System this. System that.
What the hell is the “System” you keep referring to?
What is the System?
The System is my framework for trading BTC.
It’s a set of rules and criteria I follow so I can make trading decisions to:
- Maximise the probability of having winning trades that are as large as possible while also,
- Minimising the probability of having losing trades and, when they do occur, minimising the losses
The goal of the system then is for it to be profitable over the long run and for as long as possible.
Are you sure? What is the System?
Okay that was a bit over-exaggerated. So:
Why do you need a system?
Trading is hard.
It’s hard because you are trying to profit by predicting what happens next in the financial markets. Sure price can really only go up, down or sideways, but even choosing correctly between those simple options is crazy hard.
There’s too much noise, uncertainty and random stuff happening all at once.
Because of this, you can’t tell if you are a good trader by the outcome of a single trade.
I’m not saying one big win isn’t good. It’s great. But one win doesn’t make someone a good trader, the same way one losing trade doesn’t make someone a bad trader.
A good trader is someone who can demonstrate an edge across many trades and over a meaningful period of time. As the sample grows, the influence of randomness fades so that the underlying process (skill + system) becomes clearer.
So how do you know if you have this edge?
You need a system.
What’s in the System?
My system is basically an extended decision tree and series of questions I ask myself to determine if a trade should be taken and how to configure it.
Some key questions that make up the System include:
- Is price at a key level?
- Is there meaningful volume?
- Is the risk-reward ratio worth it?
- How much am I willing to risk?
This is a big simplification of it, but a more in-depth guide to the components of the actual System will follow.
What is a good system?
To simplify things, a trading system should tell you:
| What | Decision |
|---|---|
| Open a position | Should I open a trade? |
| Trade direction | Should I take a long or short position? |
| Position size | How large should the position be? |
| Stop loss | When is the trade no longer valid? |
| Profit target | Where am I aiming to exit? |
| Trade management | What do I do while the trade is open? |
A system should remove (or reduce) as much of the guesswork as possible so that you can make key decisions quickly in a highly variable and noisy environment.
A system also helps to deal with feelings like greed, fear, and overconfidence along with any second-guessing.
Above all, or just as importantly, a good system needs to be measurable...
How do you measure a system?
To successfully measure a system, you need to be able to define the right metrics that are ideally as quantitative as possible. You shouldn’t ‘think’ or ‘feel’ it works. You need to know.
The key numbers to track:
| Metric | What It Means |
|---|---|
| Total Return | The total R return |
| Win Rate | Total winning trades divided by total trades taken |
| Average Win | The average R return from winning trades. |
| Average Loss | The average negative R return from losing trades. |
| Average R/Trade | The average R return of total trades taken. |
| Rule Adherence | The percentage of trades where the rules of the system were followed./td> |
Aim to get these stats over a sample of 100+ trades to get a decent view of a system (that’s what I’m doing here). Yes, building a (money printer) system takes time.
You might be wondering where is profit? Where is the money? Why am I measuring ‘R’?
‘R’ stands for a unit of risk. It measures each result relative to how much was risked, making it easier to compare trades and assess profitability consistently.
This separate article on R explains why in more depth.
How do you improve a system?
A good system should improve with new data and evidence based on outcomes.
All trades have variables and you need to be able to identify and spot patterns, collect data, and analyse them. You then need to determine if that variable has a positive or negative impact on trade outcomes. Once you collect data and deem a variable worth tinkering with, you do just that.
You tweak them, and see what then happens, did the metrics improve or not?
Then you repeat over and over again, until you get a good system.
Then you repeat it again.
Yes, it takes time.
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