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Hi Eric,
We normalise based on the indicator. So, if it is an RSI, it is
very easy, as this is always between 0 and 100, and we just map
that range to -1 to +1. If it is some trendline that we fitted,
we may use -1 or +1, based on wheter it is above or below the
trendline. Also, for highest high/lowest low type stuff, we use
a +1/-1 approach - +1 if say above and -1 if below some previous
high. But for this last example, we typically will also add an
indicator that is a percent, so that we have two inputs, the +1/-1
as well as the percent above/below that value.
We often use percentages to normalise. When we calculate the MACD
for example, we then express it as a percent of the close, and so
we have something that is between -1 and +1. We also use standard
deviations, such when we divide the most recent percentage change
by its standard deviation. But we don't use standard deviations
that much.
If all else fails, there is the tanh function, that will map
any value to somewhere between -1 and +1!
So, when we prepare inputs for the net, we use a variety of
techniques, whichever makes most sense (to us!) for that indicator.
When we do the one-size fits all optimisation, that does not end
up in a net, we use a similar approach. Something like the RSI
can easily be standardised, but something like the MACD or CCI
we simply normalise to its own historical range. This sometimes
leads to confusion, as you get a +1 or 100% reading a couple of
days as the say CCI reach new highs and is normalised back to 100%
every time. But it is good enough for our purposes.
If you are going to feed the stuff into a net, you must pay some
attention to this as it adds lots of value once you start training
the net. We used to just throw values at the net, but got MUCH
better results once we first standardised it. If it is just to
compare with other standardised values, I think it may be a bit of
an overkill and you can just use historical or standard deviation
as a quick fix.
Regards
MG Ferreira
TsaTsa EOD Programmer and trading model builder
http://tsatsaeod.ferra4models.com
http://www.ferra4models.com
--- In equismetastock@xxxxxxxxxxxxxxx, chichungchoi <no_reply@xxxx> wrote:
>
>
> Hi MG Ferreira:
>
> > One thing we have also used, for a more thorough, automated
> solution,
> > is to take a number of 'good' systems, say what we feel are the best
> > 30 of the 1 ... 100 systems. Then we do not optimise, but
> > standardise all of these 30 inputs. Again, this is not trivial and
> > there is no simple answer, but we try to generate a value between -1
> > and +1 for each of the 30 systems. So in stead of taking the say
> > RSI (between 0 and 100), we divide by 50 and subtract 1 to get it to
> > between -1 and +1, and do something similar with all the rest. So
> it
> > is easy to compare and easy to optimise.
>
> This is the process of normalization as you mention, do you have any
> suggestion on how to select the appropriate normalization please?
> Referring to the article "Normalization" on Oct 2000, TASC, p.58-68.
> There are three different types of normalization, such as
>
> 1) normalized to standard deviation
> 2) normalized to average true range
> 3) normalized to its own historical range
>
> Should I only apply one type of normalization for all indicators, or
> should I apply different type of normalization for different
> indicators based on their own best performance?
>
> On the other hands, if I don't normalize the indicators, and try to
> define +1 for buy signal and -1 for sell signal for each indicator,
> then do you know the drawback for this approach?
>
> Thank you
> Eric
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