QAV 718 – Poifect!

QAV 718 Club

[00:00:00] Cameron: Bold Manners the widest with Paperboy, then Smart Deal El Rocco, as they reach the 300, Liberty State shown her head and Poifect is not going away. Poifect has claimed Liberty State and the favourites in trouble. Intrepid Eagle behind them from Hard to Cross and Zambaghini. Poifect kicked away with 100 metres to go.

[00:00:31] Cameron: Hard to cross back on the inside, Poifect, 3 quarters, hard to cross, Poifect, driven out, hands and heels, wins it, Poifect first from a head bobber, Intrepid Eagle, all hard to cross with Zamboghini in photos, then came Smart Deal, who’s run a race, behind them, Pay Per View Congratulations, TK.

[00:00:48] Tony: Thank you.

[00:00:50] Cameron: How exciting was that?

[00:00:52] Tony: it was very exciting. It was great. And she’s got a bright future, which is even more exciting.

[00:00:57] Cameron: That’s fantastic. So, uh, she escapes the dog food, uh, processing plant for one more week. Uh, what kind of a winning, you don’t have to give us specifics, but what kind of a winnings does an owner get out of a win like that? Is it like big celebration time or is it like, yeah, it’s all right. But you know, we’re not going to get that excited.

[00:01:18] Cameron: Yeah. Okay.

[00:01:18] Tony: Yeah, it’s all right. Pays the bills for a while.

[00:01:20] Cameron: Right. Tax free. I

[00:01:23] Tony: Uh, well, no, but it’s in the company, so

[00:01:27] Cameron: guess it’s not, it’s not gambling, right? When you own a horse, or is it?

[00:01:30] Tony: No, it’s a choice, not tax. Well, actually it is. If you were, if I had owned it in my own name, it’d be tax free. But I can’t deduct my losses, so I’ve learned a long time ago, you’re better off deducting your losses from running the business, and paying trainers and vets and all that kind of stuff, and paying tax on your winnings.

[00:01:47] Cameron: Right. Well, congratulations. That’s very exciting.

[00:01:50] Tony: you! Yeah, she’s, she will, she may head up to Queensland, so you may, um, you may see me up there if she gets into a good race up there.

[00:01:59] Cameron: Oh, fantastic. This is QAV, by the way, the investing podcast, not the horse racing podcast yet. Although if Tony has his way, that’ll, it’ll probably morph into that at some point. Episode 718, we’re recording this on the last day of April, 30th of April, 2024. And with us, with us in the studio is, uh, Matt Walker.

[00:02:21] Cameron: Welcome to QAV, Matt.

[00:02:25] Matt: you.

[00:02:25] Cameron: Where are you at? Where are you actually, Matt?

[00:02:28] Matt: I’m, I’m sitting in an office, um, in Box Hill in Melbourne. That’s where I work.

[00:02:34] Cameron: Box Hill.

[00:02:37] Cameron: Wow. You know, I, I’ll tell you, um, I used to work in Box Hill in the early 90s, like 93, 94, 95. And there was, uh, where the, where the little strip shops are there, they’re actually one of the first internet cafes in Melbourne in circa 90, 94. And I used to work just around the corner from that, and every lunchtime, I’d go to this internet cafe.

[00:03:05] Cameron: And I’d pay my five bucks for like 15 minutes and, uh, would be downloading, uh, Seinfeld scripts and Van Halen lyrics. I think they were the two things I was downloading onto a floppy disk that I’d take in and stick in their machine. Cause I was, I was convinced at the time, this internet thing’s too good to be true.

[00:03:27] Cameron: I was like, they’re going to shut this down. Now this is like, they can’t. There’s no way they can let people get this much information, like, for free. This is crazy. I’m going to, I’m going to download the entire internet while I can. And I was talking to Steve Sabatino on Futuristic last week about, I actually got a book downstairs, like a, Like a printed, published paperback book that’s about this thick.

[00:03:51] Cameron: It’s like the top 100 websites of 1994 or something like that, that you had to go to. There was only about 150 websites, so it wasn’t hard to be in the top hundred.

[00:04:02] Tony: It was an easy job putting that book out, wasn’t it? That’s

[00:04:06] Cameron: so Box Hill plays a, plays a, has a big place in my heart for that. That’s where I, that’s where I discovered the internet was in Box Hill.

[00:04:15] Cameron: And then I got a computer in 94 and then my internet built. 500 a month for dial up. I thought, uh, I can’t afford this because I was earning about 600 a month at the time. And, uh, I thought I’d better get a job at a, how can I get a job where the internet, I’ll get free internet? So I got a job at Aussie Mail, which was the first ISP in Australia as a sales guy and got free internet for a few years, which was good.

[00:04:41] Cameron: Anyway, enough about me. Welcome to the show again, Matt from, from Box Hill. So

[00:04:47] Matt: Yeah, I was gonna say, I don’t know

[00:04:48] Tony: lucky suburb, isn’t it, Matt?

[00:04:51] Matt: It, it could be considered that, yeah. It’s definitely, you said small set of shops, it’s definitely, um, not that anymore. I don’t know if you’ve been here

[00:04:59] Cameron: I haven’t been there for 20

[00:05:00] Cameron: years.

[00:05:01] Matt: skyscraper city. There is

[00:05:03] Cameron: Wow.

[00:05:04] Matt: 12, like, really big buildings.

[00:05:06] Matt: It’s really changed in the last 5 10 years, so. It’s not a cool place to be, it’s definitely

[00:05:10] Tony: and what’s the postcode in Box

[00:05:12] Tony: Hill?

[00:05:13] Matt: Oh, you 3 1 2 6 maybe?

[00:05:16] Tony: okay, I was gonna say it was 3888 or something like that.

[00:05:20] Matt: Ah,

[00:05:20] Tony: I think

[00:05:21] Matt: nah, not quite.

[00:05:22] Tony: I thought that’s why the Chinese like living there. It’s like E8.

[00:05:26] Matt: Yeah,

[00:05:27] Tony: that’s why there’s lots of high

[00:05:28] Tony: rises in Box Hill now.

[00:05:29] Cameron: Really? They’re like the eights? Well, Matt, um, we’ve, we’ve talked about you a lot on the show over the last, uh, couple of months because you’ve been doing some great work behind the scenes on this regression testing system and you kindly volunteered to come on and talk about a little bit. So first of all, thank you for everything you’ve been done.

[00:05:53] Cameron: You know, um, Matt just reached out to me out of the blue, I think towards the end of last year and said, Hey, my dad listens to the show and I’ve been listening to the show and I didn’t believe it. So I. Build a system to test it. holy hell, it kind of works. Um,

[00:06:08] Tony: How could you not believe someone who downloaded Seinfeld scripts in the 1990s

[00:06:13] Cameron: yeah,

[00:06:13] Tony: at a Box Hill Internet Cafe, right? Yeah.

[00:06:17] Matt: Well, I think there’s something to be said for the fact that there’s so much perhaps bad financial advice out there these days that it’s, I mean, it’s, it’s nothing against you guys. It’s more of just a general skepticism against, you know, I think probably, obviously you guys resonated with me a lot in the way you guys would.

[00:06:36] Matt: Talking about things, probably Tony, you know, like a very long, mature investing career. But even still, I think there’s a healthy dose of skepticism in me. I’ve got an engineering background. So, um, that, that need to test it definitely came up. Um, but yeah, I think I, I originally heard you guys talking about doing a bit of regression testing.

[00:06:57] Matt: And at the same time, I was sort of working on something and that was about the point where I was like, Oh, Maybe it would be good to reach out. And I think I can, at least, I don’t know, Tony, maybe you’ve looked at a few bits and pieces, but the feedback you guys are giving back to me has then been really useful to make it even better.

[00:07:09] Matt: So I think that was sort of the turning point on why I reached out in the first place.

[00:07:15] Cameron: Well, I’m glad you did. Uh, and you know, it’s been fantastic to work on it and also inspiring just to see somebody who can code. We’ve had a few guys code up different things, but, um, you coded yours in Python and sent it to me and I’d been doing a bit of Python. I was like, Oh, wow, if you could do this in Python, that’s amazing.

[00:07:34] Cameron: Like we could, we could probably get something up and running here as a result of this, that we can, we can make it work and we’re confident that it’s delivering the right result. We might be able to make it available to our subscribers at some point and, um, simplify their lives. But let’s, let’s talk about the regression testing system and, um, have a bit of a chat about where it’s at.

[00:07:56] Cameron: And, uh, you know, I’m sure Tony’s asked me a lot of questions about, where it’s at and how it’s working and you know what the next steps are that kind of stuff and you’ll be able to answer those better than me but uh before we hit you with a barrage of questions why don’t you tell us a little bit about yourself you said you’ve got an engineering background uh what’s what kind of engineering civil

[00:08:22] Cameron: Um,

[00:08:23] Matt: Um, electronics. So it’s, it’s very software adjacent. Um, so I dunno, the, the software is usable. It’s not definitely, um, you know, too. Like the most perfect piece of code by any stretch of the imagination. I carried out of a necessity, not so much as like perfection sort of thing. So, um, engineering electronics background, but yeah, a bit of software, which has been useful.

[00:08:48] Matt: Um, I don’t know, there’s not much to say about myself. Uh, I’ve had, I guess, a mixed career on investing so far. I’ve invested a few times in the past, based probably more on stories. Um, or things that have been told to me, um, which I suppose didn’t really make a lot of sense to me in hindsight. Um, so, sort of how I ended up a bit more interested in this space, um, yeah, away from that, electronics engineer, been working for five, six years, that sort of thing, in industry, um, working in a company doing, uh, medical instruments, uh, which is, it’s a cool space.

[00:09:23] Cameron: right so not a coder by profession but

[00:09:27] Cameron: obviously Have done some coding.

[00:09:30] Matt: Yes, pretty much.

[00:09:31] Cameron: And how long did it take you to, you know, before you reached out to me in December when you had a working system, how long had it taken you to put that together?

[00:09:39] Matt: I reckon I started the earliest, like somewhere earlier things back September, maybe a little bit even before that. And I sort of went through feverish sprints of working on it a lot or giving it up on it a bit when it wasn’t working and then coming back to it and back and forth. So it, it started off what should be quite a simple exercise.

[00:10:03] Matt: I think doing something like that in Excel, especially with. Like the data that’s coming out of Stock Doctor, I sort of thought, Oh, it won’t be that much harder. Um, but proved to be a little bit more tricky than I was expecting, which it has been interesting. So yeah, it’s definitely taken quite a bit of time to, to develop.

[00:10:23] Cameron: Yeah, right. Well, I appreciate it. So you sent me some notes about things you wanted to talk about. You want to start off with those and we’ll get into it?

[00:10:33] Matt: Yeah.

[00:10:34] Tony: Well, sorry, before, just before we do that, thanks, Matt, for your work. It’s amazing. But the overriding question I’ve got is, what stage is this regression tester at? How do we know it’s actually not full of bugs and it’s working correctly?

[00:10:49] Cameron: Oh,

[00:10:49] Matt: No, I think that’s a really good

[00:10:50] Cameron: it there, Tony. Well,

[00:10:53] Tony: Well, before we get into the results and what’s been tested, let’s

[00:10:56] Matt: yeah, yeah.

[00:10:56] Cameron: want to, buy him

[00:10:57] Tony: is it a moot discussion or

[00:10:58] Cameron: give him flowers, you know, just, okay.

[00:11:02] Matt: Um, yeah. I think it’s, it’s a really good question and it’s definitely one that, yeah, Cam, you mentioned beforehand. I think that’s part of the reason I, like, probably looking for a bit of help on that as well. So, I think, yeah, Cam’s done some spot checks on day to day and I’ve definitely done, hey, look at, You know, essentially in essence, it’s generating scorecards week to week historically, rather than like as a single once off week.

[00:11:31] Matt: So I have done instances of generating a scorecard from, you know, the regression tester and then comparing that with the results from a current one. Um, and those are really aligned. Uh, I think there’s probably, there’s a few things in three point upturn, not no uptrend. I think there is a little bit. Off in certain spots.

[00:11:55] Matt: Um, and then the other one is, I think, historical low P. E. There’s a slight difference in, uh, essentially how it treats negative P. E. s. Um, because I think Stock Doctor or other sites report, sometimes they don’t report if it’s a negative PE, it just reports it as blank. Um, so whether or not you’re comparing that as, well, you know, if you’ve got a 0.

[00:12:23] Matt: 1 PE, is that the lowest even though there’s been negatives? There’s a few little discrepancies. I think mine is trading at even if it’s a 0. 1 and it has been negative as the lowest because negative P’s are bad. So a 0. 1 P is still good, but there’s a few little discrepancies in there like that.

[00:12:37] Matt: Generally, scorecards, I say, are relatively close. Um, the second point is probably survivorship bias. So as you move back in time, it’s, to me, harder and harder to get delisted stock data. So the further you go back, you’re potentially missing Um, certain shares or certain share performances. Um, whether, again, whether or not it’s a good thing or a bad thing, it’s hard to tell.

[00:13:01] Matt: In theory, I think Cam, you mentioned that, in theory, you’re probably not looking, generally, value investing to buy shares that are, you know, just about to go bust. More likely ones that are just about to be acquired, which probably is more likely to be a positive, but it’s hard to say without having that data.

[00:13:19] Matt: And I think I’ve been doing some reworking recently to try and get more delisted stocks into the back side of it, but I still don’t think it’s perfect. I know there’s a data source called, the ASX references out to a company called delisted. com or something like that, and they actually have all the data for every stock that’s ever been, has been, um, so somewhere on my to do list is to go through and actually have a look, hey, you know, Back 10 15 years, do we, what percentage of the stocks do we actually have data on and is that playing into it?

[00:13:52] Matt: Um, so that one’s probably still a big one to check as well. Um, the third sort of thing I was thinking, which I haven’t done yet, but I was talking to Cam about before, is potentially looking at the dummy portfolio and the, what’s the other one? Dummy portfolio and light portfolio and running a simulation and seeing if The simulation would agree with all the buys and sells that Dummy Portfolio made, um, would be like sort of a third way to test.

[00:14:20] Matt: So yeah, we’ve definitely tested on a scorecard level. I don’t think I’ve tested so much on a longer time period scale, so that might be a next test to run to give better confidence. Um, probably though, I mean, Cam’s mentioned in the past, but the one major caveat with how this thing’s running is the What’s it called?

[00:14:42] Matt: Uh, Commodity Sales. So currently I haven’t coded in any commodity sales. Uh, I think purely out of a laziness basis at the start, at some point I did theorize that to some extent the, that data should be priced into the share, even if it is at a later point. So it’s only going to make performance. worse, if that makes sense.

[00:15:05] Matt: Um, so, you know, ideally you’re going to get a bottom end of the result, not give you like overinflated results. Um, again, something else to check, uh, or add potentially in the future. Um,

[00:15:20] Tony: So we have what, four or five years worth of scorecards now, so have you run yours and checked those against ours and got similar results. Have

[00:15:28] Tony: you?

[00:15:29] Matt: yeah, I haven’t done like a bulk run back of checking every single one, but I’ve done like Pull up a scorecard and check like an individual one that that’s relatively aligned. Um, and that, yeah, it took a bit of work just trying to get those actually tuned up. There’s a few, there’s a quite a few actually really interesting intricacies things when you get into that, um, that you really need to think about.

[00:15:51] Matt: So it’s, it’s, it’s been a really interesting exercise to definitely understand the investment strategy. Um, And I guess probably to back right up to the start, I guess, just thank you to you, Tony, for, I’m sure there’s a lot of people out there with similar sentiments, but for sharing like all this knowledge, I feel genuinely a lot more educated because of this podcast.

[00:16:10] Matt: Um, so I really appreciate it. I’m sure there’s many people

[00:16:12] Tony: Nah. Good on you. Thank you. Yeah, but that’s what the community’s for though, isn’t it? Like we’re gonna hopefully benefit from what you are doing so we can fine tune. The checklist. So, yeah.

[00:16:22] Matt: yeah, any other specific

[00:16:24] Tony: No, I don’t think so. I mean, I think the parallel run is probably going to be the best test and we’ve got sort of dummy portfolios and we’ve got scorecards going back to be able to parallel run those. So that’s probably the best, the best test. I think for what you’re saying, it’s pretty close. There’s a few discrepancies, but it’s reasonably similar or good enough to be a

[00:16:42] Tony: guide.

[00:16:43] Matt: Yeah. Isn’t it that you’d rather be roughly right than

[00:16:47] Tony: Correct. Yeah. 80 20 rule. Yeah.

[00:16:51] Cameron: Hmm.

[00:16:52] Matt: Um, yeah, I think probably the one other thing was in previous shows, I think you’d mentioned about ADT not being included. So ADT is included and it’s doing like the rule of like, you will only buy shares. If the share ADT is six times what the purchase price

[00:17:11] Tony: Yeah. Right.

[00:17:12] Matt: Off the top of my head. So that is actually baked in there.

[00:17:14] Matt: Um, but yeah, it’s just the caveats I just

[00:17:16] Cameron: Oh, okay. Yeah, right. Cause it’s not, it’s not an option in the GUI that she sent me, but it’s built, it’s coded in, right?

[00:17:24] Cameron: Hard

[00:17:25] Matt: It’s just hard baked.

[00:17:26] Cameron: Okay.

[00:17:27] Matt: I’d be hesitant to add that as a variable because you might, you know, Give yourself fake hope. I mean, I guess that that’s another part of this as well. Right? It assumes you can always buy at the market rate. Like there’s, there’s no looking into market depths of like, you know, was there a lot of sales on that day?

[00:17:45] Matt: I, it is looking at like the general volume traded each day. So it’s not buying on days where stocks are delisted, but it’s, It’s definitely not like looking at market depth, knowing what it could or couldn’t buy and how that actually impacts the market. It’s just a whole other world once you get into that level.

[00:18:02] Matt: So I think generally the rule of six times ADT I’m just using is yeah, the assumption that it has negligible impact on the market.

[00:18:10] Cameron: if I,

[00:18:10] Tony: what you’re saying, if you want to buy a parcel of shares, it has to be one sixth of the ADT

[00:18:15] Tony: available. Yep. Okay.

[00:18:17] Matt: least

[00:18:17] Cameron: if I wanted to limit the regression test to high ADT stocks, I just make the size of the initial capital outlay 10 million instead of 20, 000,

[00:18:30] Cameron: right?

[00:18:31] Matt: Yeah. Yeah. So you’ll notice that if you run it with like a million dollars or like 10, 000, it’ll be buying different

[00:18:36] Cameron: Yeah. Okay.

[00:18:37] Matt: the score cards it’s

[00:18:38] Matt: generating, the scorecards it has will have. Like all the stocks similar to how you guys do and then it’ll only buy from that if it meets um, yeah, essentially I think the only extra criteria at the moment it’s checking is ADT and like like I think it’s already that scorecard is already vetted down to ones that have a positive sentiment like 3ptl.

[00:19:02] Tony: Cool. Are you, are you handling dividends at all, or are you just looking at the capital

[00:19:06] Tony: appreciation?

[00:19:07] Matt: Yeah, I pretty quickly had to code dividends when I realized everything was just selling off 3 point trendline sales as soon as they paid out dividends or

[00:19:16] Matt: like, um, 10 percent stop losses. So, I was pretty happy to leave it till later and then it became a bit of a necessity. So, there’s a bit of magic in there about how it works and it makes a few little assumptions.

[00:19:29] Matt: I think it assumes that from the, I’ve got the dividend payment dates. Um, I think it assumes the dividend doesn’t get added to cash for like, I haven’t looked at the number in a while, it’s something like 2 or 3 months later, it doesn’t add the dividend for, and it keeps the value of that added in for 10 point, uh, 10 percent stop loss and 3 point trendline calculations for the next, you know, year.

[00:19:52] Matt: Three, two, I think it’s probably closer to two months. I tried to work out an average, but I need to run through the code to look at how long that actually is.

[00:20:00] Tony: Okay. It’s a little bit different to how we do it, but it’s probably not a big thing. Cause we, um, the, usually the stock goes down on its ex dividend date, and then you’ll get the payment a couple of months later on the dividend payment

[00:20:12] Tony: date.

[00:20:13] Matt: yeah, sorry. From the ex dividend date, it’s adding the dividend value to what you would check a 3PTL against or a 10 percent stop loss. So like if it’s paid, if it’s a hundred dollars stock and it’s paid 10, it’ll still count it as a hundred dollars worth of. Value.

[00:20:33] Tony: Okay.

[00:20:35] Cameron: And Matt, you have a function in there for doing a buy list for the present date, but we don’t have data in the system to enable that right yet. How hard is it going to be to take this and turn it into a, run a buy list for this week’s stocks thing?

[00:20:54] Matt: It’s, so there’s not many numbers that need to be resourced week to week. Um, it’s probably not far off, but at the moment, uh, it’s mostly about your data collection.

[00:21:10] Cameron: It’s, it’s looking at historic data, not current data.

[00:21:15] Matt: Yeah. So yeah, the process for me at the moment to get data takes a bit. So I don’t have that as like an online process. It’s all stored

[00:21:23] Cameron: Yeah.

[00:21:24] Matt: um, which is probably the key thing that would need to change.

[00:21:28] Cameron: I mentioned to you in an email the other day, I think I’ve just opened up a line of dialogue with the FinHub I don’t know, New York slash Vietnam. So, um, they’re, they’re really keen to help us out. So, um, I’ve, I’ve downloaded a couple of test datasets for

[00:21:45] Cameron: theirs and I’m just going through the process now of trying to map the typical data that we look at at Stock Doctor over to what they’re providing.

[00:21:55] Cameron: And I’m working with Andre Bravo, who’s a long time listener of my other podcast, also a long time QAV listener from Canada originally, but he’s, he’s been I think he’s in, where is he now? I think he’s in China. I can’t remember where he is at the moment. He’s anyway, he’s traveling. Might actually be in Vietnam.

[00:22:11] Cameron: He’s traveling all over the place anyway. Um, uh, and he’s been using FinHub to generate a buy list for himself, just looking at Canadian stocks. So, um, he’s happy to work with us to sort of figure out how to port the FinStub, FinHub stuff over too. So I’m hoping that it went not too far away from being able to go click a button, generate a buy list.

[00:22:37] Matt: Does it have all the data you would normally need?

[00:22:41] Cameron: I don’t know yet. I just downloaded a run yesterday and I’m just starting the mapping process over. So, you know, uh, give me, give me a week and I’ll have an

[00:22:50] Cameron: answer to that question.

[00:22:51] Matt: Yeah. Cool, nah, I’d definitely be interested to have a play around with it.

[00:22:56] Cameron: Good. So, um, you’ve, um, been doing some tests recently. Do you want to talk us through some of the things you’ve discovered with your own regression tests?

[00:23:10] Matt: Yeah, um, So I guess, probably, first thing is, at least one of the runs I did recently, uh, is in a fairly similar model to what you’ve been using, Cam. Um, was, uh, generally about back to 2006 to 2020. End of 2023 run. Um, I’m finding that at least there’s a good amount of delisted stocks back in 2020, early 2020s, uh, before, sorry, early two thousands.

[00:23:40] Matt: Before 2000. There’s a big dip out. Whether or not it’s just all stuff from before the.com bubble got wiped and or when sort of data sources came online. I’m not quite sure. So, um. Yeah, I guess probably all that to say that, yeah, as a base run, um, one portfolio, one sort of portfolio is performing at about 13.

[00:24:02] Matt: 3. Um, I think that was with like 100k starting cash. Um, and yeah, so 13. 3 percent CAGR. Sorry, I was just getting my notes up. Um, one interesting thing is just sort of, have you, actually, maybe I’ll share my, and I guess you can probably share Images afterwards, is that

[00:24:24] Cameron: Yeah, yeah, I’ll throw some stuff out. But just, uh, just to remind people when you say the 13. 3 CAGA, if those are the same dates that I’ve been running mine on, the STW CAGA over that time frame was about 2 percent for memory. So that’s the reference point for the 13. 3%.

[00:24:43] Cameron: That’s the

[00:24:44] Matt: Yeah, which I think was really interesting to me because there was such a discrepancy there and I wanted to try and work out where it actually happened, right? So graph I’ve got here is sort of trying to plot CAGR over time or it’s really just the last year’s worth of return rates. Um, and I mean, the other sort of idea I wanted to check was, Are we, like, is QAV outperforming the market consistently across time, or is it, like, beating it at certain points, which, like, really kills it, um, into, like, overdrive?

[00:25:21] Matt: Um, and yeah, I thought this was just quite an interesting graph, um, generally is fairly above the market rate across time, with probably a few points notably, um, sort of? Around here. So end of 20, uh, 20, 21 to 2022 seemed to be quite low. Again, maybe it was, this is a 20 stock portfolio, so it could just be one stock taking a dive if it was really heavily weighted.

[00:25:47] Matt: Um, but yeah, definitely interesting to see that it’s not just like one period of extreme growth. It seems to be fairly consistently above.

[00:25:56] Cameron: This is really, this is a really interesting graph, actually, because it does, so what we’re looking at, folks, is a graph that is comparing the S& P ASX 200 to the QAV regression test results. And what’s the, what’s the green one, Matt? QAV

[00:26:17] Cameron: 0. 28?

[00:26:18] Matt: green one is, is using a score of 0.2, um,

[00:26:23] Matt: and. Only having 8 stocks in the portfolio. So, 8 stocks is roughly, at least with 100k starting, what I found, like just manually checking to get enough buyers to actually get some performance going, otherwise it was just holding too much in cash because it couldn’t buy enough.

[00:26:42] Matt: So at the moment, it’s still buying like set size parcels to try and get up to a portfolio size. So interestingly, that one did outperform, um, mostly again, quite consistently. So I think that what that says to me is that if you can buy higher up on the buy list, do so, which is perhaps a little bit counter to what you’ve said, Tony, it’s sometimes that you’re happy to buy Lower down the list, which is interesting.

[00:27:08] Matt: Um, but again, this is maybe just one test. So brain or soul.

[00:27:12] Tony: Well, I don’t know if it’s a grain of salt, but there’s a, I mean, so the CAGR for that situation of H stocks and QAV score of cutoff of 0. 2 was 15. 9%. Yeah, versus the normal QAV, which was 13 point

[00:27:24] Tony: something.

[00:27:25] Matt: So it’s not substantial

[00:27:26] Tony: No, that’s right. But that, and the question I’ve got about that is whether that’s due to the QAV cutoff or due to having an H stock portfolio, because a concentrated portfolio over the longer term should get a better return.

[00:27:40] Tony: The larger the portfolio, the more it’s going to get. Go back towards the market index performance. So it could be, could be both. Could be a bit of each. I don’t know.

[00:27:49] Cameron: But I feel

[00:27:50] Tony: yeah.

[00:27:50] Matt: an interesting

[00:27:51] Tony: So it’d be good to, anyway, the way to test it is to have a QAV 0. 1 cutoff portfolio of eight stocks and compare it to a QAV 0. 2 cutoff of eight stocks and see the difference there.

[00:28:04] Cameron: Matt, I’m interested in looking at this chart. You’ve got the, so the blue dots are the regression test results, um, using our normal metrics, and the red is the ASX 200, like the STW, I’m assuming. And, um, so if, uh, It’s returning 2 percent CAGR over this time frame, as I mentioned before, versus the 13. 3 percent for the regression test.

[00:28:33] Cameron: When you look at the dots on the chart, there are times, like in 2007, 2010, 2017, 2020, when the QAV portfolio massively outperforms the ASX200. Uh, or significantly in some cases, massively in other cases, but the rest of the time, they seem to be much of a muchness, they’re sort of together, um, but when you see it here, and sometimes it underperforms, like in the last couple of years, which we’ve, we’ve experienced that too with our real portfolios, um, the light portfolios and our super portfolios in particular, but it’s interesting to see when you, when you lay it out visually, Over time, you can see that it is very spiky.

[00:29:18] Cameron: There are sometimes quite, you know, actually, outside of the last couple of years I don’t think there are many periods here where the QAV portfolio is underperformed. For a lot of the time they’re sort of hovering around each other, with the blue slightly on top of the red. But then several, you know, 1, 2, 3, 4 periods I’d count in this, what is it, like a 17 year period where the QAV portfolio significantly outperformed the index.

[00:29:54] Cameron: So it’s those four periods of time where most of the outperformance is gathered for four periods, probably of a year each, give or take over 17 years. Where the outperformance really comes from. Am I reading this right, Tony?

[00:30:16] Tony: Well, as far as I can tell, yeah, but I guess there’s some questions about what we’re seeing here. So what does each dot represent on the graph

[00:30:23] Tony: here?

[00:30:24] Matt: Yeah, so it’s If you, how the calculations done, is it saying, so take like a point at 2007, it’s saying where is the portfolio at right now compared to where it was a year ago. So looking at like the last year performance, I did think about doing an average over time, but I figured it would get too bogged down by the end of it.

[00:30:45] Matt: I wanted to keep something that was looking year to year. How is like the yearly performance doing? So just keep in mind when you’re looking at a point here, it’s the performance between 2006, 2000 to 2007.

[00:30:56] Tony: It’s a monthly rolling 12 month performance.

[00:31:00] Tony: Yeah, okay.

[00:31:01] Tony: so most of the time, and so the, the X axis is, that’s the CAGR. So for example, if I look at the very first column, the first red dot looks like it’s performed at about 2. 25 CAGR, is that

[00:31:18] Tony: right?

[00:31:19] Matt: yeah.

[00:31:20] Tony: But then there’s a green dot way above it, which is performed at 1.

[00:31:23] Tony: 8, 1. 9 percent CAGR.

[00:31:28] Tony: Is

[00:31:28] Matt: Oh, yeah, yeah, yeah.

[00:31:30] Cameron: Well, that’s six

[00:31:30] Tony: so that’s the yearly performance for that month, is that

[00:31:33] Tony: right?

[00:31:34] Matt: It’s the, it’s, I think it’s generating it based, I think each dot is in about a weekly cadence. Um, and it’s, yeah, it’s performance over the last year relative to that date.

[00:31:46] Tony: Okay. Because I would have expected to see some like. So the x axis is in percentage, I think, isn’t it? Is that the,

[00:31:55] Tony: that’s yearly CAGR from that date. So it’s labeled 0. 3, 0. 8, 1. 3, 1. 8, whatever it is. But if it’s a rolling 12 month CAGR, wouldn’t there be like 10 percent or 20 percent be the amounts we’d expect to

[00:32:12] Tony: see?

[00:32:13] Matt: Yeah, sorry. So to clarify, this is a run starting in 2006 and I’ve only started the yearly results from the first year into the simulation, if that makes sense. So there is a simulation that runs 2006, 2007. And then as soon as it gets to the end of the first year, It starts reporting on performance. So

[00:32:34] Tony: Yeah, no, I get that. I’m just, just trying to understand the graph. So I’m just pick, just pick a dot, say the first blue dot, for example. Which is the QAV performance, um, looks like the CAGR, the way I read this is it’s about 0. 5. Is that, that’s 0. 5 percent or is it

[00:32:51] Tony: 50%?

[00:32:52] Matt: Oh, sorry. 50%. Sorry. I do all my cagas in point form.

[00:32:57] Tony: Ah, okay. That makes

[00:32:58] Matt: would be a

[00:32:59] Matt: hundred percent. Sorry. Sorry. Sorry. Sorry. Yeah. So this is like, this is like. Extreme outperformance, where it’s, you know, a hundred percent, this is like below

[00:33:08] Matt: zero is. Yeah, Sorry, my bad.

[00:33:11] Tony: No, that’s all right. I’m understanding it better. Um, yeah, no, it’s, it’s, it’s a really interesting graph. Um, basically we’re seeing lots of, so we’ve got three colors. A red dot, which is the ASX, and is that the, um, ASX including dividends or just the ASX capital?

[00:33:27] Matt: Oh, it is a good point, actually. It might, I don’t know, it does, I suppose, question back, it might be a problem with how I’ve compared this. Does the ASX 200 normally include

[00:33:39] Tony: No, ASX JO, I think it is, includes dividends, and the STW, which is a code that accumulates dividends, does. If it’s ASX 200, it’s just the capital performance of the share market, with no dividends taken into

[00:33:55] Tony: account.

[00:33:56] Matt: Interesting. All right. Then we have to, something I’d have to double check which one I grabbed.

[00:34:00] Tony: Okay,

[00:34:01] Matt: can’t quite remember off the

[00:34:02] Tony: alright. But even so, like in that first year, for example, the red lines are all clustering around sort of, High 20s as the return for the ASX. This is in 2007 to 2008. QAV is clustering at about 80 percent and then the green which is QAV with 0. 2 is clustering, you know, way above that 1. 3, 1. 8. So nearly a doubling or a tripling of the capital over that 12 months. That’s how I’m reading it.

[00:34:34] Matt: Yep. Yep. Yeah.

[00:34:35] Tony: Yeah, so what we, what we’re seeing in this graph is a red line which continues to sort of go forward in the band of, uh, probably capping out at about 0. 3, so a 30 percent rise in some years and about a similar sort of drop in some, but probably around a 20 percent drawdown for the ASX Uh, the blue dots, which is the QAV normal current process, is oftentimes tracking the ASX, but in some years massively outperforming, and then using a QAV of 0.

[00:35:08] Tony: 2 is outperforming that, is how I’m reading this.

[00:35:12] Cameron: with an eight stock

[00:35:13] Matt: It’s a good

[00:35:14] Matt: summary.

[00:35:15] Tony: Okay.

[00:35:17] Cameron: Well, I tell you the big takeaway for me for this is how powerful graphing the comparisons or tracking the comparisons, you know, week to week. Um, or even if it was just month to month over a long period is, and then graphing those just to see where QAV, I mean, I know we’ve done yours, Tony, over whatever, 20 years side by side, um, but sort of making it a little bit more granular and graphing it out like this is, um, really interesting and really telling.

[00:35:48] Cameron: And, you know, I remember we’ve seen the same things with yours. Like it is, there’s been a couple of periods over the time where it massively outperforms and the rest of the time you just. Hanging in there waiting for one of those cycles to come around again, right?

[00:36:01] Tony: Yeah, because you just can’t predict when they’re going to come,

[00:36:06] Cameron: It’s kind of a

[00:36:07] Tony: or at least I haven’t been able to. Yeah,

[00:36:11] Tony: yeah.

[00:36:12] Matt: I think that’s something I’m definitely still coming to terms with, so I definitely don’t come from a finance background myself, so still a lot I’m learning, um, but yeah, I guess I probably what did pull these up to sort of think like, you know, is there anything, is there any like thing we can infer from different periods in time, like I know we’ve talked, or you guys have talked in the past about like value cycles or growth cycles, um, Yeah, but I guess it’s just, you can’t time the market or predict the market.

[00:36:43] Matt: So you just have to go along for the ride.

[00:36:45] Tony: Well, I mean, you could overlace a few things onto this. I know you’ve got a graph somewhere else of the market PE, so it’d be interesting to

[00:36:51] Tony: see.

[00:36:52] Matt: Hmm.

[00:36:53] Tony: An overlay on that. We’ve had listeners who talk about, um, using a three point trend line for the A SX. So it’d be interesting to overlay that and see if it’s a buyer or a sell, you know, during periods of outperformance or underperformance, there could be some.

[00:37:08] Tony: Benefits to doing that.

[00:37:11] Matt: That’s a really interesting point. Um,

[00:37:14] Tony: But yeah, I think, I mean, one of the things we probably need to do, Cam, is put a shout out out for anybody who does have a stats background to take a look at this and give us their input. And the person that comes to mind is Andrew Flitman, who helped us with one of the early spreadsheets in QAV, the Flitman model, um, who I think does have a stats background, so it’d be good to get someone’s input like that.

[00:37:37] Cameron: Yeah, I agree. Like I think, um, it’s, yeah, some very powerful stuff we can do once we have this data, get people that are smart to analyze it for us.

[00:37:50] Tony: because the first thing that comes to mind is we probably should run this, right, I’m going to use the term Monte Carlo simulation and listeners will know I’m pretty fast and loose with my stats terms, but what I mean is, you know, try and randomize the start dates and the portfolio sizes and things like that and just run the, just continuously run different simulations and see what the results are, the different time periods, different, you know, different starting dates, other variables that we can change and just try and get some some knowledge from

[00:38:20] Tony: that.

[00:38:20] Cameron: Mm.

[00:38:21] Matt: yeah, I very much agree. This is, yeah, I suppose a good caveat for this, that this is a one off instance. This isn’t a guarantee. This is a single situation and. Actually having the probability to prove that, you know, in any given situation, this is the performance you are likely to get or the band of which is a completely different exercise, which is, um, substantially harder.

[00:38:45] Matt: Um, but not out of the realms of possibility, but yeah, definitely someone with, yeah, a bit of maths and stats having all of this, but yeah, be

[00:38:53] Tony: There’s the other thing too, like we’re talking about a portfolio test which started in 2006 and you can see the very first significant deviation from the sort of normal trend line is GFC. Everything drops dramatically. Um, ASX does, QAV does, everything drops. If you start after the GFC, I’m sure you’re going to get a much higher tagger than whatever it was, 13.

[00:39:17] Tony: 5 or 15. 9.

[00:39:18] Cameron: Mm. Yeah. So starting at what, 2010, when things have recovered a

[00:39:23] Tony: Yeah, yeah.

[00:39:26] Cameron: Well, one of the great things about having Matt’s system available is it’s not that hard now to just run a whole series of regression tests with lots of different dates, right? We just plug in the start and end dates and off it goes.

[00:39:42] Matt: Yeah. You’ll be, you’ll be glad to know Cam I’ve actually set up now. So it’ll, it’ll queue up simulations. So if you put in one, click run, and then you can put in a new one, click run, and you just put in like 20, and then leave

[00:39:54] Matt: it to run overnight. Yeah, I know. When I started running a lot, I was like, nah, I gotta fix this, take two.

[00:40:00] Cameron: That’s very sexy. All right. Well, uh, what else, Matt, is there anything else you wanted to, uh, talk about vis a vis these things?

[00:40:12] Matt: I’ll quickly just maybe mention two more just as a quick thing. Um, one was I had an idea of trying to rotate the portfolio once a year, just try and buy from the top of the list, sell everything, um, not substantially different to the QAV model, I can’t remember what the exact percentage is, but it’s very much in the same ballpark, so, um, a good lesson might be any time to jump in is fine. Um, which yeah, I was, I guess I’ve always wondered, is it better, you know, is there always a better investment out there if you’ve been holding something for a long time and it’s not doing much, but it doesn’t seem there’s too much in it. It seems very, very similar. So, um, that’s my probably two cents from, from one other run.

[00:40:55] Tony: Yeah, that’s, no, that’s interesting, Matt, because you said, and your numbers back it up, that the QAV 0. 2 cutoff is a better performance than QAV is with a 0. 1 cutoff, which you think would bear out if you were selling the portfolio on a rotating basis and buying from the top, because you’re always buying towards the top rather than buying and holding for a while.

[00:41:17] Tony: So, it’s surprising that it didn’t show

[00:41:19] Tony: that.

[00:41:20] Matt: But this may still be buying some, like Sacristan might be buying some 0. 11s or some 0.

[00:41:25] Tony: Oh, I see.

[00:41:26] Matt: to fill out the portfolio

[00:41:27] Tony: is just the highest

[00:41:28] Matt: doesn’t guarantee that like, The one time it buys each year is the creme de la creme.

[00:41:32] Tony: What kind of portfolio construction rules do you have? Are you double buying? Are you just buying one stock and not adding to that position? What’s the

[00:41:39] Matt: One, yeah, only allowing one stock in the portfolio. I think the base is 20, but you can vary it to whatever you want. So yeah, 20 and you can only have one of each.

[00:41:50] Tony: Okay, so there are periods when you’re in cash, I guess, a bit, a fair bit then.

[00:41:54] Matt: It does happen. I did have a look at it actually, definitely around, you know, 2009 or, you know, seven to eight is like, It drops to almost like 10 in the portfolio in certain instances, but generally it’s staying up around 19. Like it’s pretty good at keeping it up and it has some rules as well that if you sold a stock and you’ve got extra cash.

[00:42:17] Matt: It goes to larger buying sizes and smaller buying sizes. You know, if you’ve really decreased your portfolio size, it’s a little bit rudimentary, but it, it does the job to keep the portfolio mostly filled up. And I mean, I guess you don’t want to, I really don’t want that situation. And it has happened in a few isolation tests where I’ve test isolated variables, but if you’re keeping things in cash, like, yeah, it’s just, you know, It’s not time in the market in that situation.

[00:42:41] Tony: Yeah, okay. Um, so, and are we able to play around with those kinds of rules? Like, you know, things I wanted to test are rules that involve, for example, pyramiding, which is what one of our interviewers suggested would help us. Like, so we buy double or triple if something’s going up. We increase our position along the way as well to benefit from that.

[00:43:04] Tony: Buying from the top you’ve covered, I guess. Portfolio size I think needs some work, whether we can play around with a one stock portfolio, a two stock portfolio, a four stock portfolio, different sorts of portfolios and see if that changes results. I think it probably will. Yeah, and whether you test the QAV at 0.

[00:43:25] Tony: 2, but whether we should go the other way as well and put the QAV down to 0. 05, for example, and see if that works. makes a difference because I know from time to time I can’t find anything to buy but there are some big stocks below the cutoff of 0. 1 which are pretty tempting from time to time to buy.

[00:43:40] Cameron: I did,

[00:43:41] Matt: Yeah.

[00:43:42] Cameron: I did do that, didn’t I, Tony? I did that like last week.

[00:43:45] Tony: Did you go below 0. 0, 0. 1 sorry?

[00:43:48] Cameron: I did, yeah, let me, um, uh, hold on, let me see, I did, uh, 0. 05, yeah, and it delivered 13. 86, um, versus, uh, 0. 2, which delivered 14. 91. So, and the stock standard was What’s the standard one here? I think this is the standard one, which was, um, 12. 8. So 0. 05 was better. 0. 2 was even better than that. And remember then I went to 0.

[00:44:31] Cameron: 3 thinking, well, if 0. 2 is good,

[00:44:33] Tony: Yeah,

[00:44:34] Cameron: 3, no, 0. 3, it dropped down to 9. 2%. So, but yeah, the

[00:44:38] Cameron: point

[00:44:39] Tony: buy enough stocks.

[00:44:40] Cameron: probably, yeah. But the 0. 05 did okay, but not as good as 0. 2.

[00:44:46] Tony: Yeah, but what it says is that if we can’t find stocks at point two, it’s not too bad to drop down the list

[00:44:51] Cameron: Yeah. Right.

[00:44:52] Tony: something, rather than sitting cash, yeah, because like whatever it is, 12 percent or 13%, it’s still better than cash at the bank, right, so you’re better off being invested

[00:45:02] Cameron: uh huh.

[00:45:03] Tony: and lowering the cutoff, okay. Um, yeah, and there’s whole heaps of other variables like that, Matthew, like whether um, uh, we cut off our PropCaf at seven times, but whether ten times is better, or whether five times is better, or whether a hundred times is better.

[00:45:21] Tony: So it’s playing around with all these metrics and trying to get a feel for Is the cutoff right?

[00:45:26] Tony: And what do we gain or lose by varying it?

[00:45:30] Matt: Yeah. For sure. Um, yeah, the, the pyramid one sounds quite interesting. I was definitely, I’m actually listening to, I think it’s the Intelligent Investor at the moment by Benjamin Graham. And he’s, I just was thinking that, yeah, dollar cost averaging or like You know, how people generally invest in QAV. I don’t know what your listener base is generally like, but I assume there are some at least who will be doing that, like adding to the portfolio at a more consistent basis based on, you know, maybe having disposable income as they go along, or at least it’s probably more my situation.

[00:46:02] Matt: Um, but yeah, I’d be interested to build that in as well, where you’re more like adding costs, adding in as you go, um, or waiting, I think as well, like even, yeah, waiting. I can’t remember which graph I was talking about it for, but there’s also like, uh, Kelly criteria or

[00:46:20] Tony: Yeah, I love the Kelly

[00:46:21] Matt: a bit more certainly on the stocks you’re more sure on, which I mean, QAV score is almost like that, right?

[00:46:28] Matt: I look at the higher stocks as having, you know, better quality, better price. Um, certainly. Perhaps a more probable outcome, not necessarily,

[00:46:37] Tony: you’re right. So for listeners, the Kelly Criterion says we should put more money when we have a better chance of, a better edge is the term, a better chance of success. So we, yeah, if 0. 2 is a better score than 0. 1, then we should definitely be putting more, more investments into 0. 2 stocks than 0. 1 stocks.

[00:46:56] Tony: And the question then is how Well, not necessarily doubling because Kelly Criteria talks about edge over odds. That’s the way you calculate it. So what’s the edge of buying a QAV 0. 2 portfolio versus a 0. 1? It sounds like it’s about 2%. So, and then what’s the odds? Um, the odds is the return of 15%. So you put 15 over 2, and that’s what you should be putting into the stocks, which are above, um, 0.

[00:47:20] Tony: 2.

[00:47:22] Cameron: and,

[00:47:22] Tony: that’s how Kelly works.

[00:47:23] Cameron: and how, and what does that mean in English?

[00:47:30] Tony: Well, if you have a, if you have a hundred dollars doing

[00:47:32] Cameron: Klingon to me, Tony.

[00:47:35] Tony: I could pull out my textbook on Kelly Criteria if you like, it’s a wonderful stats read. It’s a wonderful stats read. Um, and, and, it’s, it’s a great topic, I love it. Uh, so, okay, if you’ve got 100 to invest, how much do you put into each stock? So, um, you should put more into the ones that are going to return you the most.

[00:47:55] Tony: And so, if we say the return is the CAGR, And then we say, how much is stocks with a QAV score of 0. 2 returning better than QAV scores of 0. 1? That difference is the edge. So you put the edge over the return. So, roughly speaking, I think Matt said before, a portfolio with QAV. 2 or better return 15. 5 percent and the normal one return 13.

[00:48:21] Tony: 5%. So it’s a 2 percent edge. So, um, we should be putting 2 percent over 15%, which is going to be what, 7%, um, into our purchases for QAV. The portfolio with QAV 0. 2 or better, and then we should be putting less into the 0. 1 scores, which would be, well it’s actually going to be, um, we’ll say there’s no edge there, so you shouldn’t put any in really, but, um, you’ll, I’d have to sit down with a pen and paper and work it out, you put less into those, in the portfolio 0.

[00:48:53] Tony: 1, um, scores.

[00:48:55] Matt: The thing we probably actually need to do is again, like this is a one off run, so it’s, it’s not exactly probabilities, but yeah. Ah,

[00:49:02] Tony: Matt, I’ve worked out the edge wrong, the edge is how much it beats the, the ASX. Yep. Yeah. So it’s, it’s, it’s the outperformance of the ASX over a 2 percent difference in buying 0. 2 stocks versus 0. 1 stocks. But there’s still a case to put some money into the 0. 1 stocks. It’s just less.

[00:49:25] Matt: interesting as well, cause I think we’d actually have to calculate. Like the, the 13. 3 percent is for stocks that are in 0. 1 to 0. 2 and above 0. 2 as well. Like the above

[00:49:36] Matt: 0. 1 still

[00:49:37] Matt: includes 0. 2s. So we’d need to run a specific run of how the 0. 2 is actually specifically performing, which is a very interesting activity nonetheless, I think would be.

[00:49:47] Matt: Might have to play around with that. Sounds cool.

[00:49:48] Tony: we should do a podcast on edge over odds at some stage, Cameron. It’s a really fascinating part of investing.

[00:49:55] Cameron: Well, we did do a Kelly Criterion episode a long time ago, but

[00:49:58] Tony: Oh, okay. We’ve done it already.

[00:49:59] Cameron: it. Yeah.

[00:50:01] Tony: Same.

[00:50:01] Cameron: I’ve

[00:50:01] Cameron: forgotten everything about

[00:50:02] Matt: might need to go back and listen to it. I was going

[00:50:05] Cameron: well, look, I tell you the, the. The main takeaway from me out of all of this, Matt, is just, I mean, how exciting it is when we can apply even higher degrees of science to testing all of these scenarios, which is, you know, something that Tony’s been, um, doing saying he wanted to do for the last five years, um, and you’ve brought us, uh, massively closer to being able to test this stuff and play around with it and see what this variable does and that variable so we can be pushing the envelope with all of this stuff.

[00:50:40] Cameron: So very, very exciting stuff. I feel like a complete nerd looking at this stuff.

[00:50:47] Tony: Welcome to my world. Because I’ve been, yeah, because I spent a fair bit of money trying to get this to this kind of level and this is great. Can I jump ahead? There’s a graph you sent me called QAV isolated metrics.

[00:51:00] Cameron: Yeah, I wanted to ask that one too.

[00:51:02] Tony: Matt? Yeah, but I was kind of struggling to read it and I wanted to double check. It’s all, um, I know people can’t see this, but it’s all color coded and I just want to get the colors right to what they pertain

[00:51:12] Matt: a, it’s an absolute mess. I spent, I reckon, two hours the other day just trying to get something like, that would look half nice with this mini metrics. Gave up in the end and just ended up generating as well, like 20 separate graphs. So it was

[00:51:27] Matt: actually, so apologies for

[00:51:29] Tony: no, that’s all right. I wonder if these graphs would look better just as like we’re used to seeing like a monthly, um,

[00:51:37] Cameron: The

[00:51:37] Tony: line graph rather than the dot plot. Yeah,

[00:51:40] Matt: Yeah, I Admission is that there’s some weird anomalies still in the data where it will still report the portfolio value, say on like a public holiday, and it reports it as being like practically nothing just because of the way the pricing data works. So though, so if you look at, I don’t know, the isolated metrics graph, you see all those dots down low on from about 2017.

[00:52:06] Matt: Um, It must be that the price of data only goes that way. So I, being lazy and not actually filtering my data out, I just did dot graphs, but it’s a fair comment.

[00:52:17] Tony: No, that’s fine. So we’ve got a graph here, uh, since 2006 of isolated metrics and their performance. Maybe just take us through that. What’s the orange and the purple?

[00:52:26] Tony: that have

[00:52:27] Matt: So

[00:52:27] Matt: the orange is the, it’s essentially what the consensus share price is. So looking at that one.

[00:52:36] Tony: So if the share price is currently below consensus forecast

[00:52:40] Matt: Yes, correct.

[00:52:41] Tony: that’s interesting. That’s, that’s the most important metric. Is

[00:52:44] Tony: it?

[00:52:45] Matt: Well, I guess probably the thing to say again with this one is it is only one run. So I am noticing that, like, I’ve done one of these runs in the past, and I think Cam, you’ve done them as well. They seem to be varying what comes up a little bit. So I am wondering if this one needs a little bit more, like, adjustment for portfolio sizes, like larger and smaller portfolios, different time periods.

[00:53:07] Matt: So we’ll caveat all that with saying that, um, yeah, I’m not, like, Yeah, I think there probably needs to be a bit more of a probability approach to the isolated metrics is the takeaway. But in this instance, that was, that was the case, the consensus, the consensus target.

[00:53:24] Tony: reason why it surprises me is because one of my criticisms of using that metric and I put it in is that, you know, something like 70 percent of stocks are always less than the consensus forecast because stock brokers put together the forecast and I want you to buy the stock. So it’s, it’s, it’s hard to, it’s hard to, it’s almost like the whole market is going to be in that test.

[00:53:45] Matt: Which I guess probably keep in mind as well here. So when we are isolating the metrics, it’s the isolated metric as essentially the quality score. Um, so you still have three, it’s still trading on three point trend lines and it’s still trading on like, The division by the price to cash flow. So you still like price to cash flow still is an important part of each one of these runs.

[00:54:09] Matt: And so is the like three point trend lines. Um, I could, I, I guess I probably don’t even know where to start trying to code out three point trend lines because it’s like, when do you buy or sell? I guess just based on that, but here, yeah, they are still part of it. So it’s, it’s the combination of those two factors plus the isolation variable.

[00:54:30] Tony: Um, cause I think the more interesting question about consensus forecast is what’s the performance for stocks that don’t have one. Because my experience is they tend to outperform because we’re kind of ahead of the curve and they’re undiscovered in terms of the valuation until, you know, fund manager comes along or the stock broker comes along and gets interested in them.

[00:54:49] Cameron: So, looking at stocks, like, with all of the other metrics, but just leaving out consensus forecast?

[00:54:57] Tony: No, um, only include those stocks along with all the other metrics, but, but the ones that don’t have a consensus forecast.

[00:55:03] Cameron: Yeah. So all the normal metrics, but they don’t have a consensus forecast. And they’re measuring that against the normal

[00:55:13] Tony: Normal QAV.

[00:55:14] Tony: Yeah.

[00:55:14] Cameron: Yeah. Right. I was just looking at my regression testing list. I haven’t actually isolated a consensus. Um, I didn’t get to, I haven’t got to that

[00:55:24] Cameron: one yet. So that’s interesting.

[00:55:25] Matt: So it could be in line

[00:55:26] Tony: So the question that begs for me is, is that normal QAV? Because like, I think something like 70 or 80 percent of stocks are going to have a price less than consensus forecast. You’re almost including the whole universe in this

[00:55:39] Tony: test.

[00:55:40] Matt: Yeah, quite possible. Um, which, well, yeah, a whole universe still with highest price to cash flow

[00:55:48] Tony: Gotcha. Yep. Yep.

[00:55:50] Matt: maybe a three point

[00:55:50] Tony: Okay. It’s interesting

[00:55:51] Tony: though.

[00:55:52] Matt: Yeah.

[00:55:52] Tony: And what’s the, so that’s one of them. There’s another metric which is doing a similar sort of return high

[00:55:56] Tony: up.

[00:55:57] Matt: So it’s, it’s wittily one that I was not convinced on in the past, but, uh, Record Low PE, um, happened to shoot the lights out on this one, um, as well, which is definitely interesting. When in the past, I hadn’t had the. Best results with this one, but in this instance, it, yeah, again, seems to have done really well, uh,

[00:56:20] Tony: It doesn’t surprise me again because uh, if it’s got a low, if it’s got a low prop calf, it probably has a low PE

[00:56:26] Cameron: Well, it’s interesting. I, I have tested both of those. I’ve isolated Record Low PE and PropCaf and they came out very close. Record Low PE came out at 10. 9. PropCaf came out at. 11. 4, 11. 5. Um, but you know, that’s like, they’re halfway through my rankings that go up to 14. 9 for the TK special. It’s like a Saturday night, like a Saturday night special, but, uh,

[00:56:54] Tony: Yeah.

[00:56:55] Matt: Yeah, I guess record low PE for me, though. I was just interested that, like, like, it might still not have a good PE, if that makes sense. Like, the PE still may be extremely high. It may just have the lowest PE it’s had. Um, I guess you’ve still got that division by the, the price to, price to cash flow. So there is still that value element included.

[00:57:16] Tony: Yeah. Okay. Although, if something has a high PE and it’s divided by a low prop calf, it’s gonna get a good score, isn’t it, under this scenario.

[00:57:24] Matt: Uh,

[00:57:26] Tony: Whereas we want something with a low PE and the low prop calf. So if something has a low pe Sorry, is it, are you just giving it a one and then dividing it by the prop calf?

[00:57:33] Matt: so this is, this is record low, record low P. E. is if it’s had the lowest P. E. in the last

[00:57:41] Tony: Yeah. Three

[00:57:42] Tony: years, six halves.

[00:57:43] Matt: yeah, uh, three, uh, yeah, whatever

[00:57:45] Tony: Yeah, but when it comes to scoring it, are you just giving all of those stocks that meet that criteria a 1, I think we give it a 2 actually, a 2,

[00:57:53] Matt: Uh, I, sorry, it, it, it will, it will have a 2, so it’ll be 2 divided by 1, which is then multiplied, yeah, so yeah, it could probably have a 1 just when you’re isolating it, but I just tend to, to use the same scores, so, I mean, anything that’s got a 0 will just have a 0 QAV score,

[00:58:09] Tony: Yeah, right. Which could be a

[00:58:10] Matt: only

[00:58:10] Matt: buying things that meet that criteria.

[00:58:12] Tony: okay. So we’re eliminating some stocks that way. Okay. Well, very

[00:58:17] Tony: interesting.

[00:58:18] Matt: Hmm, indeed.

[00:58:20] Tony: when can I get my hands on this to play around with all these different variables and tests?

[00:58:25] Matt: You’re welcome to have it as of right now, there’s probably I don’t know how many little weird intricacies there are. Cam can probably tell you more about what they are than me because I don’t see them anymore. Um, but it, it, I’m pretty much happy to give you a copy of it if you want to muck around with it.

[00:58:41] Tony: Yeah, cool.

[00:58:42] Cameron: just have to get Python up and running on your Mac first, Tony. I, I’ve been, I’ve been, I’ve been Trying to get Tony to install a new microphone for about a year, Matt. And he can’t do that. So the idea of Tony getting Python up and running on his Mac to run this, I’m like, Oh God, this is,

[00:58:58] Matt: you

[00:58:58] Tony: okay, I know who to call.

[00:59:00] Cameron: yeah,

[00:59:01] Matt: just to clarify, you actually won’t need Python. So I’ve got, um, the way I’ve got it compiled, I think originally I tried to get you going with Python, but I think there’s so many different like dependencies of packages and having the exact right versions and stuff that in the end I’ve actually booted up my wife’s very old Mac book and compiled it on Mac.

[00:59:22] Matt: So it’s now a compiled version. You should just be able to run it. You have to run it for the command line weirdly, but other than that, you should just

[00:59:27] Cameron: he’ll have to open up Terminal and cd through to the directory and then

[00:59:31] Cameron: run it, so I don’t

[00:59:31] Matt: You will have to do that.

[00:59:33] Cameron: I could probably walk him through that. Yeah, well, I can, I can send you the version that I’ve got, Tony. I’ll give you a folder to download that Matt has sent me and I can walk you through it and you can play around with it to your heart’s content.

[00:59:49] Tony: Beautiful, thank you.

[00:59:51] Matt: Sounds good.

[00:59:51] Cameron: And I’m gonna, I’m gonna, uh, start running an isolated, um, uh, consensus test in a minute on mine. I just booted mine up. Ha ha. So, actually, price less than consensus, I did, I must have done that. It’s like one of the first things in the, yeah. No, it’s not on my list. Okay. I must’ve skipped it. Thought, ah, that won’t be any good.

[01:00:17] Cameron: All right.

[01:00:18] Tony: Sorry, before we go, on that graph, what’s the worst metric there that hasn’t given us much

[01:00:23] Tony: performance at all?

[01:00:24] Matt: I think it’s a slight, I did probably mention it in the email, but I think star and, to caveat, it’s because it struggled to make buys. So I had everything still at a 20. Um, stock

[01:00:38] Tony: Yeah, right,

[01:00:39] Tony: okay.

[01:00:39] Matt: and it just, it was just struggling to buy anything. So it was really just sitting in cash while everything shoots off.

[01:00:45] Matt: Um, and it will occasionally get buys, but I probably could tailor them a little bit more, just like tailor down how many shares it’s buying, um, to do it. Uh, but I haven’t as of right now.

[01:00:56] Tony: So if I run this code, will I get the actual buy lists that are generated each week?

[01:01:00] Tony: Is that, do they get

[01:01:01] Matt: Uh,

[01:01:02] Tony: into a folder or

[01:01:03] Tony: something?

[01:01:03] Matt: It’ll generate them into like Excel. It generates them in some other random file that you don’t need to worry about, but it also spits out an Excel version. So you’d be able to look at it

[01:01:12] Tony: Yeah, cool.

[01:01:13] Matt: compare the results. And then it, the simulation results also dump into Excel. So they’re human readable.

[01:01:18] Tony: Yeah. Okay. Cause I think one of the things I’d like to test is, um, is, you know, we talked about buying and selling methodologies, but, but like even just a buy and hold, how does it compare to a buy and hold strategy? I don’t know if you can do that through your testing, but we can probably do it if we take a buy list and then see how those stocks perform over time.

[01:01:40] Matt: possible. I think there’s quite a few, there has been a few tests I’ve run where I’ve just manually coded something

[01:01:45] Tony: Yeah, right.

[01:01:46] Matt: exposing GUIs a little bit more work, um, but it’s definitely doable. Um,

[01:01:52] Tony: on the weekend was, um, going back for as far as we have buy lists, so four or five years, and taking the first stock on the buy list that had an ADT threshold that was useful to me, and was the highest up, so it had to be at least 0. 2, so you couldn’t do it every week, but some weeks, and just holding on to it and seeing how it worked out.

[01:02:13] Tony: And it was, it was outperforming just for the last couple of years. Which kind of is what we, you know, would expect because we know that we’ve been, not so much this year, but in last year we were cycling a lot through trades, um, so buy and hold might work better, which makes me interested to see going back to 2006, if you buy and hold, how that would work.

[01:02:34] Matt: yeah, it is. I mean, it’s. Yeah, be interesting to see. It’s funny, right, because 10 years down the line, it may not have a particularly good QAV score anymore.

[01:02:45] Tony: Right,

[01:02:45] Matt: Oh, it just would be interesting to see what the result is. Yeah, it’s

[01:02:48] Tony: have gone up a lot too, so yeah.

[01:02:50] Matt: yeah. absolutely.

[01:02:53] Tony: Because that’s the question, is the QAV score relevant? I’ve never found the QAV score relevant to selling, right? So something can, I’ve had stocks before which are on the buy list and they go off the buy list because their share price is rising, but it keeps on rising, right? So if you said, I haven’t been able to develop a rule which buy at above 0.

[01:03:11] Tony: 1 and then sell when it gets, you know, below 0. 01 or whatever the

[01:03:17] Tony: number is.

[01:03:18] Matt: Yeah, okay.

[01:03:19] Tony: Yeah, so, um, it’s, the question is then, how does a buy and hold compare? And how much risk are we taking on for that?

[01:03:27] Matt: Interesting.

[01:03:29] Cameron: all right, Matt. Well, we’ve got other stuff we need to talk about. Do you want to stick around for the rest of the show? And, uh, do you want to hang in there or do you have to go and like, earn a living? All

[01:03:39] Matt: I probably should go and earn a living. will be listening to the podcast, though, so I’ll hear what you’re talking about regardless.

[01:03:46] Cameron: right. Well,

[01:03:47] Tony: great. Well, thank you. Thank you for your hard work. It’s brilliant.

[01:03:52] Matt: No worries. Thanks for having me on, guys. I appreciate it.

[01:03:54] Cameron: thank you, Matt. Appreciate it, mate. Take care.

[01:03:57] Matt: You too. See you guys.

[01:03:59] Tony: Yeah, so good.

[01:04:01] Cameron: Yeah,

[01:04:01] Tony: How talented.

[01:04:02] Cameron: Yeah. What a, what a clever guy.

[01:04:05] Tony: Yeah,

[01:04:07] Cameron: I wish I was that clever. Um, all right,

[01:04:10] Cameron: Tony.

[01:04:11] Tony: to be, you know people who are that clever.

[01:04:13] Cameron: Yeah. I’m Henry Fording my

[01:04:14] Tony: next best thing. Yeah.

[01:04:18] Cameron: All right, well, let’s get on with the rest of the show, Tony. We’re already over an hour, but, um, I didn’t have much to talk about today. Stock Doctor’s still broken, um, so I’m not even bothering sending out our buy list this week because I think our buy list isn’t worth the, uh, paper that it’s written on.

[01:04:36] Cameron: Uh,

[01:04:37] Tony: Well, we can talk about this off air if you like, but there is a bit of an audit check in the buy list, the master spreadsheet anyway. Because Stock Doctor, when we do a download, gives us their PropCaf. And then we calculate ours manually. And the difference is they use a different number of shares on issue to what we use.

[01:04:59] Tony: Um, and there was a column in the, in the spreadsheet, which gives us the difference. And what I found is that there’s probably three or four companies on the buy list this week, which have massive differences between Stock Doctor’s PropCaf and our PropCaf. Um, but the rest look okay. So

[01:05:17] Cameron: okay,

[01:05:18] Tony: people can check that themselves, I guess, in the buy list, if they’re doing their own downloads.

[01:05:22] Cameron: okay, um, all right, well, with that caveat, I’ll shoot it out this week and people can have a look at it. I’m just, you know, I, I, I, the.

[01:05:31] Tony: the first three on the buy list were wrong.

[01:05:33] Cameron: so I checked those three and went, ah, this is broken. Not looking at, no point looking at it anymore. Um, they are aware

[01:05:39] Cameron: of

[01:05:40] Tony: more, which was 360, which is a growth company, which was on there as well, further down the buy list, looked wrong as well. Yeah.

[01:05:49] Cameron: aware of it, he’s looking into it, um, but, you know, I brought this to their attention at the beginning of last week when I discovered it. They fixed the couple that I found last week, but then there are more showing up this week. You would have thought that they would have done a complete Review and Audit, um, which apparently they haven’t in the weekend.

[01:06:08] Cameron: I don’t know. People are paying through the nose for access to this data. You would think they’d be, at least as I said to him yesterday, I think you should be sending an email out to your subscribers saying, Hey, uh, the data’s, uh, got some problems. Be careful what you’re investing in, but I haven’t seen any email come through.

[01:06:25] Cameron: So, um, you

[01:06:27] Tony: Well, I’m not sure if it’s a data problem or if it’s a stock filter problem. Like I said, it’s, um, it’s when PropCaf, it looks much more reasonable compared to the one we calculate manually because it, because of the shares on issue.

[01:06:41] Cameron: What do you mean a stock filter problem?

[01:06:44] Tony: Uh, so let me just give an example here. So Schaefer Corporation is the one, is one that’s, um, looks like it’s wrong. And Stock Doctor’s price to cash flow using their calculation, which uses shares outstanding, uh, is. Let’s go look this up, hang on, financial trend, price to cash, 6. 11, and then when we do it, that calculation manually, we get a, uh, PropCaf of zero, and then in the column to the right of PriceToOperateInCashFlow, so I call them AI in my spreadsheet, is um, saying it’s out by like 136, 000%. So that’s what I’m using as the audit check. So I think it could be a data problem, but it could also be that um, that they’re, they’re doing some calculation behind the scenes which is working for them, um, and not for us in the filter process.

[01:07:47] Cameron: But if I go and have, the ones that I’ve picked up, like the first few and the buy list, when I go and look at their financials in their system, they’re wrong.

[01:07:57] Tony: Oh okay, so you’ve checked the data, have you?

[01:07:59] Tony: Okay. Yeah,

[01:08:00] Cameron: yeah yeah yeah yeah.

[01:08:02] Cameron: I,

[01:08:02] Tony: interesting then, if that’s wrong, that they get a PropCaf, which looks reasonable when it

[01:08:06] Tony: gets downloaded.

[01:08:07] Cameron: where are they getting their propcaf from if the, if the

[01:08:11] Tony: Don’t know.

[01:08:12] Cameron: Outstanding figures as well. Yeah, so what I’ve been doing when I, when I look at one that looks, when I see a stock like SFC turn up, the first thing I’ll do is go to Stock Doctor, look at what, into their actual website, have a look in their financials and see what the, um, shares outstanding is, and when there’s been a, when it’s gone from like, Two and a half million, billion shares outstanding last month to 12 this month.

[01:08:36] Cameron: I’m like, okay, yeah, that’s probably an issue. And then I go to the ASX and check to see what they’ve got listed and, and just to make sure. But, um,

[01:08:45] Tony: Okay.

[01:08:46] Cameron: yeah, so, uh, anyway. People can do that comparison just to try and pick up the ones where there might be anomalies, but just be really careful, folks out there.

[01:08:59] Cameron: Uh, well, the only other thing I had to talk about is Nick Scali in the news.

[01:09:03] Tony: Mm hmm.

[01:09:04] Cameron: Nick Scali mounts UK push, realizing long held dream in the financial review. Harry LaFrenz. Is the uh, reporter Nick Scali is acquiring a specialty UK home furniture retailer to break into the British market and rebrand the business in its own name, taking its successful model global.

[01:09:22] Cameron: For the first time, the retailer flagged an equity raising of up to $60 million to fund the purchase of Anglia Home Furnishings, which trade trades as fab furniture. It was founded in 1979 as a co op and later owned by a property company, FAB’s 21 stores are in retail parks across the UK. We’re big fans of Nick Scali, uh, here, what do you think of this story?

[01:09:48] Cameron: A good thing? Red flag? Raising the money? Or not in this case because they’re spending it to buy something. Mm, mm,

[01:09:55] Tony: It’s so hard to say, isn’t it? I mean, when I first read the story, I thought, oh, not another Australian company trying to, especially retail companies, trying to buy something in the UK. We haven’t had a, as a country, a successful track record. Most notably when Bunnings tried to do it in the UK and couldn’t pull it off.

[01:10:13] Tony: So, um, having said that, if anyone can do it, someone like Anthony Scali could, because he’s run Nick Scali so well.

[01:10:20] Cameron: mm,

[01:10:21] Tony: um, good luck to them. It’s not raising a red flag to me, um, at this stage. And it’s, uh, there’s a capital raising, so people know to read the documents and check what the dilution is and can pair the offering.

[01:10:35] Tony: Now the price that they’re being offered shares at to the current share price and make sure they’re not paying more than what they can buy the shares on market for because, um, generally they’ll come out of a trading halt and the market, the share price will adjust for the share raising. Uh, so yeah, do the normal sort of capital raising tests, um, but yeah, it doesn’t raise a red flag for me.

[01:10:55] Tony: I’m just, I am a little bit skeptical of retailers trying to buy into the UK market though. I can’t think of any that’s done it successfully.

[01:11:01] Cameron: mm, yeah, why, why is that? I mean we’ve talked about this in the past, um, the struggle that Australian businesses have when they do that kind of expansion. It’s

[01:11:13] Tony: Well, I mean, they’re very, very basic situations that, um, it’s on the other side of the world. If, if you’re a manager, you’re either having to relocate there or you’re here working through the night talking to your staff, um, in their time zone. So it becomes logistically very hard. If there’s a problem that crops up in the UK, you’ve got to jump on a plane and take two or three days to get there.

[01:11:34] Tony: And you’re not going to operate. Off the bat, full potential, because you’re probably going to be jet lagged. So there are all those kinds of operational issues, just for a start. Um, I did note in the press release that they are keeping on most or all the staff involved in the company they’re buying. So that will help

[01:11:51] Tony: if they can trust management, but still your arms, you have to run these things at arm’s length.

[01:11:55] Cameron: mm,

[01:11:55] Tony: It’s very hard to do.

[01:11:57] Cameron: mm,

[01:11:59] Tony: And it’s very different to say a Shell or McDonald’s who are going to have thousands of people in Europe anyway, or um, uh, infrastructures which are used to regional management, all that kind of thing. This is one guy in Sydney trying to run a company in the UK. It’s um,

[01:12:13] Cameron: mm,

[01:12:14] Tony: it’s harder to do than running one in Sydney.

[01:12:17] Cameron: mm, alright, what do you got on your, uh, list of talkie talkies this week?

[01:12:24] Tony: talky, similar article, oh sorry, similar situation, an article about GrainCorp, um, a share I own, it’s been on the buy list for a while, on and off. Uh, headline in the AFR was ASX activist HMC Capital takes aim at GrainCorp. H HMC Capital has revealed a position in GrainCorp, making the group’s fourth public bet from the highly concentrated Capital Partners Fund.

[01:12:49] Tony: Um, so the important point here was to talk about the, what they see in GrainCorp. Um, uh, we believe equity markets are failing to appropriately value the critical infrastructure under GrainCorp’s control, and there may be opportunities to realize greater value from the infrastructure assets via increased utilization or ultimately a structural separation, the fund manager says.

[01:13:14] Tony: She says the fund also likes the company’s burgeoning agri energy business, which includes plans to set up a biofuels facility in Western Australia. Yep. HMC’s entry into the stock follows a mixed 18 months for GrainCorp shares, which remain around 20 percent below their all time high reached in early 2022.

[01:13:32] Tony: In February, the shares shed more than 10 percent in a single day after GrainCorp forecast a large drop in earnings and profit as farm production fell from record levels. So HMC, if, uh, if people are aware, may not be aware, they, uh, they’re a fund manager, their concentrated portfolio, um, their biggest.

[01:13:52] Tony: Success to date has been in taking Chemist Warehouse through a backdoor listing by Sigma, um, Sigma Health, I think the company’s called, Sigma Pharma, Sigma, anyway, yeah, through Sigma to the markets and it’s been a, they own shares in Sigma, then put the deal together with Chemist Warehouse and, and David, the pillar, the person who’s the principal at HMC, had relationships with, uh, Chemist Warehouse and was able to do this, um, deal, but it’s paid off well for Sigma.

[01:14:21] Tony: investors. Sigma was on our buy list a year or two ago, so there might be one or two listeners out there who still have shares and they’ve done very well through this. But this is an example of something which has happened in the U. S. for a long time and hasn’t been that big in Australia where we have active, we don’t tend to have activist investors.

[01:14:38] Tony: So in this case they’re taking a position in GrainCorp and then they’re going to agitate to improve the operations of the business. Potentially, as they’ve highlighted through doing something with the port facilities, either improving the utilization or spinning them off to, um, realize better value for shareholders.

[01:14:57] Cameron: I did note with interest in this it says, uh, talking about HMC’s high conviction strategy which launched in 2002 with around 300 million has already returned 55 percent for investors and currently holds only five ASX stocks. It’s not a strategy could run 50 names on, says, uh, Ms. Hardy, Victoria Hardy who runs the fund.

[01:15:24] Cameron: So,

[01:15:25] Tony: because of the, the way that Chemist Warehouse and its backdoor listing through Sigma has shot the lights out. I would say most of that, if not all that, 50 percent returns through that one transaction.

[01:15:35] Cameron: right. Yeah, interesting. You heard, you heard of these guys before? You’re obviously

[01:15:42] Tony: Only because they’ve got a lot of coverage through Chemist Warehouse, yeah.

[01:15:45] Cameron: Yeah, right. Okay, what else, TK?

[01:15:49] Tony: Uh, they have a pulled pork to do. Um, yes. We probably, we may also be able to know what the RBA is doing with interest rates because they’re meeting this afternoon too.

[01:15:59] Cameron: What time?

[01:16:02] Tony: It’s normally out by about now. They usually meet at two o’clock.

[01:16:05] Cameron: Hmm,

[01:16:05] Tony: Have a look and see if we have a interest rate result. But yeah, certainly interest rates have been the market focus for a while now. We’ve seen wild swings. First of all, because people thought that interest rates were going to get cut in the second half of this year.

[01:16:20] Tony: And then more recently, the markets retreated because people are worried that the next rate movement may be up rather than down.

[01:16:29] Cameron: Just went to the Financial Review. The only thing I can see is why Donald Trump is a style icon. So, um,

[01:16:36] Tony: It’s not April 1st, is it?

[01:16:37] Cameron: leading with the big stories there. Jemima Kelly on the Financial Review.

[01:16:42] Tony: Oh my goodness.

[01:16:43] Cameron: earning a living today.

[01:16:45] Tony: Slow news day. Okay. Do you want me to go do a pulled pork or do we have enough content today after Matt’s interview?

[01:16:54] Cameron: I think we do, dude. We’re going to be like here for the rest of the day.

[01:16:58] Tony: All right. I’ll push the pulled pork to next week, but we do have a question.

[01:17:03] Cameron: Uh, we’ve got a,

[01:17:04] Tony: two questions.

[01:17:05] Cameron: yeah, well, the first one’s more of a backgrounder than a question, but this is from Glenn. He says, um, I’ve been following yourself and Tony for a little while. I first came across you from the Iron Fist Velvet Glove podcast. That’s my mate, uh, Trevor’s podcast that I guest on from time to time. Whenever he’s looking to get some complaint emails, he invites me on to Explain the benefits of communism to his audience. I’m hoping to be in a position soon to join the QAV group, but that’s a little beside the point. I’ve just listened to a recent free podcast where you and Tony look into hostile ships.

[01:17:38] Cameron: Back in the 90s, I was a welder there for some time. What Tony was saying about their operating fluctuations and the causes is spot on. Also, hostiles taking a hit on contracts is not new either. I think the board, Jay Rothwell, believes sometimes the reward down the track is worth it. Austell’s built Aussie Rules Greg Norman’s luxury yacht.

[01:18:00] Cameron: I’m surprised, as keen golfers, that didn’t get a mention. Well, just one of us is a keen golfer, actually, Glenn.

[01:18:07] Tony: and not necessarily a fan of Greg Norman to be honest.

[01:18:10] Tony: Yeah,

[01:18:11] Cameron: The story goes that Norman’s contract was for approximately 70 million AUD. The build specifications and the timeframes stipulated in the contract had financial penalties that were certain to be triggered and it was an open secret that Norman already had a buyer ready to take ownership before completion.

[01:18:27] Cameron: I believe Norman would have it for two years and then the new owner would purchase it for 70 million USD. A very shrewd businessman. We were all aware that Hostiles was taking a big hit on the deal right off the bat, but in the long term, there was much publicity. Then Hostiles then went on to build patrol boats for Australia, Yemen, and secured the U.

[01:18:47] Cameron: S. Littorial Combat Ship contract. So, dot, dot, dot, question mark. Anyway, love your content, across your many interests. I’m keeping QAV on my buy list. On my to buy list. Regards, Glenn. Thanks, Glenn. Always good to get, uh, some, you know, Background intel from QAV listeners.

[01:19:06] Tony: yeah, inside information.

[01:19:08] Cameron: Yes.

[01:19:09] Tony: Yeah,

[01:19:10] Cameron: Wow.

[01:19:12] Tony: no, we haven’t traded.

[01:19:14] Cameron: Uh, yes. Yeah. Inside information if we were trading in

[01:19:19] Tony: Yeah.

[01:19:21] Cameron: Uh, so questions from Nick. TK’s thoughts on what’s happening with DUR. No, it hasn’t broken the 3PTL, but does feel like it’s broken out of its support range. Given its relatively short trading history, would TK fudge or still hold until a 3PTL slash Rule 1? Rule 1 is higher for me, he says. What do you think about DUR?

[01:19:43] Cameron: Tony, would you fudge?

[01:19:45] Tony: No, I personally, I wouldn’t. Rules are rules, as we’ve said many times. This is probably one of our most commonest questions, isn’t it? Um, something’s gone up a lot. It’s turned down a bit. What do I do? And really, um, the answer is rules are rules as to what I would do. And I’m not, I’m not going to give out specific advice, but if you’re feeling like you want to take a profit, then by all means take a profit because, um, Yeah, Nick, you, you’ve got to sleep at night.

[01:20:11] Tony: Um, so, but we’ve, we’ve found that, that things go up, you know, the share price goes up on a zigzag pattern. So you often do get periods when it outperforms and then it drops back and then it gets a second wind and keeps going up. So I don’t know Duratec that well. And you also asked a similar question about LAU, um, Lindsay, Australia.

[01:20:33] Tony: So, um, the same thing applies there. Uh, I did, you asked the question about whether you should use a shorter time period. I did. Try running the graphs over three years. Monthly, it still looks like the share price is above the sell line, even in that case, so you wouldn’t be selling yet on that basis. I did notice that the Renco graphs had turned red, which is because they’re basically a trailing stop loss.

[01:20:57] Tony: And as you said, the share prices retreated recently. So they’re blinking for a sell. So look, completely up to you, Nick. If it was my stock, and I’ve held many stocks that have done this, where they’ve gone up and come back. Um, and, uh, you know, it’s just the way the share market works sometimes. I did try and get to do some research and as to why they might be retreating and I couldn’t find much.

[01:21:20] Tony: Um, but, uh, I noticed a couple of things. So first of all, both posted what looked like good results. They both still appeared on the buy list. You know, around that time, so I couldn’t see anything in the numbers that looked bad. I did notice that they both increased their short positions around the time that their results came out.

[01:21:40] Tony: So either analysts were thinking the numbers may have been bad or, or they didn’t like something in the numbers, but the shorts have gone back to zero now, so, or close to zero. So they’ve all sold and moved on. Um, And I did notice too, in both cases, the Stock Doctor financial health went down after the latest results came out, but I couldn’t work out why, so it might need a deep dive to work that out, but that might be, um, you know, spooking some investors if, if, if, for example, debt levels have gone up, um, didn’t have time to check that, but that Might be worth investigating, Nick.

[01:22:14] Tony: And, but again, we don’t sell on those, on that basis. Maybe we should research and add it to the checklist, but at this stage we don’t do it. So rules are rules and I would be holding on myself, but up to you, Nick, if you, if you feel more comfortable and by all means sell.

[01:22:30] Cameron: I just note that I hold both DUR and LAU in a number of, uh, of our portfolios, light and dummy portfolios. And I am going to have to sell LAU today, probably tomorrow at this stage. It’s just become a rule one sell, and one of those, the most recent one, where I bought it in November last year at 1. 12, it’s now 1.

[01:22:53] Cameron: 96. But, um, I’ve held it in the dummy portfolio since June of 22, bought it at 42 cents. It’s up 129 percent since then, and the other portfolios it’s doing well. Also held up since 2022. It’s been a good one. But, uh, yeah, like I just add to what you said, Tony, I know when I ran my light, um, analysis a few months ago, had to look at all the rule ones and calculate it.

[01:23:22] Cameron: If we would have been better off if we had held onto them or not, it came out relatively neutral. Um, and that was just over a couple of years. So, um, I know it, it, it feels painful when you, like in these portfolios, seeing stocks drop by 30 percent over a couple of months. Um, as you say, odds are that they will turn around.

[01:23:46] Cameron: We just need, we need them to turn around 60 percent of the time to, um, come out, come out on top.

[01:23:53] Tony: yeah, and it’s, it’s these two stocks too I think aren’t, aren’t very large, um, and so they’re not, I couldn’t find much in Google News about, about them. So, um, if someone does think there’s a problem, they’re keeping it to themselves and we’re not seeing what the problem is, which, which also makes me think that, um, you know, someone’s I’ve taken a very technical knife to these results and they’re finding something they don’t like, which could be good or bad, but it could also be that they’re being a little bit picky and that their stocks will recover.

[01:24:25] Cameron: All right. Um, well, I think that’s it for this week, except for after hours, Tony.

[01:24:32] Tony: Yeah.

[01:24:34] Cameron: Hold on. My

[01:24:34] Tony: Well, you’ve covered off my after hours at the start of the show.

[01:24:37] Cameron: The Poifectwin?

[01:24:39] Tony: do have one running tomorrow, which people may not hear about in time, but nothing seems to fit. Races tomorrow at Race 2 at Canterbury on Wednesday.

[01:24:47] Cameron: you, did you come up with that name? Is that

[01:24:50] Tony: I did.

[01:24:50] Cameron: you were, you’re in your wardrobe, getting dressed in the morning?

[01:24:54] Tony: No, no, it’s, it’s, um, the, I forget now, uh, who the horse is out of, but, uh, there was a rain theme. And when the horse first started training, it was so wet and sinewed, we just couldn’t get, get it to the track. And so I tried to call it raindrops keep falling on my head and waiting for a sunny day. And I both got knocked back.

[01:25:14] Tony: So nothing seems to fit was the next line in that song.

[01:25:17] Cameron: Oh, right. Oh,

[01:25:19] Tony: a guy who’s. Neither too big for his bed, yep,

[01:25:23] Tony: nothing seems to fit,

[01:25:25] Cameron: don’t sing. Don’t

[01:25:26] Tony: yep, ha, ha, ha,

[01:25:28] Cameron: a reason I cut our theme song out just before you start singing.

[01:25:31] Tony: ha, ha, ha,

[01:25:35] Cameron: Well, I finished the three body problem. Um, yeah, I think I told you when we were doing the bullshit filter last week. Yeah. It wasn’t, uh, it wasn’t happy with the way they finished it up. Pushed it too far, too fast, too many, too, too much. Uh, like what? No, that’s ridiculous. Anyway. Um, also I’m still reading my Dong Xiao Ping book and I’ve started, I’ve come across a couple of really interesting YouTube videos.

[01:26:01] Cameron: Um. about him. One was from the launch of the book that I’m reading, which is written by a guy called Ezra Vogel, who’s like the Harvard professor for Asian studies or something like that. Um, the book came out in the, I think the nineties and it’s him on stage. I, I assume at Harvard, wherever he is with some dude who’s moderating it, who was, who met Deng Xiaoping a number of times Uh, in his role as some diplom American diplomat going over there with the, with the American ambassador a number of times to meet with Deng.

[01:26:39] Cameron: And a U. S. general who met with Deng on a bunch of occasions. Uh, he had some capacity at the time for, I don’t know, China relationship. Including meeting with him just after Tiananmen Square, but met with him many years before that. He was like, he’d been meeting with him since the, uh, 70s, uh, late 70s and for, in different capacities.

[01:27:00] Cameron: Um, which was really interesting. Like all these American guys just talking about how he was the most, um, actually the guy moderating it, who’s, you know, I don’t know what his position at Harvard is. And he said probably the most, um, not just one of the Uh, most impressive world leaders of the 20th century, but one of the most impressive world leaders in all world history.

[01:27:21] Cameron: And then the second video I watched was Lee Kuan Yew giving a speech talking about Deng Xiaoping, who he knew very well and, you know, had met, you know, from the, I guess, since the creation of Singapore from the 60s through to the 90s. And, um, he said, he said Deng Xiaoping was the most impressive. Person he’d ever met.

[01:27:45] Cameron: Um, yeah, really, uh, big fan. And I’ve just been reading in the book, uh, the period where Dong, in the late 70s, starts meeting with these guys as the vice premier he was at the time, Hua Guofeng was still the premier, but he’s meeting with them all to try and shore them up. to support them against Vietnam, who was about to invade Cambodia to get rid of Pol Pot, but Vietnam was, uh, very tied up with the Soviet Union at the time.

[01:28:15] Cameron: China was very worried about the Soviet Union, so they were trying to get all of the Asian countries to line, align with them against Vietnam and the Soviet Union. Um, but yeah, he and Lee Kuan Yew, Uh, got along very well and, uh, had a lot in common. You know, and I know from that other book, The China Model, I’ve been reading how China’s, you know, since the days of Deng in particular, have tried to model themselves.

[01:28:38] Cameron: on Singapore and Japan, you know, it was how do we, how do we modernize like Japan? And how do we build ourselves into a financial power like Singapore? And also, you know, the Lee Kuan Yew dictatorship model. I mean, they don’t have a dictatorship like Lee Kuan Yew did. You haven’t had one man running China for 40 years, but the, the model of pick the best and the brightest from your society and put them in charge of running things.

[01:29:08] Cameron: Get

[01:29:08] Tony: Sounds basic, doesn’t it?

[01:29:10] Cameron: Yes, get the best and the brightest, trial them in low levels and see how they perform and if they perform well, promote them to bigger and bigger areas of responsibility. But yeah, it’s just, like, it’s just crazy to me how little, I mean, I’ve been meaning to read more about him for decades, but, um, it’s taken me this point to really go deep on his life and, like, seriously, uh, an impressive, uh, Uh, impressive man.

[01:29:36] Cameron: Everything that he went through and everything that he did in the time that he had and how he turned the country around and, uh, the amount of respect that all of his contemporaries had for him from the Americans through to, well, pretty much everyone. Yeah. Hmm.

[01:29:53] Tony: Yeah, that does, that does, I mean, probably there’s elements of this in China as well, but it does contrast with my experience many years ago watching, uh, friends make careers for themselves in politics and, and they were bright people and good people, so I’m not going to say that they weren’t the best and brightest, but the skills that they were tested for that, you know, the evolution of democracy was trying to, to weed, you know, to try and to reinforce was that, um, you know, it’s, it was how many votes could you deliver?

[01:30:22] Tony: I don’t know how good were yous. spinning stuff on your feet. How many internal votes could you deliver to the faction in the local area? All those kinds of machine politics type things that are important to get ahead in modern democracy. It wasn’t about, you could say that the baseline was they had to be good, otherwise they’d get found out.

[01:30:43] Tony: But yeah, we weren’t picking the best and brightest on merit, basically. We were picking the ablest at climbing the greasy pole in democracy. And of

[01:30:57] Cameron: Yeah. Yeah. Very different. And I mean,

[01:31:00] Tony: course it works in America of course because everyone tells me so that the best person is, uh, running for prison.

[01:31:06] Cameron: and that’s not to say that China doesn’t have its problems and Singapore didn’t have their problems too. Like there, there’s always corruptions and that’s what the psychopath epidemic was largely about, right? Doesn’t matter what system or what organization, you’re always going to have. Psychopaths.

[01:31:20] Cameron: You’re always going to have people that try and, uh, graft their way through things and, uh, you know, get away with certain stuff for a certain amount of time. And then they,

[01:31:31] Tony: just that, the best and the brightest might not be universally good enough

[01:31:36] Cameron: yeah,

[01:31:36] Tony: well. They might have blind spots like any human being does.

[01:31:39] Cameron: Yeah. And they, you know, they can be ambitious and not be able to

[01:31:44] Cameron: execute. That’s kind of the thing I was on. I was a guest on a podcast, uh, last week and we got, I got talking about communism in the 20th century and, you know, the great leap forward and the five year plans in all the socialist slash communist countries and explaining how, you know, they, They were compelled to try and rapidly modernize for very, very valid geopolitical and, and, and domestic reasons.

[01:32:14] Cameron: They had to feed a population. They had to defend themselves against far richer and better resourced capitalist countries who were going to try and, uh, invade, um, or, or take them out through other means, fair or foul. And so they had, they tried to rapidly modernize their mostly illiterate. countries with very little.

[01:32:37] Cameron: Uh, developed infrastructure that had mostly missed the industrial revolution and they didn’t have computers and they didn’t have the, you know, communications technology to help them rapidly modernize. They didn’t have trained, uh, modern managers, uh, or engineers or all this kind of stuff. And in many cases it failed and they actually did damage because they destroyed the existing, uh, Agricultural capability to try and build a better one.

[01:33:10] Cameron: It ended up with neither of the two and people starved. So their ambition wasn’t, um, doable. They couldn’t execute for, for, you know, again, a bunch of reasons. I mean, there was some, you know, there were egos involved in all of that kind of stuff as well, and corruption and all the ills of human nature. But in many cases, I think they genuinely thought they could pull it off and they just couldn’t.

[01:33:36] Cameron: Cause they didn’t have the, the people or the wherewithal or the money or the skills, and they were fighting too many battles or too many times. And it was a disaster. And, but one of the fascinating things about Deng, as I think I said last time is, uh, and one of the things that I think guys like Lee Kuan Yew really respected about him in these American generals is he was willing to acknowledge all of that.

[01:33:55] Cameron: Yeah, we failed. We’ve, we’ve massively failed the Chinese people and we need to fix it. And we need to fix it now. We need to fix it quickly. Um, which is. Um, uh, an unusual level of humility and pragmatism, I think, for somebody at those levels.

[01:34:18] Tony: And you definitely wouldn’t hear that in a paid job. Uh, Democratic Leader.

[01:34:24] Tony: We failed, but we’ll fix it.

[01:34:25] Cameron: Yeah.

[01:34:27] Tony: When they write their memoirs after they’ve been turfed out, but, but it would be, We inherited this problem from the other guys, and now we, they, they blocked us from trying to fix it.

[01:34:37] Cameron: Which is human nature, right? And you you’re worried about your legacy and you’re worried about holding onto power and all of that kind of

[01:34:43] Tony: Political nature.

[01:34:45] Tony: Hey, bringing you back to QAV, what do you make of the articles in the last week or so about electric vehicles and how BYD is doing really well, I think I read in the Fin Review today that they’re Europe was thinking of introducing tariffs to try and make their car makers more competitive because BYD and there’s one other Chinese car maker I forget were doing so well in Europe and selling cars and then Tesla came out and their stocks have been going down a lot but they came out and said they’re close to releasing their first driverless car, which I think was conveniently talked about when the BYD sales numbers came out.

[01:35:24] Tony: So there’s a lot going on with Chinese manufacturing, I guess is what I’m trying to say. And how that’s accepted or received by the world is interesting too.

[01:35:33] Cameron: Well, I think we’re going through, uh, did you, did you see the Ray Dalio video that I posted?

[01:35:39] Tony: No, it

[01:35:40] Cameron: Really interesting. So Ray’s done this five

[01:35:42] Tony: was on TikTok. I don’t go on TikTok.

[01:35:46] Cameron: Ray’s done this.

[01:35:48] Tony: Guess I’m in an asbestos suit to get rid, to get out of the dumpster fire alive.

[01:35:54] Cameron: TikTok’s great, man. You just, you need to let it, um, the algorithm program for you, for what you’re interested in, right? So you just

[01:36:04] Tony: I went on once when your boys told me to and I got a, the very first video I saw was one of Hunter sitting in his room playing with a fidget spinner and I thought, okay, if that’s TikTok, I’m out. Forget it. I’m done.

[01:36:17] Cameron: Wow. There’s a lot of great content on TikTok. Um, but you, you know, you need to, you need to moderate it, curate it. Anyway, Ray posted this five minute animation, um, talking about, um, Uh, the rise and fall of empires and what leads, and he’s, he’s sort of isolated, uh, 10 things that indicate, you know, that where an empire is in terms of its rise and fall.

[01:36:44] Cameron: And he shows how they, there tends to be overlaps, you know, one, and the, the, the empire de jure is declining as the next one’s rising. And where he’s sort of mapping is this is the U S and China, right? The U S empire is obviously high and Russia’s on the rise. I’m sorry, China’s on the rise. Um, And, you know, we’ve seen Blinken over there, Anthony Blinken, you know, America’s biggest complaint about China right now is overcapacity.

[01:37:10] Cameron: You’re making too much stuff.

[01:37:11] Tony: Yeah.

[01:37:12] Cameron: Stop making all of this stuff. You know, you gotta stop it. For 30 years, we’ve been asking you to make all of our stuff and now you’re making all of our stuff and we don’t want you to make all of our stuff anymore. Stop making so much stuff. You’re flooding the market with stuff.

[01:37:28] Cameron: We can’t

[01:37:28] Tony: And isn’t it amazing? Again, an article, an article I read last week was, um, about the fact that the Chinese government said, okay, property’s not working well for us now. Let’s just take some, all our resources out of property and put it into manufacturing. Let’s, you know, let’s improve our economy through building stuff and selling more.

[01:37:46] Cameron: Well, the, the, the Chinese now, uh, you know, they can see what’s happening, like the, the quote unquote decoupling and they’re re engineering their economy around domestic, uh, sustainability, um, and, uh, also innovation, cause they’re not going to be able to buy the latest computer chips, uh, from the U S or any country that, uh, The US, uh, can tell what to do.

[01:38:16] Cameron: So yeah, they’re, uh, but they’re going to continue to, I think, barring unforeseen, um, accidents, they’re going to continue to get better. They’re going to put all of their focus and their money into being the, the producers of the highest quality, uh, stuff in terms of AI in particular. Um, And yeah, it’s electric cars, all of that kind of stuff.

[01:38:42] Cameron: I do expect China just to sort of take over the world with pushing all of that stuff out until the world tries to stop them. You know, they’ll use the World Trade Organization to try and stop them from flooding the markets with all of their low

[01:38:56] Tony: possibly, or tariffs. Tariffs are probably more likely, but I think if they make enough of it, they’ll be cheap enough to still succeed, even with tariffs in place. But they’ll, US will try, Australia will try. But isn’t it, isn’t it interesting, like at the same time as that’s going on in China, on the front page of the papers today is an article about our supercomputer.

[01:39:17] Tony: And

[01:39:18] Cameron: no, not a supercomputer!

[01:39:19] Tony: you can’t pick

[01:39:20] Tony: a quantum computer,

[01:39:21] Cameron: a quantum computer.

[01:39:24] Tony: you can’t pick winners. You can’t invest in just one thing. It may not work. And like, this is how China gets ahead. Like they just keep pumping money and they pick something and they say, we’re going to dominate on electric vehicles.

[01:39:35] Tony: We’re going to sew up all the supply chains, all the minerals that are required for it. And we’re just going to flood the world market with it and dominate on that. No one’s in China going, you can’t pick winners. You can’t invest in manufacturing. Let the free market sort it out.

[01:39:51] Cameron: Yeah, like, I, I think, I mean, I am skeptical about the Australian government’s investment in this, uh, Brisbane startup to build a, spend a billion dollars to build a quantum computer. That said, you know, if Australia has any hope. of having, uh, uh, an economy for the rest of the 21st century. It, we need to decouple ourselves from uranium and coal and start thinking about 21st century, uh, economic models around, you know, mostly it’s going to be technology, right?

[01:40:26] Cameron: Or clean energy.

[01:40:29] Tony: Yeah, look, it’s a hard one because historically we’ve always been an export nation, whether it’s riding on the sheep’s back or now it’s iron ore, but that won’t go on forever. The question is how much do you try and shore up ourselves against the time when that runs out now, or do you just wait for it to happen and then do it then?

[01:40:49] Tony: Sort of like the Saudis do with oil, right? They think the oil’s going to run out one day and they’re trying to pivot to something else whether it’s a tourist destination or whether it’s sporting companies or whatever, they’re trying to, you know. Make a, make a pivot change, which is hard.

[01:41:04] Cameron: Yeah. I, I think it’s too late when that runs out to start thinking about investing in it then. I mean, a, as the article on the quantum computing and the fin said today, or the A, B, C, wherever I read it, we don’t want it to be, uh, a repeat of what happened with FTO Volta Excel, which were developed in Australia and we’re not leading the world in Voltaic technology.

[01:41:30] Cameron: Photovoltaic technology, right? It’s, uh, China that’s leading the world with solar

[01:41:34] Tony: Rooftop solar was invested, was developed in Australia and was developed by, uh, an Australian of Chinese heritage who learnt, you know, here in the universities and did research into it. And then went, looked around for a manufacturing plant to do it here. And he went, no, this is not going to work. He went to China and now he’s a billionaire.

[01:41:52] Tony: And China leads the way in low cost rooftop solar.

[01:41:56] Cameron: Which is an interesting thing in the Deng Xiaoping book where I’m at in the late 70s. He is trying to, uh, trying to get, he’s, he’s, you know, trying to do normalization with the United States, and he’s trying to get Chinese students to go to American universities and Japanese universities and universities around the world to study and people are asking him, aren’t you worried that they’re gonna leave and never come back?

[01:42:21] Cameron: And he’s like, no, they’ll come back.

[01:42:24] Tony: Yeah,

[01:42:25] Cameron: He’s like, I’m not worried. No, no, they’ll, they’ll come back. Some won’t, but enough will, and they’ll bring that knowledge back with them. It was, you know, that previously, you know, these, uh, socialist countries were very worried about their brain drain or

[01:42:39] Tony: a brain

[01:42:40] Tony: drone,

[01:42:40] Cameron: leaving.

[01:42:40] Cameron: And he was like, no, no, it’ll be fine. They’ll come back. And, um, yeah, there you go. All these tech, all these people have gone back and uh, you know, obviously he needed to fix the economy and fix the country and make it a place where people wanted to be, particularly people of Chinese heritage.

[01:43:00] Tony: But even if they don’t go back, right, they’re available as a connection that they can train people. Back in China on how to fix things.

[01:43:06] Cameron: Yeah, they’re our contact. You know, yeah, that you can reach out to. Yeah, look, I don’t know, man. I don’t know much about the EV market and where it’s going, but I do think that, uh, as we get better AI, and better, which will enable self driving vehicles to be a real thing. I mean, Elon’s been hyping this up for a decade, uh, and I read conflicting reports on how close it really is, but I think, you know, the big issue is, The quality of the AI inside of it to make the right decisions and make them quickly enough.

[01:43:46] Cameron: And then you’ve got the problem that the humans that are on the road driving, uh, very unpredictable and, uh, very dangerous. If you could just, I was talking with the boys about this on the weekend, if you could just snap your fingers and make it all AI driverless cars, uh, overnight, it would probably be, uh, a lot more effective and safer than it is with some sort of a hybrid of human drivers and AI drivers.

[01:44:12] Cameron: And governments will hopefully be providing incentives to make that happen as quickly as possible. But, um, I do think driverless vehicles, I do think EVs are going to be where it’s all

[01:44:23] Tony: Yeah. Look,

[01:44:24] Cameron: in

[01:44:24] Tony: I don’t know one way or the other, but I think, I guess where I’m coming from is tech, tech heart hardware in particular, but I guess also software and manufacturing will always flow towards the low cost producer. So China’s probably going to fit that bag. I mean, their, their wages will increase, but they’re going to have scales.

[01:44:46] Tony: They’ve got so many people there who can work on these things. China, India, they’re always gonna be the manufacturing centers of the world. So as soon as Elon solves self-driving cars, it’s not gonna take long for BYD to catch up. Same with Nvidia chips, right? There must be, you know, thousands of companies in China or factories in China, reverse engineering Nvidia chips.

[01:45:08] Tony: I know there’s constraints on the important materials and metals and things that go into them, but, but you know, yeah, I think the West only has. I think it used to be like a five year advantage, probably like a one year advantage now, in terms of developing this stuff, and then China’s just going to flood the market with a cheaper version of it.

[01:45:25] Cameron: And, you know, I’m not sure how long the cost of human labor is going to play into these things. I mean, robots are already

[01:45:32] Tony: Yeah, right. Mm

[01:45:33] Cameron: vast majority of this stuff. And as we get more and more effective humanoid robots, which is now starting to, Oh, did you tell you that Taylor had a mate? From his drunk engineer’s days, you know, when Taylor was making the drinking can things, one of the Canadian guys, um, had been at Apple for the last couple of years, working on the Apple car project, secret, top secret.

[01:45:57] Cameron: Well, they’ve shut that down. And Taylor was speaking to him a couple of weeks ago. He said, have you found another job yet? He goes, yeah, I got an offer, another job at Apple, but I’m not taking it. He’s gone to figure. Which is one of the humanoid robot companies over there now. He’s apparently working on the head.

[01:46:14] Cameron: Uh, he’s one of the guys working on the head. So, there’s gonna be this massive, you know, um, The guys, like the guy, Brett, who’s the CEO of, Uh, figure and Elon with his Tesla bot, all the robot manufacturers and, and Jensen Huang at NVIDIA that’s providing their robotics, humanoid robotics platform. They’re all saying that within like 10 years, there’s going to be a billion humanoid robots, um, on the market.

[01:46:41] Cameron: Hey, Jensen Huang, I saw a talk with him recently where he said you can buy a car now for 10, 000 to 20, 000. Uh, you’ll be able to buy a humanoid robot for that in a decade. And there’s just going to be a flood of humanoid robots with AI connected in their brains to everything. And, um, so you think about that, not just in traditional manufacturing, but think about that in terms of building houses, housing, the housing crisis.

[01:47:06] Cameron: What does it cost to build a house when you have a hundred humanoid robots that can work 24 seven? Um, what, you know, not just that, but what about climate change related issues? Um, what do we do with, uh, A million humanoid robots, what can they do for the environment? Um, it’s just, it’s, we’re, we’re moving into a world where there’s going to be billions of humanoid robots working 24 7, very low cost.

[01:47:41] Cameron: Uh, in, in the community doing God knows what, working in hospitals, working in, you know, mowing your lawn, doing your dishes, building you a house, repairing your house. What that world looks like. I don’t think anyone’s ready for yet. And it’s going to happen faster than anyone thinks. If, if these guys are right, unless there’s some sort of a hurdle that we hit that they haven’t seen yet, but.

[01:48:05] Cameron: All of the guys I’m following that are building these humanoid robots are saying, yeah, 10 years and the market’s going to be flooded with these things.

[01:48:14] Tony: And as long as I don’t become sentient, I’ll keep enjoying being our slaves, I guess.

[01:48:19] Cameron: They will become sentient. I mean, there’s, I, I see this coming in two phases. It’s what I call the utopia phase where we have AI and robots doing all this stuff for us and making life better. A million new, PhD, Virtual Scientist, working on all of the hardcore problems, Cancer, Climate Change, Economic Inequality, etc, etc.

[01:48:41] Cameron: And then the second phase, which is what I call Order 66, when they all just decide, okay, these humans are becoming a problem. Um,

[01:48:51] Tony: get out of the way. Human. Hold my beer.

[01:48:54] Cameron: they’re all connected. They’re all networked and they just go, all right, you know what? The humans are just, we could, we could clean this place up and we could, we could make progress so much faster if we got rid of the human. blockages. So they just, one day they go, all right, um, new plan, humans,

[01:49:15] Tony: Yeah.

[01:49:17] Cameron: shut

[01:49:17] Tony: Oh, and

[01:49:17] Tony: someone’s Or, Or, or, someone’s gonna be sitting in Silicon Valley going, oh, I shouldn’t have put that line of code in there. Should I optimize the planet? Yeah.

[01:49:27] Cameron: humans won’t be putting lines of code in these things for much longer. They’ll be coding themselves very quick, very soon. Uh, yeah. So then we have the order 66, um, phase, and I’m not sure what happens after that. It

[01:49:39] Tony: where does that term come from?

[01:49:41] Cameron: Oh, you don’t know that? That’s,

[01:49:43] Tony: No.

[01:49:43] Cameron: that’s, uh, in the Star Wars prequels, man, when the, the, uh, Jedi’s have built millions of clones that

[01:49:53] Tony: Ah, right. McClean Wars. Yep.

[01:49:54] Cameron: army, and then the Emperor says, Execute Order 66.

[01:50:01] Cameron: And this little, uh, backdoor switch and all of the clones goes off and they turn around and just shoot all the Jedis and kill all the Jedis. Except Yoda, Yoda escapes, and Obi Wan escapes, and, uh, Ahsoka escapes, um, Anakin’s student from the Clone War cartoon series. And then all the Jedi get wiped out, which I’ve always said, How, how pathetic are these Jedi?

[01:50:26] Cameron: Like, they’re in touch with the Force and they can’t, they can’t sense that the clones are about to turn on them and, you know, they didn’t see that coming, that’s pretty piss weak. Anyway, they deserve to get wiped out, I think is

[01:50:38] Tony: and no one checked the code.

[01:50:41] Cameron: Yeah, well they were just ordering these clones from the clone factory, man, and, uh, assumed that the code was good.

[01:50:47] Cameron: Yeah, they just turn on them, overnight, and, uh, the, that’s, that’s when the Empire wins, is they just, that’s when it becomes the Empire, actually, is when, um, Palpatine, before he’s the Emperor, um, uh, has all the clones kill the Jedi, yeah. Anywho, that’s the

[01:51:07] Tony: And here, yep.

[01:51:08] Cameron: That’s a two hour show.

[01:51:10] Tony: Yeah, I didn’t do a pulled pork. Anyway, we can wait for next week. Yeah.

[01:51:14] Cameron: Thank you again to Matt for coming on, uh, and for all the work that he’s done. It’s really tremendous stuff. And thank you TK as always for your time and, and, uh, effort in teaching us how to be clever investors.

[01:51:28] Tony: No problems. Thanks, Cam. Talk to you next week. Happy QAV, everyone.

[01:51:31] Cameron: Yeah. Have a good week.