How does The Motley Fool rank recommendations?

Throughout The Motley Fool’s central investing database, we ask our individual analysts to build portfolios composed of the companies they watch. Our analysts will then give position weights to each idea, which equals a total portfolio allocation of 100 or less. These weights represent the analysts’ individual convictions for individual ideas. This allows us to differentiate between the highest conviction (or favorite) recommendations, from recommendations we feel less strong about, as well as from negative-conviction ideas (or stocks we may sell).

This data is collected into an aggregated list, where we then make a series of small adjustments to build the most informed view possible. These informed views are created with a weighted “up-or-down” voting methodology, which pulls select information from each stock our individual analysts are watching. After pulling this information, we then adjust each opinion based on the following criteria: the size of the analyst’s workload, how their recommendations have performed in the past, and what The Motley Fool, as a whole, thinks of similar companies.

After applying these adjustments to the analysts initial conviction ratings, we reach the adjusted conviction rating. Our adjusted conviction ratings reflect a real number we then use to generate a ranked list that reflects all recommendations in our database. 

Once this ranked list is created, we then separate the list into high, positive, neutral, and negative groups. High conviction ratings are given to ideas that our analysts are overweight in. Positive conviction ratings reflect equal-weight ideas. Neutral and negative conviction ratings represent ideas The Motley Fool would not buy today, but are still recommendations. Some stocks do not have a conviction ranking.

The rankings of our recommendations regenerate on a daily basis. Additionally, the ranking will change if an analyst (at their discretion, depending on their company analysis) updates their conviction inputs. Please note that while we believe this can help you better make sense of our stock recommendations, we have no data yet to suggest that higher-ranked stocks will perform any better or worse than lower-ranked stocks.

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