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IMO backtesters that combine money management, scaling in and signal
ranking in one step are not using the best, or most efficient method.
On the contrary, this approach can muddy the waters and create
confusion for the user, especially new comers.
It is well known that if piano students do not start by learning the
correct, albeit funNOT techniques, they will almost certainly never
learn to play at advanced levels.... the end justifies the means (and
the high attrition rate).
Collecting all matched buy/sells first is the best approach (as used
by RalphVince and MSA Analyzer) .... sequential or random testing of
MM, scaling in, trade sample space analysis and ranking etc can be
performed, as per user requirements, from the trade matrix, which
afterall is a constant for any constant set of rules and data.
For anyone who is thinking of attempting it privately:
- the system rules i.e. buy/sell/prices/stops etc (not MM rules) need
to be saved with the trade matrices
- when a system is reopened from the historical archive the rules
need to be auto restored to the backtester (exactly as per the
original test)
- versioning would need to be introduced ... if the user adds some
code to the the rules then they need to elect to run it as a new sub-
version (save the matrix/rules separately) OR as a new test that
overwrites the archived trade matrix.
- for optimization a user election would save all matrices and rules
as sub-versions
- scaling in should be treated as a new and different sub-system ....
system 1 = conditional on the set of rules A
scaling in = system 1.1 = conditional on A then apply rule B
.... different combinations of MM rules can then be tested on system
1 + system 1.1 versus system 1 OR system 1.1. to find where the
optimum returns are.
- ranking signals is a challenge ... my first thoughts are that the
ranking indicator would need to be collected with the trade signals
and saved with them.
The careful reader might have noted that this discussion is an
extension of the topic SYSTEM PERFORMANCE INDICATORS where I came up
against the (wall) limits imposed by computation and AFL .....
ripping the mimimum data (trades only) required for performance
metrics i.e. core metrics, process only the essential metric
(objective function) and doing it on the fly (cached) for a reasonale
number of symbols is the challenge.
Currently obtaining all matched signals (trades) in AFL isn't the
default and perhaps a little difficult to achieve.
Finding a fast efficient way to do this is the key to the challenge.
>From what I can find out from the docs the AB method is to save
trades in a trade list .... I assume this has a time penalty attached
but in programming alternatives seem few and far between ???
My interest now is the relative speed OR otherwise of different
langauges/matrix/array processing when ripping the trade series from
the data followed by the subsequent speed when calculating the
metrics (the bias is on getting the trade matrix though).
I have been experiencing repeated thougnts about 64 bit programming,
using tricky methods to store trade data, with minimal memory use,
and 3,4, or more, dimensional matrices ... how crazy is that ... I
don't even own a 64 bit compputer and barely know the first thing
about computers or programming?
I don't find AFL a good language to learn programming from (for first
timers like myself) possibly because it has been simplified and also
because it doesn't have an intimate relationship with the computer,
being a sort of second order C++.
For programming research and education I am looking at other
languages and open source projects ... so far R Math is #1 on my
short list. It only has a small amount of code written for trading
but there might be some potential there.
Plus there is a handful of AB people interested in R and we have the
plugin (thanks to Patrick).
At least it gives me a chance to learn something about wider
programming techniques, including lists and matrices, (AFL is
reasonably transparent and documented but R language is much richer
and completely transparent and owned by the user which makes for a
better learning environment).
What I find out there I could apply to AB via a plugin but that would
mean I would end up only using AB as a data downloader and charting
package (more craziness)!
I am not likely to publish anything for a while, if at all, unless I
get real excited about it.... one can always rely on the 'good ol
workaround'!
Lucky for AB I don't pay a programmer to write the AB plugin,
commercialise it and copyright the code ;-)
--- In amibroker@xxxxxxxxxxxxxxx, "brian_z111" <brian_z111@xxx> wrote:
>
> I forgot to mention that another prime objective, of the overall
> method, is to make efficient use of our precious data.
>
> All trades are recording in Phase I, so that our elected N value (a
> statistically valid sample)is approached using a minimum amount of
> data...... for WF analysis N could be the cut off point for the
> sample space used.
>
> BTW this one is for the programmers, and serious dudes, who for the
> most part, tolerate my biblings and scribblings (hope you like it
> Fred).... Tomasz and this forum must have good Karma!
>
> Also for K and T who stuck up for me when I was pelted with rotten
> fruit all those years ago!
>
> --- In amibroker@xxxxxxxxxxxxxxx, "brian_z111" <brian_z111@> wrote:
> >
> > Thinking a little further on this.
> >
> > Unless there is a need for advanced matrix operations 'psuedo
> > matrices', using arrays with limited AFL matrix operations, would
> be
> > sufficient for AB needs (arrays are faster and maintain backward
> > compatibility?).
> >
> > For advanced users the first phase would be the power version and
> the
> > method used would only store the core metrics with speed in mind
> (2,
> > 3 or maybe 4 datapoints, as persistent arrays, depending on the
> > objectives) and only calculate one metric, on the fly, from them
> i.e.
> > the user defined objective function.
> >
> > All performance metrics would be derived from the core metrics
and
> > therefore able to be calculated in AFL so they would be fully
> > transparent to users.
> >
> > Default metrics could be built-in and rendered as tables etc, at
> > phase II, for the benefit of newcomers, but as their skill and
> > interest develops they could then easily drill down to the code
> > behind the metric.
> >
> > Obviously the trade matrices are a precursor to advanced
Portfolio
> > Management in Phase III (RalphVince, MSA Analyser, van Tharp,
> > McDonnell, MonteCarlo Simulation or whatever takes the users
fancy).
> >
> > For my own use I intend to go right past phase II and implement
my
> > own Portfolio Manager (based on a compilation of my own work and
> the
> > work of people like RalphVince .... I am still working in the
> > background on BiNomial Simulation and if I am happy with it I
will
> > use it in Phase III).
> >
> > Part of the rational, behind the idea, is that the time value
> > (processing) in the backtesting is saved, while the time value in
> > producing performance metrics is disposable (because the latter
has
> a
> > lesser timevalue, the metrics of interest are based on subjective
> > choices and they change dynamically as new data arrives).
> >
> > I think it is a good idea but I am not 100% certain about it, not
> > being a mathematician or programmer.
> >
> > I am becoming a little frustrated with AB (perhaps I am
outgrowing
> > it) and the Portfolio Backtester is a good example of one place
> where
> > that frustration is focussed.
> >
> > I have three ways I can go with it:
> >
> > - send it to AB as a suggestion (which is why I need feedback)
> > - implement my own backtester within AB (use a DLL?) ... maybe
keep
> > it private or publish it with open source code (possibly I would
do
> > that via a team effort)
> > - go to an existing open source charting project with my ideas
> > - intitiate my own open source charting project
> >
> > Since I am biased to open source, and therefore my ideas/code
would
> > be in the public domain anyway, I have no reason not to share it
> with
> > AB and the AB community.
> >
> > If it is not a good idea then nothing is lost.
> >
> >
> > --- In amibroker@xxxxxxxxxxxxxxx, "brian_z111" <brian_z111@>
wrote:
> > >
> > > There was some recent discussion about the need to learn more
> than
> > one
> > > language to use AB.
> > >
> > > Just wondering if C++ Matrices could be used to store and
> reference
> > > trades, instead of Object Orientated Progamming, to make things
> > easier.
> > >
> > > C++ includes containers that can be considered matrices (such
as
> > arrays
> > > and, in the Standard Library, vectors, lists, and maps) OR open
> > source
> > > C++ Matrix libraries are available.
> > >
> > >
> > > Would it be possible to:
> > >
> > > - nominate buy/sell/buyprice etc in the first phase of
backtesting
> > > - run backtest over the sample space (limit space as defined in
> > setting)
> > > - store trades P & L as % in binary files
> > > - store time in trade (binary)
> > > - store entry bar OR time (binary- only needed to display
arrows
> on
> > > chart)
> > >
> > > Storing trades in binary form would be very fast (stored as a
> trade
> > > matrix).
> > > All metrics can be calculated from % P & L plus time in trade
as
> > > required so Money Management only needs to be applied in the
> second
> > > phase, if required.
> > > Only the trade matrices need to be saved, with the backtest
> > settings
> > > (also binary), for future reference, instead of the BT reports.
> > >
> > > In the second phase performance metrics could be calculated as
> > required
> > > by referencing the matrix entries, either in total or as sub
> > matrices.
> > >
> > > Matrix functions could be included in AFL and the advanced
> > backtester
> > > would use them to reference the trades to create equity curves
> and
> > > custom or default reports on demand (no need to re-run
backtests
> > for
> > > custom reports OR when adding/deleting columns from a report).
> > >
> > > It might also be possible that trade P & L, and time in trade,
> > could be
> > > stored in one 32 bit byte thereby save processing time (the
> > separate
> > > pieces of info could be unpacked into the trade matrix and the
> time
> > in
> > > trade matrix when required).
> > >
> > > Happily, the trade matrices could be rendered as tables, with
> rows
> > and
> > > columns for visual reference/charting etc, which is much more
> > intuitive
> > > than referencing the Trade Object as we do at the moment.
> > >
> > > The matrices could use a full range of Matrix operations or
just
> > some
> > > of the basics for the AFL version e.g. referencing individual
> > trades by
> > > matrix M * N notataion (I don't know much about matrix maths so
> it
> > is
> > > up to the maths people to comment on possible uses for advanced
> > matrix
> > > maths functions).
> > >
> > >
> > > When data is added to the DB, or the sample range extended,
> > backtesting
> > > could commence from the time of the last closed trade and then
> add
> > new
> > > trades to the matrix (this would save time by avoiding the need
> to
> > > repeat backtests).
> > >
> > > It is also a very nice format for exporting to Excel or
advanced
> > stats
> > > packages like R or Matlab :-)
> > >
> > > Does anyone esle have any thoughts on the subject?
> > >
> >
>
------------------------------------
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