One Risk Trick to Never Blow Your Account

This week on Talking Wealth, Filip and Pedro break down the one simple risk trick which makes it mathematically impossible to blow your investment account. Over the past few weeks, several high-profile investors have been hit with margin calls, proving that even the biggest names in finance can get risk management wrong. In this jam-packed episode, the boys break down a little-known risk formula that could completely change the way you think about managing risk and trading the markets.

• 0:01Speaker 00

  This podcast is brought to you by Wealth Within, a global leader in stock market education. For more information on our courses, head over to wealthwithin.com.au. Please note that the information in this podcast should not be considered personal financial advice. Enjoy.

• 0:20Speaker 01

  Welcome to the Talking Wealth Podcast, joined with Phil and Pedro. And today we are going to be discussing risk and showing you one formula that has really stood the test of time. It's something that is not spoken about often. It's a formula for managing your risk in a way that in theory allows you to never ever blow up a trading account. Now, I want to welcome in Pedro before we dive right into this. Pedro, here you go, mate.

• 0:50Speaker 02

  Yeah. Good day, Phil. What a, what an exciting, sexy topic we have today, I'm sure. Nobody ever said they're excited to talk about risk, but it's such an important part of trading, isn't it?

• 1:03Speaker 01

  Oh, mate, it's the most important. It wasn't sexy when I was going, like this all came about, I was going through some, some old boxes that I had to put away. You know, those boxes that you never put away, but at some point they're sitting there in that garage and they're like, all right, it's time for you to finally go. And anyway, I opened it up and there was a whole box of books that I had read over the journey. And the ones that I had kept, books on trading, books on investing, books on psych, not really. I don't read stuff on psychology, but actually I do, I have read one book on psychology. But books around all that kind of stuff. And I went back and I went, damn, you know,

• 1:44Speaker 01

  I've read a lot and one, it's got a green cover. So it really stands out. And it's called the Cali Criterion, or the Cali Formula. The book's called Fortune's Formula. And it really speaks in a unique way about how a group of people worked out a specific methodology in terms of how to manage risk properly. And when I first read it, I was blown away. I was like, oh, wow. I've never seen anything like this before. And I think it's timely that we talk about it today because before we dive into that book, I just want to, you

• 2:29Speaker 01

  know, outline where things have gone in the last couple of months. Because that is the biggest, the biggest reason why I'm doing this, or why we are doing this podcast today, because risk is back in the spotlight. We've seen over the last couple of years, everyone's been focused on finding that next big AI winner, or the next crypto meme, or stock out there. And in these environments where things are moving so fast, ultra bullishness, a lot of people are making money in markets, risk gets forgotten. And what we've seen over the past two, three months, even up to, leading up to this week, the first thing we saw was, I don't know if you remember a few weeks ago, in South Korea, the South

• 3:13Speaker 01

  Korean stock market, which is, as you know, mainly driven by that semiconductor trade.

• 3:21Speaker 01

  That saw people, and I remember you were talking about in Taiwan, people talking about getting into semiconductor stocks and, you know, we're going to make all this money and we're just going to buy, buy. But what happened in South Korea, the stock market fell. And the South Koreans, before it dropped, and it only came to light when it dropped, was because South Korea had one of the world's highest levels of retail leverage going on. And the retail investors piled into these stocks. After the correction, there were massive margin calls, as prices fell, forced a lot of liquidations. So it forced brokers to sell. For anyone who doesn't know what a margin call is, because it's, I think I

• 4:02Speaker 01

  should explain it, because I was chatting to, to media yesterday, and the lady, I said, do you want me to, do you know what a margin call is? She said, no, but you explain it to me. So I thought, oh, okay, it's important that we explain it before we move on. For those that don't know, I apologize if you do know, and I'm repeating things. But basically, what happens when you invest, you have a pool of money, let's say a hundred thousand dollars, for the sake of a round number. If you invest that hundred thousand dollars, the volatility of that money being invested will either go up or go down. If it goes down to where that hundred thousand dollars is going to zero, especially if you're trading on leverage, what will happen is a broker will call you. And they will say, you need

• 4:47Speaker 01

  to put more money in your account right now, or we are going to force close your position. So you may believe that it's still going to go higher and you want to hold the stock, but you've just maxed out on how much money is in the market and it's gone against you. And the broker could close your position for you. And that's what happens when they say people get margin called.

• 5:08Speaker 02

  You, you have to put more money in or close out your position, because you can keep it open if you pile more money in. And the way that I usually explain it to students, you know, it's really about that loan to value ratio. And I use the example of a house. So imagine your house is valued at a certain amount of money, and then you've got a loan against it. Just say it's, it's worth 500,000. You've got an 80% loan to value ratio on that house. Now your house falls to, to 400,000. That's the beauty about houses. I mean, they won't ask you to, to top it up. But with shares, if that value drops, then exactly you have to top it up, or they close it off.

• 5:47Speaker 01

  Maybe not residential, but investment properties, they do, you know, they, they will.

• 5:53Speaker 02

  Yes.

• 5:54Speaker 01

  So yeah, good point. Now, that's what happened in South Korea. So we're already, you know, last week or two weeks ago, we saw that story come in. I thought, hmm, interesting. Retail investors taking on huge leverage, getting margin called. That's, that's interesting. That is a sign of, of, of maybe where we are in the times. Do you want to say something?

• 6:15Speaker 02

  Yeah. You know, another interesting thing I found, I was looking a little bit into that, that trade, what in Korea, they brought out two to three times leveraged ETFs there.

• 6:25Speaker 01

  Yeah.

• 6:26Speaker 02

  So on top of that, you know, leverage and piling on top of two to three times leveraged ETFs, it's, it's, it's a recipe for, for disaster.

• 6:38Speaker 01

  Mate, this story is as old as the story of creation. Before every serious market crash we get, or any, whatever sector, whatever instrument, whatever it is, before a crash, you often find the retail end wildly speculating. Happened with gold recently, happened with Korea just now, happened with crypto. It is one of the best markers to tell you that, hey, you're near the top.

• 7:07Speaker 03

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• 7:33Speaker 01

  We move on from the retail space now to what happened in the other day, the other day with our friend Leopold Ashenbrenner. Why this story becomes interesting is because it's not just the retail end taking on wild risk. There is so much belief and so much hype around AI right now, that this story was of an AI researcher that worked for one of the Google or Meta, whoever it was. And he basically wrote a white paper on, on the future of AI. Somewhere along the line, he doesn't work there anymore. And Wall Street

• 8:13Speaker 01

  catches on to his white paper. And he gets offered a hugely large sum of money for him to go and take, become a fund manager. So he's got his, his fund, which is called.

• 8:29Speaker 02

  Situational awareness.

• 8:30Speaker 01

  Situational awareness.

• 8:32Speaker 02

  Same name as the white paper.

• 8:34Speaker 01

  Yeah, situational awareness, which when, when we finish this story, you'll realize that he has actually no, it's so perfectly fitting to call it that, because there was no situational awareness in what was done. Because he basically blindly bought in his story that AI was, was going to continue and the rate it was going, which was damn near vertical. And for a while, it produced some really strong gains. But the reality was, the market corrected. He had such a big position relative to the total capital

• 9:12Speaker 01

  of, of, of the, the portfolio, that that correction triggered a margin call. And he was forced to liquidate those positions into weakness. So the lesson here isn't, and if someone's turning around and saying, yeah, but he was up 400%, and we've seen comments like that. So what? He, he's not going to be able to see out his conviction now, because he had no thought for risk. He ran out of time. And this is the, the story behind what is going on. There's risk problems on the retail in this, again, no, no concern for risk. This is a kid 24 years old, never been a fund manager. They've thrown him in

• 9:56Speaker 01

  the deep end and expected him to do something with it. And he forgot the golden, the first rule of investing. They're called money managers for a reason, is because their job is to protect, to protect capital, to understand volatility, to know how to place the right size bets, so that that money works to see out the thesis that they have. So you can see out the story that you, you want, and not get stopped short by getting your, getting the markets, getting your position sold on you, because you've taken on way too much risk.

• 10:29Speaker 02

  Yeah. You know, in his defense, I read that he, he did try to hedge. So he was short the software companies and long the hardware companies, right? But he took a double hit. The software companies went up and the hardware companies came down. So the semiconductors. So it was a double whammy.

• 10:51Speaker 01

  Well, then that tells me another thing about him. The whole purpose of hedging is so that it cancels out each other. And that's a crap hedge. And.

• 11:05Speaker 01

  And so, and it's a hedge in the same field. A lot of times you see hedges in, in non-correlated um asset classes.

• 11:15Speaker 02

  Yeah, yeah, exactly. Yep.

• 11:18Speaker 01

  So um anyway, it's not a story about his investment, uh you know, what he's doing with his investing. It doesn't matter. It's, it's what can happen and why risk is at the forefront right now and how it's going to help you guys. Uh and girls listening to this, um or ladies and gentlemen, I should say, we're adults here. Uh not, not guys and girls, but um.

• 11:38Speaker 02

  It's good to start early.

• 11:40Speaker 01

  Ladies and gentlemen, and you know, uh I'm sure there's, there's a few other classifications that, that we've missed and we have to be, we have to be equal, equal to everything in today's world, Pedro. All right.

• 11:51Speaker 02

  Um, yep. Training knows no bounds.

• 11:55Speaker 01

  No, no, that's right. Now, let's, let's move on to the third example of risk going a little bit haywire recently. Um and this is our good old friend, Michael Saylor at Strategy. The Bitcoin uh guru. Now, this was not a margin call. It's slightly different. So I want to explain what happened with him in the last day or two. So Strategy, uh which is the, the listed company of Michael Saylor, basically had to sell Bitcoin. Um it sold its largest portion of Bitcoin in July, so its second largest portion of Bitcoin um recently in, in August.

• 12:37Speaker 01

  And he basically stated the reason he was selling was to shore up cash reserves.

• 12:42Speaker 02

  Hmm, I heard that too, to, to meet uh short-term debt obligations or something.

• 12:48Speaker 01

  Sorry, mate. It means you've, that's just that fancy word for means your exposure is risky. If you have to sell your, the thing your company is built around, which is conviction around Bitcoin price rising. That means, and, and, and price is falling, that means the financial uh health of the company is in such a stress that you need to shore up cash reserves. Uh that is a proxy margin call, if you will. Maybe they haven't told him out, but he's uh closed him out, the brokers, he's closed himself out to be able to protect the financial health or, or the view of the financial health of the company, because obviously

• 13:32Speaker 01

  uh you know, being listed, there's, there's reporting and there's all that kinds of stuff going on. Um so

• 13:39Speaker 01

  there's the, you know, and let's not even go into the conversation of, this is the guy who said he'd never sell Bitcoin. So let's not talk about the convict, his conviction in Bitcoin. Let's not talk about what that means and the flow and effect for people that are diehards and, and, and believe that you should hold forever. Let's not talk about if Bitcoin goes down to twenty thousand, if he's selling at sixty, what happens at twenty thousand with his fund? Um.

• 14:03Speaker 01

  None of those questions we're going to answer today. Um but the point, the point we're going to talk about is that, again, someone who risk, um it seems, because somebody with, with healthy risk uh controls doesn't really need to uh chop into the investment

• 14:31Speaker 01

  or destroy the investment to, to shore up the safety of the company. It's like, you know, you, you run a business and you, you, you sell whatever. You're going to stop buying product to shore up the company because you've taken on too much risk, where the buying the product and selling the product is what you, how you earn money.

• 14:56Speaker 01

  That to me is, is just says it all about no consideration for risk. And a lot of, when you relate it back to this strategy here, uh not the company, but what they've been doing. I think it goes back, back to the talking, talking point. I'll get your thoughts on this, on

• 15:13Speaker 02

  Hmm.

• 15:14Speaker 01

  how these people are investing. Um, in my opinion, Michael Saylor's investment thesis is dollar-cost averaging to some degree.

• 15:25Speaker 01

  Um that's what has been employed, you know, constantly just buying, no uh thought for selling unless you're in trouble. Um and I think that conversation needs to be had now because uh if you're someone who, you know, like our, our students and our clients that have come to us, margin calls don't happen. Um if they're following the sound risk and management that's being taught to them, because um the only times I can see what investment strategies you can get margin called is something like a dollar-cost averaging method, where you're consistently buying, let's just say in a bull run, as it's going up, you're adding, you're adding, you're adding, even if you're adding to pullbacks.

• 16:07Speaker 01

  Or in a downturn, you're adding, you're adding, you're adding, but the stock doesn't stop falling.

• 16:12Speaker 02

  Um, yep.

• 16:14Speaker 01

  That's where, if you don't have stop losses in price, if you don't have capital controls, if you're only risking an X amount of your total capital each time. Um if you understand that your edge should uh garner you m- more profit than, than loss, so you allocate your position sizes accordingly. I don't think there's any of that going on here with, with Michael Saylor's style. And it is a hallmark of one of the main risks somebody takes is dollar-cost averaging. And, and that is a big thing in these markets today and has been in the past, because we hear it all the time. People come to us, say, hey, my mate told me about this company that does um

• 16:55Speaker 01

  yeah, I don't know, lime bricks that are going to change the, the, the building industry. Okay. And I've just been buying. And we look at the share price and the share price has been falling from three dollars down to four cents.

• 17:10Speaker 02

  Hmm.

• 17:10Speaker 01

  And I'm just buying it because, you know, it's a good story and, and my mate told me that they're going to release something in two years. Or they're going to release something next week. The CEO is going to do this. Um and then the share price dumps and you've been margin called.

• 17:24Speaker 02

  Yeah.

• 17:25Speaker 01

  Because you've lost half your capital or your, or your capital. Um.

• 17:30Speaker 01

  What are your thoughts on that?

• 17:33Speaker 02

  Yeah, I, I think this was always going to happen. When, when he bases his whole business on just two decisions, whether to buy or sell Bitcoin, he's really playing with one hand, or maybe even both hands tied behind his back. I mean, really, the, the way that, uh one of the ways that you manage risk is to diversify a, a little, uh not diversify by going into too many things. But I mean, what we teach i- in our course, you know, eight to twelve stocks or, or, you know, different types of uh, of, of assets and, and things like that. Whether you're trading a little bit of oil, uh you know, a bit of stocks or whatever. I mean, that's the way that I do it.

• 18:11Speaker 02

  Uh so if you're wrong in one of them, it's not going to completely wipe you out. Then you're right in the other one and you just kind of even yourself out. But I mean, I'd struggle too. If I, if I, if I was limited to only trading just one thing, you know, it's going up, you've already put your position, it's going up, what else is there to do? I think that, you know, he, he's really, he shot himself in, in, in the foot. And I think that he was really relying on that kind of hype of everybody to, to, to hype up that, that asset class.

• 18:43Speaker 03

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• 19:13Speaker 01

  And he's, and that's a, you know, a nice word, trading. He's not trading, he's just buying.

• 19:18Speaker 02

  Hmm.

• 19:19Speaker 01

  Which is, you know, um but anyway, I think this

• 19:24Speaker 01

  this brings the, the, us to the, the cool part of the, the podcast, which is, you know, whether you're a retail trader billionaire or the biggest Bitcoin bull on the planet, i- it, it all comes back to exactly the same problem. How much should you actually risk? So this is where we get into the Kelly formula. Now, I want to explain what the Kelly formula is a little bit. I know I touched on it earlier. And then we can dive into its application to how you can use it as a trader. So basically where it came from, it's the, the Kelly criteria was developed in nineteen fifty-six by Bell Labs scientist John L. Kelly, Jr. His paper wasn't about investing. It was about maximizing information transmitted through noisy telephone lines.

• 20:08Speaker 01

  So later mathematicians realized exactly the same mathematics applies to betting and investing. Now, this, one of the most famous books, as I mentioned earlier, is called Fortune's Formula by William Poundstone. It's a good read. It, it's a really good read because it, and I employ everyone to, to go and have a read of this book, because it, it doesn't just, you know, talk about him, uh the formula. It talks about uh Bell Labs, how it was created, how they came up with this. It talks about some people in the, in, in the book, which are, you know, you would know Ed Thorp. I'm pretty sure you know him. Ed Thorp, the trader. Have you heard of him?

• 20:46Speaker 02

  I, I think we've talked about him before in, in one of our previous podcast. Yeah.

• 20:50Speaker 01

  So John Kelly, who's another one, another guy called Claude Shannon, these guys took this criterion, what was one of the um the cool parts of this story is they took it to the casinos. And originally, and they had this machine where on the roulette table, they could work out the rate, the speed that the ball was spinning, they could work out approximately where it will la- would land.

• 21:15Speaker 02

  Yep.

• 21:16Speaker 01

  Because they had like a speedometer. And they would

• 21:19Speaker 02

  Right, that's, that's interesting. Yeah, it's a similar story to what happened in Spain where they figured out the wobble of, of the table.

• 21:26Speaker 01

  The wobble, yeah. These guys had a speedometer and it would automatically assign, calculate at that speed, starting at that ball, this is where it should land. So they'd place their bets. Um, but they

• 21:36Speaker 02

  I wonder what the casino thought of them standing there with the speedometer.

• 21:40Speaker 01

  That it was hidden, everything was hidden. Um, but they eventually got caught and they probably got punched up a few times as well. Um, it says it in the book, they had to wear, um, they had to wear, uh, costumes to not

• 21:53Speaker 02

  Right.

• 21:54Speaker 01

  Yeah. Um, nevertheless, they, they made a, a bit of money out of that, that venture. But the point is not only how they could see it. Once they realized where it was going, it assigned a percentage and they could allocate a position size relative to that percentage and relative to that edge. And it wasn't always the same position size. Sometimes the edge was like, this is a 90% success rate, a hundred percent success rate. From the examples in the past, you'd allocate a higher, um, position size to that. This one's a 10% and you allocate a low, lower position size. But the key is that you have the right data and you have the, the, you know, um, you really understand your data. And so

• 22:38Speaker 02

  Sounds familiar, doesn't it?

• 22:40Speaker 01

  Yeah, yeah, exactly. Um, our students would know exactly when talking about building strategies and backtesting and all that kind of stuff. But, um, so this then transferred, he, he, uh, John Kelly and it thought then it ended up transferring it into Wall Street and hedge funds. Um, where they ran funds and, and, uh, applied this theory. So it's really cool story where it comes from. Um, I'll explain a little bit about what it is as well. Um, so this is how I'll explain it because it, it, it can be a bit tricky. Imagine I gave you a coin. Right? Every time you flip heads, you double your money, tails, you lose everything you bet.

• 23:24Speaker 01

  And you're able to play forever.

• 23:28Speaker 01

  How much should you bet?

• 23:31Speaker 01

  Right?

• 23:32Speaker 02

  Right. Yeah. Do you put in 50% of your capital?

• 23:36Speaker 01

  But if I was to ask you that, you get to play forever. How much would you bet? If you said it doesn't matter if you lose, would you say everything every time?

• 23:47Speaker 02

  If it doesn't, so you, when you lose, you lose nothing.

• 23:51Speaker 01

  So if you lose, you lose everything. If you

• 23:53Speaker 02

  Oh, you lose everything.

• 23:54Speaker 01

  If you win, you double your money, but you can play forever. How much would you bet?

• 24:01Speaker 02

  Yeah, that, well, that's a good question. You'd have to figure out the position sizing and how much.

• 24:06Speaker 01

  Well, you're talking like someone who's a bit, give me the, give me the dumb answer. Don't give me the, the, the smart answer. You'd say everything.

• 24:13Speaker 02

  Yeah, for, for sure.

• 24:14Speaker 01

  You're saying, you're saying I can play forever and I can double my money. I'm just gonna risk everything.

• 24:20Speaker 02

  Just, yeah.

• 24:22Speaker 01

  And some people will say half.

• 24:27Speaker 01

  Very few people will say what you said. Work it, work it out. Um, 10%, they might say. Now,

• 24:34Speaker 02

  Yeah.

• 24:35Speaker 01

  What Kelly proved mathematically is that there is one bet size that grows your wealth faster than any other over a long run.

• 24:45Speaker 01

  You bet more, eventually you'll blow up. You bet less, you'll survive but grow slower. And this is where this formula finds the sweet spot.

• 24:53Speaker 02

  Mm hmm.

• 24:54Speaker 01

  Okay. Um, why it was revolutionary was before Kelly, people were always asking which investment should I buy? He said, how much of it should I buy? Completely changed the game. Um, and I think one of the best examples in, from the book was the gamblers, because he, he showed this formula to a bunch of gamblers and the ones who ignored Kelly, they usually went broke even when they had an edge. Think about that. So imagine a casino game where you win 55% of the time, you lose 45%. That sounds incredible for casinos.

• 25:29Speaker 02

  For sure.

• 25:30Speaker 01

  Sometimes the edge is 1%. Now, yet you keep betting half your bankroll. Eventually random losing streaks will destroy you. So the edge wasn't the problem. It was the position sizing.

• 25:43Speaker 02

  Mm hmm. Yep.

• 25:44Speaker 01

  Because if you bet half your bankroll and you got four, five losers, even though your, your edge is statistical, you're going to get wiped out.

• 25:54Speaker 02

  Yeah, yep.

• 25:55Speaker 01

  So

• 25:56Speaker 02

  Because if you put too much,

• 25:58Speaker 01

  Yeah.

• 25:58Speaker 02

  Then eventually you'll get wiped out. Yeah.

• 26:01Speaker 01

  And, and even if you put, yeah, exactly. So I'll give you the formula, um, and how traders kind of use it today. So let's just say the pure Kelly formula is the Kelly percentage, which is how much you should risk equals the edge divided by the odds. So in trading, it's usually written as the formula equals the win rate minus the loss rate divided by the risk to reward ratio.

• 26:33Speaker 01

  You don't have to calculate it every day, but it's the principle that matters, right?

• 26:38Speaker 02

  Um, yeah, yeah.

• 26:40Speaker 01

  Now,

• 26:43Speaker 01

  the reality is a lot of, in modern application where, where these guys have taken this is professional investors, they rarely use the full, the full Kelly criteria and they're, they're often using like half, quarter or even smaller because and when I say if you, once you work out that formula, you decide to use half of that risk or a quarter of that risk. And the reason I say that is because most people, if, if we're being honest, truly don't know their edge.

• 27:10Speaker 02

  Hmm.

• 27:11Speaker 01

  They don't understand it. So

• 27:13Speaker 02

  I don't think most people know what an edge is as well, that they should even have one.

• 27:18Speaker 01

  Hmm.

• 27:19Speaker 02

  Or maybe they, they wrongly think they do have an edge when they don't.

• 27:24Speaker 01

  Yeah. Yeah, it's so true.

• 27:26Speaker 02

  I remember you were talking about a student that would just be buying the dips and he was making money just buying the dips. And he probably thought he had an edge and then it's like, but when is a dip not a dip? Uh, and you know, so when does that become? And if you don't have this type of risk strategy, then you're going to get wipe out all of the stuff that you, um, that you profited from earlier.

• 27:51Speaker 01

  Yeah, there's a difference between understanding real edge and, and understanding, um, or being uh, slapping on a set of criteria to noise and, and assuming that to edge. Um, very different. And, and look, even the professionals, mate, you know, hedge funds, they deliberately use fractions of the Kelly, uh, percentage that they get because estimation errors are often bigger than the people realize. We're talking professionals even leave a buffer for human error in understanding their edge.

• 28:26Speaker 02

  Hmm.

• 28:27Speaker 01

  You know, we have a formula that we teach our students in terms of how much of your total capital you should risk. And that, and that is somewhat in line with what is being said here. It's, it's part of the same conversation.

• 28:43Speaker 02

  Um, yeah, definitely. I can see the, the relationship.

• 28:46Speaker 01

  Hmm. So I think, uh, if we get to, I, I want to give like an example, if that's all right, because I think we might be uh, getting, uh, out of time in what we're doing, but if I can give an example that, that might help kind of explain this, um, again, uh, uh, to, to leave it. So imagine you've got two traders, right?

• 29:16Speaker 01

  Both have a hundred thousand dollar account. A strategy that wins 60% of their time. Average winner is two times the average loser. So two to one risk to reward, right?

• 29:29Speaker 02

  Mm hmm. Yep.

• 29:31Speaker 01

  They take the exactly same, exactly the same trades. Now trader A risks 20% of his account on every trade because he's confident. So he starts with two losing trades. His account goes from a hundred to eighty to sixty four. Now he needs a 56% return just to get back to where he started.

• 29:52Speaker 01

  So his strategy at 60% win-loss was a good strategy. But his position sizing is way too aggressive, taking 20% of risk on the account.

• 30:02Speaker 02

  Yeah.

• 30:03Speaker 01

  Now trader B uses the Kelly formula or more realistically, maybe half the Kelly formula. And he says, oh, 60% re, uh, win-loss. Uh, plug that in, um, two to one risk reward. And that he decides, okay, that's 10% on the number, but I'm only going to risk 5% per trade. Okay?

• 30:26Speaker 02

  Mm hmm.

• 30:27Speaker 01

  He also starts with two losing trades. His account goes from a hundred to ninety five to nine, nine, ninety thousand two fifty. So he's down less than 10%. He's still calm. He's still following his strategy and he's got plenty of capital left to take the next winning trades. So again, the difference wasn't the strategy, it's the amount he risked. Now, I'll give you another example and, and then further explain it in real world, how, how I uh, look at it and, and, and some of our things. But the second example is a coin toss.

• 31:02Speaker 01

  Imagine I offer you this game. I'll flip a coin, heads you win two bucks for every dollar you bet, tails you lose a dollar. Would you play? Most people would. Now here's the question, how much of your money would you bet each flip? If you bet a hundred percent, you'll eventually go broke. Fifty, you'll probably still too much. Twenty five percent it's better. You've got four chances. Five to 10%, now you're thinking about survival. So Kelly is simply the maths that tells you how much to bet, not whether, um, whether you should uh, take the bet. Now, when I liken it to my real world, uh, type of trading, I look at it like, let's just say you have an opportunity, you have a stock that's come uh, to an opportunity for you, whether it be, you know, it's at a level that, that, that looks really attractive like Cochlear or CSL, whatever the case may be.

• 31:48Speaker 01

  You have to have a systematic approach in, in, and, and a skill set in able to classify. Is this opportunity higher risk? Is this opportunity lower risk? This setup, what, how strong is this edge? Is this an 80% win-loss, 90% win-loss? Is it a 10%, 20% win-loss? What's the risk reward associated to that as well? Because if we take Cochlear, for example, let's just say you bought Cochlear after a 60% correction. In my opinion, that's a high risk, but a high reward type setup.

• 32:24Speaker 03

  Hey podcasters, are you curious to learn how you can gain more confidence with your trading? Check out the Australian Stock Market Show on YouTube every Tuesday night from 7 to 8pm. Discover how you can become a more successful trader and take your trading to another level. Get your most burning questions answered with Dale and Janine. We look forward to you joining us.

• 32:49Speaker 01

  Because it's higher risk, you've been given an entry, you decide, I'm only going to allocate 20% of my normal position size. Let's say in two months' time, you get another entry and things are lining up telling you that it's really giving you signals that things have turned. Now on that next opportunity, you say, okay, this is more in line with the higher win-loss type trading opportunity. So now I allocate a full-size position or 70% size position. Or you may have trading rules where one trading rule you know is a little bit more risky. So you allocate a percentage of that for that entry and you

• 33:32Speaker 01

  have other trading rules with more confirmation that have a higher percentage of success. So you allocate bigger sized positions to that. Where this is advantageous is because how many traders or how many times have you seen, you want to get into the stock but you're waiting for the perfect setup and the perfect setup doesn't come and you miss the opportunity. And you kick yourself and you go, damn it, I'm bloody too strict with my rules. I waited so long. But if you have a handful of rules that are going to get you into where you want to get in, but you know how to assign the right amount of capital to that relative to how that's looking at that point in time, and assign the risk to the setup, one, you're never going to miss an opportunity. And if you're wrong, you've

• 34:13Speaker 01

  assigned the right amount of risk to it. More often than not, you're assigning a lower amount of risk to an opportunity that's higher risk.

• 34:21Speaker 02

  Absolutely, absolutely. I have a similar rule, but it's to do with the ranking of stocks. So if it's a stock outside of the top 200, I assign a lower amount of capital to that stock. And of course, I mean, I look at the volatility as well and I look at how speculative it is because just say 5,000 in a nice liquid stock, it only needs to move 10% and then you got, you know, 500, right? Or it needs to move 50% to get to 2,500, so right? But it's doing it in a much safer manner. Whereas a specky one, I could put

• 35:01Speaker 02

  1,000 in there and it would have to go 250% to get there. But it is achievable if the volatility allows it, but I'm not risking as much.

• 35:13Speaker 01

  Yes.

• 35:14Speaker 02

  So yeah, totally understand where you're coming from with that.

• 35:19Speaker 01

  Awesome. Well, we'll leave it at that. I think, guys, it's something that has come to light over the past couple of weeks, risk, money management. Keep it in the forefront of your mind. Remember when you're investing or trading, first and foremost, you are a money manager. Your job is to protect that kitty, make the most of that kitty when the time permits, and know how to allocate that kitty correctly so that you give yourself the best chance of growing your portfolio the safe way. So thank you very much for joining Pedro. We'll leave it at that.

• 35:53Speaker 02

  My pleasure. It was an interesting one.

• 35:55Speaker 01

  Yeah, awesome. And thank you, guys, for tuning in. Please, as always, if you could give us a five-star review, that would be awesome. We can keep sending out interesting topics like this. And have a great weekend on that point. We will catch you on the next one. Bye for now.