Dan Murphy: What’s up, everybody? All right. So fine in here. What’s going on? Prasad? All right, I’m just going to clean up my desktop a little bit here. We’ll get the show on the road. Howdy, Russ? All right.
I have to clean up my desktop. I have a lot of action, man, this is going to be a lot of fun. I’ve been really looking forward to this training today, and I just want to make sure everyone can hear me and see me.
Is that camera a little crooked? There we go. Not bad. Get a little extra light. Mood lighting. Let’s get the mood lighting in here, as the former Kevin Samuels would say, right? Yeah, all right. We’re good.
Is everyone saying hi? Okay. Like I said, I have to scoot some things around here because I got a lot going on today. A lot to cover. Let’s see. Everything’s coming in louder. It says Randy. Hi, all.
Hey, what’s up, Tom and Mark Allen. Greetings to you as well. Courtney. Richard, Michael, Brennan. Dan Carrey is here as well. Good to see some familiar names. Nalini. Yeah. Let’s get going here. Get the show on the road here. And I’m just going to move a couple more things around so I can see a lot better. There we go.
Okay, so we have a lot to cover today, guys. So, I’m going to go through kind of fast, I suppose, and we’ll go ahead and save the questions for the end.
Am I on camera here? Okay. Because what’s going to happen, guys, is this is going to be recorded, and I need to move this camera a little bit. Speaking of which, wasn’t really facing me here. There we go.
Not that I have to have things ultra-perfect or whatever, but this is being recorded and it will be turned into a bunch of bite size videos for your viewing pleasures. It’s going to be really cool. “Great sunny day for PB,” says Jack. Awesome. Okay.
So you are in the right place if you want to go ahead and make your portfolio look like this. Hopefully on your screen, you can go ahead and see this Meta strategy here. And this is a simple demonstration. It was very easy to create and the rules are very, very simple.
So, I’m going to ask you a few questions, though, if that’s okay first here. I want to go ahead and have a lot of participation in this class. I want to make it interactive, but again, I am going to have to ask you to write down any questions you may have so we can circle back around to the Q&A section, and that way I can just go through each piece and each chunk of this video here.
So, let me know in the chat, why did you get started in trading in the first place? And while you enter that into the chat, make sure you select everyone in the chat there instead of just panelists and hosts, that kind of thing. Just select everybody in there. How big is our class today? Okay, it’s a good size. Good size. Awesome.
I like seeing things live. That way I can interact with you all. It’s like doing a comedy routine, and you’re just by yourself when I do some of these videos. So, it’s better to have a nice live audience to do it, and I’ll feed off of you guys as well. Craig says, “Freedom.” “Make some money,” says Robin. Okay. “Freedom,” says Gary. “Financial freedom.” So, I’m noticing a trend over here, so you guys are definitely in the right place, if that’s what you’re looking for.
“Take control of my financial future,” says Randy. Mark says, “Life security.” Arthur says, “Love it. Make more to give more.” I like that Chris as well. And I was just telling a friend about that I did a lot of charity work until their lawyers got mad at me for—I don’t know, I sent over too much money to Make a Wish. That was really weird. I guess you can’t use their logos or something. That was a really odd charity event, for sure.
“Control of my own finances,” says Brennan. “Retire happy.” Okay. Alan says curious, it was 1966 by mail. Okay. I think that “financial freedom” is basically winning out on this whole deal here, which is not very surprising.
Let’s do another question here. Why is trading better than many other businesses? Go. “For me, it’s the commute. There’s no commute to work.” We’re not messing around with employees. Leave that to me. But unfortunately, I had to develop the tech. No one else has this. And I had this dream, and I’m like, “Wow, I got to start the company.” I have to do it. I kind of like that too. Who was I talking to before we were chatting it up? Was it with Russ? Was it with you, Russ? Yeah, I think it was Russ. We were talking about the discovery and just being along for the journey.
Russ is one of my one-on-one private clients as well. Salt of the earth, fella. Good to see your name on here as well. There he is. “Liquid. Spend the time you want.” Yes. “Cool and flexible, control the future.”
But yeah, a lot of times what I’m more interested is not necessarily the money, although that’s a nice perk for sure, and money does solve a lot of problems. Don’t let anyone tease you about that and steer you wrong.
But for me, it’s the discovery. And so that’s why I had to start this company, is to discover all these really cool things, because not that many people will share all the cool goodies that go into an AI trading company.
Okay, let’s see Allen saying, “The ability to use creativity, direct your own path.” “Control of my life,” says Mark. “Time. Time,” says Dan. I like it. So we are on the same wavelength. Let me make sure too.
And there’s a method to my madness, why I’m asking all these different questions here. And let’s go ahead and talk about what you’re hoping to get out of today’s Meta AI training. Let’s talk about that.
Obviously, it’s probably both of the above, but what else? Is there anything else that you want to get out of the Meta AI training besides what you’ve already answered for financial freedom, that sort of thing?
Courtney says, “It’s on me to succeed or fail with maximum flexibility.” I 100% agree with that. And you’re talking about family and charity activities. 100% agree that this is the ultimate in meritocracy.
Now, they’ve been talking about those ESG and equality of outcome, which is communism. It doesn’t work in society. That’s why it always blows up. And I’m thinking right now of— as you guys enter your answers. I mean, I’m thinking of Prices Law, which is that half of the productivity comes from the square root of the number of people. So you could imagine as the number of people grows, a very small percentage, actually—folks like yourself are responsible for all the growth. And that’s the ultimate meritocracy, right? And that’s why really quickly people have learned on really quick that, boy, when you fail, then you don’t know as much as you thought you did, right?
Let’s go to the chat here. “Better trading with less stress,” says Dan. Okay. I see Terrence wants to learn how to set things up. “Meta strategy is smooth as a chart. You’re showing consistency,” says Mark and Dallas, “Maximizing returns and stop listening to financial media.”
Yeah, especially after all that crap with Kramer. Boy, I swear, allegedly Kramer is just unloading crap to you guys for his buddies as things collapse. It sure looks that way, doesn’t it? We were joking around that Kramer just needs a 200-day Moving Average.
So yeah, there’s a reason I bash on these people; they’re terrible, terrible. I see, “failing is learning, not failing.” Okay, we keep going here. “Develop smooth rising equity. Very specific direction on where to start with Meta.”
“AI recommendations for improving,” says Courtney. I like that. “Better workable understanding of PBs.” And, “Can you put the Kramer inverse ETF into PB?” says Terrence. Well, I’ll tell you what, unfortunately, that doesn’t have enough history but we all know it’s probably going to work.
And in fact, there was somewhere I was looking up, it was a Quant Fund where they shared a strategy that they would short just about anything that Kramer mentioned. It was hilarious.
Okay, did you guys get that email I sent? There was a handout, by the way. I want to make sure you guys got the Excel handout with the Josh 100 returns, okay? I’m seeing a lot of yeses in there.
One more thing: this is going to help steer me in the right direction, the proper direction for you guys, is type in the chat right now, what kind of annual returns you’re looking for? Annual returns, what do you want to make on average? And please don’t say a million percent. I’m pretty sure this group isn’t going to say something like that, but let’s be realistic here. What are you guys looking for? 60, 80, 30, 60, 10%. Anything above that would be awesome. 100, 150. “Over 200%,” says Richard. Okay. “65.” “40,” says Nalini. Maybe Nalini is the voice of rationality here. “Over 100,” says Robin. The problem that we’re having right now is actually throttling this thing back.
So it’s a lot like a racehorse, right? So there’s a lot of new things that as we go through this. I’m going to describe things that are going to be…There’s like three features that are going to be part of Portfolio Boss in the very near future.
I don’t think it’s going to be a big deal to add, but right now, we have to throttle things back. And that was one of the reasons I gave you that handout as well. Let me see if I can… I’ll drop a link into the chat real quick as well.
And by the way, I’m expecting this, and I think I told you in the emails, I’m budgeting in two hours for this call, and that includes the Q&A. And I’m going to go in here to Dropbox real quick and see if I can find…There we go. And I’ll copy and paste that link into you… This is being recorded, but if you do leave early, you won’t be able to ask me questions live here, but you will get the recordings. Like I said, we’re going to chunk this up. I have this completely outlined and so everything is done with a purpose here.
All right, so we’ll circle back to the Josh 100 real quick. Actually, we’ll just take care of that right now. I’m going to go ahead and move my screen over so you can see all these strategies.
Should I show it all at once? I’ll dial it back a little bit here. There we go. Screen share. And like I said, just hold your questions for later. But if I’m messing something up because I’m known to forget to switch the windows around as I’m looking on this gigantic big screen TV right here, let me know in the chat. So that’s happened before. It wouldn’t be the first time.
Josh 100 Strategy
Okay, so we have all these different strategies and your annual returns next to them. And what I did was…Josh was nice enough to give me the spreadsheet, and then it shows some returns since 2017 in there.
And then I kind of turned this into different subcategories. So, you have single stock strategies here on the left. And I’ll keep going down. Some ETF strategies, some high-octane strategies, because what’s happened in recent events is there’s a lot of these 2X and 3X of normally volatile ETFs and their inverse that have been coming out over the past several years.
Now, if you are possibly like Nalini, then there might be some that you might want to take out—at least for now. And so I’m going to be covering more about that later. So I just wanted to open that and share it with you.
And here on the right-hand side, I divided things into subcategories to make it easier for you to look at and see strategies you like, which ones you might not want to keep, and so forth.
And then there’s a decent amount of information that these are leveraged funds right here. You guys can all see that, right? Let me hit Cancel. There we go. Don’t need that data. All right, I’m going to switch windows here and get back to the cool stuff.
So, you guys did give me a great idea of what your expectations are, and I think that we can do that pretty easily. And again, it’s because we’re really trying to throttle things back at this point.
So, let’s see Daniel saying, “I’m not getting sound.” Okay. Sorry, man. I think everyone else can hear me fine, so it might be something on your end. Okay, so we’ll you’ll keep going here. We’ll keep going here.
The Importance of Trading Multiple Strategies At Once
So, let’s go talk real quick about the importance of trading multiple strategies at once. Well, I think that the most important thing is we already have an extreme demonstration of what happens when you trade 189 strategies all at the same time, and each with a tiny little percentage, obviously, less than 1%.
And that’s what Josh Jarrett did. Is Josh in the chat today? I’m not sure. Josh, he works for about 15 minutes trading those 189 strategies. That’s how he got into the top five over at FundSeeder out of 18,000 traders, which is a—Bravo, my man, bravo. That is amazing.
And so that is why it’s very important to trade a whole bunch of strategies. But of course, this invention makes it so you don’t have to actually trade 189, thankfully, due to a new technology here that includes cycle reversals.
Is Josh here. Yes. There he is. I was wondering if you were going to be busy running all your gyms and stuff, because a lot of people don’t realize that. I know that you’re getting away from possibly gym management, things like that, but it only takes you, like, 15 minutes a day to run your trading business.
And I want to emphasize the word “business.” This is all about having a trading business. Josh does take a stipend or a dividend every month to pay the bills, man. So that is part of what he does. And that’s why it’s so important to trade a whole bunch of strategies at the same time, because what it does is when one strategy zigs, the other one zag and they make up for it. If one strategy happens to blow up, it’s no big deal.
Now I’m going to go ahead and show you how things used to be done. So I’m going to go out here and click on the little hamburger icon here and go into Strategy Management.
And I’m going to be going through meticulous detail, by the way, during this whole entire training because I want to make sure that no stone is left unturned. And please do write some notes. You can go old school with a— I’ve got a pen and paper right here for the notes that you guys asked me, so you guys can do the same thing, too.
Let’s go ahead and we can basically create what strategy used to look like here. And this is what I learned over in the Turtle Trader Group many years ago as a beta tester for Turtle Trader, and he was one of the originals that tutored under Richard Dennis and Bill Eckert. And we’ll just create a multi here.
And you guys don’t have to follow this too much here. I’m just going to create, real quick, a multi strategy just to give you an idea of what that looked like and how quickly that can be done in Portfolio Boss.
So, we’ll just call it Multi Live Class. There we go. So, I create the little framework in Portfolio Boss here, and then all I need to do is add some strategies to it. And guess what? Thanks to Josh, I’ve got a whole bunch of his strategies.
I’m just going to start randomly clicking here. That’s just random. We’ll just do random click-click-click. Okay, I’m done. And then what we would do is you would individually, manually just go in and select what percentage of these you would want into each of them.
So, I don’t know how many times I clicked, but maybe it was like maybe it was 20 times. And then you have 5% into each strategy here. And this is probably going to look good. I’m not going to lie. This is probably going to be pretty decent looking test here. As just quickly go through this and just put the number five into each of these here. Okay, I think I’m done. So that was pretty easy, right?
I’m sure Josh would like it to have a button there where each percentage was automatically updated so he didn’t have to do that with 189 strategies, as I’m pretty certain that he had to do here. But look how easy it is to create a trading business.
Now this is the old way. It should look pretty smooth, is my guess. Yeah, does look pretty smooth. Nice. Get some good numbers. CAGR is kind of low, but overall, this is already a trading business. Me randomly just clicking on Josh’s 100 strategies.
This looks great. Nalini would like this, right? You got the 40% compound on the growth rate. You get your max drawdown pretty close to about nine. World class. This is world class. A lot of people don’t understand and I certainly didn’t back in the 90s when I first started, I didn’t realize that 20% a year was just amazing.
But let’s forget all this. We’re not here just to go with the old technology. Let’s go back into our meta test in here. And this, by the way, is a new search function in Portfolio Boss. Pretty cool.
I was like, “Where have you been my whole life?” This sure makes—when you’re dealing with hundreds of strategies and all kinds of instruments, let’s say I wanted to go look up…. But I’ll save this for later. I don’t want to get too distracted, actually, since we’re doing things section by section.
But here’s the new way of doing things, where you have Josh’s 100 strategies in here, and they’re all loaded up. And then we just want to trade the top 20 I had in this example. And here is the end result, the Compound Annual Growth Rate, 151%. I think you guys kind of like that. This is dialing it back, too.
I’m not trying too hard to go with Compound Annual Growth Rate. I was actually looking for a high win percentage for winning months, about 95. Very stable between our in-sample, out-of-sample, which we’re going to cover quite thoroughly as we go through this. And then we have a Gain to Pain Ratio of almost 13, which is absolutely stunning. Absolutely stunning.
And then let’s talk real quick about how often you’ll need to do this as we go through this training here. So, this Meta Ai process, you probably want to do about once a year, and I can get it done within a few hours. It only takes a few clicks of the button. You just have to kind of figure out where it is that you’re at.
That’s why I was asking you all those leading questions. It’s like, okay, put in your mind, where are you at when it comes to your Compound Annual Growth Rate? How much do you want to make? Are you more interested in having as many months went in these as possible, or are you going for the gusto?
I think I saw 200% annual returns in here. So sometimes it might be hard to do both. But we can dial up these levers, dial them down for your specific needs. So, this is making a custom trading business for you.
So, keep all of those numbers in the back of your mind. And as far as how long the test takes. This is a pretty fast computer that I’m using as a virtual machine. I think it took like 30 minutes. So you’re basically 30 minutes away from having an AI trading business. So pretty easy, and especially if you just understand yourself. So one of the old Greek proverbs was, “know thyself” very, very important right as we go forward through this training.
Cycle Reversals
So, let’s go ahead and talk about cycle reversals here. And please save your questions for the end. I’ll be covering everything in painstaking detail. Thank you. Let me see if I can pull up my… I can’t pull up my book here.
Let’s go check it out. Outfoxing Wall Street. And thank you guys, by the way, for that. It got to number two. I wasn’t even trying to promote it on Amazon. I was just giving it away to you guys. And you guys got it to number two on All of Investing, right behind William O’Neill.
It was hilarious. I guess you guys wanted some backup copies. I’m with you. It’s really hard to read some of these PDFs online, and I’m old school and I like reading the books by hand here. So, I’m going to switch windows and I’ll show you an example of mean reversion here as we check out the book.
And this was a pretty interesting strategy. There are so many people that don’t understand that this is even possible. So here we have mean reversion trades, where it is cycling back and forth, cycling back and forth between buy and sell signals.
So, buy weakness, sell strength, buy weakness, sell strength, repeat, rinse and repeat. Rinse and repeat. Rinse and repeat. Everyone here familiar? Is everyone here familiar with mean reversion, by the way, that you get it? Mark says yes.
So that’s really the key behind cycle reversal. So we’re going to see these strategies. I love this analogy, I think it’s the easiest to understand, and you probably have watched Josh and I’s podcast, where I explained it in very technical terms, drawing lines on the screen, but I think that actually works.
So, let’s say that over time, your win percentage on your strategy, your whiz bang strategy is 70%, but it’s not 70% all the time over the course of a few months. Sometimes it’s really underperforming, and maybe it’s only been winning half the time, and then sometimes it’s really outperforming. But overall, it mean reverts.
Like, for example, I made a good prediction last year when it was super-hot here in Southern California. I know that the weather mean reverts, and I said, we’re going to get a really wet winter. And sure enough, we went from this incredibly hot summer into this really wet winter. So. things will mean revert—including a lot of things in life. They do that, right? So weather, stocks, that’s just one of them, and stock strategy. So it’s not very surprising, I guess, right? Okay.
Why Do Cycle Reversals Happen?
So let’s talk about the why. Why do cycle reversals happen? Nothing is ever stable, by the way, so I can’t think of that many things that can be stable over time that have a random element to it.
And I think that that’s one of the reasons why this works so dang. Well, it and we can talk about the role of cycle reversals in trading strategies here. And I’m going to circle back to our beautiful Meta Ai screen here. This looks so nice. Isn’t that lovely? Isn’t that lovely?
Well, the secret sauce is that you might have a strategy that every now and then is really underperforming in that very short-term window, let’s say over the course of a month, it’s not doing so well.
Well, that might happen to a person that’s trading an individual strategy once a year. So you’re kind of like buffett. Maybe you have an opportunity once a year in the strategy where it’s like, okay, button down the hatches, let’s just go all in.
So, it’s like doubling down on your bet when the odds are in your favor. Now, when you have 100 strategies, as we do here, man, the odds are really in your favor, aren’t they? So many to choose from, so many. So there’s a much higher probability that you’re going to get quite a few that are underperforming at that moment. Does that make sense, guys? Let me hear yes in the chat, if you guys are following along real quick. Getting lots of yeses here. Perfect. Okay, cool.
So having this big pool of instruments, of strategies to choose from is really the fuel for cycle reversals here. And so why is this knowledge key when dealing with AI? Well, I’m going to go ahead—and it’s going to surprise you with the rules that it finds, but I want to really give you a foundation of how strategy performance can mean revert, but that doesn’t mean that the rules that it’s going to find are necessarily what you would expect.
It does find rules that are quite unexpected, and I’ve come to expect the unexpected when it comes to AI. That’s pretty dang sure. So, one of the other things, too, is that understanding that foundation of the mean reversion where strategies can underperform and then they overperform, that’s going to help a lot too to understand what rules are being picked, because that’s going to be very important as well when we start talking about dealing with black swans. And a black swan is an unexpected event that you should account for. So, I’m going to have a whole section about that just coming up here shortly.
What we’re going to jump into now is building your first Meta Ai strategy. So, let’s go ahead and jump into that real quick. Going to go back into Strategy Management and create my own Wizbang strategy here.
And it’ll be just as easy as what we just did with the simple multi strategy. So, we’re just going to go click on New Strategy, and we’ll call this the Josh 100 Live Class. And this is a meta strategy. So, we’ll click on that. I like to organize and make sure we’re all in different folders. You can create your own folder as well and make sure you’re nice and highly organized so you don’t lose things.
And if you do lose things, up here is a search function so you can find them. And please save your questions for the end. Thanks, Peter. Everything will be answered as we go along here. I’ll probably be answering your questions as we go along.
So, we have this whole new strategy, and all I need to do is… I should probably populate it with some strategies, right? All right. Let’s see if I can do this to where I don’t have to do much typing.
Is this just going to have the Josh 100 in there? Pretty much. Okay, so I’m going to select all and then deselect a few. All right. There we go. Select All. Why is it not working? All right, I guess I’m going to select them all. No biggie. There we go.
And I just did a little search function, so I just got anything with 100 in it. Kind of surprised that didn’t work quite right. At least I’m not getting the Blue Screen of Death, all those Windows demos. Or you guys see the Tesla demo when they actually were able to crack the window. It was almost like that kind of publicity. Bad publicity is actually good publicity because more people tuned in for that. So maybe I should make more things that break, and then maybe we’ll get some free publicity out of it.
So, I’m just going to click on a whole bunch here. That’s enough clicking. I’ve had enough. Okay, how many did I get in there? 51, before I kind of gave up.
Okay, the key point on here is actually, I want to go ahead and show you how to build these strategies and what the importance of everything is. And here’s the cool part: is everything is pretty much organized on the left-hand side and Portfolio Boss. So, this is just like for you old timers that have been building strategies with me forever. We like to keep everything on the left, right?
And then we’re going to have some other interesting things. I’m going to drag this to the right here. You can drag all these windows, by the way, and maybe one of the first things I might want to do here is enable the divine engine.
So, this turns on the machine learning. There we go. Machine learning activated. And so, this will make it so the rules are going to be picked by the AI—easy peasy. And what we’re going to go ahead and do is set up Periodically Switching, meaning that once a month I want to go ahead and place these trades.
This really helps a lot for rebalancing. I’m going to talk more about that in a little bit here. But what I would like for your first strategy anyways is to look at just switching between the strategies once a month.
So, what’s going to happen is that all the strategies are going to be thrown in the mix and then it’s going to look and see which are performing a certain way and then all those strategies can be ranked and then that’s how it’s choosing the top 5, 10, 20, 30 different strategies for you.
So, the other way too is that you’re constantly monitoring the strategies on a continuous basis. That means daily, and so there’s some interesting things that happen. We’ll cover those scenarios as well.
But I would rather you guys start with your first strategy, periodic switching. In the very near future, there’s going to be a new feature here with portfolio boss and that’s where you can switch up to however many days that you want. Let’s say that you want to be in a strategy for three months on average. You can go ahead and do that as well, and that will be coming out shortly.
And then over here, let’s see…we’re just switching on the first trading day, actually. And I wouldn’t worry too much about all this other stuff other than we’ll just select Cash right here so we don’t have anything else to worry about.
Let’s talk about how many strategies to hold, and there are some drawbacks to this that we’ll discuss in a little bit. But let’s say that we want to go ahead and trade the top ten here. And for certain reasons, you would want to go ahead and hold more. So more typically means smoother gains. Does that make sense? That the more strategies you trade, the more likely it is that if you have one that’s really underperforming, the other 19 or whatever are going to make up for it. Does that make sense?
I’ll us talk about all the benefits here when it comes to multi strategy trading and how many to trade at the same time, is the second benefit besides smoother results, are going to be less slippage.
So, a great example is Josh. So what Josh is doing is he’s only allocating maybe—I think it’s like ten grand or something per position, something like that, per strategy, which is only going to be a small amount of shares.
Let’s say that the average ETF price is selling for, let’s say, it’s $30. And so 10,000 divided by 30 is what, around 333 or something, I believe. Is that about, right? Yeah, right around there. So, you don’t get as much slippage when you’re trading something like that.
The vast majority of bid and asks are around 200 shares, by the way, of practically everything. And especially with these really liquid ETFs, they could have thousands of shares could be hidden, but at the exact bid and ask that the market price is going for right there, you’re not really going to….
If you put a market order to something that’s thinly traded, the price might start going up because you’re hitting all the different price on the way up. But when you spread your risk out with more strategies and more positions at the same time, the less money you’re going to have into each of them.
Now, let me make sure in the chat that makes sense to you. I want to make sure I didn’t lose anybody. It’s a slightly advanced topic if you’re just usually just doing buying and selling and. Ivan says yes. Okay. Dan says yes. Okay, cool. And, of course, Russ knows. Okay. Everyone says yes. You got it. Perfect.
Now, the rule of thumb is to never trade more than 1% of the average daily volume. So, over the course of a month, let’s say that there were 100,000 shares traded in XYZ, ETF, or a stock, then you wouldn’t want to be trading more than 1000 shares.
So that’s the bare minimum. I would not be trading more than that. Otherwise, you can get stuck into a trade. And I think the only thing on Josh’s list that seemed to be illiquid, I think, was GLL, which is the inverse gold. I believe most everything else is pretty good. Correct me if I’m wrong, though, Josh, if you’re still there, but I’m pretty sure that that was the only one. “Economy of scale,” says Courtney. Sure.
Now, the drawback is that oftentimes you’ll sacrifice your annual returns to get that stability right. And also, if you start adding too many strategies, it’s less likely that many, let’s say you did 50. It’s less likely that 50 strategies would be in a cycle reversal stage, so those strategies might not be ideal at that time. And so you’ll sacrifice some Compound Annual growth rate.
John, that’s a good question for right now, that actually makes a lot of sense. And he’s asking, are these all market orders? No, there’s market orders and limit orders. So the strategies combine both. So it’s whatever works the best. And limit orders are fantastic as well, because they reduce slippage. Good question. Thank you.
Now here’s a thing that I want to cover real quick as we do this call—of something that for a lot of people watching this as a recording, it’s going to already exist. If I go into the instruments here, there’s something that we’re going to do for risk management and that way we can compare apples with apples.
Now, if you look over— I’m not going to go over to it right now, but if you happen to have the Excel sheets still open with all the different strategies and their returns on there, you’re going to see some returns like tap oil, 2X with a 237% average annual return. Another QQQ strategy, 213%, which is absolutely phenomenal. Let me make sure that I’ve got the right column here. Let’s see. Average return. Yeah, 213%. Actually, maybe I messed up the columns here, but biotech, 213% annual return.
I guess I probably did mess that up. But oil, 205% annual return, 202% for another one. 94% for real estate. 3X long inverse semiconductors. We got a 3X fund in there as well. 143% annual gain.
It seems to me that a lot of you guys might have to dial this stuff back. And Josh is saying DRN/DRV, which, those are the real estate ETFs, DRN/DRV. Those might have a little bit low volume for you if you have larger accounts, especially as you go into the seven and eight figures.
So, you can throw those out if you want. If it’s not going to work out for you, that’s fine. Or you can go ahead …shortly we’re going to have…Everything’s going to have a default of 100% right here. But some of these strategies you might want to dial back. And this only has to be done once. So, you do a little bit of research. You can refer over to your Excel spreadsheet here, and maybe you set that at 30%.
Let’s say that it’s a 3X fund. Maybe you set that back and dial it back to 30%, something like that. That’s just a really simple rule of thumb. And there’s a description next to each strategy. So that should be really simple for you to do. So, it’ll just be in this column right here. Does that all make sense, guys? And do you understand why that might be important?
Let me really clarify here, because this is quite important is a lot of times when we’re looking for—especially lately, what’s been going on is that these funds, these 3X funds, are fairly new.
So, these are the newest funds that have been out there as the futures market is becoming obsolete for retail traders and is being replaced by these ETFs. There’s really no reason for you to go on the futures market anymore because you have all these different ETFs.
Michael is asking, “How do you set it?” It is a future function that should be available possibly as early as next week. We have to do some testing on it first, but there will be a column here, that way, you can balance things out. And again, this is going to make it… so I’m going to cover this a little bit later, I believe. Let me just check my notes here. Yeah, I’m going to talk about this more later, about when all these different ETFs have been introduced.
And just as a sneak peek here real quick, is that you can see if you do a really long back test… Like, I’ve done a back test all the way from 1994 until now. And you’ll see when all these different ETFs start showing up. So, they started popping up in 2006 and you had some popping up 2009, 2011, 2013 and 17 as well, 16. And really that’s about where we stop. Otherwise, you can’t…If you don’t have enough history, you can’t build strategies, right? You have to have some kind of historical to run a back test. But you’ll see them pop up and all of a sudden, your gains just start really shooting up as these ETFs are coming into the fold here. And so that’s something I’ll go ahead and cover a little bit more here, but that’ll be on this column over here, guys.
So, again, really the name of the game at this point is we’re trying to dial things back, because you can get really crazy if you want here, and I don’t recommend doing that, because as we’ll talk about during our Black Swan section, is you have to begin to expect the unexpected.
I know a few of you were saying, okay, I want 200% annual gains, which is doable, but just know that your risk is also going up. So, let’s go ahead and we’ll close this down over here. And you guys might notice there’s no buy rules, there’s no sell rules, there’s no ranking rules, right? That’s what the AI is going to go ahead and fill in and as longtime members of The Boss know that it’s all just automatically done for you.
And let’s continue here. We’re going to put a little setting on here and we have to go to Evolutionary. And so Evolutionary is… I’m going to go ahead and show you a little…Let’s see if I can show you a little demo here. And I’m going to turn… I think if we have audio on this. I don’t think we do have audio on it. I do have a sad announcement to make as I switch screens over here.
So, this is our documentation. This is our user guide that was made by Zayn Abe. He passed away in February. Very sad. He died suddenly. At least he lives on forever in his work. That was really awesome. He was well liked at Portfolio Boss, so we worked together a few years.
He made some really cool demo videos over here. So, if you want to see how this evolutionary stuff works, it is like this. Here’s a little demonstration for you. And I’m just going to go peek at the chat while we do this.
And right now, it’s showing that you have all these random rules, and this applies to cyber code and just regular human-made indicators as well that are in Portfolio Boss. And while that plays, I’m going to go ahead and look in the chat here, see what’s going on.
And we have a tournament going on. Survival of the fittest, man. And we were talking about meritocracy. Well, this is the ultimate meritocracy. If you fail, you die. There we go. So, all those guys that live, they can live on through their children here.
Okay, chat looks good. Awesome. Okay, so that’ll be enough. If you do want to understand this more, I’ll just go ahead and throw it into the chat for. It. There we go. I got to pour one out for my homie, Zayn. He was a really nice guy.
Okay, so having this evolutionary is going to go ahead and breed the best of the best and kill off the rest, right? So it’s more like Hunger Games than in real life, right?
Population size, you don’t have to have much, and as we go through this and we’ll talk about…There’s some advanced techniques that we have where the computer can program itself in C-code. And it’s interesting that that tends to build the most robust strategies, individual strategies, but with the strategy of strategies with Meta AI, we’re using a lot of human-made indicators. So your population size can be pretty low, just 64.
You can leave all these defaults in there. They work fantastic. We’ll select random selection. This is going to go ahead and select from human-made indicators. They’re weird, human-made indicators. I guess I’m a weirdo when it comes to trading. I’ve been doing it so long. A lot of these indicators you wouldn’t find in a book; a lot you will. RSI, things like that, you will find in there.
And so, yeah, at this time you could go ahead… We have Cyber Code enabled, so when you do get your hands on the final version, coming real soon here, you want to go ahead and select on random here.
So, the Cyber Code, unfortunately, I think it’s overfitting a bit to the past. And so that’s the last thing in the world we want. And that’ll be covered just a bit here. We’ll talk about more about in-sample, out-of-sample.
Fitness Functions
Let’s talk about fitness functions right here. So, we have. A fitness function was already put in there for us by default. Let me get rid of that. We don’t need it. What is a fitness function, by the way?
It’s basically the sandbox for the AI. It’s where you tell it what your goals are. You remember all those multitude of questions that I asked in the beginning? Why did I ask that? Because I want you to put that in your mind because you’re going to tell the computer, that’s what I want.
So like Nalini, she wanted 40%, right? Some of the other guys were… I think about what I saw is most people didn’t go over 100. So, we can just do the 100 here. We can just go with 100. So CAGR, you’re Compound Annual Growth Rate.
What else I put in there is typically going to be Max Drawdown. That’s really important. Don’t believe the hype, and don’t let anyone convince you that really complicated trading strategies are where the money is made. It’s not so really simple trading strategies.
Non-rocket science is what works the best. The fewer the rules, the better. So, we have a little rule, Total Trades Per Rule Count. I’ll add that as well. So, I want to go ahead and maximize that number. I want to have a lot of trades and very few rules. In fact, I believe what I was sharing with you earlier only had two ranking rules. It didn’t even have any buy rules or sell rules. So, we’ll circle back to that a little bit here.
And what else do we want to put at that in there? I want to have 100% winning months. That’s going to be the goal. And we’ll just click on Enter. Okay. So, we’ve got some fitness functions, keeping it really simple.
I want to have a maximum drawdown of, let’s say 5%. And I want to have a Compound Annual Growth Rate. Let’s set a goal. So a goal is going to converge… Let’s say it’s at 100%. I’m going to put that in there.
So, a goal is going to converge at 100%. It’s going to punish anything that’s more than 100% gain, which is definitely doable. It’s pretty easy to get over 100% and it’s going to punish and lower the fitness if it’s below 100%.
And there’s also other ways to do it as well where you could set minimums and maximums. So maybe you want a minimum of 75% Compound Annual Growth Rate and then you don’t punish if it goes beyond that. So, you could try all those different settings.
And then let’s say we want to go ahead and have at least 1000 trades per rule. And, of course, our goal is 100% winning months. Let’s do that. And so what I usually do is I start with –usually, the most important of people is going to be Compound Annual Growth Rate and then you dial back from there.
That’s going to be kind of the litmus test. And then you kind of dial things back and put a weight, let’s say of 75% to your max drawdown. And so a drawdown is, let’s say that you made $100,000 and now you just lost 5000, so you’re in a 5% drawdown.
I’m pretty sure everyone in this class at this point knows that. But I want to go ahead and be very thorough with what we talk about here for posterity. And let’s say, I want to weigh this, let’s say it’s like 25%.
And in winning months, let’s really focus on that today. Let’s really focus on winning months and set that as 100% for our goal right here. And then you can add more as well. Let’s say that I was doing…Let me do one thing at a time here.
Let’s say, guys, that I’m doing continuously, where it’s analyzing the markets every day—analyzing the strategy every day instead of once a month. But one of the drawbacks of that is that it might switch in and out of these strategies all the time, like every week, which that might be really hectic, and it might chew up your account.
You might have way more slippage than you really should, even if you’re trading all these different positions and then your slippage is not too high. It might just be too hectic a pain in the ass. Let’s just put it that way, all right?
We want life to be a lot easier. We don’t want to make things hard for ourselves. And so you might do something like this. You might go in here and say, okay, I want to add a position duration here, average position duration.
And when it says position, that means how long it’s in the strategy. And you remember the strategy is going to be trading in and out of different things like these ETFs and inverse ETFs. But how long do you want it to be in the strategy?
Well, let’s say that you set that to a month. There we go. At least a month. Let’s just go a minimum a month here. And you might want to put that in there if you’re doing continuously switch. But I beg of you, in the beginning, just do the periodically switch. Just do it once a month. I don’t want things to get away from you. In the beginning, you can have a strategy of strategies here, this Meta Ai, and then you kind of get used to it. And then maybe you design something else, like a couple of weeks later or a month later. Does that make sense? So, I’ll just delete this for now.
We try to make life as easy as possible for you. Let the computer do as much of the work as possible. And of course, we will have the auto trading coming soon, okay?
Exit Conditions
Let’s talk about the date. This is really important. Let’s see. Let me finish up here before we go to that. Actually, I didn’t talk about exit conditions here.
So, this is my favorite, and by default, it’s there. And I like to set that to 30, actually. And it’s basically saying that it’s going to look at your out-of-sample tests on average, and it better be increasing.
Let’s go ahead and stop the test if it hasn’t increased in 30 generations. So that way you’re not wasting your computing power and it just kills the test off. It’s not working out and it’s probably overfitting to the past. Who wants that?
So, this is my favorite indicator I use. I don’t use anything else anymore, actually. We have quite a few other exit conditions in here, frankly are probably poorly worded. Just go with the default. Make life easy. It’s the only one I use.
In-sample, Out-of-sample
Let’s talk about the date. Boy, should we talk about it now? Let’s talk about in-sample, out-of-sample. And I’m going to circle back around to this date. This is going to be a little bit of a topic here. I was kind of giving you that sneak peek earlier when I was talking about the different start dates for all these instruments.
Let’s talk about in-sample, out-of-sample. The default is 80% in-sample where the computer is going to optimize and find the best rules on that 80% of data. And then it’s going to leave a chunk, 20%, that it doesn’t look at until after all the optimization is done. And then it verifies. It says, “Hey, is my out-of-sample that the computer didn’t see while it was optimizing, does it kind of look like what was going on with the in-sample?” And if it doesn’t, that test is no good.
So, we’ll talk a little bit in a minute here about your results and what a good test looks like versus a bad test. But what I’m seeing that works really good is 50/50; 50% in-sample and a verification of 50% out-of-sample. I find this to be highly important. I’m seeing too much optimization on the past using the typical 80/20 rule. And so I strongly suggest you guys use the 50/50 that’s been working the best. And I’ve tested this many times and those numbers work really, really good.
Start Date
So, let’s circle back here and we’ll talk about that start date. And I would not use earliest date possible at all. In fact, set manually. Let’s see, what is this one? 1993. Set manually. This is the one that you’re going to use.
Now, it’d be nice to get a nice 20 year back test in here and that’s kind of my rule of thumb with a lot of these different strategies. But what I like to do here is – well, I have to explain again, and I already kind of gave you the hint about what was going on. We have a lot of these single stock strategies and they happen to be…Let’s see, let me look at that Excel file again. So a lot of these single stocks are trading on. See, we have Apple, Amazon, American Express, Cisco, Google, Home Depot, Intel, Johnson & Johnson. You’ve got Southwest, Procter and Gamble, Starbucks, Unilever, and then Valero, those kinds of stocks. Google, Nvidia.
Now a lot of those stocks go back to the 90s. We have lots and lots of history in Portfolio Boss. We have history all the way back to 1986. Paid a little extra for that. I like seeing as much data as possible. But in this case, what’s going to happen is a lot of those stocks are going to be in the beginning.
So, none of those ETFs that we’re trading, barely any of them, maybe SPY existed, and then going forward so it was 1993, SPY came out and then you have some of these stocks like Nvidia, I forgot what the IPO date was for that.
Then you have Google, it starts coming onto that 100-strategy list of Josh’s and then you start having some of these leverage products. I believe it was 2006 is when SSO SDS came out. That’s for the trading, the two times inverse and long SP 500.
Then you started having more and more as we go into 2008, 2009, 2011, 2013, and then finally in about 2017, and that’s where a lot of these highly leveraged ETFs started coming out and that’s when they really started replacing the futures market.
So, it’s approximately ten years ago and the strategy that I was showing on that other page, that was built with ten years of data. And if you want to get all the strategies all in at once, it’s going to be from 2017.
So, this is one of the few times where there’s an asterisk next to…Because you guys normally know that I love to have these huge long back tests because I think the rules are going to be much more stable over time. But what I’m seeing is because we had all these different IPO dates that we need to shorten these tests. And again, that’s why we’re doing the 50% in-sample, 50% out-of-sample. So, let’s say I set that to 2013. There we go.
Since this is kind of a weird topic, let me ask you if you do have any questions about this phase right here. Let’s open it up because I know this one might be a little weird. And so let me know if I lost you, if you’re following along here.
Dan says, “Okay, so far.” Okay, makes us good. “What is the risk on starting earlier?” Says Brennan. Well, what’s going to happen is that let’s say that you…That’s a big pitfall that could happen is let’s say that you set it up for 100% annual gains like we just did, and then you start from 1994. You know what rule is going to get picked for the very beginning of the test? It’s going to say “rank the highest volatility strategy.” The highest volatility strategy, which is not really what you want because later on, as you have the more volatile instruments, oh, boy, does it just pick the more volatile stuff.
And, I mean, your Compound Annual Growth Rate can go through the freaking roof, but your risk has gone way up. So it’s not going to be really smart about it. So, we need to be really smart and understand that these ETFs pop in at different time intervals, right? And so a test ten years ago or five years ago, that’s where we want to be. Does that make sense? Brennan says, “Got it.” And number of sample periods, one. Just keep it easy. Nothing too crazy here because you’re going to overfit to the past.
I’m going to check my notes real quick, make sure we’re in the right spot here, okay? And I’m going to just peek in the chat here real quick because this part was really important, guys. That’s why I wanted to talk about it kind of twice with a sneak peek and then again a little bit more here.
And Tom says, “Does limiting max drawdown limit your risk?” But again, so if we’re just talking about this section, Tom, it’s not going to understand. The computer is smart in what it does in a very vertical fashion, but it doesn’t have the insight that I’m giving you right now that you have all these ETFs that start popping in at different times.
They have IPO dates 2006, 2009. We go in 2011. A lot came in 13 and then 17 as well. And so when the computer is optimizing on that in-sample period over here, it’s not going to include all those crazy ETFs that are those 3X leverage that we talked about, right? Does that make sense? Are you starting to understand why?
And John said the test he ran yesterday chose ranking rule highest volatility back to 2000. Exactly. So, you’re testing too long. That’s why this insight is tremendous. Write it down. Write it down. And if you have more questions about it, we’ll circle back in the Q&A, okay?
Yeah, this part was worthy of noting twice and why not three times? We’ll cover this again in the Q&A section because I want to make sure you got it. Got to make sure you got this part. So, these IPOs of all these amazing ETFs and their inverse pairs that allow us to trade all these different markets that we didn’t have access to before, outside of the futures market, were only available, it’s about the past decade or so.
That’s why one hell of a time to be alive. All these different technologies came together in this huge crescendo. 2017, we started getting into supercomputing, cloud computing, right? And then we started getting more into the AI. Then we got into spot pricing; one of the first to really get into that at Azure.
Then we started getting all this new data that allowed us to build weird strategies using nontraditional methods. By far, that’s not in any book. And then we invented Meta Ai, which just is like the conductor of the orchestra, and it’s really just like the big cherry on top. I’m envisioning fireworks.
Start The Test
All right, let’s keep going here. So, let’s talk about the best part, which is going to be, let’s just start the damn test. Why not? So, all I need to do here is, instead of starting a local test and just doing it once, one of the things I like to do is we’ll queue up a few of them. Now, I wouldn’t sit there and queue up 50 of them.
For me, every time I queue up a test, I think, oh, I have a 1% chance that I just overfit to the past. Even with 50% in-sample and 50% out-of-sample, in my mind, I just think every time I run this, there’s a probability that I am overfitting to the past. You guys understand that’s my biggest worry, is overfitting to the past, because that’s what computers can very easily do. And so we’re always fighting that.
So maybe I queue up, like, let’s just do three. We don’t have to do too much in here. We’re using these human-made indicators. There’s not pool of indicators to choose from. One of the other cool things too, about starting a queue is I can make notes.
I really suggest you guys make memos and stuff in here. You click on Edit Memo and I just put “Don’t forget memos.” That way, if you’re doing a bunch of testing and maybe you come back to it maybe a few months later and you don’t forget what the heck you’re doing, maybe what it was different.
And for this test, I might put a memo that says, you know, this is a monthly ten year back test, right. And I was going for 100% annual gains. You could do something like that. Just do yourself a favor, though. Do your future self a favor and keep notes and keep strategies in. Nice, easy to find directories. Trust me, it all works out. As a power user, yeah, I can sometimes get lost, especially—I’m doing these tests on probably three different computers as well, and so I can kind of get lost.
Black Swans
Let’s keep going here. Let’s talk about accounting for Black Swans here. And by the way, if you want to go ahead and start these tests, you can just click on Start The Local Queue and just go, walk away, go get some lunch. It’ll probably take this is a fast computer, I think with eight computer cores. I think each test was about 30 minutes. It’s not bad because you’re using a real small population size. So maybe each test takes 30 minutes, maybe a little bit less. With modern computers, they’re getting pretty fast. So, you just want to go ahead and queue that up.
Let’s talk about Black Swans, because it’s great to have all these amazing strategies, but sometimes these things will mess up. Here’s a prime example. So, I go along and find this eureka moment like, wow. The true asset pricing from grayscale on their bitcoin product, the ticker symbol GBTC, just shows monumental gains. And it’s a really simple strategy. And holy cow, this thing can make a lot of money.
Now, what I didn’t know, at the time is that…And I gave myself an F for this strategy. It’s like one of the first Fs I’ve had to give myself in a very long time. Maybe going all the way back to the beginning of doing a lot of this, especially after discovering the importance of out-of-sample test and things like that.
So, I gave myself an F on this strategy because what happened is that the marketplace changed, okay? And all of a sudden, the strategy was just terrible. And what had happened, it became a closed end fund. They stopped the creation and redemption process. And all of a sudden, there’s a huge disconnect between the value of Bitcoin and the value of the GBTC fund itself.
And so that was something that was a marketplace problem. The market had changed. It wasn’t that my strategies were completely overfit to the past, anything like that. No, the market had changed.
And so one of the ways that we can go ahead and kind of seed the Meta AI with dealing with Black Swans and we can go ahead and click on a cell filter and before we even run the test, before we queued it up and all that stuff, we could go down and do something real simple. Keep it simple.
You could do something like add a Simple Moving Average. You could do that. And it defaults is not replaceable. That way the AI doesn’t replace this… Let’s say you want to set it at like a 300-Day Moving Average. And if you put it as replaceable, the AI will replace those rules. If it’s not a really good one.
This really helps a lot with black swans. It actually might even punish the strategy a little bit. It might give less performance in your back test. But a lot of times it’s really worth the…Because there’s always this unseen risk, right? So, we see all these amazing back tests, but you know what we don’t see?
You don’t see that shitty bitcoin strategy thrown into the mix. In fact, you might want to throw it in there. Throw in crap strategies. You kind of salt it up. That’s kind of an advanced strategy. And in the beginning, you guys don’t have to do any of this stuff. Just keep it simple. But an advanced strategy is to actually throw some bad strategies. Salt the earth, right? And you could just throw in some bad trading strategies. See how it reacts.
Now, that’s one of the other things, too, when it comes to trading a whole lot of strategies, what are the odds of them? Like a bunch of them blowing up all the same time? It’s pretty small, right? If you’re trading 20 strategies, maybe one of them blows up.
And so what if that thing went to zero? You probably would stop, right? But when you’re trading 20 strategies, if one suddenly went to zero, guess what? Your whole account is only down about 5%. Not too bad.
But something like this, where we can account for a black swan, that might be something you add to the mix. There are other indicators in here as well. We go into Cell Filters. You could use the perfect stop, go down here, perfect stop right here.
And Chris in the chat is saying, “I use some bad strategies for that purpose, stress testing the meta.” So this is one of the ways you can do it. And it because what we know about cycle reversals, is that they tend to mean revert around this certain performance.
And what it looks like on your screen might look like this. And then the performance is kind of going up and down like that. But what if it breaks? So that’s why we can put these perfect stops in there. And you’ll see this more so on continuously switching instead of periodically.
Oftentimes, you’ll see these stops come into play. And so basically, it’s saying okay in mean reverse, it’s of like pulling on a rubber band, would be the analogy. But what if you pull on the rubber band too much and it doesn’t snap back up but instead it breaks? So, this is one of the ways that we can go ahead and prevent black swans by manually entering these.
But here’s the thing too, and I’ll be able to demonstrate this better with a simple—we’ll just go Simple Moving Average. Let me share something with you. We’ll select that again and we have not replaceable… Let’s say I want to test a few different values. Maybe test a range from 100 to 300, right? Do a step size 20. Keep it simple.
Now the AI will test that whole range in there. It’ll test from 100 to 300 period Moving Average and see what works the best with what you currently have in there. But again, that’s an advanced topic when it comes to black swans. We can keep it easy in the beginning. You’re unlikely to have a bunch of strategies blow up all at the same time. But that’s something that we should always factor in when creating these Meta AI. And this is a really, really easy way to do it.
And then throwing in some bad strategies. Maybe I’ll ship… I was kind of worried about actually throwing in some bad strategies. I didn’t want anyone to actually trade it. But that’s something that you can do to stress test.
But I’d say keep it simple for right now before you start getting into all the advanced topics and things like that. I’m just going to pop into the chat, see where we’re at. Let’s see. Okay, we’ll discontinue here. We’ll save a lot of this stuff for later.
So now we’re going to get into testing and evaluation stage. So, I’m going to get out of here. Let’s just cancel this queue over here. We don’t need it. We’ll just delete these guys. Yes. Let’s go back into that, Josh, the ones I already created here. There we go.
And right now, for beta testers on this call, there is a slight bug when it comes to adding those moving averages and things like that to where it’s like delaying the start of your test. And so it affects your Compound Annual Growth Rate. There’s just like, flat line for 300 periods as it calculates this line. And that’ll be an easy fix. It’ll be done by next week. What if we can get it by tomorrow? We’ll see. You never know with software, unfortunately. It’s one of the craziest businesses I’ve ever been in.
In-sample Versus Out-of-sample Testing
So, we are back into this one. And we’re going to talk about testing and evaluation. We’re going to go ahead and start with in-sample versus out-of-sample testing. And so I want to just go show you it’s really simple pattern recognition, especially because we’re doing 50% in-sample, out-of-sample.
The two lines that we use—and I’ll delete some of the lines we don’t need to see right now. I just want to show with what you should be focused on. This is a good test, my friends. And you can see in the beginning, things were kind of squarely. These two lines were not really jiving together. And so you have the orange line, which is what the AI is optimizing on, that’s what it’s looking at. And then the verification where it was completely left out of the optimization process.
The other half of the data is the brown line. And look at that. That’s a nice-looking test, but really interesting that very quickly with the small generation, just even 64 in that population, it was converging on an answer.
By the way, it’s a little pro tip for you. I like to take a look at the later generations because the later generations tend to have fewer rules. So over time, not only do the results get better and better, but you have fewer rules added to the list. So it’s more that we’re getting towards E=MC^2. Simple yet profound, right?
Let’s take a look at the rules of this nice strategy created, just two ranking rules. Again, this switches once a month. Really simple for this. It was actually looking at high volatility. It was a mixture of high volatility for this strategy and at the same time looking at the lowest return. Very interesting. So, buying the dip on here. You guys might find a lot of other rules, but they’re usually going to be pretty simple. Simple is better. Simple works.
Let’s go ahead and take a look at a test that doesn’t work. Let’s find something. I knew I had one over here. Let’s take a look. All right, guys, you see how this is opening up like Pacman, like it’s got a big mouth at the end, instead of jiving together there and being pretty much the same. Look at this one. Let’s take a look at this. We’ll take a look at this test and load it up real quick. Mark says, “A thing of beauty.” Maybe he’s talking about the other one. Actually, that’s good timing. Thing of beauty. Not a thing of beauty. Awesome. Let’s take a look at it, though. Let’s see what happened. Mark says, “The first only.”
So, we have this nice optimized… Let’s see how long. This test was 2017, and it went 70% in-sample, 30% out-of-sample. And it really overfit to the past here. So, you can see right away that we have a problem. Look how choppy it got. So, it’s nice and smooth over here and then really choppy over here.
And how did that translate to our test suite over here? We don’t need any fancy math. You guys can all see that. Do those two lines look good? Do they look like they’re matching? Let me ask the chat.
You guys still with me? I know we’re about an hour and 20 minutes into this. Bill says, “No,” and that’s how easy it is. “Not even close,” says Lee. That’s how easy it is to really see instead of getting into a lot of complex math.
And I like to keep things simple for you guys. Nick says, “Yes.” Got it. Okay, you guys got it? I think we have different answers, but they all are referring to the same thing. That’s okay.
I don’t like looking at this. Let’s go back to a nice looking one. There we go. Here’s a different strategy. Let’s go ahead and see this one. I put a little star next to it. Actually, that’s another pro tip; if there’s something you like, put a star next to it.
I’m going to go ahead and hit the goal. The fitness in-sample was 1 and 0.97 out-of-sample. Really close. And we’ll take a look on this one. I already know from my notes that this one is monthly switching 100% Compound Annual Growth Rate from 2017.
Real simple rule for this one, that this in score was looking for the lowest percent return over about the past month or so. Real simple. These rules might change quite a bit depending on your own personal settings as well.
I think that I kind of hit a wheelhouse in there and it’s really looking for to trade that dip. Now you might think…Let’s go wind up a little bit because this might be a little bit of an insight for you.
So, you can see it buying the dip, right? It’s pretty obvious that the rank is looking for the worst performing over the course of about a month. Now, what happened to the selling when things go up? What happened to that?
Because, Dan, wasn’t that part of the whole cycle reversal strategy? Well, let me take a gander right here. Remember, this is a monthly switching right here, right? So, on the first trading day of the month, where we say, hey, what strategies are performing the worst? Which means? Means by Axiomatic default, that you’re actually going to be selling the strategies that were performing really well and buying into the strategies that weren’t performing very well. Does that make sense?
I wasn’t sure if people got that insight. So, we do have the best of both worlds right there. So, we’re buying weakness and we are effectively selling strength. I’ll just check the chat real quick here; make sure I don’t lose anybody.
Let’s keep it simple. Mark was just asking, “Should we just have the in-sample and this the out-of-sample?” You know, in-sample, the left and right on the right? Yes. Let’s keep it simple, but it’s up to you at the end of the day. But it’s a more advanced topic, right? Maybe in the Q&A, we can talk more about that for the pluses and minuses, the good and the bad when it comes to that.
So, for now, I would just say let’s just get it up and running and then we can go ahead and choose more advanced stuff a little bit later. But I can circle back to that. I’ll write a note. Thank you, Mark. And we’ll talk about reversing things, reverse in-sample, out-of-sample. And I had mentioned before that you guys can try…Let’s see, enable this divine engine here.
Cyber Code
So, you can go ahead and you can try using the Cyber Code. In fact, I recommend trying a lot of different things here because ultimately, this is creating your trading business, right? We already have all these strategies you. If you bought the Josh 100 program, we have lots and lots of strategies for you. The more strategies you have, the more likely they’re going to be in the proper cycle reversal setup. And there could be a reason where you could go ahead and try the Cyber Code.
And I’ll go over that just really quick, just real quick, because this part looks daunting for most people. But basically, what’s going on with Cyber Code is that we’re using a bunch of basic mathematical building blocks, all these guys over here.
So, we’re looking at not just the price data like open, high, low, close, and volume. We’re looking at all these random not random, but all these mathematical functions like addition, subtraction, square root, minimum and maximum sine, cosine, tangent variance, sums, some of the more common indicators as well, like Average, True Range, Simple Moving Averages, Relative Strength, and then conditional operators like greater than, less than equal, that kind of thing.
And they’re just randomly mixed together and then bred together. Remember in the evolutionary process, the worst performing strategies, they get killed off without remorse and then they’re able to breed together to build stronger and stronger trading strategies over time. And this develops really good trading strategies.
But so far, I’m not seeing much going on when it comes to creating really robust Meta AI strategies. I think it overfits a bit much, but there could be a time in the future where that is something that you might want to try to just at this point that I haven’t really seen it. Okay, let me continue here. I was actually kind of surprised, behind the scenes, I thought there was high hopes there on Cyber Code.
What Makes A Good Meta AI Test
We covered this a little bit, but I just want to be really thorough. I’ll talk about it once again. Is that, what makes a good Meta AI test? And it’s basically you want more parallel versus Pacman? Parallel versus Pacman. So I’d rather have something that looks like this. Pretty much anything with a star. Had a really good test. Something that looks like this. See, if I had a couple more in here. I had a lot of tests where I tried to break it. I don’t know how many I starred here. I’ve been working on three computers. I’m not sure what’s on this one. Not too much. Not too much. But I’ve been trying to break it to see what I could really mess up. Trying all kinds of weird stuff. Sometimes when you try to break things, it actually turns out pretty well. You find some new serendipitous discovery, and then now here we see what doesn’t work. So, is it Pacman or is it parallel? Pacman is bad. Parallel good. Keep it simple. Keep it simple. Let’s see. I’ll come back to you, Mark, after. You can go ahead and save that question for me a little bit.
Portfolio Management
Let’s talk about Portfolio Management. So let’s cover this again. It’s worth repeating. So how many strategies should I trade? So, we have those pluses and minuses again. So, the pluses, the more strategies you trade, the less likely you’re going to be affected by black swans. You’re going to have lower slippage.
Part of the con is going to be it’s going to be more active. So, you’re going to have to… I know Josh spends about 15 minutes a day on it. He’s got a whole unique process to it when he trades with Interactive Brokers. So, it might take you a little bit longer to trade.
And the other drawback is it might lower your gains. As you start adding more and more strategies, it might lower your gains. But if you’re trading just a few strategies, you could have a lot more likelihood to have some volatility in there.
So, you might end up, you know, one of your five strategies, let’s say… What if it turned out to be like that GBTC strategy I told you about, where the strategy? It completely changed because the characteristic of that strategy completely changed because the marketplace changed when the fund became closed in.
So, what if that happens and then you’re only trading five strategies? Well, right away, let’s say it went to zero, well, then you just lost 20%. So, there’s definitely a wheelhouse. I like a lot of tests. 10, 20, 30, right in that range. And you get a lot more risk as you start trading fewer and fewer of these. So those are the pluses and minuses.
And again, the rebalancing of strategies here. This will be added shortly, and it’ll be in this section over here. Whoops, my bad. Let me check this little line thing. And for certain strategies, if you want to, you can delete some of these strategies.
The more the merrier though, because the more strategies you have, the more that you’re able to choose from, right. The more that are likely to be in a cycle reversal. But in the very near future, we want to go ahead and dial some of those back, unless you are… I forgot who it was that said they wanted over 200% annual gains. And then maybe you just want to leave those alone. It’s up to you. But you probably will have bigger swings in your portfolio because those things are highly leveraged.
Okay, let’s see. And then also the pro tip was that they’re labeled. So anything that has the crazy 3X or 2X, all that’s labeled in here. So you’d be able to dial back pretty quick. It only has to be done once again.
And I think that for most of you guys that you could accomplish all this within a few hours. I would say probably an hour learning curve after you go through this. And then you’re looking at just setting up a few tests, walking away and then coming back and then selecting which strategy you want to trade. It is that easy.
Making the Trades
Let’s talk about actually making the trades here. Let’s talk about that. Let’s see, giving myself some room here, and we can see some trade signals for today. This is for the opening. And we can see that we have our little trade management here, some signals, and it tells you exactly which strategy that each of these trades belongs to.
Like, for example, Single Stock-HD, you can see that there is a buy with a limit order at 284.36. So, trying to get you into that particular stock. And then we have the China, it’s trading YINN. There is a sell limit on there and then we can see the energy it was selling out of ERX, getting the ERY and then getting out limit order to get out of real estate here.
And then it’s selling SDS, buying SSL and at the same time this can happen where it’s in other strategy here is it was already in SDS and then getting into SSL so they’re kind of crossing themselves. And don’t worry about all that stuff. I know it incurs a little bit of commission, a little bit of slippage, but it works out in the long run. Keeps that portfolio really nice and stable in here. And then of course, it’s selling out of the short tech and trying to get into a limit order with this long over here. And then all your open positions are down here as well. And they’re in positions as well. So pretty easy.
One of the other things too, guys, is we do have a trade manager in here, but the only way to see it is you have to disable this Divine Engine. So, disable the Divine Engine here and we can get into the Trade Manager here, Trade Plan. We can click on that. This is going to be much more sophisticated in the very near future with automation, with Interactive Brokers and let’s say that it was $200,000, is what you’re trading with and then you can do some suggested quantities and this will tell you exactly what you’re going to be doing for the day.
And this Basket IB thing is just on our side that we have been testing and something like that is what Josh has been using the Basket Trading, it makes things a little bit easier. But I’m leapfrogging that technology and we’re going for the automation.
It’s going to analyze your account, if you have an account with Interactive Brokers, and then it’s going to know how much of everything that you have already and trade accordingly and make life a whole lot easier for you.
And also, another thing too, if you have a larger account, especially if you’re into seven/eight figures, it’s really smart to get into Interactive Brokers. We’ll have it hooked up to where we’ll be able to use their algorithms, like accumulation and distribution.
That way, let’s say that you have an order for 10,000 shares to buy and you’re not just dumping 10,000 shares into the market. That would be really silly. It’s going to move against you really fast, and you’ll get a lot of slippage that way. You’ll incur a lot of slippage, actually, about 10,000 shares depending on what you’re getting into.
And so we’ll have all that ready for you shortly. I’m actually hiring another person. We’ll get a second person on this job to speed things up, speeding everything up here. So that’s going to save you some time right there. And really that’s about it. I mean, right now things are still manual, but very manageable and especially the amount of money that people are making—and you guys have been sharing your brokerage statements with me—It’s well worth your time. Well worth your time to do this stuff.
Okay, let’s see. I’m going to just look into the chat real quick, make sure I didn’t lose anybody. So, Lee is saying that there’s something wrong with the emails. Yeah. Chris is saying, “I find trade plan using the previous close going to be pretty far off of the open.” That’s okay. Chris, everything’s accounted for. We know that we’re buying on the next day’s open. Yeah, I get it.
We did a study and we found that the vast majority of the time that it all comes in together very close to the close. Sometimes it’ll gap down, sometimes it gaps up. And we did a measurement of how that works over time, and it all converges at the previous day’s close. Now, the only problem that could arise is non-margin accounts.
So, when you’re trading non margin accounts, you could have an issue where you’re trading maybe too many shares, and let’s say an IRA, something like that. So that can happen. The way around that is to use, let’s say, you have $100,000 in your IRA, and you could do something like you put in $90,000 instead of your total cash. So, sometimes you can have an unused portion of cash in your account, but that way you don’t get flagged as not having enough money in a non-margin account. Okay, keep going here. We’ll talk about that later, Peter. And then Brennan you’ll see all this later. We’re about to release. Do a big release, be a big party. Want to get this training to you first before this is going to show up automatically in the new version of Portfolio Boss for you.
And let’s see. Let me look one more time before I get into the next. Let’s see basket stuff. We’ll circle all back to that stuff. Okay, we are over the hump here. We’re getting really close to the end, and then we can do open it up for Q&A.
Maintaining And Improving Your Portfolio
So next up we have maintaining and improving your portfolio here. Portfolio. I must be talking too much here. My lips are going numb. So, what do you do with spring cleaning? And you start looking at your strategies and then you figure out, hey, let’s get rid of them. I like about once a year. I think that that’s pretty smart to prune about once a year, you can look in there and if there happens to be any duds that just totally did what happened to the GBTC strategy? You can throw it out.
If you have the Boss Super AI, then what you can do is over time, or you can do it all at once if you want, is that you can continuously add new strategies over time to the mix. And you can even use the same symbols because oftentimes the boss will find completely different rules. It’ll use different data on the same instrument, like, let’s say for the wildly popular SSO/SDS pair.
And so members of the Boss Super AI, they know all about that and creating those pairs. But we’ve developed all kinds of… I’ve seen so many different rules occur because we’re just using really weird data, especially when we’re using all this ishares country ETF data for trade signals, instead of just using price.
So, you could continuously add that way if you want. The more the merrier. I don’t think that there’s any barrier here to how many strategies you can bring to the mix. And we don’t have anything that limits. Right now, let’s say it gets into too many strategies that have to deal with SPY, I’m not seeing any huge drawbacks on that. There could be black swan risk, but I’m not really seeing it too much. A lot of these strategies, they trade the same instrument but different rules. And then that’s why right now, you saw in the trade signals, the SSO and SDS were being traded at the same time. You’ll see a bit of that, but it all works out at the end. It creates more smoothness to your portfolio.
One of the other things, too, is over time, we may add more strategy packs, and that’s especially true… I want to have a mad dash and get into intraday data as well. And that’s one of the reasons why I’m hiring a second person on the auto trading, is I want to get into intraday trading. I think there’s huge edge there. And so I want to prove or disprove my hypothesis about that.
And again, I’ll say that it’s just highly important to have a big, diverse pool of strategies. The more of the merrier, because the more likely you’re going to have that perfect cycle reversal setup.
Identifying Hidden Risk In Your Portfolio
And then, let’s talk about identifying hidden risk in your portfolio here, and that way you can go ahead and avoid asymmetric risk, which is a lot like black swans and things like that happening. And Dan Carrie says, please get into Intraday.” Yes, I’ll keep going here. We’ll save a lot of those questions for later, guys. Write them down, please, and I’ll cover that in the Q&A here.
And so I would say that the biggest risk of Asymmetrical risk he tried to say, is going to be short selling. But I don’t see a problem with it as long as you are doing it, let’s say on the Dow 30 stocks. And here’s why. You guys remember GameStop? Everybody and their mother was saying that they had cornered the market and they were going to F over all the head hedge fund guys.
Well, they actually did F over some hedge fund guys, but those guys actually create the rules. So at the very end, it looks like the vast majority of people all bought GameStop on about the same day. And so over 90% of those people lost it all as that thing just fell like a rock in value. So at the end of the day, those guys all won. Not surprising. Like I said, they make all the rules. Most people didn’t know about clearing houses.
They obviously didn’t understand short selling. You cannot have more than 100% short. It was not true, anything they said. I checked with S3 data whose entire existence is to analyze short interest. And the short interest is actually something like 53%, I think they said 158%. They didn’t have the right denominator. Sounds a lot like COVID. If you don’t have the right denominator, you get a bad answer.
But it does bring up a really good point. It’s like, we don’t want to be in a GameStop and suddenly you get wiped out, because that’s exactly what would happen. That’s what Asymmetrical risk is all about.
So, if you shorted, let’s say at 100, the thing goes to 1000. Well guess what? You’re wiped out. That’s the end of it, right? And so we want to stay away from that kind of risk as much as possible. So, if you are going to develop strategies that go short, then go ahead and do that on Dow 30 stocks.
What Josh did, I like, it was all this highly liquid stocks. You’re not likely to see apple double overnight, something like that. And a bunch of what do they call those guys? I know, bitcoin is like, the holder, hodlers, holders, whatever.
I forgot what they call, maybe Stock Trading Bros or something. But they all thought that they could get one over. They got their stimmy check and then decided to go blow it on some crazy bet against the whole establishment. Trying to blow up the establishment by playing in the establishment, doesn’t sound very smart to me.
And then I’ve already told you the story about bitcoin becoming a closed end fund. That’s another way that you can have unseen risk, a black swan happening.
And then another one too, it was a huge wake up call for me that I was over trading, and I was over leveraged. I was trading a lot of contracts during the flash crash of 2010. I had a good-sized portfolio, but all of a sudden, what happened is, during the flash crash, trade station order system got jammed, and so my automated execution was not happening.
And so there was an unforeseen black swan. I didn’t realize that that could happen. I didn’t realize that their network was just totally laggy and wouldn’t be able to handle that many orders coming in at the same time.
So that was another unforeseen event. And so the point of me telling you the story is so that you can expect the unexpected; you can expect…In the market wizards books, there was a guy that he was supposed to make a trade, but I think he was on vacation, and then suddenly he couldn’t get away, like, the time escaped him, and then he unfortunately had some positions go against them, that sort of thing.
And so I always want you guys thinking about risk first and foremost, and so just understand that there is a possibility of things going against you. We saw an oil ETF kind of blow up as well during the pandemic. And so that’s another reason why I want to stress that even though your back test could say one thing, watch out for trading things that give you those 200, 300% gains. Because defensive traders are those that live to trade another day.
Offensive traders, they tend to blow up over time. The people that are really aggressive. One of the few that I didn’t realize that he was so aggressive, was Paul Tudor Jones. If you watch the Trader documentary, he does sound like a very emotional trader.
And I don’t recommend that at all. I’d rather you guys not stare up at the ceiling and worry about your finances and there was some weird event that you weren’t expecting and maybe calm things down a little bit.
Because, again, what’s my whole thing that I’ve been saying this entire time? It’s like, we’re dialing things back, right? We’re dialing things back because this thing can just take off like a rocket ship at this point because these leverage ETFs, they can really supercharge your portfolio.
But I just want to stress to you that there’s going to be unforeseen risks. There’s going to be things that a back test doesn’t show that can happen in real life. And so hopefully, those stories can help you out and mitigate risk because I don’t want to see you guys blow up. I don’t want to see you guys getting ulcers and that kind of thing. I don’t want to see emails or phone calls from—let’s say there was asymmetrical risk with China. That’s another good one, Black Swan event, they cut off the Russian ETF suddenly just stopped trading. Imagine that happened with the China ETF. So, expand your imagination a little bit and just be careful out there.
Future Enhancements To Meta AI
Let’s talk about an overview of future enhancements to Meta AI. There’s a small little bug fix that I mentioned that’s affecting when you add that. Let’s say that you want to try to black swan proof your Meta AI portfolio here. There’s a little bit of a bug that should be fixed really soon.
And then I was mentioning that over here we’re going to be adding… So, the default is going to be 100% for most strategies, but things like with a 3X leverage, maybe you want to dial that back a bit, right?
Maybe you put 30%, something like that. And again, it’ll be a one-time thing. It shouldn’t be very daunting. Most of these things you could probably just leave at the default. And then a few of these, you might want to go ahead and dial it back a little bit here.
The other thing is when it comes to periodically switching, we’re going to add another feature where that allows you to select the amount of time. You might want to do quarterly. It might be a lot easier on you.
Frankly, I’m intrigued of what we might discover using something like that. And then the third thing is we will add more rebalancing features. So right now, we don’t have rebalancing unless the AI gets out of the strategy.
Let’s say that a strategy was doing really well and then the ranking rule was to buy the worst performing, and so it gets into the worst performing and then maybe it gets out. There is the possibility a couple of the guys had some rules where one strategy would suddenly dominate and take up like 40% while all these other strategies were just kind of taking up small amounts in the portfolio. We don’t want that. That introduces a lot of unneeded risk, and we don’t want risk. It’s the last thing we want.
Bill is saying, “Under quarterly, could it sell before earnings?” No, don’t worry about that stuff, man. That’s all baked into the cake. We want to stay away from that kind of information. Fundamental information is pretty useless, and I have so much data and 99.9% of it is completely useless.
I have a subscription with Y Charts. They’ve got everything you could imagine under the sun, Bill, and for everyone else listening as well. It’s a good lesson. It’s junk and it don’t work. The vast majority I just try to distill things to you guys, man, so you don’t have to waste your time on all this stuff, waste your energy.
The most valuable thing really is not you’re going to be your portfolio, it’s your time. And so I don’t want you guys worrying about stuff like that. It just doesn’t matter. It just doesn’t matter. Oh, my God, I was just having a flashback of what was that? A Bill Murray movie? What was that? It was like a camp movie. I don’t know, it just popped into my mind. That’s hilarious.
But those are going to be the three main things that we’re going to be adding here. So that’s going to make life a lot more comfortable, I think, for you, and balance things out. And also, what I was saying before is that even though you have these 3X strategies, we want to dial it back.
The added benefit, too, is when we put these weights on every one of the strategies. Well, if you wish, if you want to dial it back is then you can compare apples with apples, where maybe you can run a longer back test, actually, because you’re dialing things back a little bit.
So, at the end of the day, man, you’re going to get there. I think Russ and I were talking about that, and Russ had a good attitude when it came to drawdowns. It’s like, it’s eventually going to get there.
You lose this amount of money, and then we’re doing so well with all these new strategies that you’re going to make up for that very quickly. And so my whole point is, I don’t think that you need to rush things. I really don’t.
Recap
And that comes to the conclusion here. And I’ll just do a recap of those takeaways. And obviously, as we segue in the big one is like, let’s dial things back, man. Live to trade another day. Don’t go two walls of the wall, because you can with this technology. Watch yourself.
We covered cycle reversals, right? We know a strategy, it tends to have some kind of performance level, but that performance over time, it goes up and down, and it’s just how this turns out that you can go ahead and buy when things are underperforming and ride it out till it’s overperforming, and you’ll do really, really well. Those simple rules are no joke.
Trading lots of different instruments, that’s another big one. It gives you more chance to get into a cycle reversal. The more the merrier. You can add a lot of stuff here, and if you’re using the Boss Super AI to create things, you know, that a lot of times it’ll find completely different rules, and it has its own little fingerprint on how it trades the markets and what it looks at.
And we are continuously adding more data, and that I do have some more decisions to make as far as more data is concerned. We might get into, like, Twitter data, and there’s all kinds of stuff that we can do as well.
We can trade all these different markets. And obviously, as we covered from, let’s say, the 80s and 90s, more of the strategies would be individual stocks. And then we got into 2006 and you start having these leveraged ETFs.
And then you started getting into 2009 and 11 and 13. And then all of a sudden you have all these different ETFs in all these different markets. And then in the past ten years, there’s been an explosion of these highly leveraged ETFs, they’re wildly popular, just millions and millions and millions of shares being traded every day. The ETFs, the companies, they go manage the futures for you. Their management fees are negligible compared to what we’re doing. You don’t have to worry about rolling contracts. You don’t have to worry about this month is expiration, that month is expiration Contango, and all this crap. They do it all for you.
And then of course, we have the different styles that we can trade as well. And that’s going to be a function of all the different data that we get. And so we’re constantly improving Portfolio Boss it is my mission and it’s probably, I would say it’s one of my highest purposes and gives me the most pleasure and fun. It’s not the money; it’s the discovery. It’s really important to understand who you are as a person. And I started this whole class off and talking about the Greek is it a proverb? Know thyself, it’s extremely important.
We talked about what it is that you want out of this class. We talked about what kind of gains are you looking for. And then hopefully with this information, I’ve been really stressing to you, dialing things back and I hope that that has sunk in.
Q&A
And with that, I’ll go ahead and open the Q&A section right now. Hopefully, you guys wrote some things down or you can copy and paste some of the things you talked about before.
How’s my golf game? It’s wet, man. So, I haven’t been playing, but thanks for asking, Dan, because I think I’m going to buy and build a simulator. Yeah, that’ll be fun. That’ll be fun. And plus, over the driving range over here, I don’t know what it is, but I don’t have allergies normally, but my eyes are watering. It’s the one closest to my house. It’s like, oh, it might be a lot more fun just to go practice over here and then every now and then do an expensive course so I don’t have to wait. That would be nice, because when I go… you know, Costa Mesa Municipal is way backed up. It’s like six and a half hours play a round of golf. Thanks for asking. Man.
Okay, so Peter is saying, “How did Josh create his 100 strategies?” Boy, that’s something I can’t really answer very shortly. Everything that we’ve learned about. How did he create the strategies? A little bit of everything: using Cyber code, plus TAP. Josh, I think you said that it’s like 60% plus using the TAP data, the True Asset Pricing.
Let me keep going here. Josh said, “That’s right.” So there’s a lot of TLC goes into it. I would just note, Peter, that the vast majority of these strategies are damn simple, simple, simple. But you would have never figured it out without using the computer.
And a lot of them it’s really important, too, with the TAP data is a lot of the rules are just, like, greater than, less than to where there’s no overfitting of, like, a moving average, that kind of thing. That can lead to serious overfitting of the past. And that’s what I’ve really noticed and love about Tap data. It’s very, very robust. And so I’m still making a decision on Fund Flow Data as well. It’s very expensive. But we’ll see.
I saw a question: “Is this ready to go right now?” We’re just about ready to. There was two bug fixes we need. There’s a new version of Net that the guys had to upgrade to, and it’s not this weekend, but it should be….I think this Tuesday is our schedule. It’ll be ready to rock and roll. I also want to get you more. I want to create some templates for you as well. Unfortunately, there’s a few things that we need to add on there that I think would be really smart before giving you templates.
And so that includes the weighting function that I was talking about over here. But it’s very stable. Things look really great, and we’re just about ready to rock and roll. Why is this freaking out? There we go. Just about ready to rock and roll for you.
Let’s see. Marcus saying, “Do we use the Country ETFs when running the meta strategies with Cyber Code?” No. Do we use them? Yeah, they’re part of the data. Of course. Whatever the strategy uses. Whatever the individual strategy uses. Obviously, you need that data when you’re running the metas. That’s all available. We’ve really been dialing in all the data downloads, and we’ve been going straight to the source as well for all that tap data.
Mark is saying, “If you’re switching continuously with Leveraged ETFs, do you need to trade only part of your account to avoid being flagged for trading non settled money?” No, I’ve only heard—let’s see, if you’re trading some of the VIX products, they didn’t like that in IRAs, like UVXY or the Tickers. I don’t think we have any of that stuff on Josh’s list, though. Those were not good for…
But it doesn’t count against your leverage, though. So internally at the ETF, they use leverage, but it doesn’t count towards yours. During certain volatile events, then every broker is instructed to sometimes lower their margin rates. But we’re not really trading on margin. The only margin that we trade on, because, again, it’s like, why? We don’t need margin when we have all these three times leveraged funds and we’ll get there eventually anyway. I just don’t want to see anyone blow up by trading, like, a tiny couple of strategies and then going for a thousand percent back test or something, and then something unexpected happens.
I would hate for that to happen to you, but I think what we can also do better than Nalini was saying as well, she was being very realistic and conservative with 40%. I think we do much better and stay very sound with liquidity.
I’m not sure if I fully answered your question there, Mark. Yeah, so that might be a question you’re asking about IRAs with the T plus three and that stuff, but there are IRAs that you can start.
Where you don’t have to worry about all that stuff. Interactive brokers is where to go. I’m not a tax guy, any of that stuff, but I know that people are doing it.
Randy is saying, “In your example, there was a good test, 50% out-of-sample, and then 70/30 was bad. Was that the only difference?” Yeah, I believe yeah, that was just to demonstrate how powerful it is to really do that 50 50 split. I believe that was the only difference.
Terrence, “Was backing up the talking about the good faith violation. If you trade too quickly, as long as you give it three days, you’ll be fine. I think that there’s a workaround for this stuff. There was a UVXY strategy. Okay. You might want to get rid of that IRA. I know for sure that UVXY, those products on VIX, they aren’t allowed in an IRA. It’s big brother is watching over for you, even if you know what you’re doing, they just don’t like it.
I don’t know how I missed that one. I didn’t see that on the list for some reason, although my eyes are going kind of bad, but I don’t know why. I saw GLL. That’s going to be low volume and not appropriate for some accounts, but…Oh, there it is. It was at the very end, those volatility, yeah, they don’t like those in IRA accounts for whatever reason.
I think it’s because those VIX products, one of them blew up. And so you definitely got to watch yourself on some of these products here. But again, you can really mitigate risk by doing what? Trading a lot of strategies. It’s not too hard. And I think the average holding time for all these strategies is ten days on average, with all 100, I think it was around ten days. That’s about two weeks.
Okay. Mark is saying, “You don’t need a leverage account?” It sure helps to have a leverage bridge account. That way there’s no settlement time. And then you can go sometimes you can go over or under, but you don’t need to have that. But ask other people. That’s not my thing, so I don’t talk much about taxes or margin, things like that. It’s not appropriate for me to talk about that. But when I’m saying appropriate, there are ways where you don’t have to worry about settlement. There are ways too; you can start corporations. There are all kinds of workarounds.
Let’s see. And Mark is saying, “Yeah, margin. IRA Interactive Brokers”. Kendall saying, “Is a virtual desktop a good option? Any input?” Yeah, I’m on a VM right now. This is not actually the one you’re looking at. This is in the Azure cloud. You can use Amazon, Azure. Those are probably the least expensive. I like it. It was easy to set up.
We also were talking earlier about reversing the in-sample, out-of-sample. Let’s talk about that real quick. So, with Portfolio Boss, you can actually uncheck this. And there we go.
You could reverse it and use your in-sample over here, the most recent, and then verify on the previous stuff. So, there can be some that can backfire a bit. If your test is too long, you could have it to where sure it looks amazing over here. And then there’s fewer instruments on this left-hand side. Remember, as we start going back to the 90s, there’s fewer and fewer and fewer instruments so they won’t show like big volatility. So that could be a detriment for you.
I just say keep it simple, man. Keep it simple. We’ll just keep it simple. There we go. Do what works best in your brain. For me, what works best in my little old brain is to say, hey, I want the in-sample where the computer is optimizing to be in the past, and then I want the out-of-sample to be now.
Right. And especially because the rules are just they seem to be timeless when we’re doing this 50/50 in-sample, out-of-sample testing on here. They’re so simple. They appear to be timeless for me. They really do.
And I’m really curious what the rules are going to look like when we we add that volatility waiting function over here. I’m really looking forward to that because I think it’s going to make the test just almost identical, almost like a mirror image.
So to say to where you could get right at a one for in-sample and right at a one for out-of-sample as well. Let’s see. Keep going here. Yeah, just keep it simple. Man. And Russ is saying, “Does the average cycle duration vary considerably between Josh’s strategies?”
Not really. I mean, it can, but there does seem to be a bit of a wheelhouse there, but I haven’t really seen much of a cycle variation. But at the same time, we’re running up against what I’m saying with the testing where things are…We’re not comparing apples and apples, because as we start going in to the past ten years, we’re seeing a lot of these leverage products come in. So, it’s a little bit hard to give you a feel on that right now, Russ. But shortly we’re going to have that waiting, so I’ll be able to tell you in our calls.
Mark’s saying, “Ten day holding of stocks would be good.” Tom wants me to talk more about money management, how much to devote to each strategy. So, we’ve talked about that a couple of times, but it’s always worth repeating. I think it’s one of the most important things is money management. And so, the rule of thumb is: never have more than 1% of the average daily volume of something, and most of these instruments are really good with that.
There’s GLL and some of the real estate DRV and – was it DBN? If you have a bigger portfolio size, we can toss that out. We just don’t want to get a lot of slippage. Typically, this is something that you really see when people trade penny stocks, they buy a million dollars’ worth of a penny stock, and then suddenly they realize they can’t unload it. They’re affecting this thing goes up and down too much.
Every now and then, you see that, where somebody maybe they just get into trading and they have no idea how the markets work, they don’t understand that there’s bid size, there’s different bids and ask. And then as they get hit, the price starts going up, right? So, you get worse and worse and worse slippage as your order fills, right?
And so the vast majority of these instruments are all highly liquid. One of the things, too, that Josh did was he trades a huge amount of strategies. And then the plus is that he’s barely taking up any of the volume in that particular instrument. The other plus, too, is that the more strategies you trade, the smoother your results tend to be.
Let’s say I’ll do 30 here. Let’s check it out. Let’s see how that affects performance. Let’s go ahead and check that out. Okay, so your CAGR dropped to about 78. So, it went from about what? It was about 100 to 78. And then your max drawdown was about 8%. Get some out-of-sample. You can really tell it looks pretty smooth.
Now you’re 100% in-sample for monthly and then 91… And this is during a bear market, too. That’s one of the unfortunate things about having… This is a shorter test. This one’s from 2017. And so you had a one year bear market over here.
These other ones were pretty quick. So that could be some of the discrepancy between the in-sample, out-of-sample. It’s a very short back test. But the 2017 test have all the instruments in it, so all the leverage stuff, they’ve been just adding more and more and more products so you don’t have to go to the futures market anymore. And what’s part of our risk management, too? The more stuff you trade, the less likely something is going to go against you. And so, yeah, there’s a lot of great things happening.
And then the black swans for money management, so many great things happen, you’re less at risk. Let’s say tomorrow they ban China, right? Decree! The west has banned China! Well, they did that to Russia and overnight that what was the ticker? RSX? Gone, wiped out, vanished, done.
So that’s why I like to give you the realities of what could happen. It doesn’t mean it will, but it allows you to, if you were thinking about going balls to the wall, hopefully you’ll reconsider a little bit and just at least keep that in mind.
Hopefully that answer is a bit more about money management. And right now, it splits everything up evenly. So, if you had 30 positions, what is that? About 3% per strategy? And then it’ll be even less as we add the leverage product, that feature for waiting as well. So that’s high on the list of—the-get-shit-done list is very high.
And Mark is saying, “What about breaking it up into several periods?” Not sure what that means. Oh, with in-sample, out sample. No, keep it simple. I would not do it. It doesn’t need to be. Keep it simple for individual. That invention was actually made for intraday trading, by the way, keeping it to breaking it up. If you have a huge amount of history or you’re trading, let’s say your history back from 1986, it was to keep the in-sample, out-of-sample really stable, and it was really meant for intraday trading as well.
What I’m referring to is back down here, that you could have a whole bunch of in-sample, out-of-sample periods, like ten. We’re one of the few on the market that has this ability, but not that many people thought about it.
You see it’s bitching at me here because the back test is too low, right? It’s all by design. But what we’re doing, we don’t need that. It’s going to really lead to overfitting to the past. You don’t need it. Keep it simple.
And Mark is saying, “How to let the computer optimize the day of the month to switch strategies.” Don’t even optimize that. Keep it simple. Hey, if you don’t want to trade, think about switching strategies on the first of the month.
Don’t optimize it, man. If you sit there and you’re trying to refine it and you’re like, oh, let’s just trade on the 13th trading day of the month. No, you don’t need to, because we’ve already gone through a phase where we’re building the strategies and there’s the potential for overfitting there. We don’t want to do anything remotely that be overfit. When we’re creating meta strategies, it has to be simple.
Now, there’s a lot of wiggle room when you’re creating individual strategies. There’s a lot of different techniques that you can use. It’s beyond the scope of this call, but that’s including having all these different in-sample, out-of-sample periods. There’s a wide variety of things that you can do.
But think about this thing as an amplifier. The meta is an amplifier of what you already have. So, it’s going to amplify any flaws in your strategy. Got to keep it simple. No overfitting. Everything in your power to avoid overfitting is fine by me. I guess I can’t say that enough. It’s a good question, thank you.
And then Dean saying, “Confirming from the email, the weight percentage is the percentage of the value of your account for that trade, right?” Yeah. So, what it’s saying is, like, let’s say that…Let me just switch it back to 20 because it’s easier for my brain to process 20 strategies. Because one strategy is going to be 5%.
Dean, why is this bear keep popping up? There he is. That’s why I didn’t ask for that. Microsoft, get out of here. Let’s do a mouse. Over. Just wants to pop everything up on me. Okay. Must be something new. I haven’t noticed that before.
So, each one of the strategies is going to be 5%, right? Now, if I look at our trading strategies over here take a look. I can already tell you which ones are not performing well and which ones are. So, we can look at our weight here. If we know that each strategy should be weighed 5%, that means that this strategy right here—I got to pull it out a little bit more here, so you can see the whole left-hand column. You know that this is a losing position because it’s weighted under 5% right now. So, it’s probably losing a bit. This one’s probably losing a bit. This one’s losing more than normal. And then this one’s making money. And this was making money as well. That’s kind of interesting because of how big their weighting is. So if it’s 5% then that’s 1/20th of your portfolio. Does that make sense?
Hopefully that answers your question about the different weights in there. And then the trade plan is smart in the way that… I don’t know if it’s super smart when it comes to shorting strategies yet, but if we look at the trade plan calculator, check this out, it does know that you’re swapping stuff.
And then you can see it over here. Where is it? My eyes aren’t so good on this one. I think I was looking at something earlier. Yeah, never mind. My bad. I’ve looked at so many things. I thought that there was a really good demonstration. Not on this strategy, unfortunately. But hopefully that answered your question about the weights and stuff.
Randy’s asking, “Is the Basket file in the release?” No, it’s not. We haven’t done full…See, I wanted to leapfrog that so you didn’t have to use basket and then do the auto trading. And like I said, I’m hiring a second person on it because it’s taking way too long.
I don’t want one employee to slow us down for where we need to go. It’s been a really weird year or so, more than a year, dealing with so many programmers in this auto trading. I don’t get it. We just had really bad luck, as far as I can see.
How are we on time? About 2 hours, 20 minutes into it. Okay. I’m glad I budgeted at least 2 hours into it. You guys have any other questions for me? I would be happy to answer for you until you run out of questions for me because I know this is a totally new topic, and I appreciate you guys.
This is the first time I’ve taught it, so I appreciate you guys hanging out with me. And looks like we actually have more people that joined us during hour number two. What the heck? That’s cool. And then what’s going to happen, guys, is this is going to be made all pretty and will blur me out a little bit.
We’ll make this chunked up into individual sections, and I’m going to get this over to a video editor and then I have everything all mapped out so they can just go ahead. And when I’m jumping around a little bit, they can make it nice and pretty for you and easy to digest so you can refer to it all you want.
We’ll be adding more sections to it as we progress and add more features. And then John’s asking, “Any plans to extend other brokers with an API?” Yeah, we just want to perfect it once with IB and then I think that we can go to other brokers as well.
Well, thanks, Mark, appreciate you enjoying this very thorough training here. It has to be, because I want to be able to for you guys to be able to refer to it any subsection that you want on there and then I like throwing in a lot of anecdotes as well.
I hope that that instead of sticking to the script the whole time, I like to jump around a little bit to give you examples as well. I wish more people would have told me about black swans and things when I was trading, I probably wouldn’t have listened those much, but you guys are at a level…Just to get into this class. It’s very expensive compared to pretty much anything else on the market for good reason. It actually works. You guys are at a different level, though.
This is all about treating trading as it should be, a business. I always say, say trading is one of those weird events where it’s the equivalent of you teeing up next to Tiger Woods. So, you going up with a professional. You have all these sharks, man. They’re sharks. They’ll slit your throat and take your money. They don’t care. You got crooks, literal crooks on TV doing illegal stuff, in my estimation. Say, Bill Ackman, I think what he did was illegal. Pretty damn sure. Pump and dump on live TV. But basically, we all have that ability to tee it up next to all these professional sharks that will just take your money. And so we need to trade as a business, treat trading as a business. They do, man. They have front offices, back office. They have a lot of tools at their disposal. But what I have modeled this company after is Jim Simons and Renaissance Technology.
It is 100% going down their footsteps. Everything I could figure out and reverse engineer from those code crackers, because the way that their minds think is how I think. That is exactly… It was this uncanny as I was reading through that book, The Man Who Solved the Markets.
This is what they’re doing, as far as I can tell. It’s very similar approach. It’s like an Uber strategy. And now we have meta strategies, right? It. They use a lot of weird data. Thanks for coming on, Courtney.
I appreciate it. Randy’s saying, “Let’s run multiple meta tests using random and never got anywhere. So, the new evolutionary option will fix that.” Yes. You really need the whole suite on there. Actually, the boys put in some stuff on metas that I didn’t even ask for, and I was like, “Yeah, I don’t like this. We should have put the evolutionary on here in the first place.” And they’re like, “Yeah, sounds good.”
So, yeah, the evolutionary option will fix that. That’s pretty much what the whole training was about. Fixing all that stuff, making it amazing, having the entire suite of tools at our disposal: in-sample, out-of-sample testing, the whole show.
We took it from building individual strategies to building meta strategies, uber strategies, strategies of strategies. Thanks for coming on, Bill. I appreciate you. Thanks for everything you’ve done, man.
Really appreciate it. Thanks, Russ. I was hoping it was going to be exciting! Thank you, Gary. I appreciate you. Robin and Dean. The pretty version is showing up real soon here. The boys have been the fellas that’s the engineering team, they’ve been rushing.
There’s like a new net version, and then we have a guy that just breaks Portfolio Boss. It’s like a simulation where they pushes every button possible, and I guess he broke it. So, Horatio is like, “Hey, we’re not ready quite yet, so let’s find why this thing is breaking and then we’ll release it.” But, yeah, we’ve been. Ready to go for I’ve had this in my hands for quite a while and. Just been refining and just a. Couple more features. And I think we’re at 100% here.
Yeah, the recording. Thanks for coming on, John. Allen, Tom. Shout out to you too, Dallas. And I’m sure he appreciates that. Josh appreciates that. Sharing his hard-earned top dog strategies and his top getting to the top of the field at FundSeeder was not the easiest thing in the world, but you just.
Have to have some gumption. He really worked hard building those strategies. Put in a lot of hours with the boss, a lot of. Time.
All right, guys. Thank you very much. For showing up and hanging. Out with me. I’m going to go ahead and end it there and I’ll go ahead and keep you updated on exactly when everything is being released. I hope you’re really excited with anticipation here and I’ll go ahead and get this video just made.
Nice and pretty. We’ll get it into different subsections so you can refer to it. Anytime you want. I wish you health, wealth, and man, just kill it, man. I hope you guys make a lot of money with it.
And in the back of your mind, just think maybe be a little more defensive than offensive. So, with that, I’ll catch you later, man. Have a good one. Dan Murphy signing out.