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These are all un-optimized results. My question is should you optimize at this point to "create" positive ME? If it's not positive to begin with, shouldn't we continue development, not optimization?
Thanks for your input.
Can you help answer these questions from other members on NexusFi?
Call me an amateur, but in my research and hunting for an edge, some of my better prospects and systems came by discovering an idea was bad....but really bad.
Backtesting on something, when you see a negative performance (which includes slippage and commission) and you say..."man, not only is that bad, it's spectacularly bad." Then as you suggested, you reverse the polarity and suddenly, you have a viable edge....it's not the one you were looking for, but not all discoveries are intentional.
The phenomenon has to be bad enough to overcome slippage/commission, as that works against you both ways....so many times, a higher frequency system, will appear to have a significant negative edge, but really, when you look at the slippage and commission, the slip/comiss independent edge wasn't that large (negative).
In essence, if you have a strat that trades 3000 times over a sample, and has -$150k performance isn't anything noteworthy, as when you flip it, you'll find the results are close to zero (not $150k positive).
"A dumb man never learns. A smart man learns from his own failure and success. But a wise man learns from the failure and success of others."
Can you describe why the first one fails to make a profit? Is this because you have some significant outliers as your %win seems over 50% and you average more profit than loss per trade, I would expect your sample would be profitable. I am having trouble envisioning the data-set that would give you a negative expectancy.
I assume from Expectancy you are talking about the expected value based upon the weight sum * probability of that event?
