Course 5

Trading System

(Van Tharp)

  • The only trading system you ever need to learn

Everywhere you go, online or trading courses, people tell you to have a system, to have rules, to have a plan, to have a strategy, etc. and to respect all of that.

When you start, what the hell is this?

I always journal everything, outside of trading. When I took Moonin papa’s trading class, he talked about journaling your trades and your trading overall. So this is the first thing I started to do, I wrote down everything I could – how I felt, what I thought, but more importantly, I was sketching my rules, my trading plan and my trading strategy.

Looking back at it, it is very very funny, sometimes I was using very high leverage, putting at risk basically almost all my money, and I could not sleep. One time I sold at a big loss and I was so relieved to know that I had lost only 20% of my account, and not 100%. I wrote down how I felt and how proud I was to take the loss. See, I wrote down earlier that you need to keep your losses small: 20% is NOT a small loss, it is very bad. You can’t grow an account if you lose money, you can't grow if you don’t PRESERVE CAPITAL.


Having a trading system is actually very easy. First of all, you need to determine when you enter, when you exit, and do it with discipline. The “do it with discipline” is the hardest part, because it relies on our emotions. This is why we do Algo trading, because it removes the emotions. Then, it becomes VERY easy, enter if X condition is met and exit if Y condition is met.

Second of all, a trading system is like a living organism, or like someone – you, me, your friend or whoever – it needs to evolve! It needs to learn, fail, learn again, and grow.

Third of all, a trading system need to be measured OR evaluated, assessed, with a specific methodology. This is what I will explain below.


I did not create it, I am not smart enough. Van Tharp created it and I got it from reading his book “Trade Your Way to Financial Freedom”.

You need to evaluate your trading system by answering the following questions:

- What is your reliability? This means, how many trades out of 100 are winning trades? This is your win rate, course #1.

- What is the relative size of your profits compared to your losses? This means, when you win, how many losers can this winner cover for? If on average you lose 2% and on average you win 10%, then the relative size is 5. Because, when you win, you win 5 times what you lose – on average.

- What is the cost to do a trade? This means, when you trade, what do you lose no matter what? For example, if you have any fees, or if you have a slippage, or if anything else that may make you lose money, inherent to placing the trade. Note that for my #1 algo, I do not have any trading fees, most of the time. The only difference between my algo theory and the live results, is some slippage, which is hard to circumvent (not impossible though, but trying to go for no slippage comes down to taking other risks hence other results/performance).

- How often do you get the opportunity to trade? This means, how often does your entry condition is met per day? How many signals do you get per month? If you trade a 50 and 100 periods EMA crossover on the daily chart, chances are you won’t get a lot of opportunities to trades. If you trade the same thing on the 5 min chart, then you will get much more opportunities.

- What is your position size? This means, do you enter with 100% of your position? Or less? Or more (= leverage)? If you keep entering trades with 10% of your account balance, and you make on average 20% per trade, then your account balance will only make 10% of the 20% profit so 0.10 x 0.20 = 0.02. Your account balance will grow 2%.

- What is your account size? Basically, Vam Tharp explains how if you trade with a $100 account and you have a $20 flat fee per trade, then it will be hard for your system to make money. You would need to make at least 20% to cover the $20 flat fee. In crypto it is a little different, because there aren’t any platform that charges flat fees like that – at least not to my knowledge. In course #6 though, I will give you a concrete example how the account size in relation to the trading fees could have an impact, if you use leverage.

All these points above, are items I go through with every single algo I develop. ALWAYS.

I start by calculating the win rate based on historical values (RELIABILITY).

I measure the average profit, the average loss, and I compare them (RELATIVE SIZE OF WIN TO LOSS).

I make sure to run my algo on a timeframe that allows me to fill orders with my “no fee technique” (COST TO TRADE).

Then, I count how many trades did the algo take per day and per month (OPPORTUNITY).

Finally, I run a few simulations using either 100%, 200% or more, of my account balance (POSITION SIZE).

Note that for the position size, sometimes the equation is reversed to “how much am I willing to lose” = what is my risk when taking a trade, instead of deciding to use an arbitrary trade size based on so many X’s of account balance. I don’t worry too much about my account size, the last point, because I know that crypto offers opportunities for the small guys too, with only $100 to their names. If you read this and only have a $100 to start, don’t lose hope YGMI.


1 – Create a simple system – entry on X and exit on Y.

2 – Understand it needs to improve based on feedback, learning, based on RUNNING LIVE. Learn something (like the cost to trade of your system!).

3 – Measure your system based on Reliability, Relative size of win/loss, Cost to trade, Opportunity and Position Size.