How Analysts are Ranked

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TipRanks developed a 3 tier unique proprietary formula to rank financial analysts. The three factors taken into account are the analyst’s success rate, the average return per transaction, and statistical significance.

Success Rate: This measure looks at each transaction in a binary form, as it either lost money or earned money. The average is the win-to-loss ratio. We add this to ensure that an analyst does not have 10 losing transactions offset by one winning transaction with a high profit – making his or her performance unreasonably high. This measure is often referred to as the hit ratio.

Average Return: The average return of all transactions is the best measure of performance. We don’t want to measure single lucky hits but rather the analyst’s overall performance. Analysts in the biotech field will naturally have higher returns on their winning trades, but those will still have to compensate for higher losses on bad recommendations.

Statistical Significance: A higher amount of recommendations ensures the analyst’s consistency. For this reason an analyst with many recommendations will have his or her ranking scored higher than an analyst with a low recommendation count (with all other things being even). In the same way an analyst with 1,000% average return but one recommendation would rank very low, an analyst with just 2% average return across hundreds of recommendations would rank very high.

How do I use the star ranking in my decision making?

The analyst’s star ranking does not pinpoint his or her return or hit ratio, but rather compares him or her to all analysts tracked by TipRanks. Reaching a 5-star rating is extremely difficult and guarantees the analyst has a high success rate accompanied by a high average return and high transaction count. TipRanks also dedicates a whole section to our top ranked 25 analysts, which you can further filter by sector to see who you should trust!
Mark Mahaney