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MG - Thanks for your notes; but you strike me as a brainy individual
who must not be trading their own money.. you must be trading "smart"
money.. that is taking risks with other people's money. Your comments
and answers seem somewhat vague and not pointed. When people come
back with negative back test results with what you suggested, you
point them towards a different optimized direction..
Appreciate your insights; but its not for me.. its better for someone
who has to work on their PhD, and not have to put their own real
money on the line..
I am sticking to the basics, trade long when its obvious the trend is
up.. and use moving averages to tell the story ala Supefrag style...
I will certainly keep checking out Elliott waves as I purchased the
AO software; but am in no hurry to jump in.. I think almost every
trade that TG recommended using AGet Elliott waves in the Optionetics
seminar in Detroit last December, went sour. What a rip-off for a
system touted as 70% winning trades.. Enjoyed the Optionetics
classes and learned a lot; but you can't believe most of what people
are preaching when they are also selling.. as they are after all,
selling.
MG - you strike me as very sharp.. so do keeop chipping in to this
forum. Try to be more specific with actual systems you have done and
seen, offering your test results and pls don't lead folks astray..
--- In equismetastock@xxxxxxxxxxxxxxx, "MG Ferreira" <quant@xxxx>
wrote:
>
> Just a few comments. I am certainly not trying to deceive or
> mislead anybody. I have often encouraged you to not take my
> word for a statement, but also gave references to those who
> independantly came to the same conclusion. I am not testing
> the Theta model at the moment, I am submitting it as one technique
> to this group and am awaiting your and others' observations, and
> acting on those already given, trying to fine tune it a bit and to
> see if it makes sense to include in a suite of models. Let us
> together and objectively see if the Theta model works. I suspect
> it will work very well, but, don't take my word for it, let us
see...
>
> Results on the latest 'linregslope' refinement anybody?
>
> In order to do this, your inputs are appreciated and valuable as
well.
> So, if I have in any way offended you, please do not resent me or my
> inputs, and I apologise for my many hasty comments that may have
> offended you.
>
> Now, in terms of optimisation. Let me not address its problems,
> which are many, since you have already spend some time addressing
> those. Let me rather take some time in its defence.
>
> Suppose you start trading today, using the simplest of methods. Say
> you use just a simple moving average and use this crossover of the
> market as a trade signal. Now, if you see that you are not doing
> that well, or if you backtest it and see that it does not work, and
> make even just one adjustment to the length parameter - even just
> one - it can be taken, no matter what the result of this adjustment
> is, as one iteration in an optimisation process. If you test even
> just one alternative model, say using an exponential moving average,
> then you are performing one step in a cross-method optimisation
> process. If you ever play around with indicators, or alter
> parameters, and then 'eye ball' the results, you are busy with
> optimisation.
>
> Suppose you read a certain paper every morning, and look at your
> moving average model every night, and based on these you make a
> decision. Then you are working with a suite of models which you
> aggregate internally, one model quantitative, one qualitative. You
> dynamically assign weights to them, consult them and use them to
> make a decision.
>
> What mathematics bring to the table is ways to externalise this
> process and to objectively play around with model parameters until
> the best one is discovered. There are many pitfalls, but it
certainly
> is neither a foreign nor a malicious process.
>
> Regards
> MG Ferreira
> TsaTsa EOD Programmer and trading model builder
> http://tsatsaeod.ferra4models.com
> http://www.ferra4models.com
>
>
>
>
>
> --- In equismetastock@xxxxxxxxxxxxxxx, "Jose" <josesilva22@xxxx>
wrote:
> >
> >
> > > Mmmmmm, the gloves are coming off it appears.
> >
> > MG, please don't take it personally, but unknowingly or
otherwise, you
> > are leading potential traders up a garden path with your
optimization
> > suggestions. You did it years ago, and you are still doing it
now.
> >
> >
> > > Interesting to note that the site you refer to was cancelled in
the
> > > previous century some time and basically lives on for historical
> > > purposes. I can assure you the weaponry used today are much
more
> > > sophisticated, though it derives from what must have taken you
an
> > > awful lot of time to find on the internet, and for which I have
to
> > > congratulate you!
> >
> > You are probably right - the 25min it took me to find your
information
> > and post a reply to your mail, could have probably been better
spent
> > on something more productive.
> >
> > However, the fact remains that little has changed in your
thinking
> > since the "last century", as you put it:
> >
> > "...and optimise on periods. When this line goes above zero, buy,
and
> > when below, sell. Please let us know the results."
> >
> > Optimization did not work in your ancient webpage, and it still
does
> > not work in the new millennium.
> > Optimization favors past outliers, a favourable performance which
is
> > very unlikely to repeat in the future.
> >
> > Encouraging others to take this path when one should know better,
is
> > misleading to say the least. Dressing it up in irrelevant jargon
does
> > not help either.
> >
> > Enough said on this subject from me.
> >
> >
> > jose '-)
> > http://www.metastocktools.com
> >
> >
> >
> > --- In equismetastock@xxxxxxxxxxxxxxx, "MG Ferreira" <quant@xxxx>
> > wrote:
> > >
> > >
> > > Mmmmmm, the gloves are coming off it appears.
> > >
> > > If I look at the site mentioned, I see a spectral chart used to
> > > illustrate the concept of optimisation of strategies. I see an
> > > example of the space one has to deal with for a simple, cross
> > > over strategy. I don't really care about the trading costs at
> > > this stage, since I am interested in the specific topology I
> > > have to deal with. Dealing costs will be added once I
understand
> > > this, as will proper tests to ensure I am not overfitting and
so on.
> > >
> > > The spectral chart indicates the dangers of just using the
Fibonacci
> > > numbers, very popular at that time for that particular market,
> > > and the benefits that can be obtained by still using a very
simple
> > > strategy but just fine tuning it a bit.
> > >
> > > Interesting to note that the site you refer to was cancelled in
the
> > > previous century some time and basically lives on for historical
> > > purposes. I can assure you the weaponry used today are much
more
> > > sophisticated, though it derives from what must have taken you
an
> > > awful lot of time to find on the internet, and for which I have
to
> > > congratulate you!
> > >
> > > One thing I have to agree with, and, trying to steer this back
to
> > > the Theta model somehow, is that overfitting is dangerous. In
the
> > > Theta model that we utilise, we do not optimise, we simply use
it
> > > with an arbitrary period selection.
> > >
> > > I am well aware of the high volatility in higher frequency
data, but
> > > this does not mean that it can not be used profitably. In a
geared
> > > environment, you often simply do not have the luxury of riding
out a
> > > position for a couple of days. Even if you were spot on say a
week
> > > from now, market movements in the interim may have wiped out
your
> > > margin and closed you out at a huge loss - that will cost you
plenty
> > > a shirt. So sometimes you have to use shorter term data. We
have
> > > tested a variety of series on 5, 10, 15, 30, 60 and 120 and
above
> > > minute bars and, interestingly, many can be traded profitably
at 30
> > > minutes. We thus prefer this bar length when working with
intraday
> > > data.
> > >
> > > Finally, let us try and keep this to the Theta model in
particular
> > > and in general to technical indicators of interest.
> > >
> > > Regards
> > > MG Ferreira
> > > TsaTsa EOD Programmer and trading model builder
> > > http://tsatsaeod.ferra4models.com
> > > http://www.ferra4models.com
> > >
> > > --- In equismetastock@xxxxxxxxxxxxxxx, "Jose"
<josesilva22@xxxx>
> > wrote:
> > >
> > > "...and optimise on periods. When this line goes above zero,
buy,
> > > and when below, sell. Please let us know the results."
> > >
> > > And please don't trade the above, because you are sure to lose
your
> > > shirt on it.
> > >
> > > Whilst it's taken for granted in trading circles that
optimization
> > > to historical data (curve-fitting) very seldom eventuates into
a
> > > profitable strategy in the real world of trading, apparently
this is
> > > not something yet discovered in the theoretical & jargon-laden
quant
> > > world.
> > >
> > > Here is a perfect example of theoretical/optimization modeling
gone
> > > wrong:
> > > http://www.quant.co.za/OptStrat2.html
> > >
> > > Basically, the author claims to have optimized a profitable
trading
> > > strategy based on optimized SMA crossovers (and no transaction
> > > costs), and comes to the naive conclusion that the shorter-term
> > > indicators generate a much higher profit:
> > >
> > > Daily Data (Four Years) 1,335 points total 334 points a
year
> > > Hourly Data (Two Years) 1,380 points total 690 points a
year!
> > >
> > > The problem with the above - as anyone with any basic
backtesting &
> > > trading experience will know - is that short-term trades
generate a
> > > prodigious amount of whipsaw and brokerage/slippage/spread
costs,
> > > turning any theoretical strategy into a real-life losing
strategy.
> > > Both examples above are very likely to produce major losses
once
> > > transaction costs are factored in.
> > >
> > > The above mistaken conclusion could be forgiven if it was the
work
> > > of some inexperienced bright-eyed young system developer
straight
> > > out of school, but the it actually came from someone that
claims a
> > > very impressive CV.
> > >
> > >
> > > In the laboratory-like world of theoretical system optimizing/
> > > modeling, transaction costs and liquidity issues that overwhelm
> > > profits in the real world are often ignored. Numerous essays
and
> > > white papers are written by academics & pseudo-academics each
year,
> > > trying to model a system more complex than the most complex of
> > > weather patterns, yet offering very little insight into the mass
> > > psychology and real-life vagaries of the markets.
> > >
> > > Caveat Emptor.
> > >
> > >
> > > jose '-)
> > > http://www.metastocktools.com
> > >
> > >
> > >
> > > --- In equismetastock@xxxxxxxxxxxxxxx, "MG Ferreira"
<quant@xxxx>
> > > wrote:
> > >
> > > Hi Andrew,
> > >
> > > Let us just backtrack a bit. I noted, when coding the T3 and
IE/2,
> > > that the IE/2 appeared to be similar to the Theta model, which I
> > > know to be a good model. So I did not bother to test it,
assuming
> > > it also to be a good model. The Theta model implementation
provided
> > > is based on what can be done in Metastock in a very short time
span,
> > > and was given on request, and has maybe too many shortcuts in
it.
> > > If anybody has ever tested the IE/2, I think we can safely use
that
> > > as a proxy for the Theta's performance and vice versa.
> > >
> > > Now, since I appear to be the defender of the Theta model. We
(yes,
> > > I happen to be part of a team) use the Theta model extensively
to
> > > prepare short term forecasts of monthly data, such as M3, CPI,
> > > wholesale trade and so on. We use it as part of an array of
models
> > > and we never use the results of just one model, but the Theta
model
> > > shines in this capacity as a good performer and often has a
fairly
> > > large dynamic weight allocated to it. Here performance is
measured
> > > in forecasting accuracy, which usually is a poor indication of
> > > whether it will work in a trading environment.
> > >
> > > But we also use this model, for end-of-day data, in a trading
> > > environment as part of yet again a suite of models. This is
quite
> > > fashionable and dicated by theory as well - using a suite of
models,
> > > and I am in a way recommending this to the group and also
> > > recommending the inclusion of the Theta in such a suite.
> > >
> > > Now, let us not run away from the real point, testing the Theta
> > > model as a singular trading model. I note your observation, as
well
> > > as that of some other members of this group, and can well
believe it
> > > - that the Theta did not perform well when you tested it.
> > >
> > > This is true of prediction models in general, so allow me to
expand
> > > a bit. A good prediction model is supposed to predict where the
> > > market will be in future, say tomorrow. Now, if it is a good
> > > projection model, then it will be unbaised, so that the market
will
> > > be above it about 50% and below it about 50% of the time. The
> > > residual or error for a good model will be random. So if we
use a
> > > prediction model as is, we are trading white noise, and should
not
> > > get good results. So we have to apply our minds a bit. I am
> > > thinking aloud, why is the Theta not performing as I would
expect,
> > > so please bear with me.
> > >
> > > In our trading model, we do use the Theta model's prediction as
well
> > > as its slope. So we extrapolate the model and note the slope of
> > > this extrapolation and we use both in the model. We have noted
that
> > > when the Theta long term line (theta = 0) turns, it often
indicates
> > > a turnaround in trend. This could be a better way to build a
> > > trading model, using the slope of the long term component. The
> > > slope of the extrapolation is in fact half the slope of the long
> > > term component, since the extrapolated short term is constant
and
> > > the Theta is
> > >
> > > ( lt + st ) / 2
> > >
> > > so
> > >
> > > d( lt + st ) / 2 = dlt / 2
> > >
> > > since
> > >
> > > dst = 0
> > >
> > > Another note, we often take the log of the series before we
> > > calculate the slope, but this should not make a big difference
in
> > > many cases.
> > >
> > > Anyhow, try the following test
> > >
> > > linregslope(log(CLOSE),periods)
> > >
> > > and optimise on periods. When this line goes above zero, buy,
and
> > > when below, sell. Please let us know the results.
> > >
> > > Note that the parameter should be on the long side. It should
> > > ideally be above 30 for a number of statistical reasons that I'd
> > > rather avoid for now. I think a good starting point would be 50
> > > days and test up to at least 250.
> > >
> > > Regards
> > > MG Ferreira
> > > TsaTsa EOD Programmer and trading model builder
> > > http://tsatsaeod.ferra4models.com
> > > http://www.ferra4models.com
> > >
> > > PS : I *really* appreciate your opening sentence.
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