Okay folks, welcome back. This is the fourth installment of month two of the ICT Mentorship. We'll be specifically talking about why losing on trades won't affect your profitability. What trading with fear of taking losses actually does to your trading?
While staying concerned about taking a loss promotes fear-based decision making. Equity that is managed by traders that cannot take a loss can't profit long term. Losing is inevitable. Fear-based decision making keeps focus on the adverse. Finally, fear-based decision making fosters trade paralysis or inability to execute efficiently.
Now why profits are achievable despite taking reasonable losses? The professional equity manager understands that losses are costs of doing business. Using sound equity management and high probability setups yield handsome percent returns.
Trading scenarios that encourage potential 3 to 1 reward ratios provide initial foundation. And finally, defining trade setups that frame 5 to 1 reward to risk or more efficiently cover losses. Okay, folks, we're going to give a brief overview on framing a trade just for the context of this discussion. Looking at this sample size of data as it relates to price action. We're going to be referring to a specific concept note as market setup and framing the risk to reward multiples.
Obviously, we're going to use a standard in my repertoire, the bullish order block. As we can see here, the market returns to a previous institutional area of buying, noted by the down candle prior to the previous rally higher. By noting the down candle or the bullish order block high to open price defines the fair value gap or most probable support.
Now specifically inside of that retracement into the order block, there's a mean threshold and a hypothetical long entry on the secondary bullish order block. What I'm going to refer to is This down candle here, the middle of that candle, we're going to be using that as a mean threshold. In other words, we don't want to see that violated on a closing basis.
Now using 20 pips as the trade stop loss easily frames reward multiples of 3 to 1 reward to risk and 5 to 1 reward to risk or even higher. New to an old high. 20 pips above it gives us a nice objective above where price would be retrading to. Now, having a simple trade idea based on the things that we taught in September on what to focus on or what you should be focused on right now in price action, let's take a look at some things regarding those setups and how we can frame good reward.
multiples, how we can frame the ideas and justify why taking and losing trades doesn't really or shouldn't have that much of an impact on your long-term profitability. We're going to assume that we're using a hypothetical account size of $5,000 and we're going to start with a low accuracy rate of 30%. That means that you're losing 70% of the time.
We're going to be looking for trades that are reward to risk ratio of 3 to 1. That means we're hoping to make or willing to hold on to a trade to pay out $3 gained for every $1 that we risk. We're risking on each trade 1% of our $5,000 account. Because we're risking 1% and we're looking for a yield of 3 to 1 reward to risk, our average win trade should be $150 and our average loss should be $50 or 1%.
We're going to be focusing on a sample set of 10 trades and we're going to say that 30% of those 10 trades are winners and obviously 70%. would be losing trades. Out of those 10 trades, we are assuming that three wins in 10 trades and seven losses in 10 trades. The average profit, again, is $150, and the average loss, again, is $50. The subtotal for the three wins at an average profit of $150 would bring us to a $450 winning basis on the three trades out of ten that were winners.
And the subtotal for the losses would equate to $350 or 7 times $50 of an average loss. Even in this low accuracy rate with a multiple of 3 to 1, you still can marginally eke out a net positive profit. It's not much, and to look at that, it doesn't seem like anyone would be terribly excited about that.
But if you were doing 10 trades over the course of a month, and you netted a 2% return, I can tell you that is an absolutely amazing return for managed funds. So if you're not going to be trading your own capital, or if you're aspiring to be a trader that manages other people's money, so again, 2%, while that's not terribly... impressive. In the grand scheme of things, 2% compounded over the course of a calendar year, 2% per month, that is an astronomical return for managed funds.
Let's assume for a moment now we're going to start focusing on reward to risk multiples of 5 to 1. That means we're trying to make $5 for every $1 that we risk. And we're keeping the same sample set of looking at 10 trades and we're still looking at the accuracy rate of 30%. The only thing that's changed now is we're framing trades that have a multiple of 5 to 1 reward to risk. Suddenly, our three winning trades out of 10 sample set, the average profit becomes $250 or three wins at $250 average brings us a subtotal of $750. The seven losses in the sample set of 10 trades, average loss is $50.
I still... leaves us at a subtotal of $350. $750 minus $350 gives us a net profit of $400 or a 8% return. Now again, if we're looking at 10 trades over the course of one calendar month, to see results like this with a very, very low accuracy rate of 30% still brings us an 8% return. That's a wonderful return for a monthly rate.
Now we're going to take a look at having a low accuracy rate of 30% with the reward to risk multiple of 5 to 1. And now we're going to be risking 2% of our account. So now the average win jumps to $500 and the average loss jumps to $100. Again, keeping accuracy at a low 30% accuracy. That means we're losing 70% of our trades. Out of a sample set of 10 trades over the course of a calendar month, 3 wins.
At 2% risk per trade, multiple of 5 to 1 reward the risk. Our average profit jumps to $500. If our three winning trades at $500 average profit, this gives us a subtotal of $1,500. Our seven losing trades at an average loss of $100 or 2% of our equity.
The subtotal would obviously be at $700. Now, the average loss and average profit would increase. as the equity increases or drops. But for these examples we're looking at the sample size of data and a sample set of 10 trades. So the details are being shown here with a very hypothetical basis.
But with a subtotal on 3 wins of $1500 and the 7 losses, a subtotal of $700, that would give us a net gain of $750 or 15% return. Again, crazy returns with just a very low accuracy. Now think about this for a moment.
When you first got into trading you were wanting to get 90% accuracy or 100% accuracy or 98% accuracy. You can still make ridiculous returns with having very low accuracy. You don't need high accuracy.
You need the framing of the reward to risk multiples in your favor. And we didn't really go crazy with our risk either. We're only doing 2% maximum per trade. Alright, so now we're going to look at an accuracy increase to 40%.
Nothing's changed outside of the previous example here. So now we're going to say 40% of a sample set of 10 trades, 4 of the 10 trades are winning trades. Average profit per trade is still at $500.
Our 4 trades at $500 average profit brings us a subtotal of $2,000. Our 6 losing trades out of the 10 average loss still remains at $100 per loss. 6 of them would give us a subtotal of $600.
That would give us a net profit of $1400, which would be, again, that's a 28% return with just a 10% increase in accuracy, the factor of 2% per risk, and reward to risk ratio, again, framing on a model of 5 to 1. Now we're going to look at... increase in our accuracy say we've been trading for a while we know our trading model a little bit more intimately we know what we're trading we know how to frame our trades we've learned patience we've been able to stick to our rules and our parameters about our reward to risk framing we know how to reduce our risk while we're in a trade and our accuracy increases by default We're going to say we jump to a 50-50 basis. In other words, half our trades are winners and half our trades are losers.
On a sample set of 10 trades, the average win stays at $500. The average loss stays at $100. Five wins at an average profit of $500 brings us to a subtotal of $2,500. While five losses of the 10 sample set trades, average loss is $100 or a subtotal of $500.
So $2,500 minus $500. dollars lost on five losing trades because it's a net profit of two thousand dollars or a forty percent return on ten trades the factor of Just increasing a 50 50 hit rate We reward the risk five to one with a risk per trade two percent The only thing we're doing is framing our trade around a little bit more success In other words our ability to read price action Look how fast our multiples jump up and we haven't increased the number of trades. We haven't increased the risk per trade either. Accuracy rate of 50%.
Our reward to risk model stays at 5 to 1, but we're going to lower our risk per trade to 1%. That means the average win drops back down to $250 per win and the average loss is down to $50 per win. Our hit rate, we're going to say, is 50-50 still.
That means five winning trades out of 10. Average profit is $250. And five wins at $250 brings us a subtotal of $1,250. And then five losing trades out of the sample set of 10 trades, average loss being 1% of the $5,000 account, or $50 in this case.
Five losing trades with an average loss of $50 gives us a subtotal of $250. So $1,250 of... The five wins minus the subtotal of $250 on the five losing trades gives us a net profit of $1,000.
Now, I want you to take a look at this for a minute. Okay? Think about this for a minute.
You only have to be right half the time. Or another way of saying it is you can afford to be wrong half the time. You're looking for trades that pan out five to one, and you're risking 1% of your account. Now, think back to the moment when you first started learning about trading. and you felt that you had to put big risk on.
We're not talking about 2%, which is the industry standard here. We're talking about 1%. 1% makes millionaires. If you look at the 1% risk per trade and the accuracy rate of only 50%, this by itself is exactly what everyone would dream of as a rate of return. 20% per month.
If you could get 10 trades per month, half of them be wrong, but framed all of them on 5 to 1 reward risk with 1% risk only, your rate of return is 20% with only 1% at risk. This is optimal trading goals. This is exactly what you should be aspiring to do. You're not trading a lot. You're not demanding a high rate of success or accuracy.
You're not pushing the limits on your risk. You're keeping it at a low. You're doing half the industry standard in terms of risk per trade. Usually it's 2% maximum.
OK, well, we're doing 1%. Let me ask you a question. What if you were to drop that risk per trade down to a half a percent? Would you be upset with 10% return per month?
My question would be, why would you be upset with that? Now, imagine if we were to consider what was 2% per month with 30% accuracy. 1% risk per trade with 3-to-1 reward-to-risk model on our first example.
That's exactly what large funds look to do for their clients over the calendar year. They're looking for 1% to 2% per month, and if they can compound that over the course of a year, they can give their investors a 25% to 28% return on the year. And believe me, there are millions and millions of dollars sitting out there that would love for someone to be able to do that for them.
So you don't need to have these astronomical rates of return per month to manage other people's money. Believe me, they would go crazy if you give them 1%, 1.5%, 2% per month. And you only need to do 3 to 1 reward risk to do that with 1%. If you do 1% here and you have a 50% chance of being accurate, and you frame your trades around 5 to 1, look how easy it is to get into a really high end yield for the month. 20%.
You don't have to trade every single month if you're managing your money or other people's money. See this is an optimal goal because it gives you the cushion to do basically half the year of trading. There are some months in the year that you don't really want to be trading. So if you can do a multiple of 5 to 1 and yield really handsome results, and I'm not saying that everyone's going to get 20% returns or higher every single month, but this should be a good trading goal for you to frame your trades around where expecting only half your trades to be accurate, framing on 5 to 1 reward to risk, keeping your risk low 1%. By doing this, it gives you the optimal objectives.
It gives you low-hanging fruit. It doesn't force performance. And it gives you an opportunity to relax and actually enjoy the process of trading.
There is no fear that's justified in taking losses. They are all part of this business. It's all part of the game. It's all part of your job as an equity manager.
You're going to weather losses. You're going to assume losing trades. That's all cost of doing business.
No one goes through their career without taking losses. You're going to have lots of them. If you trade for a long time, if you had a column of all your wins and all your losses, your losses are going to be very, very long in the list.
But it does not dampen or does not remove the profitability factor that's still available to traders that know how to frame their trades with good multiples of reward to risk, keeping risk managed and defined, and thinking about how they're going to trade. with these parameters. If we use the example we showed in the beginning of this video, with a 20 pip stop, all you have to do is take, well, what's 1% of $5,000?
It's $50. So if you have a 20 pip stop, you divide that by $50. And that will give you your dollar per pip leverage.
And that's what you would use for your trade. And that would give you all of these numbers that you see here. Now again, we can only speak in terms of hypothetical, but it's a rule or general principle that you're going to build on as a trader. Highlighting the fact that you don't need high accuracy. I did not show 60% accuracy.
I didn't show 70% accuracy. I didn't show 80% or 90%. None of that's necessary. But as time goes on and you grow in your proficiency and your understanding about price action and you as the trader, by default, your accuracy rate will increase and you'll never demand or need for it to be higher than 50-50.
So until the next discussion and next teaching, I wish you good luck and good trading.