Test data

| I am about to generate some data to test some technical analysis functions.
| 
| I expect I am not the first!  Has anybody some advice about where to 
| look for some data sets?
| 
| What I need, naturally,  is pairs of series, input and output.  I expect 
| I can roll my own without too much difficulty but...

As so often, Pat Burns has already been there and done that.  See this

   Patrick Burns. "The Technical Analysis Challenge" (pdf) This draft: 2003
   October 07

   Abstract: We report on a study of the ability of analysts to distinguish
   an actual price series of an equity from random alternatives. Virtually
   all of the statistical tests on the results support the hypothesis that no
   skill was exhibited in selecting the correct response. Many of the
   analysts were extremely over-confident about their ability to select
   correct answers. The one area where it seems skill might have been
   exhibited is in the selection of correct answers that happened to be far
   from the random choices.

   Pointers to the graphs and data for the test, results of the participants,
   and so on can be found here. Instructions for using the data in R are in R
   for the Technical Analysis Challenge.

from the page at http://www.burns-stat.com/pages/working.html where you can
find links to paper(s), code and data.

Hope this helps,  Dirk

 
| cheers
| Worik
| 
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I am about to generate some data to test some technical analysis functions.

I expect I am not the first! ?Has anybody some advice about where to look
for some data sets?

What I need, naturally, ?is pairs of series, input and output. ?I expect I
can roll my own without too much difficulty but...

In developing indicators and technical methods it is very helpful to
feed models various synthetic data streams. I have a library of these
and will discuss a few that I use here.

1. Instantaneous change. The is a dead simple series, but it can be
amazingly informative. Mine runs at 1 and then jumps to 2. You might
be surprised at the results you get, especially if any form of
advanced smoothing is used.

2. Sine, triangle, saw tooth and square waves of various periodicities.

3. Idealized typical technical patterns, head and shoulders, double
bottoms and tops, wedges, simple reversals and the like.

4. Cyclically varying volatility.

5. Most of the above coupled with trends, say  plus or minus 10%
annualized growth rates.

The ideal is of course to torture test transforms so you will know
what to expect from them in evolving market conditions. This is
especially helpful in avoiding signals that are artifacts of your
transforms rather than of the data. Try plotting 20 period, 2 standard
deviation Bollinger Bands with 10, 20, 30 and 40 period square waves.

Best,

    John