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Gary,
I agree with all 3 points, especially 2 and 3, but don't
agree on using the equity curve as a feedback mechanism.
It actually contradicts points 2 and 3, IMO.
What's the point in using *current* equity curve as a
driving force in changing the strategy (or sticking with it)
rather than studying what caused such equity pikes in your
backtests in the first place, and then switching strategies when
those conditions occur again? There's a significant difference in
the two...
And all this talk about markets constantly changing, etc. begs
a fundamental question... What percentage of behaviors in
the market can one identify that one positively can NOT
identify in say last 20 years of the market history? That
example of going through a totally different kind of jungle
is not valid when considers the fact that you can play with
99% of the jungle simulations before ever you set your foot
in one.
Jitu
--- In amibroker@xxxxxxxxxxxxxxx, "Gary A. Serkhoshian"
<serkhoshian777@xxxx> wrote:
> Pal,
>
> You description of stationarity vs non-stationarity was nothing
short of poetic. I had to read through your e-mail twice, but thanks
for taking the time.
>
> I certainly agree it is good to know that we are not dealing with a
stationary data series. The big headline I take away from all this
discussion is:
>
> 1. Beware of over-optimizing.
> 2. Build in ways of detecting market changes
> 3. Have circuit breakers on your systems assuming #2 doesn't work.
>
> I'm an Army guy. So, if you can't break it down to some useable
rules, it's just talk. After all, we trade where the rubber meets
the road, not in the clouds with all the academics.
>
> Regards,
> Gary
> palsanand <palsanand@xxxx> wrote:
> I agree. I would love to hear your comments on the following:
>
> The more you have information, the more you are confident about the
> outcome. Now the problem: by how much? Common statistical method is
> based on the steady augmentation of the confidence level, in
> nonlinear proportion to the number of observations. That is, for an
n
> times increase in the sample size, we increase our knowledge by the
> square root of n. Suppose I am drawing from an urn containing red
and
> black balls. My confidence level about the relative proportion of
red
> and black balls, after 20 drawings is not twice the one I have
after
> 10 drawings; it is merely multiplied by the square root of 2 (that
> is, 1.41).
>
> Where statistics becomes complicated, and fails us, is when we have
> distributions that are not symmetric, like the urn above. If there
is
> a very small probability of finding a red ball in an urn dominated
by
> black ones, then our knowledge about the absence of red balls will
> increase very slowly – more slowly than at the expected square root
> of n rate. On the other hand our knowledge of the presence of red
> balls will dramatically improve once one of them is found. This
> asymmetry in knowledge is not trivial--it is a central philophical
> problem for such people as Hume and Karl Popper. I can confirm that
> an investor trader is a bad investor (if he blows up); but I can
> never rule out that he may be one.
>
> To assess an investor's performance, we either need more astute,
and
> less intuitive, techniques, or we may have to limit our assessments
> to situations where our judgment is independent of the frequency of
> these events.
>
> But there is even worse news. In some cases, if the incidence of
red
> balls is itself randomly distributed, we will never get to know the
> composition of the urn. This is called the problem of stationarity.
> Think of an urn that is hollow at the bottom. As I am sampling from
> it, and without my being aware of it, some vicious child is adding
> balls of one color or another. My inference becomes thus
> insignificant. I may infer that the red balls represent 50% of the
> urn while the vicious child, hearing me, would swiftly replace all
> the red balls with black ones. This makes much of our knowledge
> derived through statistics quite shaky.
>
> The very same effect takes place in the market. We take past
history
> as a single homogeneous sample and believe that we have
considerably
> increased our knowledge of the future from the observation of the
> sample of the past. What if vicious children were changing the
> composition of the urn? In other words, what if things have changed?
> The "science" of econometrics consists of the application of
> statistics to samples taken at different periods of time, which we
> called times series. It is based on studying the times series of
> economic variables, data, and other matters.
>
> Studying the European markets of the 1990s will certainly be of
great
> help to a historian; but what kind of inference can we make now
that
> the structure of the institutions and the markets has changed so
much?
>
> Stanford economist Mordecai Kurz puts it as follows:
> The process of structural change (i.e. non-stationarity) in our
> society is the central building block of its complexity and the
root
> cause of the diversity of beliefs about it. In such a system, the
> past is not an entirely satisfactory basis for assessment of risks
in
> the future.
>
> Practitioners of the "financial engineering" methods measure risks
(I
> just use stops), using the tool of past history as an indication of
> the future. We will just say that the mere possibility of the
> distributions not being stationary makes the entire concept seem
like
> a costly (perhaps very costly) mistake. This leads us to a more
> fundamental question: the problem of induction which is a different
> subject.
>
> rgds, Pal
>
>
>
> --- In amibroker@xxxxxxxxxxxxxxx, "Gary A. Serkhoshian"
> <serkhoshian777@xxxx> wrote:
> > Ahh-hah ! You see this is where watching the equity curve would
> tell you that you are bouncing off trees rather than moving through
> the forest unimpeeded. Also, if you recorded your journey through
a
> large forest rather through a simple patch of trees you would have
a
> better gague on growth patterns of trees and hence your path.
> >
> > Taking this a step farther, pine trees grow differently than
> redwoods. So, you would run into trouble if you took a recording
of
> a journey through a redwood forest, and used it to guide you
through
> a pine forest.
> >
> > What people fail to understand is by virtue of picking some set
of
> parameters we are optimizing. I see people with smug looks on
their
> face when they say they don't believe in optimizing, but are hell-
> bent on making decisions with a 12,26,9 MACD.
> >
> > It's like a social drinker berating an alcoholic. They both
drink
> alcohol, it's just that the social drinker ensures he doesn't wake
up
> in the gutter. Over optimizing is a disease just like over
drinking.
> >
> > Regards,
> > Gary
> >
> > Joseph Platt <jplatt@xxxx> wrote:
> >
> > Lots of talk lately about Optimization, Overoptimization,
> > Robustivity, Randomness, etc. Regarding optimization here is a
copy
> > of an email I sent to a FastTrack friend of mine
recently....don't
> > know if it makes any sense or not.
> >
>
**********************************************************************
> > ******************
> > You know, most all systems depend on optimization at some level
but
> > one day when I was in a dreamy mood, (perhaps muscatel induced),
> this
> > analogy with regards to optimization popped into my head. Takes a
> > little imagination....
> >
> > Suppose a person decided to take a one mile walk through a well
> treed
> > area of woods. He would have no trouble negotiating the path
since
> > the trees are quite visible and he could navigate a path right
> around
> > them.
> >
> > Suppose further that he had been carrying some kind of an
> electronic
> > recorder with him (this is the part that takes a little
> imagination)
> > and every step along the one mile stretch was recorded.
> >
> > Still feeling energetic he decides to pick up where he left off
and
> > try another one mile hike through the next stretch of woods. He
> > reasons that it's not necessary to look for an unobstructed path,
> at
> > least not as carefully as he did on the first stretch, because
> after
> > all he has a recording of the whole journey and all he has to do
is
> > put it in the "play it again Sam" mode.
> >
> > The analogy doesn't have a very happy ending....he got through
the
> > second mile alive but just barely....you would hardly recognize
him.
> >
> > But to be fair there is a difference between trees that, as far
as
> we
> > know, grow randomly and the stock market which arguably isn't
> totally
> > random as many claim.
> >
>
**********************************************************************
> > ******************
> > I guess my friend got the email OK but his only response
was "watch
> > out for the trees".
> >
> > .....Joe Platt
> >
> >
> >
> >
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