S3E26 Noah Healy Data Science Applied to Commodities

S3E26 – Noah Healy – Data Science Applied to Commodities
Noah Healy – Data Science Applied to Commodities. My next guest is a mathematics and data specialist who has been working on a platform that helps large institutions save money and increase profits with commodities. In this episode, we talk about his company, some of the specific problems it solves, and a little bit about the commodities market. Please welcome Noah Healy.

Payback Time Podcast

Payback Time is a podcast for investors. The goal of this podcast is to help make investing approachable and easy to understand. We will interview beginner and experienced investors and ask them to share stories on how they got started, what challenges they faced, what mistakes they made, and what strategy works for them today. The overall objective is to provide you with a roadmap that helps you become a better investor.

Key Timecodes

  • (00:37) – Show intro and background history
  • (01:24) – Deeper into his background and career path
  • (03:27) – How he monetized this business
  • (05:36) – What is his SaaS core idea
  • (06:24) – What are the benefits for the institutions using his services
  • (09:58) – Is he collecting data with his platform?
  • (11:51) – Deeper into his SaaS business model
  • (12:58) – The importance of commodities business in the world economy
  • (14:21) – What is the major milestone he is focused on
  • (16:07) – A key takeaway about commodities for retail investors
  • (20:50) – What amount of returns can be expected for retail investors investing in commodities
  • (21:48) – A bit about the risks in the commodities market
  • (23:42) – His recommended resources for those who want to know more about the commodities market
  • (27:37) – What is the worst advice he ever received
  • (28:04) – What is the best advice he ever received
  • (36:40) – Guest contacts

Transcription

[00:00:04.160] – Intro
Hey, this is Sean Tepper, the host of Payback Time, an approachable and transparent podcast on business investing in finance. I like to bring our guests to hear authentic stories while giving you actionable takeaways you can use today. Let’s go. My next guest is a mathematics and data specialist who has been working on a platform that helps large institutions save money and increase profits with commodities. In this episode, we talk about his company, some of the specific problems it solves, and a little bit about the commodities market. Please welcome Noah Healy.
[00:00:40.440] – Sean
Noah, welcome to the show.
[00:00:40.970] – Sean
Thanks for having me here, Sean. Thanks for taking the time.
[00:00:46.300] – Noah
Why don’t you kick us off and tell us about your background? Well, I’m a computer programmer and algorithmic expert that works in computational mathematics and found myself backing into finance when I discovered this game theory approach to developing market mechanisms for group consensus, if you will. And so I’ve been working on this for the better part of a decade. I’m fighting with the patent office and spreading the message through podcasts and other things, looking for people that want to build new, more robust marketplaces. Got it. All right, so let’s dive into this a little further.
[00:01:24.570] – Sean
Just one context in your background, how many years have you been in software engineering? Got into that out of college.
[00:01:32.470] – Noah
I actually studied nuclear engineering and a bunch of other basically random stuff. So I needed a job and I got out of college in 2000. So jobs in tech were plentiful and easy to get for people who could breathe. And so I got one of those and started studying the math and really had an affinity for it. Got it.
[00:01:55.910] – Sean
Now, did you work for financial institutions or did you work just in IT at a general?
[00:02:02.630] – Noah
Not at all. I worked for a bunch of different kinds of companies, but they were almost all tech startups and just a wide variety of things. The finance stuff actually came out of work I was doing just under my own steam on effectively communication theory. M arkets are very specialized communication tools from a computer science standpoint. Got it. When did you start.
[00:02:27.160] – Sean
Working on this company or product you’re working on right now? The initial patent filing, so I.
[00:02:33.710] – Noah
Could actually talk to lawyers to try to get one that could do the full patent application, was June 2015. Got it. Okay. Are you still working.
[00:02:43.850] – Sean
On the patents as we speak? Yes. The way the patent process.
[00:02:48.710] – Noah
Works is there’s an expert that you work with to see whether or not it’s patentable and get it into the shape. T hen they give you something called a notice of acceptance. And then you can take that and apply for your patent. And basically that plus the patent application equals a patent. I’ve gotten two notices of acceptances for this patent, and both of them have been withdrawn after we’ve actually applied for the patent. One is rare, two is, as far as I know, completely unheard of. I’m very familiar with the process because we did something similar with Tykr.
[00:03:27.600] – Sean
I’ll share that story in a moment. But it sounds like now, 2015 to 2023, eight years you’re still working on the patent. Have you gone to the market? Are you monetized? I’m working with about half a dozen at this point people who are trying to set up.
[00:03:46.230] – Noah
Markets, but they’re overseas. So they’re outside of the patent window, and it’s actually set up to be under a Creative commons. I think it’s the third tier Creative commons license, which the patent will exceed inside the United States. But just to keep the ball rolling and get some things going, there’s a Creative commons license outside US jurisdiction that some people are taking advantage of. Got it. And so to answer the question again, are you monetized? Are you charging these customers outside the States? One, yes.
[00:04:20.080] – Sean
The others so far, no. Okay. So just to back up a second, how are you generating…
[00:04:26.550] – Noah
I have to ask this question because a lot of entrepreneurs are…
[00:04:31.110] – Sean
If you’re not working for a company, how are you generating a paycheck? Mostly I can fund this off of the savings from.
[00:04:40.210] – Noah
When I actually do my regular job. I’ve had day jobs and a couple of other consultancy gigs along the way. I can do data science and stuff like that. And the thing is, I don’t live particularly rich, and so the minimum that people pay for the work that I do is three times what I actually live on. So that can allow me.
[00:05:04.630] – Sean
To stay.
[00:05:05.480] – Noah
In the game. Right on.
[00:05:07.250] – Sean
So essentially, you probably have your own LLC and you can act as a consultant, whether it’s probably a project per project basis to generate some revenue. I’ve done a.
[00:05:18.660] – Noah
Few of those. Like I said, I did have a day job for a few years in the last nine, but a few years will basically pay for nine years of doing this. So that’s all it takes. There you go.
[00:05:34.280] – Sean
Along with a few other bits and pieces here and there. Yeah. Run and lean, working on the patent. So let’s dive into the model a little bit more. So is this an enterprise focused.
[00:05:47.810] – Noah
Platform like a software as a service for larger institutions? Yes, it is. So the core idea is actually as a service for people that are offering marketplaces. And it replaces the existing market mechanism that people are very used to is just the clearance and the Tykr. So as you want to buy or sell, you’re put into one of two different lines of buyers and sellers. When those things clear, there’s a clearance algorithm to figure out who wins the tie breaks, and then the actual trades are published. This is a replacement mechanism for.
[00:06:24.760] – Sean
That part of the marketplace. Okay. Let’s talk about the net benefit here for the institutions that use the product. Are they looking for a certain level of alpha or certain returns month over month.
[00:06:38.080] – Noah
Year over year? So the core of this idea is that this actually removes the buyer seller paradigm, and this is why it’s more commodities focused and takes it to a producer consumer forecast or operator paradigm. Each one of those four roles gains an advantage from this switch. So for the operator, which is where your question is focused, the cost of operation reduces precipitously. Existing operators generate petabytes of data, which costs a lot of money to store and transmit and maintain and compliance. This system can replicate the behaviors of markets with only megabytes of data, so those costs basically vanish. There’s also a lot of compliance costs with regulatory issues around know your customer, which this doesn’t do much for, but also anti money laundering. This structurally eliminates money laundering. But probably the most important thing is that the existing system is based around a concept of offer flow, where you’re basically paying a very tiny fee for each attempt at trade that you make. And so the operator is making money off of a large amount of noise that they are processing. And what this does is changes the paradigm to a commission on delivery trades that go through the system.
[00:07:56.520] – Noah
And since the existing overheads are in the somewhere between 5 and 15 % range, the operator can actually undercut the primary cost to their necessary customer base and actually get a bigger hunk of the deal flow. So to put some numbers out there, CME group has an annual revenue in the 4 billion range on commodity market overhead cost in the 800 billion range per year. So they’re absorbing roughly half a % of the potentially available revenue. This technology would allow an operator to drop that overhead while raising their fraction. So they could take 10 % of half of that and have 10 X the potential revenue of, say, the CME crew. Got it. So to put it in simple terms, from my perspective, an institution that trades commodities like their customers will use their platform to trade commodities, your tool, your platform can come into the equation and help the institution lower the costs of all those trades and slightly increase the margin they make. Sounds like there’s a little higher fee they.
[00:09:04.580] – Sean
Can charge as well. Is that correct? Correct, yes. Because the quality of the service that they’re offering, that information condensation means that there’s a lot less noise for their customer basis to have to wade through. So basically it’s a higher quality product from a market perspective. Because you said you’ve got one paying customer right now outside the States, I assume in the UK? No, South Africa. Oh, really? Okay. And you’re collecting data as we.
[00:09:34.020] – Noah
Speak to show, because you probably want to leverage that data to sell other institutions. That’s still, unfortunately, somewhat early days. The primary cost of setting up markets is regulatory compliance and customer acquisition. And all the people I’m working with are.
[00:09:50.020] – Sean
In that phase of the markets. Okay, interesting. You’re really hustling along here for eight years.
[00:09:55.950] – Noah
And dealing with.
[00:09:57.460] – Sean
This patent. I’d like to share a story with you. And I know you’re more B2B, whereas Tykr is more B2C. But check.
[00:10:06.070] – Noah
This out. So Tykr was an algorithm I originally wrote in Excel, very much inspired by the teachings of Phil Town, which is inspired by Warren Buffett and Charlie Munger. But I put all these equations into.
[00:10:19.970] – Sean
Excel, used it for four years just to test the algorithm. It brought it to people asking them, Hey, what do you think of this? Here are the returns I’m getting. And the general response was, Hey, you should turn this into a tool to share with others. So that was 2019. Built the tool, took about a year. But anyway, I went for a patent. I’m like, I should probably put a patent on this thing. And then it turned into a provisional patent at first, easier put, easier effort. And then started talking to business partner, Elgar, as well as some of our customers. And we thought, Hey, what if we just flip this on its head and make it all open source and get rid of the patent completely? And that actually ended up being a wise choice because a lot of people are like, Wow, you guys are being transparent. You’re being open. So we pitched it as, Yeah, it’s totally open source. You can go to our site, see all the equations. You can put it into Excel, and we even tell people you can go create your own version of Tykr, but we still hope you stay with us.
[00:11:37.910] – Sean
And by doing that, it’s become a nice marketing tool because there’s other screeners out there that don’t do the same thing. So with that in mind, could you do that to build a little more trust and transparency at the enterprise level if you took away the patent? Well, that’s actually why.
[00:11:58.370] – Noah
I’m doing this inside the United States, outside the United States strategy. So it is open source outside the United States. It’s under a Creative Commerce license. There’s some code that people can look at. I’ve published out the white paper, so people are free to download that, take a look at that. And again, the equations are sitting there. You can go and do the math yourself. But at the same time, maybe some people would prefer to come into an investment with patent protection. And so that’s where the patent comes in. If you’re inside the United States, then you can have that patent licensing protection. So we’ll see which way it’s going. Right now, the open source is getting all the pickup. On the other hand, the patent is pending and not actually in place. That process is currently heading to court. If the patent is granted, it might gain some interest at that point.
[00:12:58.170] – Sean
Okay. Is it ave you weighed the pros and cons? Is it really worth pursuing at this point? In other words, is the juice really worth the squeeze at the end.
[00:13:09.910] – Noah
Of the day to get this patent taken care of? This is the most economically valuable activity that human beings are presently engaged in, period. The current overhead cost of commodity exchange on a global level is on the same near order as the economic growth rate of the human species. And this would allow that number to be reduced precipitously, which would go straight to the bottom line of production across essentially every industry, whether you’re talking about energy or food or water or textiles or building materials, everything. And so this would change the trajectory of economic growth for generations. So yeah, the reason I started doing this in the first place is because that’s what the math said. The math hasn’t said anything different in the last nine years. And so that’s just it. Until the math says that there’s anything that’s more valuable than this to do, I’ve got to keep doing this. Okay. All right. Short answer. Yes. Right. Well put. All right. So what’s.
[00:14:14.260] – Sean
The next major milestone you’re focused on at.
[00:14:17.350] – Noah
This point? So I was.
[00:14:19.330] – Sean
Just in a conference talking about ethics of AI and the problem of getting AIs to do things that are valuable and interesting.
[00:14:28.140] – Noah
Which is very similar to the kinds of work I’m already doing. So that’s a new area for me to explore with this approach. And that would be another potential revenue stream, keeping me in the game, other ways to get this out and having some proof of concept going on. So this conference is just a couple of weeks ago, and it’s already generated a dozen follow up meetings to do and yet another potential gig for me to do some consulting. So I’m following up on a lot of those things right now. Got you. Okay, moving things along. There you go. Let’s take a quick commercial break. Do you feel like stock investing is.
[00:15:12.770] – Sean
Too confusing, too time consuming, or too risky? It doesn’t have to be. If you ever considered investing on your own but you don’t know where to start, I welcome you to check out Tykr. Tykr guides you through your investment journey by steering you towards safe investments and away from risky investments. There were two main reasons why I created Tykr. Number one, I wanted to remove emotions from investing. In other words, I wanted a software to make buying and selling decisions for me so I don’t have to. Number two, I wanted to save time. Analyzing stocks can take hours, if not days, and I didn’t want to spend all day looking at the computer. I have other hobbies in life I’d rather be enjoying. If you’re interested, you can get started with a free trial. Visit Tykr. Com. That’s TYKR. Com. Again, Tykr. Com. Now, our audience, they’re primarily retail investors. We don’t have too many enterprise, you could say, listeners, part of this podcast at least, that maybe work for a large institution and they’re a higher up decision maker. But knowing this is commodities, do you have any key takeaways you can give our audience regarding commodities?
[00:16:29.870] – Sean
Maybe they could learn more about it, maybe ways they could generate a revenue stream from it.
[00:16:36.500] – Noah
Commodities are incredibly tough for the retail investor because it’s hard to know more than the people that have to play or the people that spend a lot of money so that they can play to win. So it can be a pretty dangerous business to get into. However, there are a few things, both general and specific to my thing that I’ll get into. So one of the general things is that there’s a general business principle of commoditizing complements. So the classic example is Bill Gates getting IBM to open source the specs for the XT. Bill’s selling operating systems. He’s selling IBM operating systems. If IBM owns the specs to his complement product, then Bill becomes basically a subcontractor of IBM, and Microsoft never becomes a multinational powerful company. But since everyone that’s got a chip that can now make an IBM mainframe desktop laptop, slash whatever, and Bill can sell to all of them. Suddenly, the people making the thing that people need to use your thing are competing with each other to make their thing as cheap and as ubiquitous as possible. You’ve essentially turned your partners into your salesforce. So when you’re doing investing, that’s a thing to think about because commodity markets exist.
[00:18:08.740] – Noah
Part of figuring out a business plan is working out whether or not its complements have been commoditized are being effectively commoditized. So you can look at commodity markets as part of the system around a company that you’re examining to see whether or not it’s in a good or bad position growth wise, like, does it have that system propping it up or not? Or could it have that system propping it up if it was moving in a better direction? Are there people taking advantage of those kinds of things? That can exist both at the raw materials level, maybe the company is valuable because they own all the copper sources out of South America. And so it’s actually commodity play. It just looks like an equity play. Or maybe the company is valuable because the raw materials are going to be coming in from all over the planet for dirt cheap because people are just trying to sell as fast as they can. So that’s a general thing to think about of mixing commodities into your view of markets and specific stocks and how to think about these things profitably. The second one is that my basic mechanism is about network consensus.
[00:19:21.190] – Noah
So it’s about drawing together multiple points of view into a single better idea than any of the individuals could actually have. So for the retail investor, exploring some of my technologies might give you ways to create investment groups that could be internally managed to invest in ways that would be more wise than other sorts of approaches you might want to take. One of the people I’m consulting with is actually trying to set up a DAO, distributed autonomous organization, and their goal, it’s all crypto, they want to create synthetic markets that basically Asians would be able to pseudo invest in equities and other types of things from around the world without having to deal with the regulatory issues because they’re not really investing. They’re investing in these shadow things. But the key is that they need to be able to manage a lot of parameters about how big or often the penalties need to be for errors and so on. And so they’re using my kinds of technology to manage the parameters of the market space. And so a retail investor that would want to join a group could use these sorts of technologies to manage that group in ways that would be measureably fair and measureably valuable to the individual group members as contributions were made on an individual basis.
[00:20:49.930] – Sean
Okay. Do you have any ideas of what returns retail investors can expect trading or investing in commodities?
[00:20:59.980] – Noah
In general, the average rate of returns in commodity markets is the same as the average rate of returns in other marketplaces, because if it gets too far out of whack, the big institutional players will start doing their big institutional player thing and even that out. Again, because of how much information asymmetry exists, retail investors generally do a little bit worse in the commodity markets than they do in other places. Now, the flip side is that commodity markets are relatively uncorrelated to the other marketplaces in general. So if you’re looking to diversify your portfolio, that’s something where it might be possible to dip a toe and get something that will be counter cyclical to basically everything.
[00:21:47.280] – Sean
Got you. Okay. Thanks for that transparency on the risks here. I’ve talked to people who trade commodities, and some are stating they’re beating the market. And I’ve actually talked to one guy, he’s like, all I aim for is to win 51 % of the time because that means I’m making money. And maybe that’s a win for him. To me, it’s like, really? Boy, I’m an investor, so I’d like to win.
[00:22:13.770] – Noah
The whole structure is very different. We were talking about this a little bit before the call, but the concept of commodity markets is really about managing a deal flow system. Whereas an investment, a pretty small fraction of companies frequently turns over in any given quarter. Whereas basically all the wheat that’s grown every year is going to get sold. And then next year, we’re going to grow all the wheat again, we’re going to sell it all again. So a company like Alphabet or Facebook doesn’t see 100 % transfer in a decade, basically. So it’s a very different animal from that point of view. The goal isn’t so much the value of the underlying assets. The goal is stabilizing the value of the ongoing trade stream. You can make an enormous amount of money being right 51 % of the time because of how big and how wide that trade stream actually is. But if you are thinking like an investor and you’re thinking like, Well, I’m going to get into wheat and wheat is going to get worth more money and I’m going to be happy about that. Well, maybe we will be worth more money, but you’re now taking a very tiny piece of the stock and taking that risk along with everybody else.
[00:23:33.500] – Noah
And the real thing is to try to get into that flow stream and play that game really well. So it’s a much more active style of trading.
[00:23:42.570] – Sean
Before we jump into the rapid fire run, do you have any recommended resources, maybe a book where our retail investor audience could learn more about commodities trading?
[00:23:53.580] – Noah
That’s very tricky, sadly. The markets bifurcated a few centuries ago, and the two don’t really play nicely with one another. Quite frankly, the best resource for understanding commodity markets to this day is the film Trading Places, where they explain to Eddie Murphy what commodities are. And then you watch a pretty classic commodity manipulation play out at the end. And while the pits don’t exist anymore outside London, that’s basically all real. They’ve all worked like that for centuries. And that’s essentially what happens.
[00:24:30.450] – Sean
Trading Places. I remember seeing the movie years ago. 1983. Nice. Eddie Murphy, Dan Ackroyd. All right, that’s your educational resource, kids. Yes.
[00:24:40.750] – Noah
I’m afraid it is.
[00:24:43.100] – Sean
Fair enough. All right, let’s take a quick commercial break. Hey, this is Sean. I’d like to say thank you for taking the time to listen to this podcast. I know there’s a lot of other podcasts you could be listening to, so thanks for taking the time to listen to this one. I have a quick request. If you have a moment, could you please head over to Apple Podcasts and leave a five star review? The reason is the more ratings we get and the higher those ratings are, the more Apple will share us with the world. So thanks in advance for doing that. And then I have a quick comment. If there are any questions you want me to ask the guests, please head over to our Tykr Facebook group. You can drop a question right there. I’ll go ahead and make a note and I’ll do my best to ask that question on the podcast. All right, back to the show. Well, this has been good. And I definitely have to circle back to you in maybe six months to a year to see where your enterprise play is. We love hearing those success stories of people building businesses, especially from my perspective.
[00:25:39.010] – Sean
I love hearing about SaaS businesses, whether it’s B2C or B2B, like which you’re working on. All right, well, let’s dive into the rapid fire round. If you can, try to answer each question in 15 seconds or less. You ready?
[00:25:53.180] – Noah
Sure.
[00:25:53.400] – Sean
What is your favorite podcast?
[00:25:56.600] – Noah
Terrible with names. There was one I was on where they were interviewing people around the theory of multiple intelligences. I was their expert on math logic intelligence, and we got to have this fascinating conversation about quines. I’m probably past my 15 seconds, but they came up with this notion that I hadn’t heard to me before. It turns out that bacteria and amoeba are biological quines. That was fascinating to me.
[00:26:28.660] – Sean
Very fascinating. You have to shoot me a link to the podcast if you get a chance to remember what it is.
[00:26:35.330] – Noah
Yeah, I will look that up once I’m offline.
[00:26:39.670] – Sean
All right, next question. What is the recent book you read and would recommend?
[00:26:44.420] – Noah
Well, we actually just had our Friends of the Library sale here. So I got my class of books and I’ve got it sitting right next to me, actually. Two person game theory, The Essential ideas. This is actually even more readable than the Rand Corporation’s cartoon book to explain game theory that they came up with. So yeah, I’d recommend this one. Nice.
[00:27:09.760] – Sean
All right, movie question. What is your favorite movie?
[00:27:12.580] – Noah
Star Wars. Going back.
[00:27:13.570] – Sean
To the original.
[00:27:14.660] – Noah
My babysitter when I was two was my aunt, and she worked in the theater that had the first one in Star Wars. She hates the movie, mostly because she took the job because nobody came to theater. And then Star Wars changed all that. But it is bone deep. I was learning how to talk while I was watching Star Wars.
[00:27:35.060] – Sean
Embedded in you. That’s great. All right, we got a few business questions here. First off, what is the worst advice you ever received?
[00:27:46.880] – Noah
Quit? Yeah. I’ve had numerous people tell me that I’m basically taking my life into my hands to do nothing consequence. I’m still here and progress has been made, so I think they’re wrong.
[00:28:02.330] – Sean
That’s the spirit right there. All right, flip that equation, what is the best advice you ever received?
[00:28:09.200] – Noah
People learn in stories. The primary challenge for me along the entire way has been trying to turn a concept that’s relatively straightforward when expressed in integral equations and turn it into something that grabs people by the lapels and actually gets them to come along for the ride. It’s been a very long and very slow process for me of working out what that actual path is. And stories was a big step forward for me.
[00:28:38.270] – Sean
Now, I want to drill into that. Are you talking about using the concept of telling a story as a sales tool, or are you referring to the agile methodology of creating stories?
[00:28:49.540] – Noah
More the sales tool end of things, but just in terms of conversation, personalizing, characterization to get people to engage the existing structure of buyer seller to characters is an easier story to tell and understand than my four character story. And so doing that four character story not as a projection of a high dimensional space onto a different high dimensional space, which, as I said, is mathematically the easy way to see what’s going on, into tales of you got a farmer and a Miller, and they need to trade with each other. But you don’t just have one farmer and one Miller, you’ve got 10,000 farmers and 500 Millers. They can’t all communicate with all of them or they wouldn’t have enough time to do their own jobs. And so they need to negotiate and mouse. So how can two large groups of people with a common interest in their common interest, but individually diverse interests come to a common understanding?
[00:29:55.970] – Sean
You really sum this up nicely as taking the two different individuals, the two different parties of the story, characters, you could say, and how do they interact with each other? And the en masse comment is brilliant because you can’t. They have a day to day job to do. Where does a tool come in that can help stream line and make things efficient, make things transparent, they can see? That’s where you come in.
[00:30:20.440] – Noah
That’s the moral.
[00:30:21.820] – Sean
Of the story here.
[00:30:23.500] – Noah
Yeah. And that basically took me five years to come up with, which it was a lot more work than it should have been.
[00:30:30.420] – Sean
I tell you what, I’ve learned that too, is you think your pitch, your story is simple, and you got to peel back the onion even more. And how do I make this even more simple? Even no matter if you’re talking to consumers or businesses, you’ve got to make it simple. And if you can create characters in the story, that’s almost that aha moment like, I get the problem you’re solving. Yeah, sounds like you’ve arrived there. So good for you. Thank you.
[00:30:59.560] – Noah
I’m going to keep peeling the onion as far as I can get.
[00:31:05.020] – Sean
Simplify, simplify. Even more. All right, one more question here. This is a time machine question. If you could go back in time to give your younger self advice, what age would you visit and what would you say?
[00:31:17.990] – Noah
Thanks for the heads up on this one. I think I’d have gone to eight when I was actually introduced to computers in the first place. When I was first being shown computer programming, it was all being done in context of games and computer graphics and that thing. I guess they wanted to capture the imagination of children. I regarded those things as unimportant toys, and so I never really got into it. I like to have shown that self computational mathematics because when I was actually exposed to computational mathematics when I was 25, I found it endlessly fascinating and a direct continuation of the kinds of math that I liked back when I was eight. And so I think I could have gotten myself 22 or 17 free years of work and effort if I’d been able to reorient what this stuff is actually for and what’s good about it. Based.
[00:32:20.220] – Sean
On those comments, you weren’t the one playing Oregon Trail on your Apple II?
[00:32:25.210] – Noah
I have played Oregon Trail. I know that in the library. But we were shown Logo, which actually my company’s logo was written in Logo. But they had this lesson plan. I don’t think the teachers understood what was going on. I know we, the students, didn’t understand what was going on. They had these set things to show us that were showing us the power of recursion, but they didn’t know that the point of these things was the power of recursion. So it was being lost on everybody. And yeah, So we wrote a handful of simple programs and drew some octagons and circles. And then there was this game you could play where the thing would draw up an asteroid field and you’d try to play golf, draw lines through the field that didn’t go through any asteroids, and just by writing commands in free hand. And I believe some of the other students enjoyed that. But to me, it was just like, oh, computers, meaningless toys, and just a full dismissal. Well, I like.
[00:33:33.850] – Sean
The backup a second. I like what you talked about there as the yes, there’s a lot of meaningless tools and apps, and we see a lot of apps I think you and I would agree on. Probably some of the apps that people use today, they’re meaningless. What value do they provide? I think of some social platforms out there. But anyway, you were drilling down into the how on how does this function? Looking under the hood, how do you create these games and diving into the code, looking into the math? That’s probably where your interest in data analytics, data science really started. Yeah.
[00:34:07.480] – Noah
Well, basically I got to school, was shown counting, worked out multiplication. And then your parents sit down with you, your homework when you’re in first grade or whatever. My dad accidentally taught me algebra at that point. And then I float coasted to seventh grade where there was an accelerated pilot program that I was one of the three people in. I actually took an algebra course. The teacher, after a few weeks, basically cut a deal with me that if I stopped participating in class so that he could actually teach the other students something, then I wouldn’t have to participate in class anymore. I finished off the book in a few weeks and started bringing books into school to read just for fun. I’d read during his class. He gave me Shirley, you’re Joking Mr. Feinman, Richard Feinman’s autobiography, but I bring in other books as well. And then that formed new habits, took calculus, started taking other higher math when I got to high school. And so then I got to college and was just like, well, I guess I take math classes. So spent some time, took like 17 math classes. They kicked me out with a degree, leave me the job.
[00:35:22.720] – Noah
And the guy that I used to beat at Settlers of Catan was the CTO of an internet startup. L ike I said, they were hiring people that could fog mirrors. So I got that job, and that’s where I discovered regular expressions are a thing. And it turns out, as far as I can tell, not a complicated thing, but that’s not the general consensus. And so I started developing analysis languages and command line protocols and all these things just started bubbling up. And I had a career all of a sudden. So that’s something that probably could have happened to me at any point in the previous decade and a half. But I just didn’t know that that was even an option.
[00:36:08.230] – Sean
Because I was smiling, watching you tell this story, the last three, four minutes, you should lead with that. That was fun. That was a lot of fun, actually, because it’s much different than any other story I heard, especially somebody’s youth, their interest in mathematics at a young age, and how it led up to your college education, then of course, getting a job in the tech industry. I would say lead with that. That was fun.
[00:36:34.070] – Noah
Okay.
[00:36:35.500] – Sean
Going back to the story lessons learned there. I think that’s awesome. But, but, Noah, this was a lot of fun. Thanks for diving into commodities. You’re doing some complex stuff here. I know our audience, they can’t really take massive action, but maybe they can understand commodities at a higher level, the complexity. And if they want to reach out to you and learn more, where can they reach you? Well, the.
[00:36:57.850] – Noah
Most direct way to get to me and the quickest is just send me an email, noahphealy@y ahoo. Com. Please connect me on LinkedIn if you’d like to follow my work. I post stuff to there, so just noah Healy there. And for this specific idea, if you’d like to learn more, I’ve got a website at c orddisc. Com. There’s some video you can watch to see the story of how it works. There’s the white button for the download. There’s other resources to learn more about game theory, market structure, that stuff. Cool.
[00:37:30.480] – Sean
All right, Noah, thanks for your time. Appreciate it.
[00:37:32.810] – Noah
Thank you.
[00:37:34.050] – Sean
Hey, I’d like to say thank you for checking out this podcast. I know there’s a lot of other podcasts you could be listening to, so thanks for spending some time with me. Also, if you have a moment, could you please head over to Apple podcast and leave a review. The more reviews we get, the more Apple will share this podcast with the world. So thanks for doing that. And last thing, if you do hear any stocks mentioned on this podcast, please keep in mind this podcast is for entertainment purposes only. Please do not make a buy or sell decision based solely on what you hear. All right, thanks for your time. Talk to you later. See you. Enjoyed this episode? if yes check out our previous episode on how to earn the returns of a hedge fund without the red tape with Bob Elliot