Question for anyone interested but especially those with experience in systems development and backtesting
Firstly, what do I mean here by a robust system? One that performs similarly over the long term. In other words a more 'future-proof' system, one that is not as likely to produce nasty surprises in the future.
In terms of robustness of a system, assuming all other parameters are the same - which is more robust - a system whose stops are based on ATR (eg 1-ATR) or a system whose stop is based on a percentage value?
The difference being that the former will produce a different value for each market, whereas a percentage value stays the same no matter what. I think introducing ATR into a system will greatly increase the probability of curve fitting but I am inexperienced and curious hence this thread.
A few more examples to ponder:
Which system is more robust (assume other parameters are the same)
-One whose entry is based on a MA crossover versus one whose entry is based on a highest-high value (eg Highest high of the last 50 days)?
-System with an index filter (to turn the system on/off) vs one without
-One whose entry is based on a 20/40 day MA crossover vs one whose entry is based on a 25/45 day crossover? The latter has more data points for the system to consider
-Crossover of closing price over MA vs a crossover of two different MA's
-A system with both a trailing stop and a volatility stop (i.e two different stop systems) or one with just one type of stop?
In some of the above examples there might not be one more robust than the other.
Feel free to add your own examples.
Perhaps 'KISS' better with systems design? I dunno.