I have already noticed and posted (see
here) that some similar (to SETDS) technique is used for Stock Market Technical
Analysis. So I have decided to apply SETDS methodology to the stock price data to see
what that could show to us.
1. Getting Data
I have downloaded the stock price data in csv format from here: http://eoddata.com/ (I had to pay for that, but
it is really cheap). So far I decided to analyze only daily data, but less
granular data is also available from that site – later I plan to play with the
hourly data too. Also I have downloaded the DJI historical data from here: http://research.stlouisfed.org/
(free).
2. Building iT-Control Chart
First, I have just looked at the particulate stock symbol just a trend and
it looks like growing...:
As far as it is a daily data, I have built the 12 month baseline based
31-days monthly IT-Control chart (how to do that see HERE
and HERE).
It confirms that it is slowly growing, plus it higher that 12 monthly baseline
average. But currently the entire economy is going up as we can see see on the
DJI trend chart:
But looks like our stock growing faster... How to to capture relative
performance of the stock price in comparison with DJI to see if the stock
performance is better or worse than the economical background (even if the
absolute value is still growing to keep up with DJI index)?
Let’s normalize that by using the following formula:
Relative Stock Growth (RSG) = 1- (DJI – a stock
price)/DJI
So the trend picture of our stock in this term will be a bit
difference:
Base on which our stock is growing not so fast as it seems!
Let’s build iT-Control chart for RSG: and we can see that in August it
actually was not growing at all:
3. Resume
Looks like IT-Control chart gives some interesting analysis result, that
could be useful to consider some investments decisions.
And SETDS method could be a promising technique to analyze massive number
of stock symbols to capture automatically:
- Stocks that had some anomalies (SEDS exceptions) and
- The pattern changes (by applying the Trend detection part of
SETDS).
Check the progress of this research in my future posts!
