Activity Spectrum and AFC of MTS using the Moving Average advisor as an example - page 4
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Something similar has been realized long ago. Self-training EXPERT (lsv)'.
No, there's a different song there - patterns and training.
We do not train the expert, but allow him to trade only at certain quantum frequencies. This will not make him smarter.
That is, there is some MTS that contains a period dependency. In fact, you are saying that the behaviour of the MTS (trading system) relative to the condition that the period is defined correctly is invariant... That is, if I have defined a period and entered a number into the MTS, then the MTS will work *right* and the same as on past data?
Even if your MTS trades not by signals but by time - for example: trades open every Tuesday at 14:00 - frequency filtering is still possible. Only in one case the system is powerless - the signals are generated by a random number generator, because the repetitiveness of such signals is random.
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And if you are talking about whether there will be profit from those frequencies, well, "where the money lies" in the future? It is unlikely for all of them, but for most of them, yes. Some previously loss-making frequencies may become profitable, while others may become profitable. Everything is in development.
{...} Unlikely on all of them, but on most of them, yes. {...}
Counter-question: on average, how many of the profitable frequencies
remain profitable? And on what time interval on what average size of window were these statistics collected?
The point is that you don't even need to draw any frequencies in general.
Here we are talking about switching to a different type of thinking - not a specific MTS with parameters, but a set of MTS.
And how you number them - by frequencies, indexes - in general it makes no difference.
At some point they give a result - then a run on OOS - then a run on forward (real).
The best ones are chosen, of course. Do you have statistics of such runs on your system at least for a year?
jartmailru wrote >>.
jartmailru писал(а) >>
16 hours is a bit long. Do you really collect statistics manually? Here's my data: collecting 3000 results of different combinations of input data (3000 trading systems :-) ), then taking the 20 best ones and running them through "optimization", and then running the 5 best ones through "forward" - it takes exactly one minute! This was me solving the problem of selecting inputs to the probability network. To tell the truth, I have not showed proper imagination neither in a choice of data, nor in a choice of the teacher, therefore I have nothing to boast except speed of calculations ;-)
16 hours is a bit much.
And that's on an i7 965 and 6 simultaneous optimisers.
Maybe you are testing in "all ticks" mode ? My tester works "on bar opening".
I compared the results of the two methods: the time is almost halved, but the quality of the calculation was not satisfactory.
Source Expert Advisor Moving Average
Same Expert Advisor, but after applying frequency filter
Initial Moving Average Expert Advisor Same Expert Advisor, but after applying frequency filter
I.e., we took the results of the initial Expert Advisor and used them to build the filter.
And then, knowing a priori the distribution of trades, we obtained the result?
How is it different from gathering statistics by a number of instances?
in a series of successful and unsuccessful trades?
.
Why don't we use a probability network which simply stores
all the times to open - and not run it?
Or you could filter trades with a perceptron from Reshetov's EA :-).
Although if you know the perceptron coefficients - why do you need the original EA :-).
The results might be much better.
.
If you play by the rules - then be kind enough to measure the spectrum.
on the first half of the year, and apply it on the second half.