That makes the system quality unconditionally dependent on the number of trades, which doesn't make sense. I devised the System Achievement Score to get around that flaw.Quote from nonlinear5:
Give me any instrument, and I'll find a system that generates 20 winning trades in a row for that instrument. That's the magic of "curve-fitting". The more trades, the more difficult it is to curve-fit. What I'd suggest is calculating a system quality measure which includes the number of trades. For example:
System Quality = sqrt(number of trades) * AveTrade / StandardDeviation(all trades)
SAS == 4*k*max[ 0, E ]*PF*min[ 1, N/mant ] ,
where
SAS is the System Achievement Score,
k is the solution to the Kelly equation (see below),
E is the expectation (see below),
PF is the profit factor (see below),
N is the number of trades in the SAS evaluation,
mant is the minimum acceptable number of trades.
E == sum[ Ri ]_i=1toN / N ,
where
Ri is the return (%) of the i'th trade.
The Kelly equation is
0 == sum[ Ri/(1+k*Ri) ]_i=1toN
PF == sum[ max[ 0, Ri ] ]_i=1toN / sum[ max[ 0, -Ri ] ]_i=1toN