Something that would be useful for C2, would be a very standard metric: Risk of Ruin. It determines how likely that the system is to blow up.

The formula is: RoR = ((1 - A) / (1 + A))C, where

A is your trading advantage.

C is the number of units you have.

To figure A, subtract the percent chance you have to lose from the percent chance you have to win. So, if you expect to win 55% of your trades, your advantage would be 10% (0.55 - 0.45 = 0.1). To figure C, divide one by the percent of your capital you’ll risk on each trade. So, if that’s 4%, you have 25 units (1 / 0.04 = 25).

“Risk of ruin” (below) depicts the chance you’ll blow out given certain trading advantages. The number of units you have has a clear impact on the outcome. Overly aggressive trading - betting a high percentage of your stake on each trade - may give you some big winners, but it also will take you down in the end.

An important caveat with this risk of ruin calculation is it assumes your winners and your losers will be equal - an unlikely occurrence. Nevertheless, this still can be a good measure of the viability of your techniques.

A simple way would be to use inverse of the Profit Factor ((1 - A) / (1 + A))

C2 currently calculates risk of ruin in a slightly more nuanced way – we run Monte Carlo simulations using actual intraday drawdown stats as the input data. I would posit this is a bit more accurate than using average trade stats, which is essentially what you propose.

We calculate not only the risk of literal ruin (100% loss of capital), but also the risk of x% of capital where x is a multiple of 10% (e.g. risk of 10% account loss, 20% account loss, 30% account loss, etc.)

These stats are already displayed on the system details page.

it is pretty sure that some systems with 0% chance of 100% drawdown are fantasies.