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Pal,
You're kinda talking about nonstationarity (although the markets are
not random). Stay tuned for posts 2 and 3. On drawdown, stay tuned
for post 5. You want a solid theoretical foundation? Talk to me
offline about Edgeworth expansions and the nonparametric bootstrap
we'll use to estimate *future* drawdown.
Regards,
Mark
--- In amibroker@xxxxxxxxxxxxxxx, "palsanand" <palsanand@xxxx> wrote:
> Unlike gambling, where the outcomes are known and probabilities
> constant, in trading we have a multitude of random outcomes with
> undetermined probability of winning. The maximal loss is a
> nondescreasing step function, with random amplitude leaps occurring
> at random moments.
>
> So, there is no real evidence to suppose that the maximal loss and
> maximal drawdown achieved will persist in the future.
>
> rgds, Pal
> --- In amibroker@xxxxxxxxxxxxxxx, "Joe" <run_for_your_life2003@xxxx>
> wrote:
> > I have the same question regarding what you are refering as "sound
> > theory" . The bottom line is does it make you money?
> >
> > --- 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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