I'm Jeremy Sheepard. >> And I'm Daniel. >> We use data to expose deceitful property experts and their marketing BS. >> This is the expert busting series. >> Welcome to episode 13 of the expert busting series. Time in the market versus timing the market.
Let's dive in. Jez. Yeah, there's been this uh debate raging for many years whether you should just spend time in the market and be patient or whether you've got to enter the market at just the right time timing. So, in this episode, we're going to have a look at both approaches and show you why the superior strategy is actually timing the market. All right, so time in the market is all about patience. If you wait long enough, eventually capital growth will come.
Alternatively, timing the market is all about picking when you buy. Uh the idea is to time your purchase to occur just before the next boom. The timing approach might also include when to sell. Now, because the two terms sound very similar, timing and time in, I'm going to refer to the time in approach, the patience approach as holding long-term. And I'm going to refer to the timing approach as trading, trading property. So, we've got holding long-term versus trading.
That's basically what we're talking about here. And trading, of course, means buying and selling. All right, next slide. >> So, holding long-term. So, how did this expert busting series episode come about? >> Uh, I just heard uh a lot of investors um experts, fake investment experts out there.
Well, I suspected they were fake. Um, banging on about holding for the long term. And you hear a lot of excuses. Why hasn't this market that you picked, why hasn't it outperformed? Oh, trust me, it'll it'll outperform over the long term. And I just wanted to see are there cases where you can outperform over the long term or is it all about uh short-term timing?
>> What makes a real property investment expert? >> Past performance. >> Past performance. Good answer. >> Yeah. All right.
Uh holding long-term. So time covers over a multitude of ineptitude. Eventually property prices do go up. So it's almost almost guaranteed. Uh, and once you've bought, you don't have to do anything. So, it's nice and easy just hold for the long term.
Um, it's not a great option though for older investors nearing retirement because well, they don't have time on their side like the uh young investors do. Uh, and it does not deliver the best returns. The longer you hold a property for, the more likely you're going to get average returns. What if you looked at let's say the last five years, you bought an investment property and especially if you used a buyer's agency service and you didn't at least beat the national average growth rate and you just had even potentially flat growth or negative growth, there's got to be some sort of repercussion for that advisory firm. No, but there's not. That's the biggest challenge within the industry.
>> But what's their excuse? You'll thank me in 10 years time, in 15 years time. >> You'll thank me once I've retired and um in overseas. [laughter] >> That's right. >> Trading property. >> Yeah.
So, the big problem with trading property is that it costs it costs a lot to reallocate your equity elsewhere. >> So, to exit the market, that is to sell uh you have to pay a sales agent a commission. Uh you also have to pay the atto capital gains tax. Uh and then to re-enter the market, that is to buy a replacement property, you have to pay stamp duty. Stamp duty is the big one. Uh and of course there are legal fees for both exiting and re-entering.
Uh on top of the costs to trading the advocates of this holding for the long term, they say it's risky because you don't know if you're going to get better growth by investing elsewhere. And I would agree with them too if I had no idea what a growth market is likely to experience. what growth that a market is likely to experience. So if you can't predict future growth then the best strategy is to hold for the long term. So anyone who recommends holding for the long term uh is someone who cannot predict future growth at least not to any reasonable degree of accuracy. And that is where the uh long-term hold advice stems from not being able to forecast capital growth.
>> How can you forecast growth? >> Data. It's all in the data. >> Yeah. Looking at historical growth uh metrics and patterns and so on. Yeah.
>> I I'll just always say go to market metrics on our suburb data website and just type in the suburb. Easy. It might cost you like what a dollar or something $2. >> Uh what you mean just for a single suburb less than that? >> Yes. Single sub.
>> Want to check the DSR? I think it's like less than 50 cents for the DSR. >> If you've got a portfolio and you're not sure how's it performing, one I'd get a valuation to see how much you purchased it for. what's it worth now and then work out what's the potential for capital growth and then I'd also look at maybe the trend in historical charts over the last year to see is it flattening out or um is it still increasing so there's things that you can do >> might have been flat the whole time they've owned it >> might have been flat but that's maybe the call that you make oh I've got a property property that's just flat it's not doing anything I look at market metrics it's got a DSR3 score of 50 the growth isn't happening >> yeah flat for a while >> to come there's other markets that are flying saying maybe that's I need to be a bit more active with my property portfolio. >> Yeah, we do have a uh service where we answer the question, should I sell if [clears throat] you're interested? >> Yeah, it's just more about I guess a bit of how we would approach it.
That's how I always view >> these circumstances. Like if this was me, I held this property. I looked at these circumstances. What's the game plan? >> Yeah. >> So again, like I said, it's really difficult when you've just got that one property.
If you've got two, three, four, you don't feel the pain as much because you're most probably getting some sort of growth. >> Yeah. In one of them, especially if they're diversified. >> Well, think about it. Let's say you've got a portfolio that's worth roughly, let's say, $2 million and it's growing at what, 3%. That's what 60 grand a year.
It's just growing in value. >> Yeah. Just sitting on your hand. >> Sitting on your hand, sleeping at night. And all right. So, how does uh trading property work?
>> Yeah. So there are two reasons why trading property works. Three reasons. There are three reasons. >> Three reasons. >> Okay.
So firstly, uh growth happens in spurts. It's not consistent. And that means uh you have to sit around uh waiting for your property to grow for long periods of time before eventually it takes off. Uh the idea of trading is to be invested in spurting markets. Can I use that term? uh spurting markets all the time rather than just some of the time.
[clears throat] >> And secondly, there's a tendency for all markets to grow at the same rate over the long term. And that means the longer you hold a property for, the more likely you're going to get growth in line with the national growth rate. So you can't get ahead by investing for the long term. And thirdly, Australia has uh a diverse property market. uh one city can be booming while another is lagging. So there's always an opportunity somewhere.
Um anyway, this is all just words, uh opinions, theories. What we want is proof with with that long-term growth rate. Even like that sort of three years, a lot of investors might say, "Look, this property has grown 30% the last 3 years or two years. I don't want to invest there because someone told me that that's not the right way." But longterm over the last 10 years it might have only been growing 2% peranom. So you've had that growth recently but there still might be another 50 60 70 80% >> to go. So you don't want to be wiping out all those suburbs.
They still actually can keep pushing forward. >> Yeah. Yeah. You don't know if the growth spurt is a threeyear growth spurt or a fiveyear growth spurt. Anyway, I started looking for proof rather than just having opinion. we uh how we do things here is we want to know rather than guess.
So here's what I did. I created a simulator that would make historical trades based on a consistent set of rules. Uh for example, buy in the area with the best value for some metric, which I'll come to in a second, and then sell when that metric has returned to normal sometime in the future. and after selling look for the best market at that new point in time and repeat the process. And then what I did is I applied those trading rules to historical data to see where would it buy and when and when would it sell uh and where would it buy next, how long would it hold for, how much growth would it have, um yeah, how much gains would it get? So I included all the costs to entering the market and exiting the market to make it a fair simulation.
And I also considered the um a little bit of a time gap between selling and being able to buy again. Uh and then I calculated the performance to see if trading would have outperformed holding long-term based on historical data. Now obviously I could have cheated by looking back in time uh used hindsight to create the perfect trading algorithm uh with some very complicated rules for entering and exiting uh various markets. So to ensure there's no cheating I made the trading rules extremely simple and they're on the the next slide. So, the trading algorithm is going to be based on a single metric called market cycle timing. And market cycle timing, for those of you who aren't familiar with it, it's a score out of 100.
Uh it's for the likelihood that a market is about to enter its next growth phase. Uh the the market cycle timing is is scored based on the market's uh prior growth history. If the growth has been exceptional in the recent past, then the MCT score is quite low. >> Uh if however the market's growth has been flat for a long time and it's showing some recent signs of of movement, signs of growth, then the market cycle timing will be a high score. And uh for a more detailed explanation on market cycle timing, you can go to uh suburbdata.com.au. There's a data page there where we list all the metrics and one of them will be market cycle timing and have a complete explanation.
>> All right. So ordinarily I would never advise anyone to make an investment decision based on a single metric and market cycle timing is a single metric. But I'm using a single metric in this case for a couple of reasons. Firstly, I need data uh that can be dated back a good 20 or more years since I'm going to compare this to holding long-term and some people would argue that even 20 years is not long enough. Um, and a lot of metrics in property investing are quite modern. So the market cycle time is one metric for which I've calculated scores dating back beyond 1990 which is more than enough history.
Uh and the second reason I'm going to use a single metric is to prove a point about how easy it is to outperform long-term holding. uh if the simplest trading algorithm based on a single metric can come anywhere near the performance of holding long-term then surely more modern algorithms with um like dozens of metrics can beat long-term holding by an even bigger margin. So I need to lower that standard of decision making uh a long way to compare closely with with holding long-term. So the simulator starts off in 1990 uh looking for the best market as scored by market cycle timing. It then simulates a purchase >> in that market, holds the property until the market cycle timing has gone down again. Uh and that usually happens after a decent growth period.
Once the market cycle timing is half the nationwide median market cycle timing, that triggers a sell. However, if that happens within the first 18 months of of of making a purchase, then it's ignored because we need some some time to give the metric time to work. Uh so those are the very very um simple buying and uh selling rules. >> Do you factor in the DSR3 in any of it? So, for example, let's say that MCT is half of the national nationwide median MCT, what's the average at the moment off the top of your head? Do you know >> for the MCT?
>> Yeah, MCT. >> I think it's below 50 because >> let's just say 50. And then you're saying you're looking for something you exit once it gets to 25 for example, like half of that. >> But then it's a matter of what if the DSR3 is still really strong in that market. >> The DSR3 is what I would call a sophisticated algorithm. That's too good.
I'm bringing the benchmark down to a single metric to show just how easy it is to outperform holding over the long term. >> And the MCT is made up of, like you said, long-term growth, short-term growth. It's just not looking at like the last three years. It's capture. How far back does the MCT go? >> It only goes back 10 years, but it looks at the last 6 months growth, last year, 2, three, four, five, 10 years.
>> Would you go 20 years back or just wouldn't be worth it? >> Could do. there is a a cycle over 10 years. 10 years is usually long enough, >> but again, whatever inefficiencies or inaccuracies the MCT has, it's if it's the only metric we're using and we can still beat um holding longterm, and a little spoiler alert, obviously it it does, >> um then it shows just how easy it is to use a modern fullyfledged algorithm like the DSR3. >> So, reallocating equity. So, you got exit costs and entry costs.
Uh yeah, so I factored into the simulator the cost to sell a property which includes a 2% agents commission uh capital gains tax which is based on the growth the property has had up to the sell trigger >> and of course uh legal fees and in the simulator calc I've assumed property is owned in the investor's personal name uh not in a self-managed super fund. So the capital gains tax is much lower in a self-managed super fund. um making trading property um in an SMSF more more likely to be better than holding longterm, but I've assumed worst case scenario. And then to re-enter the market, I've factored into the simulator cost of stamp duty at um 4%. Uh I know there are some states that are higher than that. Uh depending on the price range, it might be higher than that.
more legal fees to sell this time and uh other items adding up to a total of four five%. So the simulator takes about 7% off the profit plus CGT. >> Mhm. >> So it's it factors in all these things. All right, couple more caveats to be aware of in the next slide. So I've ignored yield.
Uh two reasons for that. Firstly, doesn't date back far enough. Oh, that's another reason why I can't do DSR3. It starts from January 2010. So, I need to go back a lot further back to 1990. Uh, and yield yield doesn't date back that far as well.
[clears throat] Uh, and secondly, uh, uh, what was the second reason? So, yeah, it doesn't date back far enough. Uh, and it doesn't really contribute anyway to the whole of performance like yields. You think this This market has a 5% yield versus that market has a 3% yield. It's like 2% peranom. When you have a look at some of the capital growth that you'll see in these outperforming markets, 2% is nothing.
Just doesn't factor in. Um secondly, to overcome the inaccuracies of calculation of capital growth, uh I've aggregated data to the SA3 instead of a suburb. So, an SA3 is a bunch of suburbs, typically a couple of dozen. Uh, an SA3 is defined by the uh Australian Bureau of Statistics. It's it's probably closest to a local government area. >> So, what's an example of an SA3 for our listeners?
>> Uh, well, a lot of them have names very similar to local government areas. Um, so there's a suburb in western Sydney, Paramata, uh, that's quite local, but then you might have the post code of 2150, which includes maybe Harris Park. I think it includes maybe Northme or something like that. >> What about Rydermir? >> It doesn't go as far as Rymere, but I think the SA3 might get that close, but the SA3 is much larger. It'll it'll consist of um, yeah, dozens of suburbs.
>> Dozens of suburbs. Okay. >> Yeah. So the larger the area that we have, the more we can rely on the capital growth calculation as being accurate. >> So you got the highest one is like the SUA significant urban area which would be Sydney, >> Sydney, Melbourne, Brisbane, Perth. You can have small significant urban areas >> like uh King Aaroy in Queensland which has a population of only 10,000.
>> Uh in fact you can have >> I think you can have an SA3 that's bigger than an SUA. Yeah, they do exist, but they're they're they're remote. Anyway, so I'm just trying to say that we've got um SA3s here. There's about 330 SA3s around the country, not suburbs. And that's just so we can have more accurate capital growth calculations. And the third point there is it's only for houses, not for units.
All right, enough talk. Let's have a look at uh the first run of the simulator. Uh, so this is the first market that the simulator picked out. It's January 1990 and it was in Perth and it was the SA3 known as Perth City. There you go. There's an example.
And at that time, the market cycle timing was an impressive 78 out of 100. Uh, and about four years later, the market cycle timing had dropped to 17. from 78 down to 17 out of 100 this is uh and this triggered a sell the total growth over that time was around about 27% or 5% peranom so not very impressive and the total cost to recycle equity was 11.3% which consisted of transaction costs of 7.5% and capital gains tax of 3.8% 8% very low CGT because it didn't really perform so well. Uh and this ended up with a net gain of 15.2% which is the equivalent of 3.4% peranom. So first run of the simulator uh with this algo which is just the MCT pretty bad result. Um the next slide >> with the sorry with the entry costs I would have factored in a little bit higher closer to 6% but that's okay.
I know you're just doing it for modeling purposes. >> Bear in mind this is back in 1990. >> Okay. 1990. Okay. >> Yeah.
>> Fair enough. Good. >> All right. So here's a closer look at how things played out over those four years. So the purple bars are the market cycle timing score. That's a score out of 100.
And you can see the scale for that up the right vertical axis or y- axis. So the market cycle timing dropped significantly early on, but we couldn't sell because the rule is to hold for at least 18 months to give the market time to prove itself. >> But eventually it got down low enough to trigger a sell on the far right in April 1994. And during that time, this SA3, not a suburb, an SA3, uh it did experience some growth and that's represented by the turquoise line that you see there. And you can see the scale of growth up the left vertical y-axis. Uh there's a thin white horizontal line where zero growth sits.
Uh for most of the first two years, there was virtually no growth, but the second half of the period saw double digit growth. uh there may have been more growth but the rule is to exit once the market cycle timing gets to half the national median MCT for the same era. So if we were an investor at that time April 1994 we might have had a closer look at the market and decided to hold for a bit longer but this is just a dumb simulation dumb algorithm uh dumb trading rules. So without that kind of intelligence, it decided to sell uh just when the market was booming. Unfortunate and that's probably why it uh it performed so poorly. All right.
>> So back to that point. Let's just look at So when did we sell over here? We not selling. >> It was right at the far right hand side. April 1994. >> April 1994.
Okay. So you can see the sell trigger is a market cycle timing. It was 17 at that time but it had fallen below half the uh national median market cycle timing >> which over here. But then is that mean this growth number is that total or is that peranom growth. >> Uh so that is I think it's total growth. What has it got on this previous slide?
Yeah 37.6%. Oh no that's yeah that's total growth. That's total growth. So by from the start period zero. Okay. So yeah over four year period it's grown 25%.
That's right. It's total growth. >> Yeah. Yeah. That's right. >> Yeah.
Okay. >> So not much. >> So yeah the MCT is dropping and then that's sort of coming back at the back end. >> Slow down. >> I don't know. I didn't actually analyze it past that point but the uh the uh simple trading rules meant that I had to sell.
All right. This next slide is it's the same run of the simulator, but it's trade number two. So, this is starting off where do you buy after you've sold? So, uh the date now is August 1994. Uh which is 4 months after we sold to reflect the time that it takes to obtain the sale proceeds and then buy a replacement property. And the next purchase uh is in Orburn, SA3 of Orin.
It's in Sydney's western suburbs. And the market cycle timing was um 84 back then. Uh about four years later, there was a sell signal. That's when the market cycle timing came down to 24, which is perhaps indicating a peak. So the whole period was just a short was just short of four years. uh there was nearly 38% growth and the net gain was again pretty ordinary at only 5.8% peranom.
Uh so now that you have an idea of what these uh calculations are that are being performed, I'm going to speed things up a bit with this next graphic. So it shows all the trades for the first run of the simulator. So you can see that the first trade there in the top left uh that of the Perth City SA3 and then the buy and sell dates are shown in those turquoise tags. >> Mh. >> And the dark tags show the net gain. U that's after tax in percentage terms.
So you can see the second trade was to buy in the Orban SA3 of Sydney and the net gain from that trade was 24%. And then the trading algorithm picked out Frankston in Melbourne South. Uh note that this is the Frankston SA3, not a single suburb, but a set of suburbs. And the net gain from that trade was a fantastic 216%. And the next trade was the Mount Druit SA3 Sydney's West. And the net gain after tax was 58%.
Then it was Brighton in Hobart and then Bazewater Bassendine SA3 in Perth. Uh which it has not yet sold out of since I ran this simulator which was last in July 2024. Uh the most recent data is for the end of June 2024. Okay. So each of those uh dark teal tags shows the net gain in percentage terms for each trade. And to calculate the overall gain from trading over the last 35 years, we need to compound those gains together.
You can't just add them up. You need to compound them. And I've shown that in the bottom right. So it works out to the equivalent of 8.9% growth peranom for around 35 years and this is more than double the national growth rate over the same time frame which was total of 712% or uh 6.3% peranom. Interestingly, if you look at the sell at February 20, 2011, there's a pretty big difference between that 278% growth and 216 net. And I'm guessing the reason for that is, I'd say, the capital gain.
>> Yes, >> capital gain is the big one. >> Yeah. Whenever you have a big uh a big growth surge, CGT is going to be your biggest expense. Uh yeah and yeah so you can see that that the uh total growth uh for simulation run number one, 1800%. That's over 35 years, but the national growth rate was only 712%. So it more than doubled the national growth rate.
That's trading trading as opposed to just eeny meenie miny mo pick anywhere uh across the nation. Um, oh, and by the way, if we had held on to that Perth City SA3, we remember that was the first trade. >> If we just held on to that for the full 35 years, the growth would have totaled 834% or 6.7% peranom, which is about 120% more growth than the nation, but still less than trading. So, simulation one, we're off to a good start. Uh, but what if there was something peculiar about this case? It's just a one-off.
So, we need to look at multiple runs of the simulator to establish a general rule. And the next slide is simulation number two. So, it starts again from 1990, but this time it is not allowed to pick the best SA3. It has to start with the second best SA3. So I can't pick that Perth SA3. >> Uh and in this case, the second best SA3 was Hobart and Northwest Hobart.
Uh note that it took over a decade for the market cycle timing to drop before triggering a sale out of this SO3 which happened in October 2003. Uh the net gain after considering all the costs including tax was 81%. Now that sounds like a lot but remember this was over a decade so it's actually not that good. >> Uh and the best trade was the second one. the net gain uh was only 47% but it happened in a shorter period just over two years and the total growth for the entire 35 years was nearly a,000% which is well above the national growth rate for that same period of which was just over 700%. So this simulation run wasn't as good as the first run but it still has a success overall.
Okay, to save time again, I'm going to fast forward through multiple runs of the simulator and give just a summary. So, I ran the simulator a total of 20 times to make sure the first two cases were not abnormal. And each time I made the simulator pick a different starting market, uh the next best as scored by this uh MCT. And note that I cannot keep running the simulator in this way for more than 20 cases because the markets that it's going to pick will be less and less appealing because it can't pick ones that it's already picked on prior runs. So this slide summarizes the overall performance and this is what gives us the general rule for this trading algorithm. So the average net growth rate after tax for trading was 7.7% peranom while the national growth rate over the same time frame was only 6.3% peranom.
So trading outperformed the long-term national growth rate. Uh and the long-term national growth rate is the the key benchmark to beat because over the long term there is a tendency for all properties, suburbs, cities to grow at the same rate. And for an explanation of why that's the case, check out the what is it? Episode number 11, apples and oranges. It's called >> EBS. >> Yeah, EBS episode number 11.
All right. So how many that trading average growth how many cases did you say? Was it 20 cases you were saying? >> Yes. So 20 runs of the simulator. Yeah.
Each time it starts with a different SA3. >> But is it ordered like the the best, second best, third best, fourth best >> down to the 20th best out of 330. >> How long did that take to prepare? >> Oh, this took me ages. [laughter] >> Well, yeah. If you want to know if holding long-term outperforms short-term, you've got to put the effort in.
>> It's so easy to have an opinion. It is so hard to know the truth. >> What's the bottom bit there? So, you going to run through the rest of these, I guess. >> Yeah. Yeah, I will.
But I just want to point out that there's episode 11, apples and oranges. I got a note here. Yeah. In the previous episode, which was number 12, uh why you should focus on a short term. check out uh EBS number 11 and number 12 if you want more information about why over the long term um property markets grow at the same rate. Uh so anyway, the longer you hold a property for, less likely it's going to be an outperformer over the long term.
So the national growth rate is a good benchmark to beat when comparing trading to uh uh long-term buy and hold. Uh sorry, long-term hold. All right. So, the trading algorithm had a success rate, you'll see on the third line there, of 90%. Uh, that means it beat the benchmark in 90% of cases. Uh, the state capitals outperformed the nation as a whole, which is just interesting.
But, um, they had 834% growth, which works out to 6.7% peranom. Um, that's not always the case that state capitals outperformed, but they did for this period in history. and the SA3s within 10 kilometers of each state capital's CBD, they performed even better with 970% growth. And again, that's not always the case, as we'll soon see. Uh, I threw those ones in there as an extra benchmark because, you know, many of the old school uh, professionals that are still clinging to this long-term hold philosophy suggest that you should buy in an investment grade suburb, which is usually close to the CBD, a blue chip suburb where high income earners live. But those areas do not usually perform any better over the long term, but they did for this specific period.
But the trading algorithm still beat them by6% peranom. That's 7.7% versus 7.1%. Uh but the best five SA3s within state capitals were not the ones within 10 kilometers of the CBD and they had a combined average growth rate of 8.6% for that the p that that period. Uh and they actually beat the trading algorithm. Uh lastly, the number one market was the lower Hunter SA3 with uh can you believe it uh about 4,700% growth or nearly 12% peranom. Uh but let me just show you on the next chart please that lower Hunter SA3.
Uh so this SA3 could have some issues with the calculation of capital growth. uh it is a bit remote. It's not within a significant urban area. I noticed that from 1991 in the bottom leftand corner there's a sudden jump in growth uh which separated this market from the national growth rate quite significantly. So the historical data recorded a change in median house values from 30,000 to 50,000 in a single month. So that's 67% capital growth in one month.
um more than likely an anomaly rather than true growth. Um so this is an extremely rare chart because there are no crossovers between the two curves, no pinch points where one catch catches up to the other over a very long time frame. This is almost unheard of. Um another thing to notice is that most of the growth happened in a few short years. uh and there were years when there was practically no growth. Uh and that adds to the argument of holding for short-term stints is um is better than holding longterm.
And ironically, the advocates of holding long-term would never recommend a location like this to their clients. Uh they would recommend blue chip suburbs uh that they call investment grade that are close to the CBD within the large state capitals, not any state capital. And the lower Hunter SA3 is not even within a significant urban area, let alone within a state capital. So, uh, and that was the best SA3. >> I think the Lower Hunter, that's around Newcastle, north of Sydney. Correct.
>> Yeah. >> Now, the reason why these old school buyers agents wouldn't go there. Well, I believe this is the reason why. They don't have an office there. It's easy for them to do deals. They know the streets.
They know the coffee shops. They know their That's their argument. Oh, I know the area. What do you know about it? >> The coffee shops. I know the agents.
Like, at the end of the day, >> how does that help? >> That unit that you're going to buy me maybe in eastern suburbs of Sydney right now compared to one of these other markets. Like, you're telling me that that's the best market right now? I don't think so. >> Yeah. >> So, they can argue it all they'd like.
Show us the data. >> Yeah, that's right. And the data shows shows uh telling story the other the other way. >> All right. So, uh, just to ensure there was wasn't anything funny, uh, with the time frame that, uh, that I chose. >> Well, sorry, Jez, to jump in there.
One thing that's really interesting, like especially these days, there's going to be a lot of the old school buyers agents that are going to say, "Oh, these regional markets further out, they're getting pushed up by buyers agents, yada yada yada." But this is back from 1990 >> being a regional market. >> Okay, maybe like driving distance maybe to Sydney. I don't know how many people would maybe commute, but it's definitely outperformed the national average these markets. So, it'd be interesting to sort of go back further and see how these >> Well, I don't think there were buyers agents back in 1990. >> So, it's like, well, they're not pushing up the prices there. It's just interesting.
Now, that's their argument. Oh, we're not going to buy in in um Darwin or we're not going to buy in potentially Melbourne. Sydney's always better because I think so. >> Yeah. I'm I'm looking forward to hearing the next set of excuses that are going to come. All right.
So, yeah, just to ensure that there wasn't anything funny about that time frame that I chose, I repeated uh the experiment starting from a point in time uh 5 years later. So, now you're looking at the 30-year performance results, not the 35 year performance results. So this is running the simulator from a start month of January 1995 not January 1990 and the average growth from trading from the ALGO was 8.5% easily beating the national growth rate of 7% peranom however there were a few more failures so the success rate this time was only 80% uh the state capitals had 7.5% peranom growth uh so the trading algo beat the state capitals again uh the blue chip SA3s that is those SA3s within 10 kilometers of their state capital CBD they had 7.4% 4% peranom growth. So the algorithm beat them too. Uh the algo uh even compared favorably with the top five SA3s within state capitals. So if you had a crystal ball and picked one of the top five SA3s, uh you would have only and held long-term, you'd have only just edged out the trading algo after 30 years.
And lastly, the best SA3 for that 30-year period was Golden Malwari. Malwar, I don't know how you pronounce it, which is another SA3 outside of a state capital and not even within a recognized significant urban area. And let me show you just how unreliable that chart is. >> So if you go back that SA3 within the 10 kilometers, >> that's within 10 km of the state capital. But then what's the top five SA3s within the state capitals? Top five.
So is this up made up of 30 or something like what's the difference between these two line items? uh one's within the 10 within 10 kilometers of the CBD whereas the other one is is um top five anywhere >> in the state capital. Okay, perfect. >> Yeah. and that that best SOA3. So this is the historical chart for that best performing SA3 golden malwari malwari.
Uh as you can see uh this performance is more than likely not real capital growth but anomalies brought about by limited data for that area over that period of time. So you can see huge chunks of the history missing uh and then the sudden rise of over a,000% in only a couple of years uh and then a sudden drop again and a sudden rise again. So it's debatable whether the best SA3 even beat the trading algorithm uh for this time frame because we can't trust this SA3's data. And secondly uh the vast majority of growth happened again in a very short period of time. So, you didn't need to pick this SA3 all the way back in 1995. You needed to pick this SA3 in 2020.
And again, none of the advocates of holding long-term can point to this SA3 and claim uh holding long-term is better because none of them would ever suggest investors buy there. So, again, um yeah, more and more evidence to support um trading rather than holding longterm. All right, the next summary. So back before that, where is that data missing? Because it starts becoming consistent in around 2017. So where is that growth percentage peranom?
Because I'm assuming like Goldburn, MARI, they're established SA3s, aren't they? So why is that growth data missing? >> Uh well, they may be established now, but perhaps you know a decade ago they weren't. Um and yeah, >> but the thing is like Goldburn suburb that would have that's like already built out area. know when you think about it. >> Well, let's Do you want to look at it on a map and see where it is?
The Golden Malwari SA3. >> We can definitely try. Let's um let's All righty. So, we're just going to go maps control. But anyway, even though we've got missing data there, we can see the end to end. We can't see how it got there, but we can see end to end.
And we can see that the performance the outperformance was just for a short period uh not necessarily over a uh the 30-year period. >> So if you have a look, let's just have a quick look at the maps. Gold, where are we? >> Where is Malari? >> Malari. Okay, so we got we got Golden.
If we go further back, maybe if we just adjust the layers. Can't even see that well on the screen. Okay, so we got golden. >> Could you do golden hyphen malwari? I'll spell it out for you. >> Worry.
Just typed in moroy. That's the high school there. >> Okay. So, it's it's still pretty much just goblin. They're just using two names to name it. Is that right?
>> Yeah. So, it's like it's obviously Yeah. It's just interesting to see. >> There's a fair amount of real estate there. So, there shouldn't be missing missing uh values, but I mean it doesn't affect the overall thing we're searching for here. Um you can see on the far right hand side of that chart, >> Mhm.
It's not long-term growth, it's short-term growth that makes it look like it's a long-term outperformer. >> And you can see obviously the co the co >> kaboom. Yeah. >> Yeah. You got that big uplift, but then there's a massive drop in the growth rate which looks quite unreliable. >> Yeah.
So, there could have been like a uh a Greenfield estate open up and all of a sudden there's these new fancy pants properties that are selling in the area. Um and then uh they stop selling and uh comes back down to the old property selling. How much are they selling for? Uh a lot less. >> And this is about looking at consistency in the data. Wherever you're investing or even if you're already invested, what decision are you going to be making next 25 year performance?
>> Yeah. So um this is a 25 year summary. Uh again, trading beat the national growth rate. Uh this time with a 95% success rate. uh and it beat most of the benchmarks too except for the top five SA3s in state capitals. So far the simulator has been executed 60 times.
That's 20 times across three different eras. >> Uh and there are a couple more eras to show. >> I think the main thing is what I'm getting the success rate seems to be getting better >> the shorter the time frame maybe. I do actually the the there isn't really any consistency there. You'll see there isn't really a trend, but I'll show you the the 20-year trading performance. >> 95% now success.
>> Yeah. So, the 20-year trading performance, um 95% success, beat most of the benchmarks except for the top five. Uh the best SA3 this time was the LRO Valley, which is in Victoria. >> Uh I'll show you the growth chart for that SA3. Um few bits missing there. Pretty sketchy results, but the volatility is the uh giveaway.
Uh it does look like the SA3 did have pretty darn good capital growth, but once again, it's not an area that advocates of holding long-term would ever pick. Uh and once again, you did not have to pick this SA3 all the way back in 2005 because for the first half of that 20-year period, it tracked in line with the national growth rate. it only outperformed from mid 2017 to 2022 which is uh period of about five years. Uh so all the historical evidence uh that first looks like there might be a thin argument for rare cases of holding longterm it's actually turning out to be uh short-term phenomenal gains in locations outside of state capitals. >> Moving on 15ear performance. >> Yeah.
So this is the last one to look at. It's a 15-year performance. any shorter and we're not really talking about long-term. We can't compare it with long-term. And once again, uh, trading beat the national growth rate with a 95% success rate and it beat most of the benchmarks except for the top five SA3s within state capitals and of course Latroe Valley. All right.
So, uh, wrapping up, the data shows that outperforming over the long term is more likely by trading property rather than holding over the long term. And even a relatively dumb single metric algo can beat the long-term hold strategy. >> Would you call it dumb? I wouldn't call it that dumb, would you? >> It's a single metric market cycle timing. that, >> you know, when you look at the dozens of uh data sets that go into something like the DSR, >> I'd just call it isolate.
I wouldn't call it maybe dumb. I'd call it an isolated metric instead of looking at how many more metrics within the one algo. I think that's the main thing. Like you can obviously look at the market cycle timing, but I wouldn't use that as a pure algorithm to make your investment property investment decisions. It always should come back to the DSR3. >> Yeah.
And remember that each run of the simulator could not pick the best market. It had to go to the next best and the next best and the next best for 20 runs. >> Um and those rules entry and exit very simplistic. It's not using any anything uh sophisticated. It's not using artificial intelligence, not using human intelligence. So the performance could have been improved even more.
Um, so yeah, the reason why trading is superior is because of this tendency for all property markets to grow at the same rate over the long term. Uh, which means to get ahead, you're going to have to look at trading property. The longer you hold, the more likely you're going to get just average returns. So trading works by capitalizing on those sudden growth surges uh and this understanding of growth forecasts through through uh data analysis. So yeah, if you're ever wondering uh whether you should sell a property, um you do need to be able to forecast capital growth and we can help you out with that. >> Um we do have that service if you if you wanted to get in touch.
Is it >> Yeah, reach out to our website. website. [music] >> Yeah, suburbdata.com.au and you can just book a call in with one of our professionals. >> Yeah, I think there's a there's a well the best way is there's a help button in the bottom right hand corner. Big green >> help >> help >> or services. You can book a time in that way to have an initial discussion.
But that wraps up episode 13 [music] of the expert busting series. Uh join us next time for episode 14. Infrastructure projects, do they pay off? Thanks for watching.