Hi Steve - Once you have done an IO and found some results that look
promising, then you can run a mini exhaustive opt if you want. For a
simple
example, you run an IO on a MA crossover system, testing both
MA's with
periods from 1 to 100. You won't see all possible combos
reported but maybe
the results show that MA1=10 and MA2=20 might be
good. So to see all the
other values in that neighborhood you could
then run a little exhaustive
opt, say MA1 = 5 thru 15 and MA2 = 15
thru 25, something like that, which
will run in a reasonable
time.
To test the built-in IO engines, I ran a few exhausive opts
and saved the
results, then ran lots of IO tests and compared them to
the exhaustive
results to see what the IO's found and also what they
missed. You could say
that CMAE seems to take the "safe" approach,
IMHO it finds the broad
plateaus pretty well but as you might guess
they are usually far from the
most profitable. In my experience, the
other two IO engines will generally
find those too but they also find
a lot of the smaller and more profitable
ones, which you can then run
a mini exhaustive opt on to get a more complete
picture.
Regarding the trade-off you mentioned, I would think
it is a matter of
personal taste. How greedy are you? 8 - ) How
risk-averse? I am
inclined to try the smaller and higher plateaus
first, as long as they have
a little play on each side and are doing
well right now, and knowing that
they will fail eventually and I need
to keep a close eye on them... Good
luck!
Steve
-----
Original Message -----
From: "Steve Davis" <_sdavis@xxxxxxcom>
To:
<amibroker@xxxxxxxxxps.com>
Sent:
Monday, February 02, 2009 5:01 PM
Subject: [amibroker] SPSO vs Trib vs
CMAE, was: random optimization?
> Steve,
>
> I would
like to hear more about your system optimization process. How
> were
you able to determine the size of the plateaus discovered by the
>
built-in optimizers, and how did you decide which solutions had
the
> best trade-off between plateau size and
profitability?
>
> Thanks,
> another
Steve
>
> --- In amibroker@xxxxxxxxxps.com,
"Steve Dugas" <sjdugas@xxx> wrote:
>>
>> Hi -
I have spent lots of time playing with the built-in
intelligent
>> optimizers, in my experience SPSO will return the
same results every
> time if
>> the settings are the same.
Trib and CMAE will probably return different
>> results each
time. FWIW, I find CMAE to be the worst of the three and I
>>
don't use it anymore, it will find plateaus but nearly always
misses
> the
>> much more profitable but smaller plateaus.
Using a quad-core I can
> run 4
>> simultaneous instances
and I find that by running 1 SPSO and 3
> Trib's and
>>
then comparing the 4 results together, it will generally point me
to
> some
>> pretty good param values. Good
luck!
>>
>> Steve
>>
>> ----- Original
Message -----
>> From: "gabriel_id@..."
<finance@xxx>
>> To: <amibroker@xxxxxxxxxps.com>
>>
Sent: Monday, February 02, 2009 7:25 AM
>> Subject: [amibroker]
Re: random optimization?
>>
>>
>> >
OK..
>> >
>> > Can u give me what type of engine
and with what kind of settings will
>> > get the same results
when i optimize this lines:
>> >
>> > N =
Optimize("N-minutes", 33, 1, 60, 1);
>> > TimeFrameSet( N
* in1Minute );
>> > MA1 = MA( Close, 10);
>> > MA2
= MA( Close, 20);
>> > BuySignal = Cross( MA1,
MA2);
>> > sellSignal = Cross( MA2, MA1);
>> >
TimeFrameRestore();
>> >
>> > Buy =
TimeFrameExpand(BuySignal , N*in1Minute);
>> > Sell
= TimeFrameExpand(sellSignal , N*in1Minute);
>>
>
>> > I tried cmae, 5 , 1000, have variable results.. on
walkforward
>> > i tried spso, 5, 1000, same variables
results..
>> > and also trib, 5, 1000..
>>
>
>> >
>> > --- In amibroker@xxxxxxxxxps.com,
"Mike" <sfclimbers@> wrote:
>> >>
>>
>> Tribes is a non exhaustive optimizer, meaning that it does
not
>> >> evaluate every possible combination.
>>
>>
>> >> As such, it is possible that it will find
different "optimal"
>> >> solutions every time, depending
on the nature of the surface being
>> >> optimized. For
example; If the surface has many similar peaks, it may
>>
>> land on a different one each time (local optima) instead of the
one
>> >> true optimal solution (global
optima).
>> >>
>> >> Try increasing the
number of Runs and/or MaxEval. If you have more
>> >> than
2 or 3 optimization variables, 1000 MaxEval is not enough.
>>
>>
>> >> http://amibroker.com/guide/h_optimization.html
>>
>>
>> >> Mike
>> >>
>>
>> --- In amibroker@xxxxxxxxxps.com,
"gabriel_id@" <finance@> wrote:
>> >>
>
>> >> > hi there,
>> >>
>
>> >> > i am a bit confused, i run the same
optimization process.. on same
>> >> > data range.. and
i got different results each time :)
>> >> >
>>
>> > and the engine was trib, 5, 1000...
>> >>
>
>> >> > thx,
>> >> >
GV
>> >> >
>> >>
>>
>
>> >
>> >
>> >
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>>
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>
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>>
>
>> >
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>>
>
>> >
>>
>
>
>
>
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> ****
IMPORTANT ****
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>
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