curve fitting is when you look at a strategy and its results,
see that its not quite where you want it to be, add in some new
variables that you know improve it and hey presto the results
improve. Thats curve fitting
Vimal -- yes, agreed, that's what curve-fitting is -- but in
this instance what new variable is matt adding to the system?
He is not adding any new variable. He's just taking profits
at a predetermined level. If anything, he is simplifying the
system not making it more complex.
....the only other point I will make having coded and tested
many many strategies (and also from research done by collegues) is
that overall, dynamic exits work far better than fixed TPs or TP
%s.
For example, the simple MA Crossover systems which in the main
use a crossover to enter short or enter long is far better
than using the crossover to enter short and then setting a x%
TP or $TP
So the question Matt is whether you have tested using a dynamic
indicator driven exit? This will be far more robust in dynamic and
differing market conditions than one that uses a fixed TP whether
it be % or $
no problem with the TP level being set. Good idea given that
profit moves to 10% in many cases but as seen in recent trades,
this can be given back
If we now have a series of 6 trades which only make it to a
9% profit before giving this back then I would not expect the
dynamics of the strategy to change such as to move this TP to 9%
with a rerun of historical results to show what 9% would have
delivered
Otherwise, yes good system and no problem with a TP provided its
not regularly adjusted as per the above example
Your 9% example would be true if the series of 9% profit trades
were purely random. If, however, the market had changed and a
9% TP consistently (say over several months) provided better
returns, then it would be a wise choice to change the system to a
9% TP. My assumption is that some market changes aren't day
to day random, but persist over several months. One way to
test this hypothesis with with walk forward optimization.
curve fitting is when you
Improved GDX swing system and statistics
Posted by vimal on 29th of Jul 2010 at 03:05 am
curve fitting is when you look at a strategy and its results, see that its not quite where you want it to be, add in some new variables that you know improve it and hey presto the results improve. Thats curve fitting
curve fitting
Posted by Michael on 29th of Jul 2010 at 05:52 am
Vimal -- yes, agreed, that's what curve-fitting is -- but in this instance what new variable is matt adding to the system? He is not adding any new variable. He's just taking profits at a predetermined level. If anything, he is simplifying the system not making it more complex.
....the only other point I
Posted by vimal on 29th of Jul 2010 at 08:06 am
....the only other point I will make having coded and tested many many strategies (and also from research done by collegues) is that overall, dynamic exits work far better than fixed TPs or TP %s.
For example, the simple MA Crossover systems which in the main use a crossover to enter short or enter long is far better than using the crossover to enter short and then setting a x% TP or $TP
So the question Matt is whether you have tested using a dynamic indicator driven exit? This will be far more robust in dynamic and differing market conditions than one that uses a fixed TP whether it be % or $
no problem with the TP
Posted by vimal on 29th of Jul 2010 at 07:58 am
no problem with the TP level being set. Good idea given that profit moves to 10% in many cases but as seen in recent trades, this can be given back
If we now have a series of 6 trades which only make it to a 9% profit before giving this back then I would not expect the dynamics of the strategy to change such as to move this TP to 9% with a rerun of historical results to show what 9% would have delivered
Otherwise, yes good system and no problem with a TP provided its not regularly adjusted as per the above example
Vimal, Your 9% example would be
Posted by algyros on 29th of Jul 2010 at 08:46 am
Vimal,
Your 9% example would be true if the series of 9% profit trades were purely random. If, however, the market had changed and a 9% TP consistently (say over several months) provided better returns, then it would be a wise choice to change the system to a 9% TP. My assumption is that some market changes aren't day to day random, but persist over several months. One way to test this hypothesis with with walk forward optimization.
vimal -- I see what
Posted by Michael on 29th of Jul 2010 at 08:10 am
vimal -- I see what you're saying.