I was watching stock market today. Pearson plc (PSON) got beaten up quite badly. Just for sake of curiosity i drilled down to recommendations by different analysts to see if they were able to predict today announced problems.
At the moment Person is trading at level of 585.50p which is 27.6% down from yesterday! Quite a drop.
October 2016 11 analysts gave recommendation. Only one of those was setting targe price low to 470p. Average target setting of all 11 analysts was 844p. Average of 10 optimistic analysts was at 881p.
November 2016 2 analysts updated their view. One giving 470p as target price repeated that. Another was downgrading target price from 955p to 940p. Two new analysts were giving their target prices 740p and 1040p! The average of the 12 optimistic analysts was actually increasing to 882p!
December 2016 4 analysts gave their view. One giving 470p as target price remained at that level. One new did not give target price, but just sell recommendation. One was moving down from 750p to 740p. The fourth was just repeating earlier target price. Now the average of 12 optimistic analysts returned to 881p.
January 2017 just before crash one analyst was downgrading target price from 825p to 808p. Another from 790p to 690p. The most lucky one was able to give add recommendation with target price at level of 835p.
This is just a limited view to the data and background of recommendations and i am not pointing fingers on any failures. It just makes me wonder on how solid ground these target prices actually are. Also it rises another question, if analysts are able to drill into numbers of companies fast enough and see the surrounding factors? Today, i think, market is developing fast and as digitization is disrupting industries, it will make even harder for analysts to predict development of companies in those turbulent areas. Prediction cannot anymore be based on earlier development and cycles known in different industries. In future i believe analysts must be more capable of understanding development of cross industrial behavior and disruptive factors.