You may be a casual binary options trader, who is just trying to have some fun and maybe make some profit along the way. But maybe you are a very serious trader, and you want to come up with a trading method which is going to net you some real gains over the long term. If so, then you may have already read our article on backtesting. In that article, we discuss the importance of testing your trading method using historical charting data, and then plotting the results in a spreadsheet. Then you can examine those results, run calculations, and establish whether your trading method will result in profit over time or loss, as you project it forward onto future trading. What statistics are important though?
There Is No One Magic Statistic
One misunderstanding that newbie traders sometimes have is this idea that there is one all-important statistic that is going to determine success or failure. For many traders, this is the win/loss ratio. Obviously you want to aim to win more trades than you lose. But what if your wins are all really small, and your losses are all really big? This could add up to equal failure. The same thing can go the other way around. Maybe you only win about half your trades, but your wins on average are substantially larger than your losses, because you would close early out of trades going against you. If this is the case, your method may be profitable despite not appearing to have a good win/loss ratio. So you can see that things are a little more complex than they appear on the surface.
So what statistics should you try to tally up while you are testing? Here are our suggestions:
1. Win/loss ratio: How many winning trades you have versus losing trades, expressed as a percentage. This is one of your most important numbers, but remember that it does not stand alone.
2. Average win size versus average loss size: Calculate both at the end of your test and compare them. If your average win is larger than your average loss, that is great, but again, this statistic does not stand on its own.
3. Net income based on your test: If you added up all your wins and losses, and took the net result, would it be positive or negative? How positive or negative? Make sure that you calculate the result based on the payout percentages and out-of-money rewards offered by the broker you will be trading with. If those numbers vary, stay on the safe side and be conservative. Use the smaller win percentages instead of the larger or average ones when you do your math, and use the lower out-of-money rewards. That way, you could feasibly find yourself with more money than you expect, but not less.
4. Net profitable trades per (day/week/month/year): This can be helpful analyzing the rate at which you would be receiving potential income, and whether it is timely enough for you. If it is not, you could for example consider adding more financial instruments to your trading repertoire. This might give you access to more trade set-ups. Another idea would be to try faster trades, but use caution with this approach. http://binaryoptionsbrokers.ca/60-seconds/ will help you find faster trade brokers.
5. Maximum losses in a row: Figure out what your worst losing streak was. That way when you are trading in real life, you will be more likely to recognize a genuine anomaly and be able to distinguish it from an expected losing streak.
6. SOLQ: This is a risk management statistic popularized by a free trading eBook by Rob Booker for currency traders. The SOLQ = Net profit/maximum loss. This number tells you how many of your largest losses you could endure in a row before you would blow your account. It doesn’t apply very well when you are just getting started, but it does tell you something relevant and interesting as you progress. The larger the number, the better. If your SOLQ was 4 for example, that’d mean a losing streak of just 4 really bad trades in a row would destroy the income you earned by the end of a certain time period (the duration of your test). If the SOLQ was 40, that’d mean it’d take 40 of your worst losses in a row to wipe out the profits you’d earned in that time. 40 is better than 4.
When you put these statistics together, you paint a much more illustrative picture of your success or failure than you would with any one statistic. You are able to see how your system would perform overall and identify specific strengths and weaknesses. You can then hone in on those weaknesses in future tests and attempt to boost your weaker statistics without damaging your stronger ones.