PETER BAKKER | from Unhedged
PETER BAKKER | from Unhedged
A dead cat bounce is a graphic description of the price action we've seen in markets this year. Just when you think the markets are recovering they plunge again. Peter Bakker from Unhedged joined me talk about his algorithms and how they are reading the signals. Inflation is playing such a huge role and it's looking like there's a lot more pain to come
“And then we should, I think, always talk about inflation lately. Milton Friedman, he won several big prizes and a very famous economist. He said the primary cause of inflation is always the creation of money. And there has been so much money created. And that means that people will say now the inflation is transitory. They don't really understand what the base mechanisms of inflation are. And you kind of often see when inflation becomes more sticky. And that's when inflation goes and wages because data becomes a spiral. So if people get paid, more companies have higher costs, they have to charge those costs, or they will raise the prices and raising prices makes life more expensive.”
Peter Bakker is an algorithmic trading fanatic, a seasoned entrepreneur and marketing executive. Peter has been trading using algorithmic methods for 12 years, with Zipline, Keras and other AI platforms. He has exited successfully from Track4 and other smaller ventures. As CMO, Peter led B2C marketing for Aussie Farmers. He also has an INSEAD MBA.
"Another algorithm that we are running is about metals. So it looks at the industrial metals, so copper and iron, and, you know, things we use for as, as more hedging metal. So gold and silver and platinum. And what we then do is look at the relative performance and the relative trajectory. And then we decide whether it's more a bull or a bear market, we position ourselves accordingly. And then the last one we have live now is a, is a really interesting if you're a mathematician for me, it's interesting, an interesting model. It's basically a model which we call a hierarchical risk parity. So what it basically does, it looks at all the sectors in the US and then it determines how much risk the sector has, and then it basically underweights or overweights each sector."
TRANSCRIPT FOLLOWS AFTER THIS BRIEF MESSAGE
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Shares for Beginners
Peter Bakker (4s):
And the copper gold ratio has a very, very strong correlation with the 10 year yields. And if you graph it over the past 50 years, you say that's odd. That's so correlated. That's amazing. So what you see now is that the 10 year yield is wavering and is basically going down again, which is remarkable because we are in a highly inflationary environment. This highly inflationary environment, usually needs bond yields to go up, to stop inflation from running wild. Now the market says they won't raise that high.
G'day and welcome back to Shares for Beginners. I'm Phil Muscatello. And today I'm happy to welcome back to the chair, Peter Bakker from Unhedged, G'day Peter, how's it going?
Peter Bakker (53s):
It's going really well. How are you?
Good. Well, that wasn't the way you said it when you first walked in. We'd both been whingeing to each other, but so yeah, we talked, I think was in January, February this year,
Peter Bakker (1m 7s):
Beginning of the year
Phil (1m 8s):
For Unhedged which is an algorithmic trading platform. So just remind listeners again, what this is, because it sounds frightening and scary, and it's kind of like, we, you know, we're always hearing that the algorithms are running the market. So, you know, there's, it's almost like there's conspiracy theories about yup.
Peter Bakker (1m 26s):
The Tin Hats I can put my Tin Hat hat on and then tell you what we're doing. No. So Algorithmic investing is basically a type of investing, what is between passive and active. So yes, we take positions in the market, but we are guarding those positions every second. And the algorithms they work, what they, or what they go on probability. So they estimate the probability that there's a, a market route, or to estimate the probability that a company has bad numbers.
Peter Bakker (2m 7s):
And then it will decide to go out or go in. It's basically more flexible. The biggest difference between let's call them out, Spaceship, Stockspot, RAIZ and us is that those companies have static portfolios or they work with like five to seven ETFs. And it's a great way of investing, right? So don't get me wrong, but it's less flexible. So it's, it does always the same in the same market. So what we're doing, we have a universe or what we call it of the Russell 3000, which is the 3000 biggest companies in the U S
Phil (2m 47s):
And this is it's all US,
Peter Bakker (2m 49s):
It's all US
Phil (2m 49s):
Peter Bakker (2m 50s):
At the moment. It's only a US base, but later we will go into Australia and London and other other areas. Now it's only a US-based. So we take the Russell 3000 as our universe, and then we find the best opportunities based on the type of algorithm. So we have one algorithm that looks at momentum, and then it looks for where the bottom it predicts, where the bottom of the, of, of the curve is and it buys in and waits until it goes up. Another algorithm that we are running as a about metals. So it looks at the industrial metals, so copper and iron, and, you know, things we use for as, as more hedging metal.
Peter Bakker (3m 36s):
So gold and silver and platinum. And what we then do is look at the relative performance and the relative trajectory. And then we decide whether it's more a bull or a bear market, we position ourselves accordingly. And then the last one we have live now is a, is a really interesting if you're a mathematician for me, it's interesting, an interesting model. It's basically a model which we call a hierarchical risk parity.
Phil (4m 10s):
Sorry, repeat that again.
Peter Bakker (4m 11s):
Phil (4m 13s):
Peter Bakker (4m 16s):
Risk parity. So what it basically does, it looks at all the sectors in the US and then it determines how much risk the sector has, and then it basically underweights or overweights sector. So it's been amazing that this algorithm has been live from January this year to now. And it actually has done a plus 2%, which is remarkable because the US market has done what is still 12, 13%.
Phil (4m 48s):
And it dropped down to 20 something,
Peter Bakker (4m 51s):
23. It depends on which index. I mean, the NASDAQ went down almost to 30, right? So it's painful. And, and so this is the biggest difference between static investing and more dynamic. What we're doing is that our primary goal is not to lose too much money and the absolute best of investors, they say, I don't care how much I lose, I'll just add money. Right? So this is just a different view and,
Phil (5m 19s):
And ride out those market ups and downs. Yeah.
Peter Bakker (5m 22s):
Yeah. And the elite tend to lower the volatility quite a bit. And that's, that's important for people's heart, right? Because if you don't lose too much, you don't have to earn it all back. I've we, we have accounts with all our competitors and in the same period that this algorithm that is a positive, we, we saw some of our competitors going down 47%, which is horrible for people who were invested.
Phil (5m 54s):
So Peter is your background in mathematics
Peter Bakker (5m 57s):
In the end, I'm a statistician. Is that mathematics well for a lot of people that is. Yeah. So I started, I'm an old man, right? So I'm started studying 8 91 after I came out of the army and I started studying rocket science or aerospace, they call it them. The technology is a lot about mathematics and models and very interesting, but I missed really human side. So then I started to do a second study next to it, doing sociology and
Phil (6m 32s):
Peter Bakker (6m 34s):
That's, that's polar opposite. I just fell in love with it. And then, because I'm really like a math guy, I decided to do statistics. Statistics is now basically the only thing I'm doing.
Phil (6m 49s):
So how, how does the maths work in there? Sorry, I don't, I know that you're, if you can't give really specifics about it, but there's a lot of people who say, well, you can't second guess the markets, you can't predict the markets, but are there, is it kind of like a pattern identification thing that you're doing? Or
Peter Bakker (7m 7s):
So basically you have to go back to the types of statistics. There are. So I grew up as a, what I call a frequentist statistician. Right? So that's how frequent does something happen? Then in last 20 years, Bayesian statistics came, became more popular and Bayesian statistics basically looks at the probability of something happening. And then also how influential the event is. That's good. So basically, so sometimes you hear people talking about fat tails.
Peter Bakker (7m 48s):
So if a fat tail is there, then there's a high is a, there's a relatively high probability that an extraordinary event can happen. But it depends on how big the result is. So in real life, in nuclear war, the probability of that happening is really, really, really tiny, but the effects are devastating, right? So it's still important that you still consider that scenario because the effect is so big. So if you have daily events in your strategy that could wipe you out completely, you still have to consider it while a frequentist would say, oh, the chances are nil.
Peter Bakker (8m 33s):
So I just ignore it. And that's where I use. I don't know if you remember 2018, there was a fund in the U S that blew up on a strategy on gas and options. And suddenly the gas moved in a very different direction for whatever reason. And the whole fund blew up immediately. So what they did is they ignored that tail risk. While if you are a Bayesian statistician, you would always cover your tail,
Phil (9m 4s):
So that's almost like an individual investor needs to think about their tail risk as well. Don't they?
Peter Bakker (9m 9s):
Yes, absolutely. Absolutely. I mean, I think a lot of investors who are in crypto have found tail risk very in their face, right? So the tail risk of the model of Luna not working was actually very much there, but most people say aah those guys as so smart. They
Phil (9m 31s):
Is that the brokerage that you're referring to
Peter Bakker (9m 32s):
Luna Luna was the, the coin that imploded. Oh,
Phil (9m 37s):
Peter Bakker (9m 38s):
That set off basically a whole chain reaction of events. And, but does chain reaction, that's also like a tail risk, right? So we could all say the broker is just, oh, they were safe. Yeah. But there was tail risk that's something they invested heavily in was going to implode. And they didn't really see that. But we have in our space, we have usually better regulations around that. Right. So, because UnhedgeS is a, is a regulated entity. We, we are not allowed to take those risks and we won't take them. You have to describe any risk in our PDS.
Peter Bakker (10m 19s):
And we have, of course, an audit procedures to, to take away all the tail risk.
Phil (10m 24s):
And of course you should consult a licensed financial planner if you, before investing anything.
Peter Bakker (10m 30s):
Oh, no, absolutely. And, and, and often, often people will say that out of like, you know, you should talk to a financial advisor, but in real life, your, your life will change all the time. Right. So your strategies would also be adjusted to it. And if you do not want to put the effort in to learn about it, which most people have better things to do, raising the kids and doing, doing fun, to be
Phil (10m 55s):
Passionate about it too.
Peter Bakker (10m 58s):
Like you, I mean, you just love to talk about this stuff and I do as well, but a lot of my friends say, oh yeah, that's you. Yeah. I'll just invest.
Phil (11m 15s):
Well, the reason why I asked you back, I mean, first of all, I know that you are going to be bringing a couple of products out to market, which we'll talk about in a moment, but I guess just from my own personal experience, and again, please don't do anything based on what I'm saying here. Don't listen to me for financial advice. However, I put a little bit of money into Unhedged earlier in this year, when you first launched, as I was very surprised at about how little it went down, compared to how much the US market went down. And now we're at a point where the US market has been recovering. And it's been going down a little bit more
Peter Bakker (11m 48s):
As a recovered. So what are the
Phil (11m 50s):
Peter Bakker (11m 52s):
Well, the algorithms are looking at probabilities and the probability that this is a bear markets bounce, or a bear market rally, or a dead cat bounce, or how are you called it?
Phil (12m 4s):
And I'll just, I'll just date stamp this, because this might be a couple of weeks before it comes out. So we're recording on August the 17th. So things may have changed, but anyway,
Peter Bakker (12m 12s):
Yeah. So if you look at the bottom of a curve is hard to detect, right? So because the curve always has like bounces in it and you don't know how the bounce, how high the bounce can go. Now, if you look at the current market situation in the U S we're now around 4,200 and a S&P, which is kind of a critical level, and it's a critical level, not because of any technical analysis, but if you look at the volume traded around that level, it's a, it's a very substantial traded level.
Peter Bakker (12m 52s):
So if you cross substantial traded levels in, in the markets, and there tend to be a large group of people that are either in profit or loss, so people will decides either I'll jump out, because now I'm again neutral or I will short it,, or I will double down, I saw it as basically the three of the three things you can do.
Phil (13m 19s):
And these guys opposing forces yeah. Acting
Peter Bakker (13m 21s):
Against it. Exactly, exactly. And why are bear markets rallys so vicious is because of shorting in general, right? So people go short. It means that they sell a share they don't have a, so you borrow a share from somebody else, and then you sell it. And if you are short, then you profit from when the market goes down. Now when the market reverses, now you start to lose money
Phil (13m 46s):
As a guys up again, as
Peter Bakker (13m 47s):
It goes up again. And then all these people who are short, they have to buy have to buy back their assets to get it back to, you have to give it back to the guy, where would they borrowed it from? And so it means that these rallies are becoming often very vicious, very, very steep up until all the shorters are again neutral. And then it's the question of whether the bulls take over and run further, or weather it neutralizes. We're right in that phase. So, and by the time you publish, we probably know what happened, but the algorithms indeed are still defensive.
Peter Bakker (14m 27s):
And they're defensive because the probability that this is a bear market rally is still substantially high. And as a few things that are really standing out, and I know my own models, so I will pick out a few small nuggets and points. Yeah, yeah. But one of the things is that you have a ratio it's called the copper gold ratio and copper gold ratio has a very, very strong correlation with the 10 year yield. And if you graph it over the past 30 years, you say that's odd. That's so correlated. That's amazing. So what you see now is that the 10 year yield is
Phil (15m 9s):
Which is a bond price and
Peter Bakker (15m 10s):
Volatile price off of the 10 year bonds that the US treasury treasury sells that that bond yield is wavering. And it's basically going down again, which is remarkable because we are in a highly inflationary environment is highly inflationary environment, usually needs bond yields to go up, to stop inflation from running wild. Now the market says they won't raise debt high. They won't raise beyond three, 4%. We don't know if that's what will be true, but that's what the market now says.
Peter Bakker (15m 51s):
Which basically means that if you look down at the copper gold ratio says, actually there will be a recession. If there would be a recession, the market would go down. But if the rates go down, then the markets will go up. So these are basically very contradictory signals. The moment a AI or machine learning model find contradictory signals, it usually does one of two things. It does nothing or does something defensive. And our models are programmed very defensively. Because as this old adage, if you lose 50% of your money, you have to double it again to become neutral.
Peter Bakker (16m 33s):
If you lose only 10% of your money, you only have to make 11% up to become neutral. So our models are programmed to be very defensive and not to lose too much when the market goes down and try to profit from the way up. But it always means that we miss in general, the first tick up. So does that answer the question is a little bit of a, of a long winded.
Phil (17m 2s):
No, it's a really interesting insight to me, you know, to, to see how markets work, because obviously in these figures, in these ratios is a lot of market psychology is wrapped up in it. And the mentality behind the people in the industry that are affecting the movement of the money in and out of the markets. Yeah.
Peter Bakker (17m 23s):
Yes, yes. And then we should, I think, always talk about inflation lately. Milton Friedman, he won several big prizes and a very famous economist. He said the primary cause of inflation is always the creation of money. And there has been so much money created. So around
Phil (17m 44s):
The world, around the world insane amounts of money.
Peter Bakker (17m 47s):
And that means that people will say now the inflation is transitory. They don't really understand what the base mechanisms of inflation are. And you kind of often see when inflation becomes more sticky. And that's when inflation goes and wages because data becomes a spiral. So if people get paid, more companies have higher costs, they have to charge those costs, or they will raise the prices and raising prices makes life more expensive. And then it's just, for me, something always fascinating is all, all these movements of these currencies, right?
Peter Bakker (18m 27s):
So why do they move? And which is extremely fascinating. Lots of people make lots of models about it. Nobody knows exactly what's going to happen because it's, it has to do with so many factors and that's, and that's frankly Phil why I think, and my team thinks. And a lot of our clients think that algorithmic investing is a lot more accurate way of investing than static rebalancing. Is that the world is not a linear place. This is not to come to a line from a to B all the things in the world are nonlinear models.
Peter Bakker (19m 10s):
And if you add non linear models to each other, then the effect becomes so hard to see,
Phil (19m 18s):
Is this the old butterfly in the Amazon Hurricane?
Peter Bakker (19m 24s):
Well, that's more about the effect, that effect of, of things that you cannot see, but our world of economy exists out of thousands, millions of processes, which are all non linear. So yes, often we can find a pro probability of something happening, but that doesn't mean that it will happen. That is a probability,
Phil (19m 52s):
Well, let's have a chat with about the new products. Oh,
Peter Bakker (19m 56s):
Very exciting. Yeah. Very exciting. So we asked our clients, so what would make you invest more? And they answered three things. The market has to go up, crypto and ESG or, or responsible investing. And then we dug a little bit deeper and also looked at why do people invest as basically most people invest for growth. So they want to build their nest egg for whatever goal. And then you have a group of people who are all older. We say, well, I want to park some money and then get every month, month money out. So
Phil (20m 34s):
That's income generate
Peter Bakker (20m 35s):
Income or, or in the end eats part of your capital budget in a very responsible way. Hmm. So the first thing we're going to launch is what we call a climate and society, positive investment strategy. We did a lot of analysis on all the goals of the Paris, 2015 agreements. And we looked at how can we invest in companies that as a whole will either have limited or positive influence on the climate. So they basically reduce their hot house gases.
Peter Bakker (21m 15s):
Then we looked at, okay, there's not only the companies, for example, Apple. So not only what Apple does, but also what Apple forces their supply chain to do. So what we did is made a massive model of all the companies in the U S we made a, what they call a graph and we looked at all the supply chain. And then we look at how the supply chain and the companies on top are improving because we believe, and I think more and more scientists are, are in the same camp. This is not about an absolute number. This is not only about this house should only have this much exhausts or this corner guard company should only do X it's about improvement because every improvement is a conscious effort.
Peter Bakker (22m 4s):
You cannot improve without actually trying. So if we see that the supply chain is improving, either the management themselves do it, or they get forced by their clients. So that's the hypothesis. And what we have seen is that if you look at the long-term and is this really predictive? Yeah. We look at whether their costs at the end of the increase because of climate costs because of taxation, because of other elements or customers leaving them, or whether their revenue can be enhanced by being more climate friendly and society friendly. And so that's what we did.
Peter Bakker (22m 44s):
And we found a model that actually does as good as, or better than the markets at times. And we expect that this will only grow. We still have to go through all the regulatory hoops because ASIC has made a lot of guidance around greenwashing
Phil (23m 2s):
It's one of their major targets at the moment
Peter Bakker (23m 6s):
Doesn't it? Yeah. And, and, and, and good for them. Right. Because greenwashing is horrible. If you look at most what they call ESG ETFs or responsible investing ETFs yes. They're full of companies like Google, Apple, for example, NVIDIA. And NVIDIA was a fabulous or, or someone who did not produce any physical product right. For, for a while. So they were called fabulous. So they were an ESG a company because they didn't have a physical product, now making bought themselves and nowaday went down into rankings.
Peter Bakker (23m 46s):
Oh, that's silly. Right? The fact that a company doesn't make a physical product doesn't mean it's a climate positive company. There's a lot of more variables that you have to take into account. If you, I mean, for people who like climate positive investing, they really should look at the ETS they invest in and what's in it. If you look what's entertaining, I think, but that has nothing to do with the climate. And that's the fallacy we want to, we want to really step out of, we say, what if we just look at companies consciously improving it's the progress and the process we think we should promote rather than the end goal, because the end goal, even if we get at the Paris agreements, we will have another goal behind that.
Peter Bakker (24m 36s):
Right? So it is just a pro a process. And we should really help companies to say, okay, we invest in you because we believe that you do this consciously. And there is a conscious effort.
Phil (24m 47s):
And then the income fund,
Peter Bakker (24m 49s):
The income fund is, is, I mean, there's plenty of income funds for, let's say very rich people, right? So they, they, they put a part of their, their, their money into annuities. And then they get every month, a distribution for people who have funds that they want to do that with, but still wanted the fund to be available. It's really hard to do that. And so what we have done is created a model that basically looks at companies that have very good, sustainable dividends and high yield bonds. So companies often have bonds that although they have enough cash to, to do the project themselves, they just want to borrow the money to do it.
Peter Bakker (25m 37s):
And those bonds are paying a good coupons and good, good interest. And they're pretty safe. So although the model will go up and down a little bit, I have with the markets and what they call multiple expansion and contraction in the end, the goal is to create a steady income of let's say three, four, 5% a year, and then letting people get that money every month. So we are launching next month auto-invest invest. So that's basically after your salary get paid. So you, you invest automatically, which is the best way to get rich in the end.
Peter Bakker (26m 18s):
It's just to invest every month, same time every week, same time. We also go into reverse that, or we have an auto withdrawal. And that means that people can say, oh, I've put a hundred thousand dollars in here. And I want to get every month, a thousand dollars from it, and then eat slowly a little bit in the capital, but they know they get every month.
Phil (26m 38s):
So it becomes like an annuity, really?
Peter Bakker (26m 40s):
Yeah. But then when you need your capital to buy a new car, or when you buy a new house, you still can get it.
Phil (26m 47s):
That's flexible, completely
Peter Bakker (26m 48s):
Flexible. It's totally flexible. Well, if you have an annuity you usually have to lock it down for many, many years, and even they calculate it such that the whole principle will be gone by the time you die. And they take a risk on that, right. It's a different type of model. So we, we really believe that it's your money, you should be able to access it any day. Anytime you want,
Phil (27m 13s):
When you're investing in Unhedged, can you weight your portfolio into these different kinds of models that are being offered?
Peter Bakker (27m 23s):
Yeah. Most people take equal weight and equal weight means that you're just taking equal part of the algorithms. And that means that in back testing that showed the least volatile outcome. But with launch of the new models, they are more theme-based. Right. So the climate and society positive model, it's more about whether you think that's more important than to have a very diversified portfolio.
Phil (27m 53s):
So it becomes opt in, does it? Yeah.
Peter Bakker (27m 56s):
Yeah. And, and so you can put a hundred percent in climate positive. You also can put a hundred percent a yield if that's what you want, but you also can create a portfolio all over. Right. And say, listen, I want the machine to calculate the best weighting across all those. And we expected actually more people to make their own weighting, but we see most people say, let the machine do it for me. Yep. And, and that's, I mean, as you have seen that gives a result that is less volatile and for most people does what it needs to do.
Phil (28m 32s):
Fantastic. So if people want to find out more about Unhedged
Peter Bakker (28m 36s):
Go to unhedged.com.au,
Phil (28m 38s):
And there's an app as well,
Peter Bakker (28m 39s):
There's an app, right? So you can look and in the app stores on there Unhedged don't type Unhinged, because as a Dutchman, people say, sorry, you said unhinged and had
Phil (28m 55s):
Peter Bakker (28m 55s):
And I just, we're launching a, a referral, your friend model in the next few weeks. So you can earn $10 if you refer your friends and yeah. Just try it out.
Phil (29m 9s):
What's the minimum investment
Peter Bakker (29m 11s):
Minimum invested in is a hundred dollars. It's really cheap. Cheap is really low. What we've seen now is that a lot of people, they try with a little amount of money. So like two or $300. And then after a month they just add thousands or a few thousand. So it's remarkable that we see a lot of people trying it. And then when they see that indeed does what it shows you do, they put more money.
Phil (29m 41s):
Fantastic. Peter Bakker, thank you very much for joining me again today. If you found this podcast helpful, please tell a friend, especially if it's someone who needs to start thinking about investing for their future, you'll be helping them and helping me to keep this show on the road.
Chloe (29m 55s):
Shares for beginners is for information and educational purposes, only it isn't financial advice and you shouldn't buy or sell any investments based on what you've heard here. Any opinion or commentary is the view of the speaker only not shares for beginners. This podcast doesn't replace professional advice regarding your personal financial needs circumstances or current situation.
Phil (30m 14s):
And thank you for listening to my podcast.
Shares for Beginners is for information and educational purposes only. It isn’t financial advice, and you shouldn’t buy or sell any investments based on what you’ve heard here. Any opinion or commentary is the view of the speaker only not Shares for Beginners. This podcast doesn’t replace professional advice regarding your personal financial needs, circumstances or current situation