Once we have created a system we consider good enough to trade, there is one more problem to solve - how long of an interval should we continuously optimize it on?
If we find out that by optimizing it on different time intervals - the last month, year, decade - that certain parameters change greatly, then we could have two solutions - either:
1) finding out on which time intervals the system's parameter should be optimized to give the best return.
2) have the system continuously adapt a given parameter in order to be as efficient as possible.
For example, in my system, that does about 1 intraday trade per day on a 5-minute chart, the parameters are:
1. ma crossover
2. time zones (outside of which trading is not allowed)
3. volatility filter
4. stoploss
Now, I would find it reasonable if stoploss, time restrictions and moving averages didn't change. So only our volatility filter changes, and without it changing our system's return would suffer greatly.
So how do we adapt this volatility filter?
1) There could be an easy way - continuously optimizing it. But then how do I know which interval I should use to optimize it, and how do I know if this makes any sense? I would have to go back in my 5 years historic data, optimize the system for january 1998, then use it for the next week or month, optimize it for february 1998, and test it on the next week/month....then try optimizing it for two months at a time, then 3 months at a time - simply impossible to do manually.
So the answer is this - either I find a software that does an "optimization of the optimization", and checks all combinations of "sliding optimizations" giving me the best one to use, or I can do try to use the second solution.
2) I can try to bind my volatility filter to some other - yet to be found - parameter that has some correlation to it.
So I ask you, before proceeding to the second, less complicated, solution - is there a software that could implement a "sliding optimization" telling me which intervals my system should be optimized on?
If we find out that by optimizing it on different time intervals - the last month, year, decade - that certain parameters change greatly, then we could have two solutions - either:
1) finding out on which time intervals the system's parameter should be optimized to give the best return.
2) have the system continuously adapt a given parameter in order to be as efficient as possible.
For example, in my system, that does about 1 intraday trade per day on a 5-minute chart, the parameters are:
1. ma crossover
2. time zones (outside of which trading is not allowed)
3. volatility filter
4. stoploss
Now, I would find it reasonable if stoploss, time restrictions and moving averages didn't change. So only our volatility filter changes, and without it changing our system's return would suffer greatly.
So how do we adapt this volatility filter?
1) There could be an easy way - continuously optimizing it. But then how do I know which interval I should use to optimize it, and how do I know if this makes any sense? I would have to go back in my 5 years historic data, optimize the system for january 1998, then use it for the next week or month, optimize it for february 1998, and test it on the next week/month....then try optimizing it for two months at a time, then 3 months at a time - simply impossible to do manually.
So the answer is this - either I find a software that does an "optimization of the optimization", and checks all combinations of "sliding optimizations" giving me the best one to use, or I can do try to use the second solution.
2) I can try to bind my volatility filter to some other - yet to be found - parameter that has some correlation to it.
So I ask you, before proceeding to the second, less complicated, solution - is there a software that could implement a "sliding optimization" telling me which intervals my system should be optimized on?