--- In
amibroker@xxxxxxxxxxxxxxx, "brian_z111" <brian_z111@xxx> wrote:
>
> The BS file is too big for Yahoo group files ... also it would clog
> up limited space.
>
> I thought about AB third party but I have to download/maintain
third
> party software to FTP upload.... that annoys me somewhat (I am a
very
> independent type).
>
> The Zboard/WordPress arrangement is a trial ... if it goes smoothly
I
> will keep it going for a while.
>
> I am happy with the WordPress (limited filetype/space) arrangement,
> with a file host for sharing.
>
> So, now I will consider other filesharing hosts.
>
> Anyone you can download from?
>
> I can put one somewhere else for you.
>
>
> Don't worry I will make sure you get one, way or another.
>
> Better to get another host though because there will be at least
one
> more big file ..... if I keep going there might be plugins one day
so
> I need a universal host.
>
>
> brian_z111
>
>
Zboard.wordpress.com
>
>
>
> --- In
amibroker@xxxxxxxxxxxxxxx, Howard B <howardbandy@> wrote:
> >
> > Hi Brian --
> >
> > I use a Hughes satellite connection to the Internet. It seems
that
> Hughes
> > appears to Rapidshare as a single user (which is always over its
> limit), so
> > I am never able to download a Rapidshare file. If possible,
could
> you
> > upload the files to the Yahoo AmiBroker file section?
> >
> > Thanks,
> > Howard
> >
> >
> > On Sat, Feb 7, 2009 at 9:10 PM, brian_z111 <brian_z111@> wrote:
> >
> > > I am using Rapidshare for file sharing.
> > >
> > > Free downloads are available but they are slower than paid
> download
> > > and limited to 1 download per time ... wait a while and you can
> > > download again (still good value for my customers).
> > >
> > >
http://rapidshare.com/files/195190948/BinomialMaster_ABVersion.xls
> > >
> > > A short ReadMe, to help understand the file, is at:
> > >
> > >
http://zboard.wordpress.com/
> > >
> > > I can answer a few questions about the details in the file for a
> > > limited time (while my memory is fresh) .... post questions, if
> any,
> > > via comments at the Zboard.
> > >
> > >
> > > --- In
amibroker@xxxxxxxxxxxxxxx <amibroker%
40yahoogroups.com>,
> > > "brian_z111" <brian_z111@> wrote:
> > > >
> > > > File limits prevented me uploading the BinomialSimulation file
> (s)
> > > to
> > > > this group ... 20MB per file. I will post links to at least
one
> > > > example, at the following temporary site, sometime this week:
> > > >
> > > >
http://zboard.wordpress.com/
> > > >
> > > > I will post some basic notes afterall because the task of
> following
> > > > the Excel sheets would be beyond anyone without them.
> > > >
> > > > The site might live on for a while after that.
> > > >
> > > >
> > > > --- In
amibroker@xxxxxxxxxxxxxxx <amibroker%
40yahoogroups.com>,
> > > "brian_z111" <brian_z111@> wrote:
> > > > >
> > > > > I decided to post the Binomial Simulation files a few days
> > > ago ...
> > > > I
> > > > > am not going to announce the upload so this post is the
> > > discussion
> > > > > link for them (one or more files will appear at some stage).
> > > > >
> > > > > FTR They do predict the eq dist quite well, for biased and
> none
> > > > > biased 'coins' but there is one thing about them that does
> > > concern
> > > > > me ... I referenced the same synthetic trade series to make
> the
> > > > > binomial distribution and to create the synthetic eq
> curves ...
> > > > that
> > > > > seems a bit incestuous in some ways.
> > > > >
> > > > > On the other hand they could be full of incorrect math
> > > assumptions
> > > > > cos I got the math off Wikipedia!
> > > > >
> > > > > Guru Brian ;-)
> > > > >
> > > > >
> > > > > --- In
amibroker@xxxxxxxxxxxxxxx <amibroker%
>
40yahoogroups.com>,
> > > "brian_z111" <brian_z111@>
> > > wrote:
> > > > > >
> > > > > >
> > > > > > > This is a valid model as long as stationarity holds ...
I
> > > have
> > > > > > > simulated random trading 'systems' and predicted the
> outcome
> > > by
> > > > > > using
> > > > > > > binomial probability, that references a frequency
> > > distribution
> > > > of
> > > > > > the
> > > > > > > randomly generated trades, and it predicted the actual
> equity
> > > > > > > distributions extremely well (a lognormal dist appears
at
> > > very
> > > > > high
> > > > > > > N's).
> > > > > >
> > > > > >
> > > > > > More precisely, I have simulated trade series, using the
> RNG in
> > > > > > Excel, for random walks (50/50 systems) and biased
systems,
> > > with
> > > > > > normally distributed trade series (I used
> CentralLimitThereom
> > > to
> > > > > > create NormDists from the uniform output of the generator.
> > > > > >
> > > > > > I simulated equity curves, using the synthetic trades,
and
> at
> > > the
> > > > > > same time used BinomialProb to model the predicted
> distribution
> > > > of
> > > > > > the eq curves (I imagined I was tossing a coin with
variable
> > > > values
> > > > > > for heads and tails ... of course in trading we can win
> lose or
> > > > > draw
> > > > > > whereas in my model we can only win or lose).
> > > > > >
> > > > > > You might like to see the files?
> > > > > >
> > > > > > I am bored with that topic.
> > > > > >
> > > > > > I am not a mathematician ... it might be a load of old
> rubbish
> > > > for
> > > > > > all I know.
> > > > > >
> > > > > > As our discussion shows .. we can't get any statistical
> > > certainty
> > > > > > anywhere in trading ... only approximations and
> probabilties.
> > > > > >
> > > > > > It is just another approximation, like MCS and involves
> massive
> > > > > > number crunching.
> > > > > >
> > > > > > I didn't finish it because I wanted a quick and dirty
> method.
> > > > > >
> > > > > > The files are rough as old bags.
> > > > > >
> > > > > > I didn't make notes so even I have a hard time following
the
> > > > > > logic ... I had a look at them the other day I had to
start
> > > > tracing
> > > > > > the formulas in the cells to see how I had done it.
> > > > > >
> > > > > > I'll post some of them in the file section one day (Howard
> > > > collects
> > > > > > trading things).
> > > > > >
> > > > > > I won't scrub them up though ... take them or leave
them ...
> > > > sorry
> > > > > no
> > > > > > questions or explanations (anyway Howard and other maths
> people
> > > > > know
> > > > > > how to do that stuff).
> > > > > >
> > > > > >
> > > > > > --- In
amibroker@xxxxxxxxxxxxxxx <amibroker%
>
40yahoogroups.com>,
> > > "brian_z111" <brian_z111@>
> > > > wrote:
> > > > > > >
> > > > > > > Gidday Mate,
> > > > > > >
> > > > > > > I wasn't planning on posting again today as I am going
> away
> > > for
> > > > a
> > > > > > few
> > > > > > > days ..... a good question though so I couldn't resist.
> > > > > > >
> > > > > > >
> > > > > > > I did notice Fred's comment on the priority he places on
> > > > > > sensitivity
> > > > > > > analysis.
> > > > > > >
> > > > > > > He has made the comment before and I came to that view
> > > > > > independently
> > > > > > > a way back anyway (Howard's random noise test is another
> > > > > > interesting
> > > > > > > idea for single sample analysis).
> > > > > > >
> > > > > > > I also recall that he doesn't believe scrambling the
> order of
> > > > the
> > > > > > > trades provides any meaningful feedback.
> > > > > > >
> > > > > > > That isn't a reason for me not to reach my own
> conclusions.
> > > > > > >
> > > > > > > Fred has also talked about small N retesting (walk
> forward),
> > > > and
> > > > > > > adjusting his system rules, on a short term basis, so
> while I
> > > > am
> > > > > > not
> > > > > > > keen on the idea I am keeping an open mind on the
subject.
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > > > This is the second time in the >past few
> > > > > > > > days that you seem to have equated trading/backtesting
> > > system
> > > > > > > >outcomes
> > > > > > > > to a random series of coin flip outcomes (random
binary
> > > > > > occurances).
> > > > > > > >
> > > > > > > > Serious question... what is your point? What is the
> > > > relevence
> > > > > os
> > > > > > > >the
> > > > > > > > "Coin Flip" metaphor where trading systems is
concerned?
> > > > > > >
> > > > > > > Well, developers are selling software specifically
> designed
> > > for
> > > > > > > performing MSC for trading analysis and at least one
guy
> has
> > > > > > written
> > > > > > > a book on the subject.
> > > > > > >
> > > > > > > In both software packages, that I have some familiarity
> with,
> > > > > their
> > > > > > > model assumes stationarity, and independency i.e. their
> model
> > > > > > treats
> > > > > > > the data as if it is the outcome of a coin toss with
> variable
> > > > > > values
> > > > > > > on the +- side of the coin.
> > > > > > >
> > > > > > > This is a valid model as long as stationarity holds ...
I
> > > have
> > > > > > > simulated random trading 'systems' and predicted the
> outcome
> > > by
> > > > > > using
> > > > > > > binomial probability, that references a frequency
> > > distribution
> > > > of
> > > > > > the
> > > > > > > randomly generated trades, and it predicted the actual
> equity
> > > > > > > distributions extremely well (a lognormal dist appears
at
> > > very
> > > > > high
> > > > > > > N's).
> > > > > > >
> > > > > > > The value, to me in that model, is that it is a
training
> tool
> > > > > that
> > > > > > > conditioned me to accept variance as 'normal' and if the
> > > market
> > > > > is
> > > > > > > stationary then it would have direct relevance to
> > > trading.....
> > > > > the
> > > > > > > worst case outcome would be that I could incur losses,
> with a
> > > > > > > probability as indicated by the Cumulative Distrubution
> > > > Function
> > > > > > for
> > > > > > > the possible equity outcomes (simulation is one way for
> non -
> > > > > > > mathematicians to calc this and view it in a chart).
> > > > > > >
> > > > > > >
> > > > > > > Ask yourself ....
> > > > > > >
> > > > > > > afer you have conducted a successful OOS, and collated
the
> > > > trade
> > > > > > > sample, when you start to trade it do you expect:
> > > > > > >
> > > > > > > - all trades to be the same, or similar, and occur with
> the
> > > > same
> > > > > > > frequency (TradeSim),
> > > > > > > - all trades to be the same, or similar, and have
> variations
> > > in
> > > > > the
> > > > > > > frequency (MSA),
> > > > > > > - something else?
> > > > > > >
> > > > > > > Trading, however, is not a coin toss.
> > > > > > >
> > > > > > > It is more like a sample generator that produces trades
> as a
> > > > > result
> > > > > > > of presenting dynamic data to the system (filter).
> > > > > > >
> > > > > > > To what extent could a 'real life' trading system
emulate
> a
> > > > coin
> > > > > > > toss, with variable values ... how could that come
about?
> > > > > > >
> > > > > > > (interesting that the very functional optF formula came
> about
> > > > as
> > > > > > the
> > > > > > > variable value coin toss staking formula).
> > > > > > >
> > > > > > > Is it possible or not?
> > > > > > >
> > > > > > > A lot of people seem to think it is, judging by their
> books
> > > and
> > > > > > > software.
> > > > > > >
> > > > > > > Presumably, when the underlying data changes, the sample
> > > > profile
> > > > > > > (mean, StDev etc) can change and we end up with a
better
> or
> > > > worse
> > > > > > > outcome than anticipated by the OOS.
> > > > > > >
> > > > > > > So, does the non-stationary behaviour of the markets
> > > invalidate
> > > > > the
> > > > > > > coin toss model?
> > > > > > >
> > > > > > > That is the ineresting question, and I don't know the
> answer
> > > to
> > > > > it,
> > > > > > > or even if there is a definite answer.
> > > > > > >
> > > > > > > I was hopeful that people would pick up on that key
point
> and
> > > > > shed
> > > > > > > some light on the subject.
> > > > > > >
> > > > > > > I know, from my long hours of simulating random data,
what
> > > > random
> > > > > > > behaviour looks like when I see it.
> > > > > > >
> > > > > > > Clearly the markets have a certain amount of random
> behaviour.
> > > > > > >
> > > > > > > Howard commented somewhere, or another, that there is a
> > > certain
> > > > > > > amount of randomness in the market (I can't recall the
> method
> > > > he
> > > > > > used
> > > > > > > to measure it).
> > > > > > >
> > > > > > > It is quite easy to observe if data has any random
> qualities,
> > > > > > > especially if we measure the core attributes (50/50
heads
> and
> > > > > tails
> > > > > > > and its persistence into 2,3,4 heads in a row etc).
> > > > > > >
> > > > > > > Once again I ask you to consider:
> > > > > > >
> > > > > > > if I measure the S&P500 index, on close, and it goes up
> > > approx
> > > > 50
> > > > > > and
> > > > > > > down approx 50 (+- variance that is typical of a random
> > > > binomial
> > > > > > > event) and the subsequent second head or tail follow
with
> 0.5
> > > > > prob
> > > > > > > etc I am justified in considering it top be a pseudo
> random
> > > > > > binomail
> > > > > > > event?
> > > > > > >
> > > > > > > I have done quick and dirty measurements, and accurate
> > > > > > measurements,
> > > > > > > on dependency (or on its inverse, which is
independency)
> and
> > > > find
> > > > > > > that there is a good deal of independency in the
markets
> (I
> > > > > posted
> > > > > > > some q&d code to measure that last week).
> > > > > > >
> > > > > > > I have speculated before, on the point, that the
rational
> > > > market
> > > > > is
> > > > > > > the market that follows fundamental value, which tends
to
> be
> > > >=
> > > > > the
> > > > > > > yearly (macro) timeframe, and, everything else is the
> > > > irrational
> > > > > > > market.
> > > > > > >
> > > > > > > Consider an intraday market ... what is rational about
the
> > > > price
> > > > > > > movement during any given part of the day?
> > > > > > >
> > > > > > > - Draw a trend line on the chart .. we will assume that
we
> > > know
> > > > > > what
> > > > > > > a trend is for this exercise, although that is a
debatable
> > > > point.
> > > > > > >
> > > > > > > - The trend, a straight line, is rational (it is
perfectly
> > > > > > following
> > > > > > > fundamental value).... it is 2007 and it is up ;-)
> > > > > > >
> > > > > > > - All of the ups and downs that occur around it are
> > > irrational
> > > > > > > (bucking the trend).
> > > > > > >
> > > > > > > - The trend line goes under the pivot lows.
> > > > > > >
> > > > > > > - Your system buys at the pivot lows and sells at = = 2
> StDev
> > > > > above
> > > > > > > the trend line.
> > > > > > >
> > > > > > > - Place a stop under the trend line at - 1 stDev.
> > > > > > >
> > > > > > > - Assume no commission and no slippage.
> > > > > > >
> > > > > > > - Your payoff ratio is 2/1
> > > > > > >
> > > > > > > - assume there is no variance in volatility so the PR
is a
> > > > > constant
> > > > > > > value
> > > > > > >
> > > > > > > - the win/loss ratio is determined by the random
> meandering
> > > of
> > > > > the
> > > > > > > irrational price movements up and down.
> > > > > > >
> > > > > > > Note they are irrational because people are buying and
> > > selling
> > > > at
> > > > > > the
> > > > > > > wrong time and for the wrong reasons - if they were
> rational
> > > > they
> > > > > > > would only be buying selling as fundamental values
change.
> > > > > > >
> > > > > > > - the trade series produced would look exactly that that
> > > > produced
> > > > > > by
> > > > > > > a coin tossed with +2, -1 value on it.
> > > > > > >
> > > > > > > Now, you have tested this system, OOS, and it is a
winner.
> > > > > > >
> > > > > > > What chance for stationarity when you trade live?
> > > > > > >
> > > > > > > If the trend continues there is a very good chance that
> the
> > > > > random
> > > > > > > emualator (system meeting dynamic data) will continue to
> > > > perform
> > > > > > like
> > > > > > > a biased coin +- variance i.e. the payoff ratio can't
> change
> > > > but
> > > > > > the
> > > > > > > W/L will (it always does when I toss a coin).
> > > > > > >
> > > > > > > If the trend changes your winning model will be more
> likely
> > > to
> > > > > bust.
> > > > > > >
> > > > > > > That could be the reason Fred, and others, like to
> > > continually
> > > > > > retest.
> > > > > > >
> > > > > > > I have another approach to getting around this problem
> (this
> > > is
> > > > > > > actually the real point of my posts) ...
> > > > > > >
> > > > > > > ..... to accomodate non-stationarity either adjust
> quickly OR
> > > > use
> > > > > a
> > > > > > > dimensionless model e.g. don't believe in trends and
then
> you
> > > > > can't
> > > > > > > be on the wrong side of them.
> > > > > > >
> > > > > > >
> > > > > > >
> > > > > > > However, that is only speculation.
> > > > > > >
> > > > > > > What do you think?
> > > > > > >
> > > > > > >
> > > > > > > Again ... what is the relevance of coin tosses to
trading
> IMO:
> > > > > > >
> > > > > > >
> > > > > > > - wonderful training tool
> > > > > > > - a good OOS can not predict exactly what the outcome
of
> live
> > > > > > trading
> > > > > > > will be (subject to nonstationarity) and neither can
> > > simulation
> > > > > > (coin
> > > > > > > tossing) but it gives a good approximation of the
> > > possibilities
> > > > > > (also
> > > > > > > subject to non-stationarity).
> > > > > > >
> > > > > > > As a quid pro quo .....
> > > > > > >
> > > > > > > ..... if you, or anyone else, can give me any
explanation
> > > > and/or
> > > > > > > proof that the coin toss metaphor has no relevance to
> trading
> > > I
> > > > > > would
> > > > > > > be delighted.
> > > > > > >
> > > > > > >
> > > > > > > Anyway, I think Patrick already answered the question,
or
> > > told
> > > > us
> > > > > > > where to find it.
> > > > > > >
> > > > > > > Good luck with your trading.
> > > > > > >
> > > > > > > brian_zzzzzzzzzzzzzzzzzzzzzzzzzzzzzzz
> > > > > > >
> > > > > > >
> > > > > > > --- In
amibroker@xxxxxxxxxxxxxxx <amibroker%
>
40yahoogroups.com>,
> > > "Phsst" <phsst@> wrote:
> > > > > > > >
> > > > > > > > Hello Brian,
> > > > > > > >
> > > > > > > > Thanks for the mention in your New Years post. I felt
> > > > humbled
> > > > > to
> > > > > > > be in
> > > > > > > > the same honerable mention list as Fred (He is a very
> smart
> > > > > Dude
> > > > > > (no
> > > > > > > > kidding!)) It took me a while (some years back) to
> figure
> > > out
> > > > > > what a
> > > > > > > > smart guy Fred really is. I've since learned that
when
> Fred
> > > > > > speaks,
> > > > > > > it
> > > > > > > > pays to think and be silent for a good long while
before
> > > > > drawing
> > > > > > any
> > > > > > > > conclusions.
> > > > > > > >
> > > > > > > > To your "crystal clear" point... This is the second
> time in
> > > > the
> > > > > > > past few
> > > > > > > > days that you seem to have equated trading/backtesting
> > > system
> > > > > > > outcomes
> > > > > > > > to a random series of coin flip outcomes (random
binary
> > > > > > occurances).
> > > > > > > >
> > > > > > > > Serious question... what is your point? What is the
> > > > relevence
> > > > > os
> > > > > > > the
> > > > > > > > "Coin Flip" metaphor where trading systems is
concerned?
> > > > What
> > > > > am
> > > > > > I
> > > > > > > > missing?
> > > > > > > >
> > > > > > > > Your Bud... Phsst
> > > > > > > >
> > > > > > > >
> > > > > > > >
> > > > > > > > This is the second time
> > > > > > > > --- In
amibroker@xxxxxxxxxxxxxxx <amibroker%
>
40yahoogroups.com>,
> > > "brian_z111"
> > > <brian_z111@>
> > > > > > wrote:
> > > > > > > > >
> > > > > > > > > To be chrystal clear about my hypothesis:
> > > > > > > > >
> > > > > > > > >
> > > > > > > > > We are trying to design a system that produces the
> same
> > > set
> > > > of
> > > > > > > > > trades, in the future, as it has in the past i.e
> trades
> > > and
> > > > > not
> > > > > > > > > combinations of trades.
> > > > > > > > >
> > > > > > > > > If a solid gold coin, minted by the US treasury,
with
> a
> > > > head
> > > > > > and a
> > > > > > > > > tail clearly stamped on each side, and only two
> values +1
> > > > or -
> > > > > 1
> > > > > > > can't
> > > > > > > > > reproduce two equity curves that look the same,
after
> N
> > > > > tosses,
> > > > > > > how
> > > > > > > > > can we expect a trading system to do that when it
has
> a
> > > > range
> > > > > of
> > > > > > > > > possible values?
> > > > > > > > >
> > > > > > > > > AND it doesn't get any better as N increases.
> > > > > > > > >
> > > > > > > > > Put your time and effort into maximising the
STABILITY
> > > > > > > > > (predictability, boundness) of the trade set 'with
an
> > > edge'
> > > > > > THEN
> > > > > > > use
> > > > > > > > > MM to optimise the equity outcome the system
produces
> > > > > (optimise
> > > > > > ==
> > > > > > > > > your definition e.g. max return, min risk or
> whatever).
> > > > > > > > >
> > > > > > > > >
> > > > > > > > >
> > > > > > > > >
> > > > > > > > > --- In
amibroker@xxxxxxxxxxxxxxx <amibroker%
>
40yahoogroups.com>,
> > > "brian_z111"
> > > brian_z111@
> > > > > > wrote:
> > > > > > > > > >
> > > > > > > > > > Howard,
> > > > > > > > > >
> > > > > > > > > > Thanks for your post.
> > > > > > > > > >
> > > > > > > > > > A very well written article.
> > > > > > > > > >
> > > > > > > > > > Some contrary comment (first referencing some of
> your
> > > > > points
> > > > > > and
> > > > > > > > > > then, later, some comments of my own):
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > > > By trying many
> > > > > > > > > > > combinations of logic and parameter values, we
> will
> > > > > > eventually
> > > > > > > > > find
> > > > > > > > > > >a system that is profitable for the date range
> > > analyzed.
> > > > > > > > > >
> > > > > > > > > > You are assuming that all successful long term
> traders
> > > > > > arrived
> > > > > > > at
> > > > > > > > > > their system(s) by using this approach ... perhaps
> > > there
> > > > > are
> > > > > > > > > systems
> > > > > > > > > > out there that have no optimiseable parameters
and
> only
> > > > one
> > > > > > > > > > underlying logic.
> > > > > > > > > >
> > > > > > > > > > If so they are likely be based on primal market
> > > behaviour
> > > > > and
> > > > > > > > > > therefore persistent across markets and time i.e
> they
> > > > would
> > > > > > > have to
> > > > > > > > > > be systems based on market characteristics that
are
> > > > > relatively
> > > > > > > > > > stationary.
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > > > testing the
> > > > > > > > > > > profitability of a trading system that was
> developed
> > > > > using
> > > > > > > recent
> > > > > > > > > > >data
> > > > > > > > > > > on older data is guaranteed to over-estimate the
> > > > > > > profitability of
> > > > > > > > > > the
> > > > > > > > > > > trading system.
> > > > > > > > > >
> > > > > > > > > > You know that in science (philosophy/logic) it
only
> > > takes
> > > > > one
> > > > > > > > > > refutation to dethrone the current ruling
> hypothesis ...
> > > > > > > > > >
> > > > > > > > > > if a long system, developed on the last 12 months
of
> > > data
> > > > > > (when
> > > > > > > the
> > > > > > > > > > market was experiencing a bear riot) is then
tested
> OOS
> > > > on
> > > > > the
> > > > > > > > > prior
> > > > > > > > > > years data it will outperform the in sample tests
> (OOS
> > > > > would
> > > > > > be
> > > > > > > > > > conducted on bull market data).
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > > > There is very little reason to expect that
future
> > > > > behavior
> > > > > > and
> > > > > > > > > > > profitability of well known trading systems
will
> be
> > > the
> > > > > > same
> > > > > > > as
> > > > > > > > > past
> > > > > > > > > > > behavior.
> > > > > > > > > >
> > > > > > > > > > Do we have any empirical evidence of this?
> > > > > > > > > >
> > > > > > > > > > First we would have to have an agreed definition
> > > of 'well
> > > > > > > known',
> > > > > > > > > > make a list of the systems, and then perform
massive
> > > > > testing.
> > > > > > > > > >
> > > > > > > > > > To scrupulously prevent any bias creeping testing
> would
> > > > > have
> > > > > > to
> > > > > > > be
> > > > > > > > > > conducted live, and not on historical data.
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > > We only know that they were successful 'in the
> past' by
> > > > IS
> > > > > > > testing,
> > > > > > > > > > or by claim.
> > > > > > > > > >
> > > > > > > > > > Do we have any, or many, certified performance
> records
> > > > > > provided
> > > > > > > by
> > > > > > > > > > traders who claim to have had success with
> those 'well
> > > > > known'
> > > > > > > > > systems.
> > > > > > > > > >
> > > > > > > > > > > Statistics gathered from in-sample results have
> > > > > > > > > > > no relationship to statistics that will be
> gathered
> > > > from
> > > > > > > trading.
> > > > > > > > > >
> > > > > > > > > > Not, so.
> > > > > > > > > >
> > > > > > > > > > They have every bearing on the stats gathered in
> > > trading
> > > > > > because
> > > > > > > > > only
> > > > > > > > > > systems with good IS performance make it to the
OS,
> or
> > > > live
> > > > > > > > > trading,
> > > > > > > > > > phase.
> > > > > > > > > >
> > > > > > > > > > OOS testing is only proceeded with because the
> analyst
> > > > has
> > > > > > every
> > > > > > > > > > expectation, or hope, that the good IS stats will
be
> > > > > > reproduced
> > > > > > > OOS.
> > > > > > > > > >
> > > > > > > > > > In fact it is the relative performance between
the
> IS
> > > and
> > > > > OOS
> > > > > > > stats
> > > > > > > > > > the encourages us to proceed or abort.
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > > Re trading the edge erodes the edge:
> > > > > > > > > >
> > > > > > > > > > It is an assumption that all players are trading
> > > > > systems ...
> > > > > > > many
> > > > > > > > > are
> > > > > > > > > > not, in fact the vast majority are not.... those
who
> > > > aren't
> > > > > > > control
> > > > > > > > > > vastly greater sums of money than those who do.
> > > > > > > > > >
> > > > > > > > > > It is an assumption that all wins erode the
> system ...
> > > > they
> > > > > > > could
> > > > > > > > > be
> > > > > > > > > > just lucky wins that the trader can't exploit long
> > > term,
> > > > or
> > > > > > > > > > successful wins that the trader doesn't sustain
e.g
> > > they
> > > > > > might
> > > > > > > not
> > > > > > > > > > have the capital, use the correct staking or
> maintain
> > > > self-
> > > > > > > > > discipline
> > > > > > > > > > in the future.
> > > > > > > > > >
> > > > > > > > > > Only a very small percentage of traders are
> successful,
> > > > and
> > > > > > > hence
> > > > > > > > > > trading a successful system ... every one else
who
> is
> > > > > trading
> > > > > > is
> > > > > > > > > just
> > > > > > > > > > making noise.
> > > > > > > > > >
> > > > > > > > > > There are millions of system permutations,
> instruments,
> > > > > > markets,
> > > > > > > > > > staking systems etc ..... how many successful
> traders
> > > > would
> > > > > > it
> > > > > > > take
> > > > > > > > > > to exahaust all of the successful permutations?
> > > > > > > > > >
> > > > > > > > > > > The follow-on point, which relates to Monte
Carlo
> > > > > analysis,
> > > > > > is
> > > > > > > > > that
> > > > > > > > > > > rearranging the in-sample trades gives no
insight
> > > into
> > > > > the
> > > > > > > future
> > > > > > > > > > > characteristics of the system. Yes, you can see
> the
> > > > > effect
> > > > > > of
> > > > > > > > > taking
> > > > > > > > > > > the trades in different orders. But why bother?
> They
> > > > are
> > > > > > still
> > > > > > > > > > > in-sample results and still have no value.
> > > > > > > > > >
> > > > > > > > > > If you are engineering an F1 racing car there is
> only
> > > > track
> > > > > > > > > > testing/simulation (99.9 of the time) and racing
> > > > > performance
> > > > > > > (1% of
> > > > > > > > > > the time).
> > > > > > > > > >
> > > > > > > > > > The more information you gather off the track the
> more
> > > > > likely
> > > > > > > you
> > > > > > > > > are
> > > > > > > > > > to perform on the track OR know what to adjust
and
> when
> > > > to
> > > > > > > adjust
> > > > > > > > > it
> > > > > > > > > > if performance doesn't meet expectations.
> > > > > > > > > >
> > > > > > > > > > Do you know of any F1 teams that don't
> test/simulate?
> > > > > > > > > >
> > > > > > > > > > Do you know of any F1 teams that only
test/simulate
> > > one,
> > > > or
> > > > > > > > > limited,
> > > > > > > > > > metrics?
> > > > > > > > > >
> > > > > > > > > > What is testing if not 'massive examination of
what-
> if
> > > > > > > scenarios'?
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > > Re MonteCarlo and stationarity
> > > > > > > > > >
> > > > > > > > > > I haven't studied the subject in depth.
> > > > > > > > > >
> > > > > > > > > > Mainly it is has been used outside of trading and
in
> > > > > > different
> > > > > > > ways
> > > > > > > > > > to the ways that traders use it .... possibly it
> would
> > > > be
> > > > > > best
> > > > > > > to
> > > > > > > > > > limit trading discussion to 'trading simulation'
and
> > > drop
> > > > > the
> > > > > > MC
> > > > > > > > > part
> > > > > > > > > > of the name.
> > > > > > > > > >
> > > > > > > > > > I have only found one book devoted to the subject
> and I
> > > > > regret
> > > > > > > > > buying
> > > > > > > > > > it .... 'MCS and System Trading' by Volker
Butzlaff.
> > > > > > > > > >
> > > > > > > > > > I have also test driven TradeSim and MSA.
> > > > > > > > > >
> > > > > > > > > > Referencing their trading apps.
> > > > > > > > > >
> > > > > > > > > > TS arranges the trades, as a time series, and
> randomly
> > > > > walks
> > > > > > > > > through
> > > > > > > > > > all permutations to simulate 'live trading'.....
it
> is
> > > an
> > > > > MM
> > > > > > > test,
> > > > > > > > > of
> > > > > > > > > > some kind, because equity is allocated prior to
the
> > > walk
> > > > > > > through.
> > > > > > > > > >
> > > > > > > > > > AB's backtester, in default mode, does this once.
> > > > > > > > > >
> > > > > > > > > > I assume other methods could be used ... as per my
> > > > pervious
> > > > > > XYZ
> > > > > > > > > > example:
> > > > > > > > > >
> > > > > > > > > > - abcXdefghi with simultaneous trades on day 4,
> > > > > > > > > > - we can only achieve a finite set of
permutations,
> > > > > > > > > > - the outcome of massive sampling will tend to
the
> mean
> > > +-
> > > >
> > > > > > > variance,
> > > > > > > > > > - we can simulate the eq outcomes using random
> sampling
> > > > of
> > > > > > > uniform
> > > > > > > > > > size, ave the result per random series and then
freq
> > > dist
> > > > > the
> > > > > > > means
> > > > > > > > > > (Central Limit Theoreom predicts a pseudo norm
> dist).
> > > > > > > > > > > 30 selections per series * ? series will
achieve
> an
> > > > > approx
> > > > > > of
> > > > > > > > > > possible eq outcomes (I'm not sure if
distrubtions
> obey
> > > > the
> > > > > > > laws of
> > > > > > > > > > sample error ... I don't think they do).
> > > > > > > > > >
> > > > > > > > > > TradeSims real life simulation assumes
stationarity
> > > (the
> > > > > > balls
> > > > > > > in
> > > > > > > > > the
> > > > > > > > > > bin, and their values will remain constant into
the
> > > > future).
> > > > > > > > > >
> > > > > > > > > > It also assumes that they will be selected from
the
> bin
> > > > in
> > > > > > the
> > > > > > > same
> > > > > > > > > > order, or frequency to be absolutely correct (the
> order
> > > > > > doesn't
> > > > > > > > > > change anything only the frequency).... to be
> precise
> > > > about
> > > > > > it,
> > > > > > > > > their
> > > > > > > > > > model assumes that if you have picked the worst
> > > > historical
> > > > > > loss
> > > > > > > out
> > > > > > > > > > of the bin 2/1000 trades that you will not only
> > > > experience
> > > > > > the
> > > > > > > same
> > > > > > > > > %
> > > > > > > > > > as the worst loss in the future but that it will
> also
> > > > only
> > > > > > occur
> > > > > > > > > > 2/1000 times.
> > > > > > > > > >
> > > > > > > > > > MSA puts all of the balls in the bin and selects
> them
> > > in
> > > > a
> > > > > > way
> > > > > > > that
> > > > > > > > > > allows new combinations (frequencies) until all
> possible
> > > > > > > > > frequencies
> > > > > > > > > > are exhausted i.e. they assume stationarity only
in
> > > > values
> > > > > > but
> > > > > > > not
> > > > > > > > > > frequency of dist (they assume dist is a
probability
> > > > > > statement
> > > > > > > and
> > > > > > > > > > not a constant or series of constants).... to be
> > > precise
> > > > > > about
> > > > > > > it
> > > > > > > > > > they assume that if it can happen it will.
> > > > > > > > > >
> > > > > > > > > > So, stationarity is the issue.
> > > > > > > > > >
> > > > > > > > > > So many people are confusing variance with non-
> > > > > > stationarity ....
> > > > > > > > > they
> > > > > > > > > > are being fooled by randomness e.g.
> > > > > > > > > >
> > > > > > > > > > we know that the trial records of fair coin
tosses
> are
> > > > > > > stationary
> > > > > > > > > AND
> > > > > > > > > > they have a surprising range of outcomes
> (variance) ...
> > > > > this
> > > > > > is
> > > > > > > > > very
> > > > > > > > > > easy to see if simulated and expressed as equity
> > > outcomes.
> > > > > > > > > >
> > > > > > > > > > Therefore, in trading, we can, at the least
expect a
> > > > > > tremendous
> > > > > > > > > > amount of variance ... no less than what can be
> > > expected
> > > > > from
> > > > > > a
> > > > > > > > > coin
> > > > > > > > > > toss experiment ... this variance can be estimated
> > > using
> > > > > > several
> > > > > > > > > > methods, simulation being one easy, push the
> computer
> > > > > button
> > > > > > and
> > > > > > > > > look
> > > > > > > > > > at the graph method.
> > > > > > > > > >
> > > > > > > > > > So, the value of the simulation is in training
the
> mind
> > > > to
> > > > > > > accept
> > > > > > > > > > variance and mentally prepare for the worst case
> losses.
> > > > > > > > > >
> > > > > > > > > > However, it doesn't matter how we design our
> systems we
> > > > can
> > > > > > not
> > > > > > > do
> > > > > > > > > > anything about stopping non-stationarity.
> > > > > > > > > >
> > > > > > > > > > Our system will get wiped out in OOS if it is not
> > > robust
> > > > OR
> > > > > > if
> > > > > > > the
> > > > > > > > > > market changes.
> > > > > > > > > >
> > > > > > > > > > If our system is robust it will still get wiped
out
> if
> > > > the
> > > > > > > market
> > > > > > > > > > changes.
> > > > > > > > > >
> > > > > > > > > > However, IMO, non-stationarity is not, or need
not
> be,
> > > as
> > > > > > > pervasive
> > > > > > > > > > in trading as we think.
> > > > > > > > > >
> > > > > > > > > > As I have said in the past, and already in this
> > > post ...
> > > > > many
> > > > > > > > > traders
> > > > > > > > > > are slayed by the innocuous looking Black Swan,
> because
> > > of
> > > > > > > > > ignorance
> > > > > > > > > > about its behaviours.
> > > > > > > > > >
> > > > > > > > > > Also, we are very lucky, in trading, to be able
to
> have
> > > > some
> > > > > > > > > control
> > > > > > > > > > over our dataset i.e. our sample space is bounded
by
> > > our
> > > > > > stops
> > > > > > > and
> > > > > > > > > > other inherent factors in the design.
> > > > > > > > > >
> > > > > > > > > > Example:
> > > > > > > > > >
> > > > > > > > > > If we have a stop in place then we are reasonably
> > > > unlikely
> > > > > to
> > > > > > > > > > experience losses beyond the stop + commission +
> > > > > > slippage ....
> > > > > > > when
> > > > > > > > > a
> > > > > > > > > > stop failure does occur it is very infrequent and
> not
> > > > > > > necessarily
> > > > > > > > > > career destroying.
> > > > > > > > > >
> > > > > > > > > > When we have a profit stop in place we can expect
> to at
> > > > > least
> > > > > > > get
> > > > > > > > > the
> > > > > > > > > > stop OR BETTER.
> > > > > > > > > >
> > > > > > > > > > We can also, in some circumstances, buy a
guaranteed
> > > stop
> > > > > > loss.
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > > In summary:
> > > > > > > > > >
> > > > > > > > > > Because, as traders, we are statistically lucky,
we
> can
> > > > > > choose,
> > > > > > > to
> > > > > > > > > > some extent, which marbles to put in the bin.
> > > > > > > > > >
> > > > > > > > > > We can absolutely limit the worst case, ensure we
> get
> > > at
> > > > > > least
> > > > > > > the
> > > > > > > > > > best case and then take everything in between that
> > > comes
> > > > > > along.
> > > > > > > > > >
> > > > > > > > > > Since the boundaries are limited, the range of
> possible
> > > > > > values
> > > > > > > on
> > > > > > > > > the
> > > > > > > > > > balls is finite and will always be normally
> > > distributed,
> > > > > when
> > > > > > > > > > expressed as possible mean P & L (central limit
> > > > > > theoreom).....
> > > > > > > the
> > > > > > > > > > staging post on the trail towards possible equity
> > > > outcomes.
> > > > > > > > > >
> > > > > > > > > > I think under those circumstances that the balls
in
> the
> > > > > > bucket,
> > > > > > > > > > collected over a long sample, are a pretty fair
> > > > > > representation
> > > > > > > of
> > > > > > > > > > what we can expect in the future.
> > > > > > > > > >
> > > > > > > > > > If they are not then we only have ourselves to
blame
> > > for
> > > > > our
> > > > > > > poor
> > > > > > > > > > system design.
> > > > > > > > > >
> > > > > > > > > > Nothing anyone can do, can put an end to
stockmarket
> > > non-
> > > > > > > > > stationarity
> > > > > > > > > > but the challenge for the trader is to find ways
to
> > > > either
> > > > > > > absorb
> > > > > > > > > it
> > > > > > > > > > or anticipate it.
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > > One important point was absent from your post.
> > > > > > > > > >
> > > > > > > > > > Kelly and Vince et al have proved conclusively
that
> > > > staking
> > > > > > > > > directly
> > > > > > > > > > and remarkably affects outcomes.
> > > > > > > > > >
> > > > > > > > > > Based on that fact I can't understand why you,
and
> many
> > > > > other
> > > > > > > > > > commentators, continue to draw inferences from
> > > backtests
> > > > > that
> > > > > > > > > include
> > > > > > > > > > a limited range of portfolio allocations ...
either
> > > don't
> > > > > > > involve
> > > > > > > > > eq
> > > > > > > > > > at all OR test across all possible eq allocations.
> > > > > > > > > >
> > > > > > > > > > (if you do opt for the latter choice wouldn't it
be
> > > > smarter
> > > > > > to
> > > > > > > do
> > > > > > > > > > that using the short mathematical solution rather
> than
> > > > the
> > > > > > long
> > > > > > > > > > massive optimisation approach?).
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > > The babblers epilogue:
> > > > > > > > > >
> > > > > > > > > > I guess it is appropriate that an informal book
> should
> > > > have
> > > > > an
> > > > > > > > > > informal ending!
> > > > > > > > > >
> > > > > > > > > > "Always look on the bright side of life" ...
> > > > > > > > > >
> > > > > > > > > > ... from the life of Brian :-)
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > >
> > > > > > > > > > --- In
amibroker@xxxxxxxxxxxxxxx<amibroker%
>
40yahoogroups.com>,
> > > "Howard Bandy"
> > > > > > <howardbandy@>
> > > > > > > > > > wrote:
> > > > > > > > > > >
> > > > > > > > > > > Greetings all --
> > > > > > > > > > >
> > > > > > > > > > > The posting was originally made by me to Aussie
> Stock
> > > > > > Forums
> > > > > > > on
> > > > > > > > > > > February 2, 2009. But in light of recent
> > > discussions,
> > > > > I'll
> > > > > > > cross
> > > > > > > > > > post
> > > > > > > > > > > it here.
> > > > > > > > > > >
> > > > > > > > > > > Some of my thoughts on using Monte Carlo
> techniques
> > > > with
> > > > > > > trading
> > > > > > > > > > systems.
> > > > > > > > > > >
> > > > > > > > > > > First, some background.
> > > > > > > > > > >
> > > > > > > > > > > Monte Carlo analysis is the application of
> repeated
> > > > random
> > > > > > > > > sampling
> > > > > > > > > > > done in order to learn the characteristics of
the
> > > > process
> > > > > > > being
> > > > > > > > > > studied.
> > > > > > > > > > >
> > > > > > > > > > > Monte Carlo analysis is particularly useful when
> > > closed
> > > > > form
> > > > > > > > > > solutions
> > > > > > > > > > > to the process are not available, or are too
> > > expensive
> > > > to
> > > > > > > carry
> > > > > > > > > out.
> > > > > > > > > > > Even in cases when a formula or algorithm can
> supply
> > > the
> > > > > > > > > information
> > > > > > > > > > > desired, using Monte Carlo analysis can often
be
> used.
> > > > > > > > > > >
> > > > > > > > > > > Here is an example of Monte Carlo analysis.
Assume
> > > that
> > > > a
> > > > > > > student
> > > > > > > > > is
> > > > > > > > > > > unaware of the formula that relates the area of
a
> > > > circle
> > > > > to
> > > > > > > its
> > > > > > > > > > > diameter. A Monte Carlo solution is to
> conceptually
> > > > draw
> > > > > a
> > > > > > > square
> > > > > > > > > > with
> > > > > > > > > > > sides each one unit in length on a graph, with
the
> > > > origin
> > > > > > at
> > > > > > > the
> > > > > > > > > > lower
> > > > > > > > > > > left corner. The horizontal side goes from 0.0
to
> 1.0
> > > > > along
> > > > > > > the x-
> > > > > > > > > > axis
> > > > > > > > > > > and the vertical side goes from 0.0 to 1.0
along
> the
> > > y-
> > > > > > axis.
> > > > > > > Draw
> > > > > > > > > a
> > > > > > > > > > > circle with a diameter of one unit inside the
> square.
> > > > The
> > > > > > > center
> > > > > > > > > of
> > > > > > > > > > > the circle will be at coordinates 0.5, 0.5. The
> Monte
> > > > > Carlo
> > > > > > > > > process
> > > > > > > > > > to
> > > > > > > > > > > compute the area of the circle is to generate
many
> > > > random
> > > > > > > points
> > > > > > > > > > > inside the square (each point a pair of number
> with
> > > the
> > > > > > > values of
> > > > > > > > > > the
> > > > > > > > > > > x-coordinate and y-coordinate being drawn from a
> > > uniform
> > > > > > > > > > distribution
> > > > > > > > > > > between 0.0 and 0.999999), then count the
number
> of
> > > > those
> > > > > > > points
> > > > > > > > > > that
> > > > > > > > > > > are also inside the circle. The ratio between
the
> > > > number
> > > > > of
> > > > > > > points
> > > > > > > > > > > inside the circle to the number of points drawn
> gives
> > > > an
> > > > > > > estimate
> > > > > > > > > of
> > > > > > > > > > > the constant pi. Running this experiment several
> > > times,
> > > > > > each
> > > > > > > using
> > > > > > > > > > > many random points, allows application of
> statistical
> > > > > > analysis
> > > > > > > > > > > techniques to estimate the value of pi to
within
> some
> > > > > > probable
> > > > > > > > > > > uncertainty. The process being studied in that
> > > example
> > > > is
> > > > > > > > > > stationary.
> > > > > > > > > > > The relationship between the area of the circle
> and
> > > the
> > > > > > area
> > > > > > > of
> > > > > > > > > the
> > > > > > > > > > > square is always the same.
> > > > > > > > > > >
> > > > > > > > > > > When we are developing trading systems, the
> ultimate
> > > > > > question
> > > > > > > we
> > > > > > > > > are
> > > > > > > > > > > most often asking is "What is the future
> performance
> > > of
> > > > > this
> > > > > > > > > trading
> > > > > > > > > > > system?" Recall that the measure of goodness of
a
> > > > trading
> > > > > > > system
> > > > > > > > > is
> > > > > > > > > > > your own personal (or corporate) choice. Some
> people
> > > > want
> > > > > > > highest
> > > > > > > > > > > compounded annual return with little regard for
> > > > drawdown.
> > > > > > > Others
> > > > > > > > > > value
> > > > > > > > > > > systems that have low drawdown, or infrequent
> > > trading,
> > > > or
> > > > > > > whatever
> > > > > > > > > > > else may be important. But, in all cases, the
> goal is
> > > > to
> > > > > > have
> > > > > > > the
> > > > > > > > > > > trading system be profitable. Assume that many
of
> us
> > > > are
> > > > > > > trading a
> > > > > > > > > > > single issue over a period of several years,
and
> that
> > > > the
> > > > > > > price
> > > > > > > > > per
> > > > > > > > > > > share at the end of that period is the same as
it
> was
> > > > at
> > > > > the
> > > > > > > > > > beginning
> > > > > > > > > > > of the period, with significant price
variations
> in
> > > > > > between.
> > > > > > > If we
> > > > > > > > > > > ignore frictional costs -- the bid - ask spread
of
> > > the
> > > > > > market
> > > > > > > > > maker
> > > > > > > > > > > and the commission of the broker -- we are
> playing a
> > > > zero-
> > > > > > sum
> > > > > > > > > game.
> > > > > > > > > > > Those of us who make money are taking it from
> those
> > > who
> > > > > lose
> > > > > > > > > money.
> > > > > > > > > > > If, instead of the final price being the same
as
> the
> > > > > > beginning
> > > > > > > > > > price,
> > > > > > > > > > > the final price is higher, then the price has an
> > > upward
> > > > > > bias
> > > > > > > and
> > > > > > > > > > more
> > > > > > > > > > > money is made than lost. This is when we all
get
> to
> > > > claim
> > > > > > it
> > > > > > > was
> > > > > > > > > our
> > > > > > > > > > > cleverness that made us money. If the final
price
> is
> > > > > lower,
> > > > > > > the
> > > > > > > > > > price
> > > > > > > > > > > has a downward bias and more money is lost than
> made.
> > > > > > > > > > >
> > > > > > > > > > > The price data for the period we are trading
has
> two
> > > > > > > components.
> > > > > > > > > One
> > > > > > > > > > > is the information contained in the data that
> > > > represents
> > > > > the
> > > > > > > > > reason
> > > > > > > > > > > the price changes -- the signal component. The
> other
> > > is
> > > > > > > > > everything
> > > > > > > > > > we
> > > > > > > > > > > cannot identify profitably -- the noise
component.
> > > Note
> > > > > that
> > > > > > > > > there
> > > > > > > > > > may
> > > > > > > > > > > be two (or more) signal components. Say one is
a
> long
> > > > > term
> > > > > > > trend
> > > > > > > > > in
> > > > > > > > > > > profitability of the company, and the price
> follows
> > > > > > > > > profitability.
> > > > > > > > > > Say
> > > > > > > > > > > the other is cyclic price behavior that goes
> through
> > > > two
> > > > > > > complete
> > > > > > > > > > > cycles every month for some unknown but
persistent
> > > > > reason.
> > > > > > In
> > > > > > > > > every
> > > > > > > > > > > financial price series, there is always the
random
> > > > price
> > > > > > > variation
> > > > > > > > > > > that is noise. The historical price data that
we
> see
> > > > > > > consists, in
> > > > > > > > > > this
> > > > > > > > > > > case, of trend plus cycle plus noise. Each
> component
> > > > has a
> > > > > > > > > strength
> > > > > > > > > > > that can be measured. If the signal is strong
> enough,
> > > > > > > relative to
> > > > > > > > > > the
> > > > > > > > > > > noise, our trading system can identify the
signal
> and
> > > > > issue
> > > > > > > buy
> > > > > > > > > and
> > > > > > > > > > > sell signals to us. If our trading system has
> coded
> > > > into
> > > > > it
> > > > > > > logic
> > > > > > > > > > that
> > > > > > > > > > > only recognizes changes in trend, the cycle
> component
> > > > is
> > > > > > > noise as
> > > > > > > > > > seen
> > > > > > > > > > > by that system. That is -- anything that a
trading
> > > > system
> > > > > > > does not
> > > > > > > > > > > identify itself, even though it may have strong
> signal
> > > > > > > > > > characteristics
> > > > > > > > > > > when analyzed in other ways, is noise.
> > > > > > > > > > >
> > > > > > > > > > > Over the recent decades, analysis of financial
> data
> > > has
> > > > > > > progressed
> > > > > > > > > > > from simple techniques applied by a few people
in
> a
> > > few
> > > > > > > markets
> > > > > > > > > > using
> > > > > > > > > > > proprietary tools to sophisticated techniques
> applied
> > > > by
> > > > > > many
> > > > > > > > > people
> > > > > > > > > > > in many markets using tools that are widely
> available
> > > > at
> > > > > low
> > > > > > > > > cost.
> > > > > > > > > > The
> > > > > > > > > > > techniques used successfully by Richard
Donchian
> from
> > > > the
> > > > > > > 1930s,
> > > > > > > > > and
> > > > > > > > > > > Richard Dennis and William Eckhart in the
1980s,
> were
> > > > > > simple.
> > > > > > > To
> > > > > > > > > the
> > > > > > > > > > > extent that the markets they traded did not have
> > > strong
> > > > > > > trends,
> > > > > > > > > > every
> > > > > > > > > > > profitable trade they made was at the expense of
> > > > another
> > > > > > > trader.
> > > > > > > > > > > Today, every person hoping to have a profitable
> > > career
> > > > in
> > > > > > > trading
> > > > > > > > > > > learns about techniques that did work at one
time.
> > > They
> > > > > are
> > > > > > > well
> > > > > > > > > > > documented and are often included in the trading
> > > system
> > > > > > > examples
> > > > > > > > > > when
> > > > > > > > > > > a trading system development platform is
> installed.
> > > > > > > > > > >
> > > > > > > > > > > Assume that a data series is studied over a
given
> > > date
> > > > > > range.
> > > > > > > > > Using
> > > > > > > > > > > hindsight, we can determine the beginning price
> and
> > > the
> > > > > > ending
> > > > > > > > > > price.
> > > > > > > > > > > Continuing with hindsight, we can develop a
> trading
> > > > > system
> > > > > > > that
> > > > > > > > > > > recognizes the signal component -- some
> > > characteristic
> > > > > > about
> > > > > > > the
> > > > > > > > > > data
> > > > > > > > > > > series that anticipates and signals profitable
> > > trades.
> > > > By
> > > > > > > trying
> > > > > > > > > > many
> > > > > > > > > > > combinations of logic and parameter values, we
> will
> > > > > > eventually
> > > > > > > > > find
> > > > > > > > > > a
> > > > > > > > > > > system that is profitable for the date range
> > > analyzed.
> > > > If
> > > > > > we
> > > > > > > are
> > > > > > > > > > lucky
> > > > > > > > > > > or clever, the system recognizes the signal
> portion
> > > of
> > > > > the
> > > > > > > data.
> > > > > > > > > Or,
> > > > > > > > > > > the system may have simply been fit to the
noise.
> The
> > > > > data
> > > > > > > that
> > > > > > > > > was
> > > > > > > > > > > used to develop the system is called the in-
sample
> > > > data.
> > > > > If
> > > > > > > the
> > > > > > > > > > system
> > > > > > > > > > > does recognize the signal and a few of us trade
> that
> > > > > system,
> > > > > > > > > while
> > > > > > > > > > all
> > > > > > > > > > > the rest of the traders make random trades,
those
> of
> > > us
> > > > > who
> > > > > > > trade
> > > > > > > > > > the
> > > > > > > > > > > system will make a profit. On average, the rest
> lose.
> > > > As
> > > > > > more
> > > > > > > and
> > > > > > > > > > more
> > > > > > > > > > > people join us trading the system, each of us
> earns a
> > > > > lower
> > > > > > > > > profit.
> > > > > > > > > > In
> > > > > > > > > > > order to continue trading profitably, we must be
> > > > earlier
> > > > > to
> > > > > > > > > > recognize
> > > > > > > > > > > the signal, or develop better signal recognition
> > > logic
> > > > > and
> > > > > > > trade
> > > > > > > > > > > different signals or lower strength signals. By
> the
> > > > time
> > > > > > the
> > > > > > > date
> > > > > > > > > > > range we have studied has passed, most of the
> profit
> > > > that
> > > > > > > could
> > > > > > > > > have
> > > > > > > > > > > been taken out of that price series using that
> system
> > > > has
> > > > > > been
> > > > > > > > > > taken.
> > > > > > > > > > > Perhaps the future data will continue to carry
the
> > > same
> > > > > > > signal in
> > > > > > > > > > the
> > > > > > > > > > > same strength and some traders will make
> profitable
> > > > > trades
> > > > > > > using
> > > > > > > > > > their
> > > > > > > > > > > techniques, or perhaps that signal changes, or
> > > perhaps
> > > > so
> > > > > > many
> > > > > > > > > > traders
> > > > > > > > > > > are watching that system that the per-trade
profit
> > > does
> > > > > not
> > > > > > > cover
> > > > > > > > > > > frictional costs.
> > > > > > > > > > >
> > > > > > > > > > > Data that was not used during the development
of
> the
> > > > > system
> > > > > > is
> > > > > > > > > > called
> > > > > > > > > > > out-of-sample data. But -- important point --
> testing
> > > > the
> > > > > > > > > > > profitability of a trading system that was
> developed
> > > > > using
> > > > > > > recent
> > > > > > > > > > data
> > > > > > > > > > > on older data is guaranteed to over-estimate the
> > > > > > > profitability of
> > > > > > > > > > the
> > > > > > > > > > > trading system.
> > > > > > > > > > >
> > > > > > > > > > > Financial data is not only time-series data,
but
> it
> > > is
> > > > > also
> > > > > > > > > > > non-stationary. There are many reasons related
to
> > > > > > > profitability of
> > > > > > > > > > > companies and cyclic behavior of economies to
> explain
> > > > why
> > > > > > the
> > > > > > > > > data
> > > > > > > > > > is
> > > > > > > > > > > non-stationary. But -- another important point -
-
> > > every
> > > > > > > profitable
> > > > > > > > > > > trade made increases the degree to which the
data
> is
> > > > non-
> > > > > > > > > stationary.
> > > > > > > > > > > There is very little reason to expect that
future
> > > > > behavior
> > > > > > and
> > > > > > > > > > > profitability of well known trading systems
will
> be
> > > the
> > > > > > same
> > > > > > > as
> > > > > > > > > past
> > > > > > > > > > > behavior.
> > > > > > > > > > >
> > > > > > > > > > > Which brings me to several key points in trading
> > > systems
> > > > > > > > > > development.
> > > > > > > > > > >
> > > > > > > > > > > 1. Use whatever data you want to to develop your
> > > > systems.
> > > > > > All
> > > > > > > of
> > > > > > > > > the
> > > > > > > > > > > data that is used to make decisions about the
> logic
> > > and
> > > > > > > operation
> > > > > > > > > of
> > > > > > > > > > > the system is in-sample data. When the system
> > > > developer --
> > > > >
> > > > > > > that
> > > > > > > > > is
> > > > > > > > > > you
> > > > > > > > > > > and me -- is satisfied that the system might be
> > > > > profitable,
> > > > > > > that
> > > > > > > > > > > conclusion was reached after thorough and
> extensive
> > > > > > > manipulation
> > > > > > > > > of
> > > > > > > > > > > the trading logic until it fits the data. The
in-
> > > sample
> > > > > > > results
> > > > > > > > > are
> > > > > > > > > > > good -- they are Always good -- we do not stop
> > > fooling
> > > > > with
> > > > > > > the
> > > > > > > > > > system
> > > > > > > > > > > until they are good. In-sample results have no
> value
> > > in
> >