There are a couple of services which collect analyst ratings and at least in the US and Europe, they have gone to great lengths to be nice to analysts so analysts will enter their ratings into their systems or banks will integrate with them. One of the things that have been built into most systems is the ability to "correct" so called data-entry errors. This functionality is heavily abused with analysts revising bad calls to make themselves look better than they actually are.
One will find fairly large differences between data sets that collect analyst ratings and "corrections" as they happen (which you are going to have to collect yourself) and analyst ratings as reported by the various services and the differences almost always make the analysts seem more accurate.
It is possible things are different in Canada, but if you look at bias-free data for the US or Europe, analyst recommendations are mostly random. Analyst recommendation data is mostly useful so you can bet against the short term spike or drop caused by people reacting to a change in analyst recommendation. This was very effective up to the 2000s but doing this with a reasonable Sharpe Ratio today is very hard (otherwise I wouldn't write about it) though it may be useful as an add on to an otherwise profitable strategy.
TipRanks was founded (I'm no longer affiliated) to solve that. Analyst opinions are extracted from real world news rather than paid for.
The point was to hold analysts accountable for their actions by objectively collecting them. TipRanks sells this data and I'd love to run a study on it but unfortunately I no longer has access.
The Marketbeat data set used here is tiny in comparison and only consists of a third of analyst recommendations if I remember it correctly.
Bloomberg has a much better dataset which is nearly as good as TipRanks'.
Again, I can't really make claims on their behalf (I'm employed at Peer5 (YC@W17) at the moment and am no longer affiliated).
Also, can confirm that TipRanks never "correct"ed any errors - which often resulted in "cease and desist"s and legal threats. No analyst who loses money likes a site saying it like it is.
The legal threats held to merit - but to be fair they were very scary as a young startup before partnerships with E*Trade, Nasdaq and others started.
One will find fairly large differences between data sets that collect analyst ratings and "corrections" as they happen (which you are going to have to collect yourself) and analyst ratings as reported by the various services and the differences almost always make the analysts seem more accurate.
It is possible things are different in Canada, but if you look at bias-free data for the US or Europe, analyst recommendations are mostly random. Analyst recommendation data is mostly useful so you can bet against the short term spike or drop caused by people reacting to a change in analyst recommendation. This was very effective up to the 2000s but doing this with a reasonable Sharpe Ratio today is very hard (otherwise I wouldn't write about it) though it may be useful as an add on to an otherwise profitable strategy.