NeuroShell DayTrader
Professional 3.3
A simple overview of NeuroShell Trader
The NeuroShell Trader is
trading system building
software. It is not a
trading system in its
own right, it is a
toolkit of both
traditional and
artificial intelligence
(AI) techniques you can
combine to form
computerized trading
models. The models can
consist of indicators
and rules like traders
have used for years,
artificial intelligence
techniques, or hybrids
of both.
It will build models for
equities, futures,
commodities, options,
FOREX, indexes and more.
You can build models for
exchanges all over the
world, like the NYSE,
AMEX, FTSE, DAX, ASX,
TSX, SFE, and many more.
To build models you just
need to be able to
obtain data for the
instrument or exchange
in which you are
interested. Then the
models you build will
automatically back-test,
and continue to give
signals into the future
as new data arrive.
Advanced
degrees and skills not
necessary
To use NeuroShell you do
not need to be a
programmer, a Ph.D., an
AI expert, a
mathematician, or a
statistician. In fact,
sometimes it is better
that you are NOT one of
those things. That is
because neural network
experts, for example,
frequently cannot come
to grips with how easy
and fast it is to train
our neural networks.
They are usually tied to
the old style neural
nets that require lots
of "tweaking"
to even get a net
working. Often they
think there must be
something inferior about
our technology because
we have made it simple
enough for traders and
other novices to use.
Neural net experts might
be happier with our
generic AI products.
Artificial intelligence
study not required
Many people think they
must have to read books
about neural networks,
genetic algorithms, and
fuzzy logic or take a
course before they can
effectively utilize our
software. That is just
not true. We have
already done all that
studying for you
starting in 1988, and
created software that
allows you to
concentrate on the
business end, not the
science end.
Our genetic algorithms,
for example, act almost
like other traditional
optimizers. The main
difference is you don't
have to give them search
increments, because they
don't search the same
way. With our advanced
neural nets, you mainly
worry about what to feed
them, instead of how to
get them configured and
running. We let you
drive with an automatic
transmission, power
windows, power steering,
and power seats instead
of making you learn to
shift gears and do
everything else manually.
Everything is chart
based
Charts are the major
component of NeuroShell.
You may open many charts
at one time, either new
ones or ones you have
previously built and
saved. When you create a
new chart, you specify
their periodicity with
which you want to see
and process the data, as
well as how far back in
time you want to load
the data. Next you
specify the related
instruments whose
historical data should
be loaded into the chart.
They are the target
instruments for which
you wish to create
trading signals.
Multiple instruments in
the chart show up in
their own chart page.
For the rest of the
discussion in this
document, let's say you
load IBM, DELL, HPQ, and
AAPL as your target
instruments. (They don't
have to be stocks; they
can be FOREX pairs,
commodities, E-minis,
options, etc).
Data
streams
Charts contain data
streams, which can be
plotted or hidden. Of
course, the first data
streams loaded will be
open, high, low, close,
volume, and possibly
more raw data for the
target instruments. You
can also insert other
data streams called
other instrument data
that will be available
in each chart page, like
indexes or
raw data
for other stocks.
This other instrument
data is information you
want to use to create
trading signals. For
discussion, let's say
you believe that the Dow
Jones US Computer Index
($DJUCR on
eSignal)
and INTC will be useful
for deciding how the
target computer stocks
should be traded. You
would then load these as
other instrument data so
that they will be
available data streams
in all chart pages.
Indicators
The next data streams
you will want to include
will probably be
indicators. Models
generally are built
using indicators based
upon the raw data and
the other instrument
data. Let's say you
believe that the
following indicators
will be useful in models
that will produce
trading signals, because
you have heard people in
your investment club
talking about them:
1. The spread between
each target stock and
INTC
2. The relative strength
between each target
stock and $DJUCR
3. A stochastic %k
indicator applied to
each target stock
Therefore, the next
thing you might do is
insert the indicators
above into your chart
using the
Indicator
Wizard.
The
Indicator Wizard can
build some pretty
complex indicators
without programming or
using a special language.
It just uses "point
and click" to
construct new indicators
from existing ones,
rules, and math
functions so that you
never have to worry
about a missing comma or
unmatched parens.
You may or may not have
a clue about what the
indicators above do -
read on.
Models
Once the chart loads up
with the requested data,
you are ready to define
one or more models in
the chart. Any model
that you build in the
chart automatically
applies to all
instruments in the chart.
Your model can be
optimized the same for
all chart pages, or
custom optimized for
each chart page. Models
can be either Trading
Strategies or
Predictions.
You may or may not have
a clue about how the
indicators you have
chosen work. If you do,
you probably have some
idea about how they
would be used to
generate trading signals,
rules like "Buy
when the relative
strength between the
stock and the $DJUCR is
high, and the spread
with INTC is low."
In this case you will
want your model(s) to be
Trading strategies, even
if you are unsure what
values should be
considered high and low
above. The genetic
algorithm optimizer will
find the values for you,
or alternatively, you
might just want to use
our
Fuzzy Sets add-on.
If you either have no
clue about how the
indicators work, or no
clue about appropriate
rules for them, you will
probably want to build a
Prediction with a neural
net for your model(s),
because neural nets find
their own rules.
Note that you can insert
several models in a
chart. Once you insert a
model, it automatically
applies to all chart
pages.
Trading
Strategies
The
Trading Strategy
Wizard is a fast
mechanism for entering
trading rules without
having to type messy
formulas or write in
some algorithmic
programming-like
language. The Wizard is
all point and click.
You just list the rules
for long entry, long
exit, short entry, and
short exit (cover). Each
of these rules is in
fact an indicator you
build just like any
other indicator - with
the Indicator Wizard.
You can also enter
indicators for stop and
limit price levels,
including trailing stops.
If you want to
optimize your trading
strategies, the
genetic algorithm
optimizer will do these
things for you:
1. Find which of the
rules you have listed
should be used in
combination
2. Find out what the
parameters of the
indicators in your rules
should be set to
3. Perform 1. and 2.
above at the same time (we
call this full
optimization)
Even your stops and
limits can be optimized.
When the Trading
strategy is complete, it
will show you historical
buy and sell signals. As
new data is entered into
the future, those buy
and sell signals will
continue to appear with
each new bar. You can
insert a variety of
indicators to plot how
your profit is growing.
Predictions
Predictions are neural
nets made with the
Prediction Wizard.
That's what our standard
neural nets do, they
make predictions about
the future value of a
data stream, usually a
price or change in price,
but any data stream can
be predicted.
Here is basically all
you have to do to make a
prediction model:
1. Choose some inputs -
data streams, usually
indicators, that you
believe are leading
indicators of the market
2. Decide what you want
to predict, usually
change or percent change
of the open or close
3. Decide how much
historical data will be
used to train the neural
net
4. Decide how much
historical data you want
to use to test how well
the neural net has
learned
If you want to
optimize your prediction,
the genetic algorithm
optimizer will do these
things for you:
1. Find which of the
inputs you have listed
should be used in
combination
2. Find out what the
parameters of the
indicators in your
inputs should be set to
3. Perform 1. and 2.
above at the same time (we
call this full
optimization)
4. Find neural network
thresholds for trading
When the prediction is
complete, it will show
you historical buy and
sell signals. As new
data arrive in the
future, those buy and
sell signals will
continue to appear with
each new bar. You can
insert a variety of
indicators to plot how
your profit is growing.