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very interesting herman, thanks very much for this. looking forward to
checking it out.
I'm slightly confused about where this fits in overall system evaluation
though. I see that the plot shows smoothness or uneveness of equity in
response to changes in the parameter under test, but I have some questions.
(please understand that I'm not disagreeing with anything at all. I'm just
trying to get my head around this approach system evaluation. I have a sense
that many schemes that backtest well do so only out of curve fit, and that
performance can degrade at any time. IMO there's no more critical piece of
the puzzle than how to distinguish a nice curve fit from something more
generally applicable, and if parameters need periodic adjustment, how to
know how and when to do that.)
- I assume you'd want to test all reasonable parameters to fully evaluate a
system. what does it mean if a system provides even response to changes in
some parameters, but uneven response to others?
- what exactly does uneven response mean? that the system isn't robust and
should be discarded, or used with caution? might you also see uneven
performance if the test exceeded the usable range of the parameter, for
instance if an MA intended to be the faster of two MAs crossed over and
became the slower one?
- why would you expect behavior for all stocks to synchronize? some
historically move much faster, or much more, and an MA, for instance, that
didn't match the stock well wouldn't do very well.
- what does it mean if equity is smooth over one time period, say 2000 to
present, but uneven, or consistently negative, for other time periods, say
1992 to present? one possibility is that market behavior has changed speed,
and a system would need to adjust. would that make it an unwise system to
use, or just one that needs recalibrating periodically?
thanks again for your thinking on this, very important. are there any books
you'd recommend about techniques for evaluating and properly optimizing
systems?
dave
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