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Hi,
There is a correct method to optimize any system that is
statistically valid, 30 occurrences with 95% accuracy.
The key to optimization is to select stable parameters with an equity
shift less than the parameter shift after equity spikes have been
eliminated. This process creates stability for optimal parameters
shifts within the four technical market phases. Parameter shift is
always geometric, but equity shift decline relative to unstable
parameter selection is usually exponential.
All systems are optimized to some degree. As soon as a trader chooses
to enter a trade on the open as opposed to the high/low/close of day,
he has made a decision as to how a system should be traded. Does he
know the high/low/close of day entry is better than the next opening
for an entry? If not why not? A potential 28% difference in
profitability exists for channel system entries between opens and
closes.
The purpose of trading is to consistently make money. This is done by
having the best information available. If a trader does not know the
best entry for his system, what is he trying to prove? That the
system isn't optimized? To lose money because a trader is ignorant of
his systen's best parameters is foolish.
Regards,
Pal
--- In amibroker@xxxxxxxxxxxxxxx, "Dave Merrill" <dmerrill@xxxx>
wrote:
> one question pal: if you prefer not to optimize parameters, how do
you set
> them? or do you have some kind of trading rules that don't have time
> constants, trigger levels, etc, that need to be set?
>
> dave
>
> I thought I might throw in my 2 cents.
>
> Vendors love optimization, because it can generate eye popping
> hypothetical profits which has no connection to real-time trading.
>
> I prefer a system to work without optimization. But if I have to
do
> it, I would make sure that the optimization is robust in the
> following manner:
>
> 1. The sample size of data should be large enough to represent
real-
> time market conditions - bull, bear and sideways markets.
>
> 2. The look-back period should be as large as possible for the
same
> reasons.
>
> 3. The testing of optimizable parameters should be on out of
sample
> data using walk-forward analysis.
>
> 4. The Central Limit Theorem says that for a sample to assume the
> characteristics of the population, the size of sample should be
> large. The minimum sample size should be around 30. But since an
> uptrend or downtrend can last for say 50 periods, I would have a
> minimum sample size of 100 periods making sure that the full
market
> cycle is there (uptrend, downtrend and congestion).
>
> 5. The optimizable parameters should be as few as possible and
tested
> in a wide variety of markets.
>
> Curve-fitting is like rolling a fair dice with 1/6 probability of
> getting any number from 1 to 6, rolling it 5 times, getting #6, 4
out
> of 5 times (80%) of time.
>
> A lot of traders fall in the trap of curve-fitting without being
> aware of it. So when designing a system, it is important to keep
your
> guard up as far as curve-fitting is concerned.
>
> Regards,
>
> Pal
> --- In amibroker@xxxxxxxxxxxxxxx, "Gary A. Serkhoshian"
> <serkhoshian777@xxxx> wrote:
> > Fred,
> >
> > Could you narrow-down your idea of a reasonable sample size for
> backtests. You've been hinting at rather sizeable backtesting
> periods, but would like to put some numbers to it. Also wonder if
> you use # of trades as a guide versus period of time for
backtesting
> period.
> >
> > Thanks,
> > Gary
> >
> > Fred <fctonetti@xxxx> wrote:
> > There are a lot of questions and provacative statements in your
> post,
> > only one of which from my perspective needs an answer/response.
> >
> > Market behavior will continually change after that ...
> >
> > Change ? from what ? into what ? I guess this is the part I
don't
> > follow. To me there is nothing new in market behavior now that
> > didn't exist last month, last year, last decade, last century,
but
> > clearly those that take a short sighted view of history and the
> > market action that made up that history will clearly never see
it.
> > It's a forest and trees thing ...
> >
> > --- In amibroker@xxxxxxxxxxxxxxx, "Dave Merrill" <dmerrill@xxxx>
> > wrote:
> > > I'm not trying to be argumentative, honest (:-)... I'm more
than
> a
> > little
> > > sick of saying the same thing over and over, but I j u s t
d o
> > n ' t g
> > > e t i t .
> > >
> > > ------------------------------
> > >
> > > I fail to see the huge difference in principle between equity
> > feedback and
> > > backtesting.
> > >
> > > let's start by assuming that backtesting performance of a
system
> > and its
> > > parameters over some period of past data tells you something
> about
> > its
> > > future performance. it's not a perfect predictor, but it's the
> best
> > evidence
> > > we have. does this seem like a reasonable starting point? what
> > alternative
> > > is there?
> > >
> > > if that's true, why is it better to do it only once? what
> > justification is
> > > there for picking one examination period over another? clearly
> > market
> > > behavior will change continually after that. don't we need a
way
> of
> > working
> > > that looks at what's been happening and evolves our response?
> > >
> > > sounds like we examine performance up to some point and
adjust,
> > trade with
> > > the best-choice system and parameters for a while, then
examine
> and
> > adjust
> > > again later. make sense? what alternative is there?
> > >
> > > so then, how often do we re-examine performance history? to
put it
> > > differently, how long do we ignore any changes in market
dynamics
> > that may
> > > or may not have occurred? why would intermittently refusing to
> look
> > and
> > > respond improve system performance or reliability?
> > >
> > > if that needs to be done, why not have the system itself do
it,
> as
> > part of
> > > its inherent operation? why is it better for us as an outside
> agent
> > to
> > > periodically run some separate tests, reach into the
internals of
> > the
> > > system, and change stuff?
> > >
> > > or should we just continue with the system and parameters we
> choose
> > at the
> > > beginning? are they somehow more valid than what we'd choose
> later,
> > using
> > > the same backtesting methods, but on a different date range of
> data?
> > >
> > > ------------------------------
> > >
> > > I realize that even if it seems to make sense logically, this
all
> a
> > complete
> > > crock if no systems put together like this even backtest well,
> > never mind
> > > forward testing.
> > >
> > > but every time I think about abandoning this line of
research, it
> > seems like
> > > the first thing I'd want to do with a new system would be
(let me
> > guess),
> > > test and possibly adjust it using data up to some date, then
run
> > with it for
> > > a while after that and see if equity growth is good. if it is,
> I'd
> > want to
> > > lather, rinse and repeat with other in and out of sample
data, to
> > make sure
> > > that wasn't coincidence.
> > >
> > > sounds way too familiar to be a completely different animal.
> > >
> > > dave
> > > From: Fred [mailto:fctonetti@x...]
> > >
> > > That IS what I was trying to say. I suspect because equity
> feed
> > back
> > > is like looking in a rear view mirror, great for letting us
know
> > > where we were and how we could have adjusted the past to
make it
> > > better, but that's about it.
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