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Al, I'm not disputing the usefullness of statistics. Far from it.
I'm merely stating that in my view, it is misleading to exclude
individual systems using past measures of profitability. Of course,
if the profitability is so dismal, maybe I would then question the
theoretcial foundations on which it is developed, and if I find it
questionable I would then discard it. A secondary system of filters
and stops will often improve the 15 year performance of a primary
trading system, as in my case. Some of the secondary systems I have
developed has better profitability statistics for the past than the
primary, but that is no reason to exclude the prmary system. It just
needs some verification and interpretation and walk-forward testing
to find the correct range of parameters...
rgds, Pal
--- In amibroker@xxxxxxxxxxxxxxx, "Al Venosa" <advenosa@xxxx> wrote:
> Pal, what you say is OK theoretically. However, in trading, the
only real theory that applies is supply and demand. How one views
that theory is what makes the trading world go round and round. What
may seem contrarian to you may be the opposite to someone else. Thus,
everything in trading is empirically based, and you can make lots of
money using empirical principles (and, of course, lose lots, too).
That's why statistical analysis is so important when making trading
decisions. You have to take into consideration the errors involved in
your observations and the probability of being right based on past
performance. You calculate your expectancy based on the % of winners
and the average win:loss ratio. If you have a positive expectancy, in
the long run you will make money if you are disciplined. If you know
things like maximum dd, expectancy, W/L ratios, based on your
extensive backtesting, you can apply Monte Carlo simulations (MCS) to
your system to verify its robustness over thousands of statistical
trials. If the MCS results still give you acceptable results you can
live with, then you can probably proceed with trading it with real
money. But all of this is empirical, not theoretical. And it's legit,
too. Practice without fundamental theory is not impossible. People do
it all the time. As Joe said, the bottom line is, does your system
make money? If it does, who cares if there is not an underlying
theory to what you are doing?
>
> Al Venosa
> ----- Original Message -----
> From: palsanand
> To: amibroker@xxxxxxxxxxxxxxx
> Sent: Saturday, November 01, 2003 8:39 PM
> Subject: [amibroker] Re: On Robustness, Post #1
>
>
> Hi,
>
> Practice without theory is impossible, theory without practice is
> useless... I believe in the "Contrarian theory" and all the
systems
> I ever developed are built around it. The only reason prices
move is
> because of an imbalance between buyers and sellers, between
supply
> and demand. Price tends to equalize supply and demand. That's
> why "contrary opinion" works. If everyone thinks an underlying
> instrument is going up, that is because they all own it. Since
there
> are a very few buyers at the current price, it takes very few
sellers
> to drive it down....
>
> rgds, Pal
>
> --- In amibroker@xxxxxxxxxxxxxxx, "bvandyke" <bvandyke@xxxx>
wrote:
> > Hi Pal,
> >
> > Can you help me understand please what you mean by selecting
> systems
> > on "sound theory", as opposed to selecting systems based on
past
> > objective data regarding their profitability? Thanks.
> >
> > Bill
> >
> > --- In amibroker@xxxxxxxxxxxxxxx, "palsanand" <palsanand@xxxx>
> wrote:
> > > Hi,
> > >
> > > In my view, it is misleading to exclude individual systems
using
> > past
> > > measures of profitability like APR, Annual trades, Percent
Wins,
> > > etc., because these statistics may disprove that a system
has
> > been
> > > unprofitable in the past, but cannot prove that it may be
> > profitable
> > > in the future. I would select systems based on a sound
theory,
> > not
> > > arbitrary systems which has no solid theoretical
foundations...
> > >
> > > rgds, Pal
> > >
> > > --- In amibroker@xxxxxxxxxxxxxxx, "MarkF2" <feierstein@xxxx>
> wrote:
> > > > This is in response to DT's and others' requests to provide
more
> > > > details on my 9 robustness criteria.
> > > >
> > > > First some administrative anouncements, lol. I've decided
to
> > > provide
> > > > them one-by-one, first due to my time constraints, second
> > because I
> > > > feel that's the best way to discuss them and third because
I
> > want
> > > to
> > > > see how this goes. I welcome all constructive debate,
> > especially
> > > > opposing views supported by quantitative analysis. But if
this
> > > > degenerates into a flame war, I've got better things to do
with
> > my
> > > > time. Treat me with respect and I'll treat you with
respect.
> > > There
> > > > seems to be a lot of interest in this topic, so let's
please
> > have a
> > > > collegial and productive discussion. This is post 1 of 9
(not
> > > > counting the dialog inbetween, let's see how far we can
get :-).
> > > >
> > > > Why care about robustness? For whatever reasons, markets
> > change.
> > > We
> > > > could spin our wheels forever discussing time series
theory,
> > serial
> > > > dependencies, random walk, nonstationarity, etc., like
> > academicians
> > > > do and get nowhere (as they do), or we can try to cut
through
> > the
> > > crap
> > > > and deal with it (the simple fact that markets constantly
> > change).
> > > > My weapon of choice is robustness. You could say I have a
> > > robustness
> > > > obsession and my criteria are overkill. But that's my
choice
> > and
> > > > you're free to make your own on how far you want to take
this,
> > if
> > > at
> > > > all.
> > > >
> > > > OK, I lied. There will be some, very light discussion of
> > > statistics
> > > > because some criteria are steeped in statistical theory.
But
> > most
> > > > can be reduced to simple, mechanical procedures that can be
> > graphed
> > > in
> > > > a spreadsheet and visually and intuitively interpreted.
Others
> > > > require simulation software and one requires proprietary
> > software
> > > but
> > > > we'll cross that bridge when we come to it.
> > > >
> > > > Speaking of proprietary, there are some things I simply
won't
> > > > disclose, such as specific parameters for certain
criteria. So
> > > please
> > > > respect my wishes and don't ask. I have my reasons. So
> > evaluate
> > > this
> > > > on your own and decide for yourself what place, if any, the
> > criteria
> > > > have in your trading. They work great for me but I make no
> > claim
> > > that
> > > > they're the Holy Grail of robustness and am sure that some
of
> > you
> > > will
> > > > come up with better ideas if there's enough interest and
> > > discussion.
> > > >
> > > > With that long winded intro, here's Criterion #1:
> > > >
> > > > Test *unoptimized* system on small, mid & large cap stocks
in
> > bull,
> > > > bear & sideways market conditions, same parameters for
all. I
> > use
> > > > the stocks of the S&P 600, 400, and 500 indices and 2 year
> bull,
> > > bear
> > > > and sideways periods (for a total of 6 years per stock).
> > Rationale
> > > > behind this: to find systems that profitably *tested out in
the
> > > past*
> > > > on a large number of (somewhat tradeable) stocks of varying
> > market
> > > > caps in multiple sectors under different market conditions,
> > under
> > > the
> > > > assumption that this indicates the system is robust enough
to
> > > > profitably *trade select issues in the future*. More on
robust
> > > issue
> > > > selection in later criteria. Looking for net profitability
on
> > all
> > > mkt
> > > > cap and mkt condition subtests, and profitable on the
majority
> (>
> > > > 50%) of issues in each subtest, the more the better.
Sometimes
> > I
> > > cut
> > > > a system some slack if it's close on one or two subtests,
it's
> a
> > > > judgement call. My commission setting(s) in AB:
proprietary,
> > based
> > > > on my *slippage* research using data from actual trades.
But
> you
> > > > could choose an arbitrary say, 1% to get started. Date
> settings
> > for
> > > > my 2 year intervals: proprietary but you can easily find
your
> > own
> > > by
> > > > eyeballing a chart of a major index. Just use the same
ones
> each
> > > > time so you compare apples to apples. My lite version of
this
> > is 2
> > > > year bull and bear periods on the ND100 and SP100 stocks,
which
> I
> > > > sometimes run as a quick pre-screen. Next time someone
posts a
> > > system,
> > > > run it through the lite or full version. Or test the
systems
> in
> > the
> > > > AFL library. The more systems you run through, the more
> > intuitive
> > > of
> > > > a feel for robustness you'll get. Note that I'm *not*
saying
> > you
> > > > shouldn't or can't successfully trade something that
doesn't
> meet
> > > > this standard, lol. That's obviously not true! I was
asked to
> > > > explain my robustness criteria and that's what I'm doing.
> > Period.
> > > > This criterion is a post-Amibroker creation, BTW. Pre-
> Amibroker
> > I
> > > had
> > > > a small test portfolio of diverse issues I used instead and
it
> > did a
> > > > decent job. I run this now because I now (easily) can,
*many*
> > thanks
> > > > to Tomasz. If you're thinking, geez, why bother with this,
ask
> > > > yourself a simple question. *All else being equal*, would
you
> > feel
> > > > more confident trading (with your money) a system that
passes
> > this
> > > > test or one that fails it?
> > > >
> > > > Regards,
> > > >
> > > > Mark
>
>
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