Quote from acrary:
My production models are in two broad categories: money flow and breakouts. The money flow is one model based on inflows/outflows to mutual funds with a 1 week hold timeframe.
The breakouts are split into many sub-categories like (volatilty breakouts, opening range breakouts, trend continuation breakouts, daily reversal breakouts, mid day continuation breakouts, time of day based breakouts, trend day breakouts). I've tested just about every other kind of system I can think of. In all I track the results of about 25 models on a monthly basis. I'm trading against 8 of the models (which I found is all I can handle). The easiest way I've found to come up with ideas is to take a blank piece of paper and draw two or three bars. Come up with all the different ways the bars can show up and classify the description yourself. For instance, two rising bars could be a continuation, or if the first bar is smaller than the second, it could be a volatility breakout.
So far this year volatility breakouts have been the best and most consistent performer for me. Trend day breakouts have also done very well. Opening range breakouts didn't have much followthrough earlier this year. Continuation and reversal breakouts have done well, but there haven't been many of them.
Now..that's really food for thought this weekend
I also took a similar approach to use different breakout models to capture different market behaviour, but I was only able to discern three categories of breakout, volatilty breakout, opening range breakout and reversal breakout. Base on these concepts , I then create variation models using different measures of volatility or reference points.
I hope we are talking about the same thing when I use these terms

). I have looked at the performance summary of prod5 you posted on another post and the it really kick my system 's ass .
Some of your other sub-catorgories (mid day continuation breakouts, time of day based breakouts, trend day breakouts)
seem to be pattern-based( definition of a trend-day?) , from my relatively little experience, these system seems to trade less (less overall profit) because the patterns act as stict filters and they also "seem" ( I am being very subjective here) to be less robust due to the increase in the number of parameters to discern the patterns.
I had some success in developing such system( their profit factor always beats the plain-jane breakouts) but they have never made into my arsenal because I always thought I was curve-fitting. But you have really made me think again. Are such system less robust to a extent than other breakouts systems?
My other question is how do you allocate capital to these system.
Because the trading frequency/overall profits of the models differ, do u give different weights to system to balance it out or do u risk the same 0.5 percentage( I remember you said this somewhere) on all models?
As another complication, do u use a seperate equity curve for each model or lump them together for position sizing purposes. So that if a system does better, the profits are invested back into the system?