Step one – Back-test your idea
The first step is back-testing. Nice and simple with no real money at risk. This is the key stage but many people can’t be bothered.
Because they want to trade and they want to have fun. Not work at it.
Don’t make this mistake. Back-testing is the foundation on which everything else is built. It is also the stage during which you get to see how your system parameters work in the real world.
One recommendation I would make is to visualise that you are actually doing the trades and the bets as you work through this. That way you will begin to understand how it will feel when your money is at risk as the market (or the match) bounces up or down until you end up with your final profit or loss.
At this stage you can also change some of your parameters to enhance system performance. The best systems are stable, meaning that minor changes in a parameter will not have a huge effect on profitability. If minor changes have huge effects then that is not a good sign.
Example 11.3: Back-testing a Trading idea
To make this process real for you I am going to put forward an idea and go through each of the six stages.
- The trading idea: Buy either the bet FTSE to be up at 12pm or the bet FTSE to be down at 12pm if the price goes to 12 or lower. Allow the bet to expire at either zero or 100.
- The reasoning: This system seeks to make money out of the early action on FTSE. If you examine how FTSE behaves in the first hour of trading you will see it can be fairly erratic and early losses or gains can be reversed. This is the sort of action this idea is looking for.
This is a simple example of a trading system. It defines the entry (when the bet price is 12 or lower) and the exit (allow to expire at zero or 100). That is all you need although systems can be a lot more complex.
Can we make money with this idea?
We are doing this process to find out.
This table needs some explanation, these are the columns:
There are only 9 entries because it is difficult to get access to binary prices going back further. You could use the underlying market with pre-set parameters or apply a binary formula but I prefer to extend the paper trading period to compensate for the shorter back-testing period.
The possible entry is either given a value of 10 or more or is stated as <10 meaning “less than 10.”
This sets out the best possible exit point of the bet. If a value of 0 is stated it means the bet simply moved down to 0 with no profit opportunity. A price above 0 identifies the best possible exit giving maximum profit although this does not imply the system captured all of that potential.
My Entry/My Exit
There are no entries for “my entry” or “my exit” as we are not taking trades at this point but these columns will become useful as we move onto later stages of the process.
I categorised the results as follows:
0 – a loss of the amount risked
A – a profit of less than 20
B – a profit of 20-40
C – a profit of 40-60
D – a profit of 60-80
E – a profit in excess of 80
I use an Excel spreadsheet to track the results but this is not essential.
Nine trades is not a large sample and is not even statistically relevant (meaning we cannot rely on the results). Nevertheless, it is useful for illustrative purposes and we can be encouraged by the results which can be summarised as:
Four profits out of nine trades – 44.4%.
Average loss was 10 points as all the losses were 10 points.
There were 4 profits. Two went all the way and the bets closed at 100. The other two gave maximum potential at 77 and 82. This raises the question do we take profits early, say at 80 (giving a profit of 70 after the entry at 10) or do we let these run all the way? If we run all the way we end up with only two profits as the other two will close at zero. If we close at 80 we will get all four profits but those which had given us around 90 points of profit will only give us 70 points.
This sort of decision goes to the heart of system design.
If we decide to close at 80 we end up with 4 profits of around 70, average profit 70 and metric #2 becomes 7 (70 divided by 10).
Multiplying the two metrics together gives us 311% which is great but, don’t forget, it is also unreliable with so few trades.
Here are the results set out in the form of a table.
Having completed step one it is now time to move on to paper trading.
Taken from the book Binary Trading By John Piper