For public companies, the stock price is one facet of their reputation that is very easily tracked. Following on from a number of conversations I’ve had recently, I have become more and more interested in the effect off news (and gossip and buzz) on share prices.
At some point, I hope to be able to publish a case study on the effect of blog buzz on share price - I think this will be likely to come about only when we have happened to have been monitoring a public company’s reputation through a crisis or release of some great news. It is hard to reconstruct these kinds of effects after the fact.
A starting point, though is to look for correlations between a company’s share price movements and online news volumes. In order to find an interesting case study for this, I looked through the recent histories of a few shares and settled on the period in January this year when Apple (symbol: AAPL) released the iPhone. This is interesting because shortly after the release of information that exerted an upward pressure on the share price, Cisco sued over the name (which is identical to the trademarked name of one of their own products - the companies have since agreed to kiss and make up).
Google finance shows a good summary of the performance on NASDAQ of AAPL through the year and most of the data used in this analysis is sourced there.
##News volumes in January 2007
The chart below shows online news volumes for major stories (along with associated sentiment) through January 2007 for Apple. It has been normalised so that the day of the greatest discussion shows as ‘1’.
##AAPL stock price movements in January 2007
In order to do my best to remove effects from the wider market, I took the closing prices for AAPL stock through Januray 2007 and rebased them to a starting point of 100. I did the same for the value of the NASDAQ index over the same period. Subtracting the NASDAQ movements from the AAPL movements left those movements that can be genuinely attributed to Apple. The data you see plotted below is the movement of the stock price (so a positive number is an increase the price). In order to be able to compare it side-by-side with news volumes, this was also normalised so that the greatest movement in any given day shows as ‘1’.
##News and stock price movements side by side
Plotting these two sources of data side by side is interesting:
As my stats professors would like to remind me (and as the freakonomics guys tell us) , correlation is not evidence of causality. I am not trying to say that online news sources caused the share price movements we see (the underlying story and offline media will obviously play a major role). It is interesting (and as it should be, in an efficient market) that practically all the major movements in the share price are accompanied with equivalent news.
I am looking forward to being able to do this analysis in real time with blog buzz volumes as there is some evidence that looking at intra-day movements, blog buzz can actually come before the share price movement.