Quote from intradaybill:
Neither very high nor very low pf systems are robust. In my experience the most robust systems maintain a pf between 1.8 and 2.4. Those other high pf systems are curve-fitted and optimized.
Please understand the math. A system with 100 trades all winning has infinite pf. If the trade 101 is a loser and let us assume R:R =1 then the pf becomes 100. If the trade 102 is also a loser, pf becomes 50. Here how it goes:
100 winner and then add consecutive losers:
infinity
100
50
33.33
25
16.6
14.3
12.5
11.1
10
9.1
8.33
7.69
7.14
6.66
6.25
etc.
You see that from infinity to pf=10 is only 10 losers way. This should tell you something. This game is really tough.
I would be the last person to say trading isn't tough. But, it's kind of a weird discipline in that it is tough/practically impossible up until the moment you know what you are doing. Then, it merely becomes difficult.
Anyway, the system in question is definitely optimized. One half of the set of trades had a profit factor of over 10. That was in an environment that was obviously perfectly suited to the type of trade this system makes. But, even the other half of this set of trades, which has been in a much different market environment, has a profit factor of about 3.5. I even know the date when the market environments switched, so I can segment the trade data by that.
So, even if the initial trades used for the optimization were in a "perfect" environment and that environment was unsustainable, the post-optimization profit factor is still 3.5.
What I would ultimately like to know is if this 3.5 is sustainable as a "minimum" future profit factor.
Also, given that the first environment was one of rising volatility and the second environment was one of falling volatility, does that mean that the system has experienced a complete market cycle and that the future profit factor will sometimes be ~10 (when the market is volatile) and sometimes be ~3.5 (when the market is less volatile)?
The other type of market environment, which we haven't experienced, would be a range-bound market, but since this is not a breakout system, I can't see how that would hurt it to the extent that the profit factor dropped below 1, especially since I could probably do further segmentation on the data and find miniature "ranging" environments and test what has happened during them. It's doubtful that the profit factor for any subset of these 100 trades has been under 1 for very long.
Obviously, there's no way to know the future and the market could come up with some environment this system can't handle. I was just curious if there isn't some point at which a very high profit factor ceases to be a reflection of obvious curve-fitting and becomes a reflection of a robust system.
