Okay, so the projected win rate, okay, so the projected win rate, that's literally, you're telling the system what you want the win rate of your strategy to be. Now the profit target basically means are you going to have your wins? This is just like if you sell, you know, if you sold credit for a dollar, are you taking it to expiration, taking max profit, 50%, 60% stop loss is relative to the trade size. If you have a 200% stop loss, it means the stop is 200 or 2x relative to the max profit. Let me jump down to row 13 and that makes it more clear. If we're using, for example, the trade size is set to fixed, okay? And you have a fixed credit. So let's say it's 1%, that that's really big, but just for round numbers. So 1% of $100,000 would be $1,000. So if you set your profit target to 100%, that means on a win, you'll win $1,000. If you have a 50% profit target, it means on a win, you'll win $500 okay? Now, similarly on a stop loss, the stop loss is relative to this trade size, all right? So 1% is $1,000. If you have a stop loss at 100%, which is 1x, it means you lose $1,000. If you had 200%, which is 2x, you would lose $2,000, okay? So hope that makes sense. Now, just to make things clear about the risk reward profile, there's literally a line that says risking x to make one. So, and just to give an example, if I had a 100% profit target, but a 200% stop loss, a loss is 2x, I'm risking two to make one. So you'll notice in this line, it has a 2, right? You're risking 2 to make 1. But for example, if you take a profit target, right, if I set a 50% profit target, but I'm still having my stop loss at 200%. So going back to that $1,000 example, my win is 500, but my loss is still 2,000. So just so you don't have to do the mental math, it literally says risking, you know, for the make one just so you know what that win loss ratio is. Okay. So, um, the line on 13 again, fixed credit. So that percent is a percent of your account. One percent is honestly kind of high, but let's just use that for now and let's see what happens. Now, there's three lines for the black swans. Let me explain how this works. When you do the black swans, you want to input them as whole numbers. Now, this lets you inject up to three random black swans. And so if I say, let's say my stop loss is 200%. It means normally on a loss, it's two X, right? If I set all three blacks ones to zero, it just means there's going to be no black swans. Now, let's say I put a five. Right. It means it will randomly inject a single five X loss somewhere in the number of samples. And if I put, you know, five, ten, fifteen, for example, it's going to have a five X loss, a 10 X loss, a 15 X loss. And those will be randomly scattered into the trade. And one thing you'll notice is on the graph, there's basically going to be two different lines. One of them is the return without the black swans. Even if you have labeled black swans in the field, and then one graph, if the red line is going to be with the black swans, because I want you to see how different having a couple black swans can really do. Okay. So this is basically the setup. If you're going to do a fixed credit now for the target credit, this basically is going to, you know, if you haven't listened before, I would, I would go to the risk calculator episode to see how we use the targeting to figure this out. But for example, about $100,000 and you see the target return, I'm going to put in, let's say 10%. Okay. If I put in 10%, it means I'm trying to make 10% of my account, which means the target return is $10,000. Right. So you actually see that printed out in line four here. Now, depending on your setup. So let's say I do again, let's use a simple one, 100% max profit, 200% stop loss or 2x. And let's say I do a 75% projected win rate. As you guys probably know, if you're familiar with PCR, with this setup, you're going to have a projected PCR of 25%, okay? And you'll actually see that in line 10. It's called expected PCR. So based on the expected PCR and the number of trades you do is going to give you a credit target. And that's what it's going to use to size each trade. So just using this example again, $100,000, 10% target, 100% profit target, sorry, 10% return target, 100% profit target, 200% sub loss, which is 25% PCR. If I did 100 trades, you'll see that it's going to give me a credit target of like 0.4%. So that's what it's going to size it at. If I had 500 trades, as you would expect, the credit target goes down per trade because you have more trades, right? It's going to be 0.08. So one thing I do want to point out, this shows you just how little you actually need to size a trade to hit a certain return target because a lot of people think like you have to trade, you know, make a percent, a percent honestly is really big, even a half a percent is really big. And I'll just give an example, like right now, let's say I set a 25% return target for the year. That seems pretty aggressive, right? So I have $100,000 and I'm trying to make 25,000, right? If I have a PCR expected of 25% and let's just say I have, I don't know, 150 trades a year. This is telling me I'm only trying to make 0.67% per trade, not even 1%. So it's quite low. So even playing with the number of trades relative to the PCR, this is going to tell you like just how little you actually need to size each trade. So like when you, if you play with this with a fixed target and you're using a large trade size of like 1%, 2%, you're going to kind of basically see the thing go crazy. one thing to note before we go into the examples. Depending on how you set it up, right, if you purposely set it up with some really bad expectancy, like you put like a 30% win rate, right, it's going to tell you that this is a negative expectancy trade, right? So you'll see the PCR actually go negative. If you set something up just for illustrative purposes that has a negative PCR, you cannot use the target return mode because it's going to basically do a negative credit. It doesn't make any sense. So if you set something up with a negative PCR, make sure you keep it on fixed trade size, okay? So that's the last thing I'll kind of stress before we go into these examples here. Now, as you guys are tinkering with this, you'll notice that every time you make a change on anything, the whole thing reruns, the simulation reruns, then graphs update. That's just basically how Google sheets works. And if you're, um, if you have something set up the way you want and you want to run through a, a number of simulations, just to go very quickly, just see the different outcomes, put your mouse, click into any of the blank cells, and just repeatedly hit the delete key on your keyboard. That actually just forces it to rerun the simulation. Now, the first example, let's look at this. I'm going to use the fixed return target mode. And we're going to set the stop loss to 200% and the profit target at 100%. And I'll go ahead and do 200 trades. So if you have this 200% stop loss 100% win rate, but basically risk to to make one, right? What I want you to do is basically vary the win rate and look at the expense. what win rate you actually need to start making money. Right. If I have a right now, 30% win rate is saying negative 110% PCR, which is obviously you'll see the graph just goes down right after 200 trades. You know, I'm losing like 80 percent of my account or whatever, you know. So if I do the 40 percent, right, the PCR is still negative, negative 80. If I go to 50 percent is, you know, 50% was negative 50%. If I do 66%, this is actually about actually, let me do 66.6666. This is the theoretical breakeven brain rate when you risk two to make one. And you'll see that it says expected PCR is zero. Now, if you raise the less, let's say we start going to 75%, as I just mentioned earlier, it's the 25% PCR, if we go to 80%, 90%. So the first thing I want you to do is just set some fixed win-loss ratio, play with the win rate and just see how that affects the graph, how that affects the PCR. You're essentially finding at different win-loss ratios, what kind of win rate you need to have positive expectancy, right? So that's kind of one exercise you can do. So another one example I'm going to go through is let's use a fixed 80% win rate. And I'm going to do again, fixed trade size, I'm going to do 100% profit target. now I'm going to adjust the stop loss. Okay. So this is a saying at a fixed win rate, what kind of win loss ratio do you need to have a positive expectancy? Right? So if I have 80% win rate, if I have 100% profit target and my stop loss is 200%. Right. Risk to to make one. I think I have a 40% PCR. Very good. So healthy expectancy. What if I widen my stop or increase my stop limit? Okay. So let's add the 300%. So 80% win rate, 100% target, 300% stop loss. Now I'm risking through to make one. The PCR goes down to 20, right? So you've cut the expectancy basically in half, but that's obvious because your, your loss size is bigger, right? So let's see how far we can go before we make the loss size actually negative or the expectancy. So I do 400% stop loss risk for the make one at 80% win rate. This is essentially zero PCR, right? We've basically killed off the expectancy. Obviously, if you do 500%, it's going to go negative, right? The system starts losing money. So you can see that. And every time you tinker with this, you know, hit the delete key and kind of rerun it to see what that profit looks like. And on this metrics, you'll see based on your setup like a raw dollar return the percent return the the win rate the average loss all the usual metrics you're used to seeing from this but you can see these update in real time one thing i want to caveat just to keep in mind this is a random simulation or it uses the random number generator. So actually the results are random. What I mean is if you put an 80% win rate, the system may not always give you an exactly 80% win rate. So in the metrics table, look at what the actual win rate is. As long as it's close to the one you want it to be the projected one, the result should be fairly accurate. But if you go through here, for example, right now I have 80% selected as the win rate. If I rerun it now, it's giving me 81.5 pretty close, 80% pretty close, 80%, 77.5, that's pretty low. And then 80% again. And that can also be affected by the number of samples. And this is a pretty interesting point, right? If I did only 10 trades, right? As you would expect in a random sample, the actual win rate could be all over the place. Let me run this. 10 samples, okay? With a supposed 80% win rate, I have 60%. Run it 100%, right? All winners, which is, which can happen if you only have 10 trades. Run again, 90% win rate, run it again, 90% win rate. So one thing to note, and this is just regular probabilities, with a lower sample size, your win rate could really deviate from the theoretical one. So you can even change the number of trades and rerun and to see how much that affects the win rate and the expectancy. So if I boost it to the max, which is 500 in this case, you would expect that realized win rate to generally be pretty close to the projected one. So again, I have on 80% win rate, I'm going to run it with 500 samples of 77.2, 81.2, 81.8, 81.2. So I'm running this and it's giving me pretty close to the projected one. Okay. So that's another thing you can do to really play with this. Now the third example, I call this the tasty trade example, because we're going to set up what people think that usually kind of the tasty trade style of trading is I'm going to do about an 85% win rate. Let me drop it down to about 300 samples here. I'm going to do a 50% profit target and a 200% stop loss. I know they don't use hard stops normally, but they say generally like if you try to manage a trade to a scratch or a small loss, let's just say on average, your average loser is 2X, your credit, okay? So keep in mind with the 50% profit target and a 200% stop loss, you're risking four to make one, right? On average, and that shows on here. And so this PCR, expected PCR is actually 13%. I mean, it's not great, but it's still positive. But here's what I want you to do now, okay? We're going to inject a few black swans here. Actually, let me lower the samples. I'm going to lower to like 200% 200 trades. Sorry. So I'm going to zero these out. I'm going to just do one black swan. If I put a one five X black swan. So normally my losses are two X. I'm going to put a single five X loss here. And I want, I'm going to compare the two returns. Right. So right now I have my win rate set at 85 and I just ran it and it gave me an 84.5% win rate my PCR for the non-black swan is like 10% it's like a 24% return I say what's my fixed credit size I'm using a fixed 1% credit okay so I have about a 24% return on without the black swan with the black swan. It basically lowered the return by like 5%. It's 20% basically. So again, these numbers, the exact numbers aren't really that meaningful. Just rerun it. You'll see what I mean. The graph is totally like one large loss, just that completely tanks the whole system. Right? So let's say the, let's say in the year, let's say you trade, you know, 250 times for example, and then I'm going to do like three black swans, right? Let's say I have three 10 X loss. I know it's maybe three earnings trade. I went bad. So even with the high win rate with three of these black swans, I'm looking right now and I see this win rate is okay. I have the blue line at a scratch. I guess it's just a bad luck this year. And the red line is like negative 27%. Again, it's, I know it's a little hard to visualize over the podcast, but just put in the black swans. You will see the impact because you can immediately see when you have these black swans, that red line just you can tell which ones are the black swans. So you can do a 5x, 6x, 10x, whatever you want. Just you'll see just how much impact even one black swan sometime in the year can have on your long term expectancy. Okay, a couple more examples and we'll wrap this up. This is a really interesting one. I want you to think about this for a second. Okay. So I'm going to do fixed size again. And I'm going to do 100% profit target and 100% stop loss. This is risk one to make one. Okay, risk one to make one. And I'm going to do a 50% win rate. So just think of an example, let's say you flip the coin, and it be 50-50 right heads or tails and let's say on a tails you won a dollar right and that heads you lost a dollar. So what do you expect the expectancy to be right. When win won or lose one 50% you'd expect the expectancy to be 0. And in fact if you do a fixed credit target, a fixed trade size, and I'm going to set it to like a quarter percent, just so this thing doesn't go wild. Run this a few times and make sure the win rate is always around 50%. You'll notice that it is about a scratch. The blue line goes up, the blue line goes down, and it generally ends up around 0% return. This is pretty much a given. winning or losing a fixed dollar amount, what if you did a fixed percent? Right? So it sounds similar. But again, instead of saying I win a dollar or lose a dollar, let's say I won 1% or lost 1%. That sounds like it should be the same, right? But it's not. Because remember the idea of negative compounding. If you were to lose, you know, a certain percent, like 5% of your account, you actually need a little bit more than 5% to get back to even. So if you lose a small amount, like 1%, you do need about a percent profit to get back to even. But if you lost a large amount, like the extreme example, if you lost 50% of your account, you need a 100% gain to get back to double up. Right. So that's that extreme example. So what I want you to do is with the fixed credit target, start with something small, like a quarter percent. And you notice that the expectancy, it usually ends up about zero. Now if you start increasing this fixed trade size, right, 100 percent target, 100 percent stop loss and 50 percent win rate. So I'm going to increase it to like 5 percent, just something extreme. This expectancy, I mean, it starts, the return starts becoming negative because remember it's scaling the trades. It's a fixed percent. It's not a fixed dollar amount. It's a fixed percent. So as the account loses, the percentage that it can gain is actually going down. And you'll see this in the line visually. If I do something extreme like 10%, it's even gonna exacerbate that effect. Like basically some of these graphs, the account ends up losing like 50%, 80% recurrent. Like it's really extreme. Now obviously there's some where it wins a lot. And that just shows the nature of this being a random simulator. But it's really interesting. Just keep hitting the lid, keep rerunning it and see how if you have a 50% win rate, and you're risking one to one or you think you are, but you're betting a really large size, that can that basically becomes negative expectancy. So that's that's a really interesting example. Now, the final one that I want to look at here is if we were to basically look at 100% profit target, again, this is going to be a little different than usual. OK, we're used to risking, you know, five to make one or risking four to make one, whatever it is. So these are negatively skewed risk reward profiles, right? The loss is bigger than the win. But just for illustrative purposes, I want to flip that I want to make a positively skewed strategy. So I want you to do a fixed trade size. Let's just make it half a percent. Set a 100% profit target, but set a 50% stop loss. Right. So the loss is half and you're risking half to make one. Okay. So basically your winners are double the losers. This is, for example. And what I want you to do is I want you to change the win rate and look at the PCR, because I want to show that when you have bigger wins than losses, you can actually have a quite negative win rate and still be positive expectancy. So I'm going to start something really low. I'm going to go ahead and send my win rate to 10%. So PCR is negative 35%. That's fine. Obviously 10% is a very low win rate. Let's go to 15%. PCR is negative 28. I'll go to 20% win rate, negative 20% PCR, 25%. Now it's 13% PCR. So it's almost getting to a zero. Zero means break even. Okay. If I go to 30%, it's only negative 5% PCR. And actually what I want to look for is I think it's 33.33. 33.33. Remember when we risk two to make one, you you need 66.66% to break even. Well, when you flip it, when you risk one to make two, you only need 33.33% win rate to break even. And that's the power and shows you the impact of the risk reward, reward profile, right? So now if I go to like something low, like 50% win rate, right? So 50% win rate actually gives me a 25% PCR. Think about that. With the 50% win rate, you can have a 25% expectancy, simply because you have smaller losses than your wins. Now I want to caveat by normally with premium selling, these are just by nature, negatively skewed strategies. People would like day trade or like do kind of futures or scalping. These types of trades, you can potentially have some kind of positive skewed strategy. So generally, don't expect that you can find a positively skewed strategy with a high win rate when you're selling options. It just doesn't quite work that way because if you set your stops really tight, the win rate goes like really, really low.