can draw a lot of lessons from our upcoming advertiser. I don’t know. Oh,
[00:04:09] Doug: from our upcoming advertiser. I was, you’re so close. I’m trying to get
[00:04:12] OG: something. It’s like, where is it? I’m like,
[00:04:16] Doug: oh, keep going
[00:04:17] OG: man. Keep going, man.
[00:04:17] It’ss in the dark.
[00:04:18] Doug: You’re there. You’re almost there. I’m in the dark
[00:04:20] OG: and I’m just trying to like me bailed. Grab something as I plummet. Well,
[00:04:25] Joe: is this, is this what you were trying to grab right here? These two? Whoa. That make No, it wasn’t that free, is it These two? We got Ben Orland joining us. Ben is, uh, Ben is a force of nature.
[00:04:37] I just, I love this guy. We’re gonna have so much fun ’cause so many people think math is not only difficult, but also incredibly boring. And as I had to learn through my career, math is often the way that stories get told. He not only. Has written the classic book math with bad drawings. He’s also written Change is the only constant math games of bad drawings.
[00:05:02] Most recently math for English majors. He’s appeared in the Atlantic Popular Science late Vox Los Angeles Times, and he himself has appeared in the lines to ice cream stores everywhere. Oh, that’s my favorite line. That’s good. He did there in Ben’s bio. BBC starred and leading mathematician Hannah Fry once described him as quote, terribly bad at drawing before kindly adding quote.
[00:05:25] He’s also fantastically clever and charming, and he is clever, charming, and he’s here to teach us about math on a Monday. What could be more fun? Let’s say hello to Ben Orland
[00:05:45] and I’m super happy we have him coming down to the cart table in mom’s basement. Pat Orland is here. How are you man? I’m doing great. Yeah, thanks
[00:05:52] Ben: Joe.
[00:05:52] Joe: I have to tell you, I hated math and I know I’m not alone. You meet people like me all the time, Ben.
[00:05:59] Ben: Yeah. We call ’em human. Many beings, as we call ’em. It’s a lot of people.
[00:06:03] Joe: The reason I hated math comes specifically from seventh grade. I had a math teacher in seventh grade. You know, we’re just starting to get into algebra. Math is just starting to become more like poetry, which you and I are gonna talk about, but it takes me a little longer. In fact, you’ve got a story in your book about a kid that you were teaching who answered all the questions, right?
[00:06:24] He was just really slow at it, right? And I felt like that was me. And so this guy would write all this cool stuff on the board, Ben, he’d write all this stuff, and then he would go, oh, but you already know that. And he’d erase it. And I never learned a thing. And, and the thing I learned was, math is bad. Stay away from math, which is the wrong lesson.
[00:06:44] Ben: No, no, that’s it. Everyone should just learn. Math is something to stay away from. Just leave it to us teachers to, you know, keep the paycheck coming our way. I gotta keep the gates up high. Yeah, exactly. That age, seventh grade. That’s a real pivot point for a lot of people with math. That’s the moment when it stops being something that you feel like you gotta grasp on.
[00:06:59] It just slips away and you watch it bobbing off into the distance in the ocean and then you never get it back. Yeah. But great student, a lovely kid who really patient and thoughtful and like, I always talk too fast and he was just a very measured speaker, very slow. He had like nice round glasses. Kinda reminded me of like a young Ben Franklin.
[00:07:15] He was gonna be an engineer. I could feel it. He was gonna be an engineer. Yeah. I could see, yeah, I could see him as a philosopher. I could, I, the kid’s 10 years older now than one I taught him, so Yeah, he, he, he’s probably already an engineer. Yeah. But so he was doing great in the class. I mean he, he very strong mathematician and yeah, I was teaching just one or two sections of seventh grade and so all the seventh grade classes gave the same test and we kind of wanted to be standardized.
[00:07:34] You know, everybody gets 40 minutes to do it, you get one period and he like only got through two thirds of the test. Like best case scenario, you’re getting two thirds of the points. And like he knew it, he obviously knew how to do it, but 40 minutes isn’t that long a time. And he just, he just worked very methodically.
[00:07:48] And afterwards, I’d never seen him frustrated like that. He was always so mellow. And he just came up to me, he was like, why, why did I only get 40 minutes? And I just didn’t have a good answer. I mean, my answer was like, your French teacher wants you. You know, like that’s basically it because it’s the
[00:08:00] Joe: American
[00:08:01] Ben: system.
[00:08:01] Yeah, that’s right. Yeah. Well, this is actually in the uk, so it’s a global system. We’ve got Oh, it’s
[00:08:05] Joe: uk. Yeah. Right. That’s
[00:08:06] Ben: right. This, yeah, it’s universal. The idea that, uh, the way we do schooling is in these funny buildings with bells ringing every 45 minutes to tell you where to go next. And we’re trying to teach this beautiful, strange subject in that little tiny.
[00:08:18] Space. And so you get some weird distortions
[00:08:20] Joe: and you write that really the beauty of math is the opposite of the way that we teach it, Ben, that truly noodling on something and letting it marinate and having fun with it and playing with it and being okay with being wrong is kind of where math gets interesting.
[00:08:34] Ben: Yeah. Yeah. You think about solving a Sudoku very mathematical idea. It’s not the numbers that make Sudoku mathematical. It’s the logic, right? It’s the idea of I, okay, if I’ve already got something in that row and that column, then this number has to go there. If you took a finished Sudoku and showed it to somebody and you’re like, isn’t this beautiful?
[00:08:49] Look at that, they’d be like, eh, that’s fine. We got some numbers. But like the joy of Sudoku is in the solving of it, right? And it’s the getting lost and running into dead ends and having to backtrack and like, and be like, oh, okay. I know it’s one of these two numbers, but Oh, okay. Yeah. And that little moment of insight, so it’s all the process.
[00:09:03] And that’s true of mathematics too. It’s the process. But of course what we do in math class is we take hundreds of years of process and say, okay, here’s the finished Sudoku, and we kind of make you memorize that. Finished Sudoku. That’s not that fun. It’s just not that enjoyable. Yeah. It’s like we
[00:09:16] Joe: rip the
[00:09:17] Ben: poetry right out of the mathematics.
[00:09:19] Yeah, yeah. We’re giving you these very condensed versions that you’re then supposed to digest very quickly.
[00:09:24] Joe: Well, I wanna dig in. I would love for you to teach us our stackers, how to make math fun, but before we get there, we’re a bunch of finance nerds, which means to some degree we all become math nerds.
[00:09:34] And it’s funny, it’s actually been through finance that I learned how closely related my English degree was to mathematics and how everything bleeds into each other and how fun this can all be. But I wanna begin with economics because maths shows us how we can break the economy. You write. With a single die.
[00:09:54] You begin with this career fair. As you’re getting ready to graduate from college, you mind telling us that story and how do you break the economy with a die role?
[00:10:01] Ben: Yeah. Yeah. Every year, you know, October, I guess when I was in college, there’d be this big career fair in the gymnasium. This was Yale, so all the investment banks would come.
[00:10:10] I was a class of 2009, so through the class of 2007, 2008, those investment banks were huge employers, right? Tons of those kids went off to go work for Goldman, go work for Lehman. Yeah. So this fall 2008, and it turns out some bad things had just happened in New York. Oh, what would that be? Bad? No, I’m
[00:10:24] aftershow: kidding.
[00:10:24] So, yeah.
[00:10:26] Ben: Right. It’s funny. Yeah. Right. Even for students today who were like a few years old when that happened, students I teach now, like they know. Oh yeah, that was bad. What happened in 2008? So there were just empty tables, right? Like you go through like I think the CIA was still hiring, so you could go talk to the guys.
[00:10:38] Oh, good. CIA, um, but, but the banks were not there. It turned out that was a huge year for Teach for America. Tons of kids from my year went to do Teach for America. Wow. Because it was like, well, okay, the banks aren’t hiring, so I guess I’m gonna go teach in Mississippi. But
[00:10:50] Joe: just to pause there for a second, that’s not necessarily a bad thing.
[00:10:53] Ben: Oh yeah. You know,
[00:10:53] Joe: you know, I mean. Surely it doesn’t pay the same way.
[00:10:57] Ben: Oh no, it’s great. Like I, I didn’t do Teach for America, but I wanted to teaching. I think that’s great. I think, you know, like you don’t, you’re not wasting a year when you spend a year teaching kids math. You know? That’s a great way to spend a year.
[00:11:04] Joe: Yeah. I interrupted. So you’re there. There’s no investment bakes,
[00:11:08] Ben: right? Right. So what went wrong and there’s, there’s a ton of ways to tell the story. And you can tell the story of incentives and you can tell the story of, uh, sort of yeah. Like prime agent problems and uh, and you can talk about the complexity of the derivatives they were creating.
[00:11:19] But one aspect of the story is just imagine rolling dice. Say you’re rolling two dice and I’m rolling 1D and just doubling it. If you played some dice games, you get a lot of sevens. ’cause no matter what you roll, there’s always a way to make seven, right? The first one is a one and the second one could be a six, or the first one’s a two and the second one could be a five.
[00:11:37] So there’s lots of ways to make seven. So you get a lot of sevens and you don’t get that many twos or twelves. ’cause the only way to roll a 12 is to roll double sixes. So you, with your two dice, you’re getting a lot of six to seven eights and the occasional two and 12 very middle kind of values. Not many extremes.
[00:11:52] Joe: It’s almost like a mountain. I’m seeing this mountain with like seven in the middle is the tall part and then Exactly. Yeah, yeah. 6, 6, 8, 9, 5, and so on.
[00:12:01] Ben: Yeah, exactly. Tallest bit in the middle there and then tapers off to the outside. And if you keep doing this with more and more dice, you get what we call a bell curve, right?
[00:12:08] A normal distribution where you roll 10 dice and you’re very likely to get a kind of middle value and very unlikely to get all sixes unless your dice are cheat dice, you know, unless you like, you know, something where you’re shaving off little bits to make it weighted differently. Like you’re not gonna get 10 sixes.
[00:12:21] That doesn’t happen,
[00:12:21] Joe: you know, as my mom does when we play dice with her.
[00:12:23] Ben: That’s right. Yeah. A little research. I found out that there are all these ways to make trick dice back in the day, and my favorite was you would make wooden dice and you’d have the tree grow around a pebble. So you’d like, you’re kidding me deliberately?
[00:12:35] No. Yeah. I don’t know. This is in John Skanes book of of Dice. He’s like a magician and like a card cheater kind of guy and game designer. One of the methods was yeah, to like grow it around a pebble and now you’ve got this heavy rock inside the wooden dye and you carefully carve it so that that heavy rock is like just where you need it to be.
[00:12:49] And then you have a way to die.
[00:12:51] Joe: Think about how premeditated this is. You know what I mean? There’s cheating on the spur of the moment. Like, I’m ready for game night to be over. Let’s just turn the dye over. Yeah. Yeah. But the fact that I’m gonna grow a tree so I can cheat at dice whole different level it,
[00:13:05] Ben: I’m gonna take the slowest growing thing we know of and I’m gonna like just cultivate this little cheat dye.
[00:13:10] And then what if you lose the dye? I know. Yeah. It seems, seems a lot of trouble, man. What percentage are you gaining? You know, maybe you get like 10% more sixes or something it seems, anyway, but people are really committed to cheating anyway, so that was a sidebar, but uh, yes, you roll a bunch of dice, you’re not gonna get all sixes.
[00:13:23] But what if instead of rolling 10 dice where like, yeah, I might get a couple sixes, but it’s gonna be a random mix. What if I just take one dye and then I put up nine mirrors next to it? So you’re just taking that one die and multiplying it by 10. You’re gonna get 10 sixes sometimes. ’cause if the first die is a six, all the others are automatically sixes.
[00:13:42] So instead of that graph, you depict that little mountain where like the middle values are the most likely and then it tapers off to the sides. And the extreme values almost never happen. You’re gonna get 10 sixes, one outta six times, and another one outta six times. You’ll get 10 ones. And so you’re just gonna get these really extreme outcomes if you just multiply that one die 10 times.
[00:14:02] So, and first inspection, you go, okay, maybe these aren’t so different, right? They, you know, if I roll two dice, it goes from two to 12. That’s the range of values. And if I roll one dye and double it again, it goes from two to 12. Doesn’t seem so different, but it’s super, super different in terms of the probabilities.
[00:14:14] Doing a bunch of independent dice, you get middle outcomes doing one die and multiplying it, you get a lot more extremes
[00:14:21] Joe: just because one die. Just the probability that you’re gonna roll the same number. On two different dice is just one and six, right?
[00:14:28] Ben: Yeah. Yeah. You can think about it too, like with opinion, right?
[00:14:31] If you go and ask 10 people about a restaurant, they get like a decent cross section of what opinion they have about the restaurant. If you ask one person about a restaurant and just copy and paste their answer 10 times, you’re not really getting the whole variety of opinion and you’re likely to get, like, if that one person loved it, you’d be like, oh, what an amazing restaurant.
[00:14:46] It’s like, no, no one person loved it. Well, it looks like 10 people now, but just ’cause we, we copied and pasted,
[00:14:51] Joe: right? So what does this have to do with the economy? How does rolling two dice versus 1D break the economy or the other way around?
[00:14:58] Ben: Yeah. Yeah. So the dice here now become mortgages. So what happens is you give somebody a mortgage, so now you’re, you’re the bank, right?
[00:15:04] We’re used to thinking of ourselves as the homeowner or the person trying to get the mortgage, but say you’re the bank so you’re loaning some money to somebody so they can buy a house and there’s a chance they default. That’s the risk for you. The upside is they’re gonna keep paying you back and you got that, you know, check every month.
[00:15:18] And then the downside is maybe they default and you just don’t get all your money back. Right? Some of what you loan to them, you don’t recoup. That’s basically like rolling snake eyes for the bank. If you do a bunch of mortgages, the question is what’s happening? Are we in the world where each mortgage is kind of its own separate dye that we’re rolling and so it’s unlikely that everybody’s gonna default on their mortgage or these mortgages more like just one dye that’s being rolled and the others are all mirrors of the same one mirrors.
[00:15:45] aftershow: Yeah. Yeah,
[00:15:46] Ben: exactly. So, so you sort of think under normal circumstances, they’re kind of, you’d think they’re probably mostly independent. Somebody loses their job, maybe they’re gonna default on their mortgage. Somebody runs into some kind of hardship, but that shouldn’t affect everybody. What if you’re giving out tons and tons of mortgages and what if you’re doing it?
[00:16:02] Because home prices keep rising and rising and rising, and that’s the only reason people can afford these mortgages is they’re just trusting that the home prices will keep rising and rising and rising. Then when the market takes a little bit of a dip, suddenly tons and tons of people default. That’s more or less what happened.
[00:16:16] Right? The, the banks were trying to model this. They had much more sophisticated models. They, they weren’t just like me sitting there at a desk with two dice studying the dice being like, Hmm hmm. But they basically made the same sort of mistake in their modeling. They were using a kind of equation that sort of assumed that the dice were separate.
[00:16:32] And it’s more like the dice were tied together,
[00:16:34] Joe: we’re all mirrors. Yeah. It’s so interesting how these huge institutions can miss something that small. And yet you could even take this same thing, Ben, to a personal level. I mean, don’t get me wrong, everything you just described, the insurance industry’s all built on this.
[00:16:48] aftershow: Yeah, yeah. About this
[00:16:49] Joe: probability and, and ensuring different risks. ’cause you and I are getting ready to record a couple weeks before this airs. There’s a hurricane that’s getting ready to hit the, the coast, but we know the hurricane’s gonna hit it somewhere, but it’s not gonna hit everywhere. So if you law of large numbers, I can have other people pay for the horrible outcome that some people in the next few hours are about to have.
[00:17:10] Ben: And same thing with insurance, right? If you’re an insurance company and you’re insuring some homes in New England and some homes in California and some homes in Florida, you’re probably okay. ’cause that would be a crazy hurricane that like goes up to Florida, bounces across, makes it all the way across continental US to California, and then goes up to New England.
[00:17:27] You’re not gonna have a bunch of insurance claims in all three of those places all at once. But if you’re an insurer that just insures homes in Florida, say just in one city in Florida and a terrible, tragic hurricane hits, suddenly you could have all of your customers making an insurance claim. Now those are mirrors.
[00:17:43] Exactly. And now all you thought you were insuring a hundred different houses that all were gonna have kind of like different dice that you were rolling, but it turns out it was really just like you were insuring one die.
[00:17:51] aftershow: Yeah.
[00:17:52] Ben: And so insurance companies have to do a lot of careful thinking about that, of like, okay, how do we balance these risks and which risks go together and which risks are more like separate dice?
[00:17:59] Joe: And even on a more personal level, this also applies I would think, to building a portfolio, right? I mean, if you’re building investments, taking different, the thing that always blew my clients away, back when I was a financial planner, Ben, was that you could add riskier stuff to a portfolio and make the portfolio less risky.
[00:18:21] Mm-Hmm. And I think that’s the same thing as your D roll.
[00:18:25] Ben: Yeah, that’s exactly. That’s funny. Yeah. That’s a great paradox. Because you wouldn’t think, you’d be like, okay, you’ve already invested in these 10 safe companies, now invest in 10 risky companies. Right? And you’re like, oh, it’s gonna make me less safe.
[00:18:35] That’s gonna be worse. Why would you do that, man? And it’s like, no, no, that’s a good idea. ’cause what it is, it’s not 10 risky companies, it’s now you’re investing in 20 companies. So there are things that happen where like, you know, the whole economy goes to down a little bit, right? Like their, their recession can hit, they’re not totally disconnected, but 20 different companies in 20 different industries, those are pretty disconnected.
[00:18:53] Those are more like separate dice. And so even if some of those dice are like, oh my gosh, that dye has 50 sides. Like if you go anywhere from one to 50, this is, this is a really unpredictable dye. If you got enough of those, it’s actually more reliable than putting all your money on one six-sided die.
[00:19:05] Joe: It’s so amazing. The math all the way through your book just shows a lot of these paradoxes. Let’s move on to something else, which is statistics. I love your quotes about statistics. Of course, your Mark Twain quote, there’s what lies, damn lies in statistics. And then what’s your, um, Winston Churchill quote?
[00:19:21] Uh, I don’t know if you remember that one.
[00:19:23] Ben: Oh, oh, let’s see. Uh, this has been a bit since I looked at it. Yeah. It’s funny. One of the things I like about these quotes is that none of them turn out to, they’re all quotes about how unreliable statistics are. Right. And then it turns out that none of them are actually, like, it wasn’t really Mark Twain who said that it was probably Benjamin Israeli, or actually it was Mark Twain attributing it to Benjamin Israeli.
[00:19:37] But we don’t have any evidence that Israeli ever said it. So it’s funny, I liked all these quotes about how like, oh, here’s a reliable quote about how unreliable statistics are, but that’s, well, that’s one my
[00:19:45] Joe: favorite quote of all time is I don’t believe stuff I read on the internet. Abraham Lincoln.
[00:19:49] That’s right. Yeah. Right. That’s, that’s my favorite. Let’s, let’s talk about statistics. How do statistics lie to us?
[00:19:57] Ben: Yeah, I mean they lie to us. ’cause we ask them to, people talk about statistics as though there’s nefarious business, but the fact is the world is too complicated. Right? It’s like it’s too many numbers.
[00:20:06] You know? You wanna know something about, I don’t know, the weather in a city you’re moving to. And if somebody’s like, oh, here’s a spreadsheet of all the temperatures high and low and every hour for the last 30 years, you’re like, thanks, I guess I’m not gonna look at this. Like, who’s got time for that?
[00:20:21] Even if I’m moving to this city, I like just gimme the headline number and that’s what a statistic is. It’s a headline number, right? Gimme the average high temperature in July. Okay. 83 degrees. There you go. So now I know the average is about 83. Now there are a lot of different ways to do an average high of 83.
[00:20:35] In Hawaii, the average high is 83 or about that. ’cause it’s always between 81 and 85. That’s very different than like the average high here I live in Minnesota. You might get a day with an average high of 83 ’cause it could be anywhere from 55 to 105.
[00:20:48] Joe: Yeah, I’m thinking about my daughter in Kansas City.
[00:20:50] Oh yeah. I mean they get the worst snowstorms and they get the most brutal heat. But on average it’s fantastic,
[00:20:57] Ben: right? Yeah. You get the average human has like one ovary and one testicle and it’s like, well that’s not, it’s not most humans at average. It’s true, but pretty atypical. But we need averages though, right?
[00:21:06] Because you, no one wants to look at all the data every single time. We need summaries. And so this was statistics too. They summarize and you just gotta be wary of what they’re leaving out. ’cause every, you know, like you look at the back cover of a book, you then don’t read the book and be like, oh, this wasn’t mentioned on the back cover.
[00:21:20] They didn’t even talk about this character. It’s like, yeah, they had one paragraph to get you to buy the book. So same thing with an average, right? It’s giving you one number. But one number, standing in for a hundred is always gonna leave out a lot of information. So you gotta just keep in mind, you know, each of those summaries, what is it leaving out?
[00:21:33] Joe: You talk about some statistics and some terms that our stackers really need to know. I’d love for you to dive into a couple, ’cause there’s a couple I think that really, really apply to our community. One that I love, that I think people don’t pay enough attention to is standard deviation. Hmm. Can you talk about standard deviation and, and also why we should use standard deviation?
[00:21:55] And what I love about your book, why we also maybe don’t wanna always trust.
[00:22:00] Ben: Yeah. Standard deviation. Yeah. This is one, one. I teach statistics, you know, we do a day talking about the mean and the median and then we spend like a week and a half talking about standard deviation. And that’s really like if you can grasp standard deviation, you’re on your way to really grasping statistics.
[00:22:14] It’s that same problem I’m talking about with Hawaii versus, say Kansas City, where even if you take a stretch of time when they have the same average temperature. Hawaii is really close to the average, right? Every single data point that you look at is within a few degrees of the average. In Kansas City, maybe it’s the same average, maybe it’s 83 degrees for that same time, but the data points are all over the place.
[00:22:32] Some of them are very far from the average, and like worst case scenario, you could have Kansas City, uh, let’s make it 80 to make the number easier. Say the average is 80, but half the days are 60 and half the days are a hundred. That’s like super far. Any given day, you’re really far from the average, but the average is still 80.
[00:22:48] It’s still the same as Hawaii, where it’s 80 degrees every day. So standard deviation is a measure of how far the data points typically are from the average. So in Hawaii, if it’s always, you know, 79, 81 around there, you’re gonna have a standard deviation of around one degree. ’cause typically data points are about one degree from the average.
[00:23:07] But in Kansas City, if the typical day is 20 degrees from the average, the standard deviation will be about 20. The technical calculation is like, I’m, I’m fudging it a little tiny bit, but that’s basically the principle. It’s, it’s how far is your data from the average.
[00:23:18] Joe: What I love about this for investors stackers, what Ben’s talking about.
[00:23:22] I love this because it tells you how bumpy the plane ride’s gonna be. When you look at a fund, you go to someplace like morningstar.com, one of the Yahoo Finance, wherever it will show you standard deviation, and that will show you, to Ben’s point, it’ll show you the amount of bouncing around this thing that you’re potentially going to buy is going to.
[00:23:41] You don’t. I always, I’m a nervous flyer, Ben, I don’t know about you, but when I get on a plane and there’s a lot of turbulence and the pilot says nothing, I’m scared to death. I think they’re all flailing out there. Everybody’s screaming, you know, we’re all about to die. But if the pilot just comes on ahead of time and tells me it’s gonna be bumpy.
[00:23:57] Yeah. And I feel like standard deviation is the pilot telling me how bumpy it’s gonna be.
[00:24:02] Ben: Oh, I love that. Yeah. That’s a nice analogy. Yeah. And the fact is right in, in finance, I mean, you know this much better than I do. The rides that are gonna get you the highest up, maybe this isn’t what you want in a plane ride, is to go high.
[00:24:10] I mixing metaphors here, but the ones that are gonna get you the best return, they’re gonna be bumpy. You pay for that return. Right. And the way you pay is with risk.
[00:24:18] Joe: I love that there’s no such thing as a free lunch, which is what we all want.
[00:24:21] Ben: Yeah. I’ve occasionally worked at places where there was a free lunch, but it’s not, it’s not really free.
[00:24:26] It was built in, my salary was probably a little lower ’cause they were giving lunch.
[00:24:29] Joe: They somehow get you with making you punch in’s. That’s right. A second you talk about correlation, which is another one that I love. And in our community, Ben, people often, and you see this all the time too, right? People mistake correlation with causation.
[00:24:46] Ben: Yeah. It’s a tricky one. Correlation because it’s a little complicated, but the best way to think about it I think is a scatterplot. And so you think about the two things you’re thinking about. So heightened weight is a classic one for people. And if you just do a little scatterplot where you know how far to the right you are is how tall you are, and then how high up is how much you weigh, they’re generally gonna go together, right?
[00:25:05] Like Shaquille O’Neal is seven foot one and like 300 plus pounds. And so like he’s gonna be way, way in the upper right corner. And my younger daughter is one and a half. She’s like two feet tall. She weighs about 20 pounds. She’s gonna be way, way down in the lower left corner. She’s very small, you know, short and, and light.
[00:25:21] And like in general, it’s gonna be a mix as you go up, but it’s gonna be a little unpredictable. And you gotta be careful about telling yourself a story. Like does height cause weight? Kind of a little bit. Does weight cause tight? Not really. And that’s the very simplest one you can talk about is weight and height.
[00:25:37] And then you get into other more complicated things and there’s always complicated variables you haven’t pictured that are kind of hiding in the background.
[00:25:43] Joe: You make some big points throughout this project. One that really resonated with me is this idea of making mistakes. That making mistakes is a part of the game of mathematics.
[00:25:54] And when people, I think first a neophyte to math or somebody that hated math like I did in junior high, goes, wait a minute, you know, I got punished for mistakes. You’re like, no, no, no. Math is all about making mistakes. How does math, speaking of correlation, Penn. How does math correlate with being okay with making mistakes?
[00:26:11] Ben: Yeah. Yeah. So I talk to a lot of people who are research mathematicians, right? Their job is to go out and solve new math problems. No one has ever solved. Yeah. Don’t do that by never making a mistake, right? It’s just, it’s just not possible, right? Research is till try something, it fails, try something, it fails, repeat that 30 times.
[00:26:28] Still haven’t solved it yet, but now you at least have a better idea about what fails, and then you can go back and spend the next month trying different things that might have a better chance of working. And the same is true anytime you’re learning. I think there’s this blank page problem. I see this in writing too.
[00:26:40] You can’t edit a draft that you haven’t written, right? You need to get a first draft down and then you can start working on it. So like psychologists love to use this classic problem, which is clearly old from the numbers in it, but like a bat and a ball like Wiffle bat wiffle ball together, they cost a dollar 10 and the bat is a dollar more than the ball.
[00:27:00] So what do they cost? Each of them?
[00:27:02] Joe: Yeah. So it’s a dollar and 10 cents.
[00:27:04] Ben: Right, exactly. Yeah. So you think, okay, it’s got a dollar and 10 cents because they add to a dollar 10 and a dollar apart. But then you actually look at that once you’ve written that down and they’re actually 90 cents apart. Right from a dollar to 10 cents.
[00:27:14] Oh,
[00:27:14] aftershow: right. And they’re
[00:27:14] Ben: supposed to be a dollar apart. But then once you’ve got that answer down and that’s a first answer everybody gives, then you can adjust it. Then you can tweak it. Right. You can say, ah, okay, so I need them to be a little farther apart, but still add up to a dollar 10. So it’s a dollar five and 5 cents.
[00:27:28] Joe: I love having the perfect Guinea pig bed. And I fell right into that one. That’s right. Well that’s, you know, you’re welcome. You’re
[00:27:32] Ben: human, right? Yeah. Right. Yeah. That’s all. I’ll slip you a 20. We we plan that in advance, but that’s exactly right though. Everybody makes that error. That is like a standard error.
[00:27:40] This took me a while to accept as a teacher, that there would be mistakes that see students make. And as a beginning teacher, I’d be like, no, no, no. Don’t make that mistake. Let me try to prepare you so you don’t make that mistake. And like, that’s not at all how I think about it. Now. It’s like, okay, good.
[00:27:50] This is a mistake you have to make. Like we’re trying to get over there. There’s a big hole in the way. You’re gonna fall in the hole. There’s no way around it. You gotta learn where that hole is. So I’ll, we’ll fall in, I’ll help you out and then we’ll, I’ll show you how to walk around the hole. Uh, many might fall in a few more times, and that’s fine.
[00:28:03] And that’s just learning. You gotta make the mistakes. You gotta see why they’re mistakes and then move on.
[00:28:06] Joe: And you also say the best way to solve problems sometimes is by walking away from it.
[00:28:12] Ben: Oh, yeah, definitely. Yeah. I went through a book, it was by Quantum Magazine, which is a lot of great reporting on math.
[00:28:17] And I just went through and it’s like reporting people, making discoveries in math. And I just made a list of all the moments that they made, the discovery. Now, when the mathematician figured out the problem, and it was like while he was dropping his son off at his piano lesson, while she was taking a train, while he was at the dentist, while he was brushing his teeth, a lot of oral hygiene involved.
[00:28:36] There was never like, and then while he’s playing the drums, it was never, while they’re sitting down working on the math, it was like, and then in the third hour of working on the math, she came up with a solution. It’s like, no, it’s, it’s never that. It’s always, they worked hard on it for a while. They did not get anywhere.
[00:28:49] They walked away, came back, and that’s when the click happened.
[00:28:52] Joe: One of my favorite stories is it was some complex math problem that was out there. I’m not gonna remember specifically the story, frankly, I don’t even have it written down in my notes, but I just remember this that you wrote about this complex math problem.
[00:29:06] Nobody could solve it. And then this, uh, I think it was a professor gets this letter or an email from this like, yeah, I love this one. Yeah. Grad student. And just the answer was far more simple than you thought.
[00:29:19] Ben: Yeah, exactly. It wasn’t even grad student, it was this guy who I think was sort of like an amateur mathematician who’d done a whole career in some other field.
[00:29:24] And then what was funny about it was the solution came this problem that had been outstanding for 40 years. People who had been trying to solve it, all the greatest experts in the field, no one could solve it. And then this guy, Thomas Roan, who’s just worked in some other field, like an insurance agent or something, he sent a Microsoft Word attachment.
[00:29:39] Like, and that had the solution in it, and that’s the least auspicious form of file you could possibly receive. That’s not like, like sometimes I write stuff in Microsoft Word, but serious mathematicians do not ever write stuff in Microsoft Word. It is not the way math, that’s not how the
[00:29:51] Joe: pros do. It isn’t pro, don’t do it that way.
[00:29:54] Ben: As if you’d sent it like written on a Pop-Tart or something. It was like really not the way you expect the solution to a 40-year-old math problem to be resolved. But there it was. And the professor received this guy Richards um, was at Penn State, looked at it and was like, oh yeah, that’s it. I’ve been looking for this problem for decades.
[00:30:09] All the experts I know have been looking for the solution to this for decades. But here it is. There. There it is. Right there. There’s this guy who just solved it and he solved it while he is brushing his teeth one day. Very simple solution. Uh, but the issue is there’s so many possible solutions out there that even if it’s simple, you need a lot of people searching for it.
[00:30:24] And it takes a kind of stroke of insight to see it sometimes.
[00:30:26] Joe: Well, and I love the idea of just being separated from, I feel like to both of those stories, the biggest insights I get about my career, about this show, about my life are when I’m out jogging or in your shower, like you said, some type of hygiene or, or, yeah, physical activity.
[00:30:42] It’s never when I’m doing it. You talk about the difference between good math and great math, and I wanna end on this ’cause this was a really nice gut punch. A good mathematician is the patience to reach complicated answers. A great mathematician is the patience to reach simple answers. And I think we just talked about that.
[00:31:01] Good mathematicians can remember all the details. A great mathematician can forget all the details. You go on and on. But the last one. Last one. Ben, I’d love for you to comment on a good mathematician wants to be the best. A great mathematician wants to learn from the best talk about math and mentorship for a moment.
[00:31:21] Ben: I. Yeah, I got sort of contrast came to me after speaking with this mathematician No. About chow. He won the Fields medal some number of years ago. So, which is kind of one of the most famous prizes in mathematics and, uh, in his home country of Vietnam. He’s like a household name. He’s like a super famous guy.
[00:31:34] I talked to somebody from Vietnam once, he’s like, oh, you spoke with no about Chow. Which I, I wish we had mathematicians like that in the us you know, that be closest we’ve got is Will Hunting, who’s, you know, like, not even, he’s like our fourth most famous Matt Damon character. Much less our, you know, our most famous celebrity
[00:31:48] Joe: can see
[00:31:48] Ben: TMZ
[00:31:49] Joe: following mathematicians around.
[00:31:50] I know mean, right? Ben Orland gets out of his car and you’ve got, you know, you gotta, yeah, I love it. You
[00:31:55] Ben: just, the camera swirling around. Yeah,
[00:31:57] Joe: that’s right. There are Minnesota. You gotta tell your kids to keep the blinds closed. That’s right. Yeah, yeah. No, I love it.
[00:32:01] Ben: So, so a good chance to speak with ’em at, there’s at a press conference and it’s funny ’cause there’s a bunch of science journalists in the room, but mathematics is so.
[00:32:07] The research is kind of so hard to access that. Even science journalists, like, I weren’t quite sure what to ask him, so I started to ask him about just his own path, his career as a kid. He’d been a real hot shot. So he had, you know, he was one of these kids who did the math competitions and was a total superstar, won I think maybe consecutive gold medals or something like that at this big international math competition, which is that, that like really puts you on the map as a very, very high level young mathematician.
[00:32:31] And he said when he was young like that, it was, it was all about the competition. He loved the competition. And it’s funny, I’m not a competitive guy that’s just like not, it’s not how I experience the world, but I see it in some of my students and it really does, it can get them excited about mathematics.
[00:32:44] I, you know, I see it in middle schoolers where like that’s, they like being the best, they like being good at something and which I, I understand, you know, that that’s appealing. But then, right Nohow, he gets to, I guess it’s grad school and he’s been flying high the whole way and he’s been doing great and then he hits the wall and he runs into things.
[00:33:01] He just can’t understand what he’s reading. He can’t understand what’s going on. Everybody hits that point, right? Nocha is one of the most celebrated mathematical researchers in the world. If he’s hitting that point in mathematics. Everybody hits that point sooner or later. He talked about that as kind of the second phase of his career.
[00:33:16] He really relied on his advisor, his thesis advisor. What they would do is every week they’d have these meetings and they’d just spend the whole hour maybe going through a couple lines of mathematics. Could be three lines on the page, like right, sort of like poetry, like we were talking about earlier.
[00:33:30] There’s a lot to digest in those couple of lines. Uh, mathematics is so dense that way. So that’s what they do. Whole hour, a couple of lines, and they did that week by week by week, and it started to click into place and he started to make sense of the mathematics he was learning. And then, you know, he finishes PhD and he starts working on this big kind of collaborative project in mathematics called the Langlands program.
[00:33:50] Which is this like kind of set of things we think are true, but we’re not sure. And so people are out there trying to verify them and prove them. And once he got into there, it was just like pure collaboration. He talks about the competitive instinct, the competitive impulse, all of that vanished. And it was just a bunch of people trying to solve this problem picture.
[00:34:06] Like a bunch of people just trying to build a bridge together. There’s like this huge river they’re trying to build a bridge across. Everybody’s working on a different part of it and nobody’s like, Hey, I want the glory of the bridge. Like, you, you get off of here, man. You don’t build anything. They’re like, oh no, Gogo, we’re trying to get this bridge across the river.
[00:34:19] Like, oh great, you’re working on that part. Cool. I’ll work over here. Like, oh, I, I, I worked on that earlier. Here’s this thing that can help you and bridge I’m using somewhat literally. ’cause it’s sort of connection between two seemingly very distant areas of mathematics.
[00:34:29] aftershow: Yeah. Yeah.
[00:34:30] Ben: It just felt purely collaborative to him.
[00:34:31] So he moved through those three phases, right? Like first competitive. I’m the best. Then the very humbling, like, I am not the best. I need help. Please help me. And then once he’d gotten that help, now it was helping each other. Now it was all reciprocal. I wish more students could get there. You know, you shouldn’t need to be one of the best mathematicians in the world to get to that final phase.
[00:34:50] I think, you know, in a good education, we can experience that the whole way through.
[00:34:53] Joe: Oh, it helps everybody. And I just love that. I think it’s a great place to end. The book is called Math with Bad Drawings, by the way. You not only get. All of these stories and all these, uh, phenomenal examples of different pieces of math.
[00:35:09] I love your chapter on geometry. That was a whole different area we’ll have to do next time, Ben, because I’m fascinated by geometry and mathematics and architecture and this idea that constraints make us better. I think that’s another theme that we didn’t have time to get to. But not only do you get all that, you also get Ben’s amazing drawings,
[00:35:28] Ben: which, uh, I appreciate that.
[00:35:30] Yeah. Yeah. I mean, the book is called Math of Bad Drawings for a Reason. You know, my, my niece who just turned nine, not only can she perfectly mimic my drawing style, she can also do several other kinds of drawing styles. So she’s just like, just strictly a better artist than I am. Um, she’s already nine, so you know, I’m 37.
[00:35:44] Yeah. You already hate
[00:35:45] Joe: that kid, don’t you, Ben? Yes. You hate that kid.
[00:35:47] Ben: Despise it. Yeah. Run me out of a job.
[00:35:51] Joe: Math of bad drawings available everywhere.
[00:35:53] Ben: Yeah, that’s right. Yeah. Yeah. And anywhere you get your books, you should, uh, get math with bad drawings. Awesome.
[00:35:57] Joe: Well, Ben, thanks for being a mentor to us and hopefully we helped a few more people love math more.
[00:36:03] I super appreciate it.
[00:36:04] Ben: Yeah, no, thanks so much, Joe. It was a fun conversation.
[00:36:11] Doug: Hey there, stackers. I’m Joe’s mom’s neighbor, Doug, and what a nice guy that Ben Orland is, don’t you think? Could you imagine that guy being mean? I don’t think so. And by mean I mean average. Well, I also mean mean, but I think we can go with both in this case. Here’s a stat that Ben often talks about that we didn’t get to today.
[00:36:30] When we talk about average, what’s the difference between being mean and being the medium? I’ll be back right after I go try to cross these parallel lines.
[00:36:48] Hey there Stackers. I’m expert parallel Parker and the guy who, Joe’s mom calls the 0.5 when she talks about how many kids people have, Joe’s mom’s neighbor, Doug. When Joe’s mom explained to me that I was the 0.5, I told her that that was mean. She said that. She wasn’t mean at all, just truthful. Which leads us to today’s question.
[00:37:10] When we talk about averages, we talk about mean and median. What’s the difference? The mean is the average of all the numbers. So if we have one plus two, plus three plus 100, the mean would 53. So you can see how that doesn’t actually get us to the middle. If we’re looking for the middle number, we’d instead talk about the median, which is like the middle of the road.
[00:37:34] So now you know the rest of the story and here comes two guys who nobody ever called the median or mean Joe and og.
[00:37:45] Joe: Well, I think one of us can be mean. I, I think, I think Doug, there’s a, there is a through line there from time to time. Maybe
[00:37:55] Doug: I’m not touching it.
[00:37:57] Joe: It is fun, og that math can tell a story.
[00:38:00] And I didn’t realize that until I became a financial planner. Really? That often it’s the numbers. I mean, how many times on this show have you said it’s not about your feelings, it’s just math.
[00:38:13] OG: How many times do I say that Every day? It’s not about your feelings. Stop crying. I don’t care how you feel. Feel that you’re sad.
[00:38:20] Stop spending money. Life is a division problem. I spend money when I get yelled at. When we think about money. I think we like to put a lot of, a lot of energy around the story that goes with it. Well, hold on. You don’t understand. You see what happened was, and it’s like this big long story and it’s like sometimes you have to go, all right, cool.
[00:38:39] But did you spend more than you make? Yeah. Yeah. But, but hold on. There’s a story. It’s like, I get that, you know, you can’t tell stories necessarily unless you’re Ben to make money. You know what I mean? Unless you’re like, that’s your job. Sometimes just kinda taking away the story. And maybe that’s why the career path that I have is what I do, because maybe I lack the velvet that sometimes goes on the hammer.
[00:39:04] Maybe there’s just not enough. Maybe it should be a little, you know, a little bit more massaged. But I can, I just good with the numbers. You know me good Numbers me. No good story. It, it just means you
[00:39:17] Joe: care.
[00:39:18] OG: I care in a different way.
[00:39:19] Joe: Yes. As
[00:39:20] OG: people say. Absolutely. So, Roger, Roger said this the other, a couple weeks ago.
[00:39:23] aftershow: Yeah.
[00:39:23] OG: When he was on the show. I just, I have a different way of showing my care. He does. It’s just to say, stop doing dumb things with your money. It’s like a warm hug from Oog. Well, I mean, it’s as warm as you’re gonna get.
[00:39:37] Joe: I know that og, we talked about standard deviation, which certainly as I mentioned, is, is probably Yes.
[00:39:42] My favorite. Super exciting. Well, it is. It’s my favorite stat to talk about back when I was a financial planner, beca and even now, uh, I like it because I will look at investment, I’ll look at the standard deviation and it kind of tells me what to expect. It kind of tells me that, okay, this is all in the range of acceptable mm-hmm minus 30 is what this does.
[00:40:01] So I should be okay with that. I really like that measurement ’cause that measurement by itself tells me a big story. Is there any mathematical measurement that you prefer when you’re talking to either clients or when you’re digging through Morningstar or are there any, uh, measurements that really catch your fancy As Mom says,
[00:40:23] OG: what catches my eye?
[00:40:24] I think that most people get the idea of Monte Carlo incorrect. I. I think people strive to get this high, high, high number of probability with Monte Carlo. If you’ve never heard that before, Monte Carlo simulations basically take your known data set, right? So I make this much money, I save this much money, I wanna spend this much money in retirement.
[00:40:45] I’m gonna add this inflation to it. Like those are all the knowns. And what’s the big unknown? The big unknown is what’s the rate of return gonna be? What’s the money gonna do while I’m investing it? And we have a hundred years worth of reasonable market data. So you can say, I’m gonna take all the known returns of a portfolio like yours, 80% stock and 20% fixed income, or 60 40 or whatever.
[00:41:06] I’m gonna take all the known returns since 1926 on a deck of cards. I’m gonna play the deck in a different order over the next a hundred years. And then I’m gonna say, did you end up with enough money? Yes or no? Did you die with a dollar? Cool check mark in the past column, and we’re gonna shuffle the deck and we’re gonna play the cards out in a different way.
[00:41:23] And you can imagine if you get unlucky with the cards, who among us hasn’t been unlucky with the cards before? Am I right? Um, if you get unlucky with the cards, you know, things start getting outta hand in a hurry, right? If you happen to retire in the beginning of 2000, you know, you had a pretty crappy 10 year period, you know, you didn’t go with the way that you wanted it to.
[00:41:46] And so what Monte Carlo does is you, you play that game a thousand times and then it gives you a percentage, and the percentage is how many times did you be perfectly successful? Meaning you, you live to your end goal with at least a dollar. And so people look at this and say, well, my Monte Carlo simulation’s an 80.
[00:42:03] I need it to be a 90. It’s like, look, if you looked at the weather and it said 80% chance of rain, you’re packing an umbrella. It’s probably gonna rain. It might not rain, but it’s probably gonna rain. And I think we strive too much for this high perfection number with these different scenario tools,
[00:42:19] Joe: right?
[00:42:20] OG: ’cause in
[00:42:20] Joe: this case it says 80% chance of sunshine and you’re packing umbrellas.
[00:42:25] OG: Yeah, that’s a great way to put it. And the other way that I look at Monte Carlo is to say, what’s the chance of having to make a change along the way? So in that 80% number, that means that 20% of the scenarios, 200 out of the thousand chances, you had to do something different along the way.
[00:42:41] And it doesn’t give you a, a severity of the difference. What I mean, like, it doesn’t say like, or else you’ll be broke. It’s like maybe you just have to slightly spend a little less for a few years, or maybe you, you know, have to change your asset allocation a little bit. It’s not a hundred percent or zero, you know what I mean?
[00:42:59] Like there’s, yeah. And 80 20 doesn’t mean 80%. I make it 20%. I’m destitute living in a van down by the river. It just means 20% of the time we’re gonna have to do something different along the way. Well, guess what? All of financial planning is doing something different along the way. You’re always pivoting when we look at planning.
[00:43:14] Nobody does a plan. Well, at least you shouldn’t. And then just say, well, I hope it works out in 30 years. You, you’re supposed, you know, you gotta, there’s the plan. Yeah. You gotta check it every so often. Right? And make sure that you’re still on track and things are going the way that you want it to. So I think what we get focused on Monte Carlo numbers and, and maybe we don’t understand what it all means or think of it the way that I think you should.
[00:43:36] And then we strive for this perfection number, which is not necessary. It doesn’t need to be 90. It doesn’t even need to be, I think 80 is probably good. Maybe 70 is even good. But if you’re stressing yourself out at 70 or 75, I don’t, I don’t think you need to be.
[00:43:52] Joe: Yeah.
[00:43:52] OG: Obviously some of that has to do with your age and where you’re at in life, but you get the idea.
[00:43:56] So
[00:43:56] Joe: because if you’re 70 or 75, you’re probably gonna be able to pivot somehow, slightly, maybe even, and still be okay in another 20% of scenarios or 15% of scenarios. Yeah. You pivot enough to make it.
[00:44:09] aftershow: Yeah. Yeah.
[00:44:11] Joe: Big thanks again to Ben Orland and it is wild house stats tell a story and sometimes to your point OG, they tell a different story than they, they think that you’re telling you.
[00:44:19] Let’s move on to our headline.
[00:44:21] headlines: Hello Doling. And now it’s time for your favorite part of the show, our Stacking Benjamins headlines.
[00:44:28] Joe: Our headline today comes to us from Morningstar, and it is written by Danny Newan, the number one Nunan.
[00:44:35] Doug: Hold on. There’s no way that’s real.
[00:44:39] OG: That’s, that can’t be true. He’s played out a cad.
[00:44:40] You think Danny
[00:44:41] Joe: Newan is
[00:44:41] Doug: real
[00:44:42] OG: day? Danny Newan? There’s
[00:44:43] Doug: no way
[00:44:44] OG: if that’s his name. I need to play golf with this dude. Honestly. Yes. I mean, he’s probably what, 60 by now? Oh, more than that.
[00:44:51] Joe: Yeah. Danny, I know Danny’s a big fan of the show, so come out yourself. Come join us on an episode of Stacky Budgets.
[00:45:00] These People
[00:45:01] Doug: Drugs. Danny, miss it.
[00:45:04] OG: Well, the World Eaters too.
[00:45:08] Joe: I’ve often thought of becoming a priest. Danny’s got some good news, og, when Danny tells us what the number one way is that Americans are becoming millionaires, what do you think it is? Bingo. Be the ball. Uh, not professional sports.
[00:45:24] OG: Oh, uh, what is the number one way? Home equity?
[00:45:29] Joe: Danny writes, patience and discipline are easily understood, but hard to put into practice.
[00:45:34] Investing serves the perfect litmus. Test one could reasonably argue. These two traits are among the most important factors driving long term investment success. So patience and discipline. Number one way Americans become millionaires isn’t through timely real estate purchases. Dang it. Home home equity.
[00:45:50] It’s funny that, uh, you said that, and that’s is number one. Or being early investors in startups, the formula is much simpler. This is good news for all our stackers. Consistent buying usually in the form of automatic contributions from every paycheck into a retirement account. Look no further than the recent report from Fidelity, which shows there’s more four one K millionaires on its platform than ever before They show the number.
[00:46:15] By the way, they went from a just over a hundred thousand millionaires in 2017 to over half a million millionaires at Fidelity. Now, OG Fidelity might have more four one K accounts than they used to have, so that could be part of it. Mm-Hmm. But, uh, certainly when you look at this graph that’s just up and left, I don’t think it’s just explained by, well, fidelity is more 4 0 1 Ks.
[00:46:36] I think there’s something to this fact that becoming a 401k millionaire is, uh, is a good way to get there.
[00:46:45] OG: Well, it’s weird that if you just do the same thing over and over again, it eventually compounds. What was the thing that we were talking about a couple of weeks ago that if you save a thousand dollars a month, the amount of time that it takes you to get to 300,000 is the same amount of time it takes you to get from 300,000 to a million.
[00:47:01] Joe: That’s amazing. Because compounding interest, the
[00:47:04] OG: snowball is starting to, you know, there’s all these threads on Reddit about like, how long did it take you to get to whatever, right? It’s like, how long did it take you to get 1,000,022 years? And then it took me six years to get to 2 million, and then it took me five years to get to 3 million.
[00:47:21] And then it took me, you know, 36 months to get to fi. You know, and it’s like all those doubles, well not even doubles, all those millions come easier. And it sounds really grotesque to say, you know, the hardest mil, the first millions of hardest is, you know, it’s like, well, yeah, no kidding. Duh. This is the problem with compounding is that you don’t see compounding in advance because you just don’t believe it.
[00:47:42] The brain cannot process it. And even if you’ve type the numbers incorrectly in your, in your calculator, you just don’t believe that a hundred dollars a month for 50 years turns into whatever. You know it, like
[00:47:52] Joe: you’re saying that Ben Orlin can show us all the math. And we’d still go. Yeah, no.
[00:47:57] OG: Well, yes and no.
[00:47:59] I think that you go, okay, yeah, whatever. Maybe it’s right, maybe it’s wrong. Sure, it’s probably wrong. But you know, I don’t have anything better to do. The only time you believe compounding is, is in the rear view mirror. You only see that backwards. And if you have any amount of wealth, if you have a hundred thousand dollars in your 401k, if you’ve got $500,000 saved, if you’ve got a million dollars saved, I guarantee that you can look back and go, golly, sometime you’ve said this, can you believe like just 10 years ago when we cracked a hundred thousand and now we’ve got 500, like what is going on?
[00:48:30] How did that happen? I never in a million years thought I would get to whatever, you know, and I’m here at 40, you know, or whatever. Yeah. You know, that sensation happens because you just can’t process it in advance. Right. So it’s the whole thing of like, how big is a piece of paper folded 50 times? Well, you can’t fold a piece of paper 50 times.
[00:48:47] I know. But if you could, how big would it be? It’s be as big as it is from here to the sun. No, what? Yeah, it is. You know, we just can’t do it in our brains. It’s just, it’s really weird. So you have to have belief and patience and discipline, like Noonan is saying here, to reap the rewards of it. Because otherwise you never get there, you know?
[00:49:09] And you have to have a certain amount of capital first as it starts to, as it starts to snowball.
[00:49:14] Joe: This is a three part story, I think, part number one, when you first start off, I think the only thing you need to do, OG. Plow as much money in as you can and make sure you’re using either something like the, frankly, as long as you’re using inequities, I don’t think it matters what you use, Frank.
[00:49:32] Small cap value. It could be, could be something fairly that be great, aggressive like that. But using slay it, the s and p 500 total stock market index, small, just just pick something that historically has beaten the heck out of inflation. That’s step one. Step two, you get to that point that it finally matters what your asset allocation is.
[00:49:53] And I think then you figure out based on your goals, what those funds are. And by the way, it, it doesn’t take 10 funds. It might be four, might be five, could even be three. But you need to diversify a little closer to what we call the efficient frontier. And then I think then the third thing is. Repeat steps one and two, and that’s it, I think.
[00:50:16] I think that is it. I think the reason why people think they need to do more is you just kind of, you’re like, oh, it can’t be that easy, but mm-Hmm. This piece from Fidelity shows it is that easy? Yep. I love where Noonan goes next with this piece. He goes somewhere brilliant, og, he says, but the investing world is filled with distractions and it’s easy to get tripped up.
[00:50:41] Rising markets often invite bad behavior with some investors making no point of differentiation between the stock market and a casino. How many times have you heard people always, almost always inexperienced investors who go, well, I don’t really play the stock market. Like when you tell me that you’re playing the stock market, you are most probably an inexperienced investor.
[00:51:04] One timely example he brings up is leveraged in inverse exchange traded funds, which now have surged in popularity. You remember how a few weeks ago we talked about micro strategy and, and they had this new ETF that was coupled into micro strategy and, uh, pundits were, were predicting, I think Michael Kites and others were predicting that this is gonna make nobody money except for the people selling it.
[00:51:32] Danny Noonan goes right after this approach. It says, A recent Bloomberg story highlighted one of those investment vehicles that’s designed to give investors three times the daily return of MicroStrategy MSTR. So what is MSTR? MicroStrategy for people who don’t know, is a company largely tied to Bitcoin because it holds a large amount of Bitcoin on this balance sheet.
[00:51:55] So MicroStrategy, at the time this was written, was up over a hundred percent this year. But get this og if you went with the product that three x is its return on a daily basis, you are down more than 80% so far this year. So then Noonan asks the question, how is that possible? And this is another Ben Orland math problem.
[00:52:21] Was he say
[00:52:21] OG: math?
[00:52:22] Joe: Yes. He said compounding also works in reverse. So if those down days or more downy down, then the up days are upy up if it slowly goes up, but it massively goes down on a few days, you’re gonna be in a world of hurt. So we’re we’re sitting as we record this, well as, as the piece was written, and it was written on September 17th.
[00:52:46] Uh, so so that means it’s
[00:52:46] OG: a buy down 80.
[00:52:48] Joe: There you go. Just get in.
[00:52:50] OG: Time to three x. The three x, can I get that fund on margin? That’s really my question.
[00:52:54] Joe: 110% up if you just bought MicroStrategy stock versus down 81% if you bought the three x.
[00:53:03] OG: Yeah. Well that, and because the, the leverage fund resets daily.
[00:53:08] That’s the other big missing piece is people just look at the annual return or the quarterly return or whatever and say, oh, it’s up a hundred, I’d be up 300. And to your point, no, it’s the volatility that matters. And that’s really what you’re playing. This is a symptom of people thinking they don’t have enough time because they don’t believe the compounding.
[00:53:26] So it all kind of comes back to the same problem, which is you’re 45 years old and you go, I haven’t done anything yet, or I’m really, I feel really far behind. I need to try to hit a grand slam here because I need to get caught up. And the problem is, is that if you do that, there’s a really good chance that you’re gonna make it completely unattainable.
[00:53:46] If you take what little money you have at 45, if you’re, if you’re behind and you say, at 45, I need to go to the casino and I’m gonna play this all on red and black until I get to, you know, caught up to my peers, it may work there, there may be an outcome there that’s successful, but a lot of times it’s not gonna work.
[00:54:04] And if you do this with investing and you do some esoteric investment choices, or you’re playing the, the options market or something like that, there’s a chance you could be successful. There’s an article that, uh, that I saw the other day about a, an investor in Canada who went from some relatively small amount, a hundred thousand, $200,000 to $450 million in Tesla in options and lost it all.
[00:54:30] And now he wants to blame the broker for letting him even do it. Right. You know, you should have told me to get out.
[00:54:36] Joe: It is so wild how emotional we get. Brian Aldi had a great social media piece going. If you’re like the 401k person. It goes 10, $10 a share to $20 a share, which by the a hundred percent rate of return, right?
[00:54:51] Mm-Hmm. I mean, huge return, but it goes 10 to 20 to 30. You are high fiving yourself, but if it goes 10 to 40 to 30, there’s so much consternation. There’s so much, what did I do wrong? How did I mess this up? And you ended up in both cases, OG, at the same point. There’s so much emotion, and I think Danny gets it right here, saying the best investing may not always be thrilling, but that’s for the better.
[00:55:18] Keep your emotions out of it. Yes. Take your paycheck,
[00:55:20] OG: take your emotions out of it.
[00:55:22] Joe: Every two weeks, just put more money in. You got it.
[00:55:25] OG: So you’re telling me there’s a chance.
[00:55:29] Doug: Interestingly, you did just have an emotion as you said, that it was anger and frustration if only he’d express anger from time to time.
[00:55:39] If we could get that outta him, we as an emotionless, we’ve been mis tagging him all these years,
[00:55:43] OG: just malcontent.
[00:55:44] Joe: We will link to this piece in our show notes at stacky Benjamins dot com, like we do every week. And of course, in our newsletter, the 2 0 1, we will dive deeper into math problems with Ben Orlin and also into today’s headline, always free twice a week, stacky Benjamins dot com slash 2 0 1 to get the newsletter.
[00:56:03] That brings us to the end of today’s show, Doug, I don’t really have anything for the, for the back porch. Big thanks to everybody who, uh, has left us a review of this show. And I did mention this last week once I, I’ve got a ton of books. I don’t wanna trade books for reviews, but I’ve done this in the past.
[00:56:20] But I’ll trade
[00:56:20] OG: books for reviews
[00:56:21] Joe: if you, if you were gonna leave us a review and what takes us to push you over the edge is the fact that you can read one of these books by somebody like Ben Orland who comes on here. Send me just a snapshot of your review or let me know that you left the review, Joe at stack Benjamins dot com and I’d be happy to, uh, clean out my office again, my semi-annual.
[00:56:44] Doug: Don’t send Joe the review. I know he just, Joe at Stack Benjamins. Don’t send him the review, put the review out for the world and then send him a little note like, Hey man, go look over here.
[00:56:53] Joe: Thank you
[00:56:53] Doug: to prove that I, and then send me my damn book,
[00:56:57] Joe: my interpreter Doug. Yes, absolutely. Amen. What, what Doug said.
[00:57:02] I think it’s all for the back, for the back porch today. Looking at the time, I think it’s time to head out. Anyway, Doug, let’s do this. Wrap it up for us. What should be on our to-do list after today’s show?
[00:57:14] Doug: Well, Joe, here’s what’s stacked up on our to-do list for today. First, take some advice from Ben Orlin.
[00:57:20] Wanna understand your investments better? Use math to make it more fun. There’s something nobody ever said. Stats like standard deviation. Tell a story that’s hard to understand otherwise. Second, hoping to become a millionaire. Try your workplace retirement plan. You don’t have to be all fancy to be rich, but the big lesson, don’t criticize Joe’s mom for singing Tom Jones.
[00:57:45] Why is that something different for her? It’s not unusual.
[00:57:53] Thanks to the Ben Orland for making math fun today. You’ll find his book Math with Bad Drawings wherever books are sold. We’ll also include links in our show notes at Stacking Benjamins dot com. If you click that link to buy it, you’ll help the podcast. This show is the property of SB podcasts LLC, copyright 2024, and is created by Joe Saul-Sehy.
[00:58:16] Joe gets help from a few of our neighborhood friends. You’ll find out about our awesome team at Stacking Benjamins dot com, along with the show notes and how you can find us on YouTube and all the usual social media spots. Come say hello. Oh yeah, and before I go, not only should you not take advice from these nerds, don’t take advice from people you don’t know.
[00:58:38] This show is for entertainment purposes only. Before making any financial decisions, speak with a real financial advisor. I’m Joe’s Mom’s Neighbor, Duggan. We’ll see you next time back here at the Stacking Benjamin Show.
[00:59:39] aftershow: We were talking
[00:59:39] OG: about emotionless or lacking empathy and, uh, Joe, you know, maybe not, no-no. But you’ve heard of Jocko Sure. In his podcast. This is probably one of my favorite bits that he has that’s, uh, shown up on my feed from time to time. Doug says he doesn’t know who this is, but I’m almost guaranteeing as soon as he hears this man’s voice, he’ll be like, oh, that guy.
[01:00:04] Okay. So, uh, I feel like, uh, I feel like it’s some small microscopic level. Maybe we have some similar DNA here. So here’s this from Jocko,
[01:00:17] bit – Jocko: one of my direct subordinates, one of my guys that worked for me. He would, he would call me up or pull me aside with some major problems, some issue that was going on, and he’d say, possibly got this and that and the other thing. And I’d look at him and I’d say, good. And finally one day he was telling me about some issue that he was having some problem.
[01:00:37] And he said, I already know what you’re gonna say. And I said, well, what am I gonna say? He said, you’re gonna say good. He said, that’s what you always say when something is wrong and going bad. You always just look at me and say, good. And I said, well, yeah, when things are going bad, there’s gonna be some good that’s gonna come from it.
[01:01:04] Didn’t get the new high speed gear we wanted. Good. Didn’t get promoted. Good. More time to get better. Oh, mission got canceled. Good. We can focus on the other one. Didn’t get funded. Didn’t get the job you wanted. Got injured. Sprained my ankle. Got tapped out. Good. Got beat good. Learned unexpected problems.
[01:01:33] Good. We have the opportunity to figure out a solution. That’s it. When things are going bad, don’t get all bummed out. Don’t get startled. Don’t get frustrated.
[01:01:51] If you can say the word good, guess what it, it means you’re still alive. It means you’re still breathing. And if you’re still breathing, well now you still got some fight left in you. So get up, dust off, reload, recalibrate, reengage, and go out on the attack.
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