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Thursday, September 18, 2014

Analyzing Stock Price Data by iT-Control Chart

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!