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Again I don't disagree with your ideas here, but as I've stated
before I only have an interest in having a tool(system) that is
competent to navigate some particular maze not every maze. If it's
good at navigating them all that's wonderful, if not I'll be happy to
restrict my activity to the maze(s) that it consistantly works in.
--- In amibroker@xxxxxxxxxxxxxxx, "palsanand" <palsanand@xxxx> wrote:
> I agree that the expert systems may be the exception to the general
> rule. The DVI (Detection, Verification and Interpretation)
technique
> I use may be categorized as an expert system (a collection of un-
> optimized systems used to arrive at a consensus signal) with
adaptive
> parameters. An optimized system behaves exactly like an un-
optimized
> system out-of sample if it is not re-optimized. Then why does an
> optimized system works sometimes and fails often? How robust is
it?
> It is the difference between training a mouse to navigate a
> particular maze and training a mouse to navigate any maze... The
> mouse that has been trained to naviagate a particular maze may do
it
> faster than the mouse that has been trained to navigate any maze,
but
> when the former mouse enounters an entirely different maze (a
market
> with different personality) it fails, hence it requires re-training
> (re-optimization). The answer may be in the number of parameters
> used by the system, i.e., how robust it is. The more optimized
> parameters it uses the more re-optimization it needs to
successfully
> cope with this change in market condition, as opposed to adaptive
> parameters (many parameters but the values fixed for each system so
> that all of the underlying instruments use the same periods for
each
> system) which require no re-optimization and is able to detect
> accurate signals regardless of the market size, condition or nature.
>
> MAs are perhaps the most widely used form of analysis because it
has
> been proven by elaborate forecasting modeling that most investments
> follow a MA process. The key to successful market timing is
> identifying when the prices are significantly lower or higher than
> the average price. This discrepancy between the current and the
> average price identifies a possible trading opportunity.
Generally,
> the price will return to the average price at some point in the
> future - hence proving the MA process itself...
>
> rgds, Pal
> --- In amibroker@xxxxxxxxxxxxxxx, "Fred" <fctonetti@xxxx> wrote:
> > In general I would agree with the concept that the liklihood of
> good
> > out of sample or real time system performance is indirectly
> > proportional to the number of parameters, but there ARE
exceptions
> to
> > this general rule at least as applied to what some would term to
be
> > expert systems. A case in point is a system I use every day and
> has
> > had for years as good out of sample, real time performance as it
> had
> > in sample. It has 27 parameters. I haven't reoptimized in at
> least
> > 18 months because there was no reason to.
> >
> > --- In amibroker@xxxxxxxxxxxxxxx, "palsanand" <palsanand@xxxx>
> wrote:
> > > My primary trading system is very simple in the sense that it
has
> > > only one parameter (the lookback MA period), and it generally
> leads
> > > to a robust system. It is objective (non-optimized and
> parameters
> > > are never subject to change) and unique in the sense it is both
> > trend-
> > > following (continuation of a previous trend or breakout) and
> > counter-
> > > trend following (start of a new trend) at the same-time. The
> trend
> > > and counter-trend following features of the MA based systems
are
> > > highly desirable because it resists becoming outdated as
markets
> > > change character (personality). Independent of the
fundamentals
> > > driving the market, these features are designed to capture
> extended
> > > runs in both bullish and bearish directions. The Verification
> and
> > > Interpretation of the signals Detected by this system was a
great
> > > challenge, but I was able to use good filters (OB/OS) and use
> > > Volatility (non-trend component of a signal) to optimize my
entry
> > > points. A robust system can be categorized as one that stands
a
> > good
> > > chance (probability) of working in the future as it has worked
in
> > the
> > > past, i.e, it is tough (able to handle all markets and
conditions
> > > regardless of size and nature) and long-lasting (durable).
> > >
> > > As discussed in a recent STOCKS & COMMODITIES article by
Jeffrey
> > Owen
> > > Katz and Donna McCormick, a rule of thumb in evaluating trading
> > > systems is that the more parameters a system has, the less
robust
> > the
> > > system is. Taken to the extreme, many fitting parameters can be
> > used
> > > to curve-fit past data to eliminate all whipsaws while
> maintaining
> > > good performance. The potential of such a system working in the
> > real
> > > world is nil...
> > >
> > > rgds, Pal
> > > --- In amibroker@xxxxxxxxxxxxxxx, "Dave Merrill"
<dmerrill@xxxx>
> > > wrote:
> > > > agreed. if the fact that a trading system did well in the
past
> > has
> > > no
> > > > bearing whatsoever on whether it does well in the future, how
> can
> > > we know
> > > > anything at all about the future performance of a proposed
> > trading
> > > system?
> > > >
> > > > dave
> > > >
> > > > The gambler”Ēs fallacy is a fallacy because the gambler
> ignores
> > > the
> > > > independence of the outcomes and looks for patterns that do
not
> > > exist. If
> > > > we have designed trading systems based on recognition of
> patterns
> > > that
> > > > precede profitable trading opportunities, and if those
patterns
> > are
> > > > persistent, then we no longer have random, independent
> outcomes.
> > > Our
> > > > trading systems do have serial dependencies and upward
sloping
> > > equity
> > > > curves. So analysis of the equity curve provides an
indication
> > of
> > > the
> > > > health of the trading system.
> > > >
> > > >
> > > >
> > > > Howard
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