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What Is an Analyst’s Success Rate? Definition and Example

What an analyst success rate measures, the different ways it is calculated, and the traps that make a high number look better than it is.

Published Updated 3 min readHow we research

Key takeaways

  • An analyst’s success rate is the share of their past calls that worked, defined either as the stock moving the predicted way over a set period or as the price target being reached.
  • In Exent’s 7-year backtest of 921,573 ratings, the average analyst’s price targets were reached 53.6% of the time and 64.6% of rated stocks were higher 12 months later (as of Oct 20, 2026).
  • Success rate alone is easy to game: small, safe calls in a rising market score well.
  • Read it next to average return per call and the number of calls.

Which stocks do Wall Street’s best‑ranked analysts agree on? See them in Exent Gems →

What is an analyst’s success rate?

It is a hit rate for an analyst’s recommendations. There are two common versions: the share of ratings where the stock moved in the predicted direction (up for buys, down for sells) over a window such as 12 months, and the share of price targets reached within the horizon.

What is a normal success rate?

Price-target hit rateAnalystsShare
Below 30%919.9%
30–40%839.1%
40–50%15917.3%
50–60%24827.0%
60–70%19321.0%
70–80%859.3%
80% or more586.3%

Source: Exent’s ranking of 1,121 analysts with enough rated calls, 7-year lookback, as of Oct 20, 2026 (917 of them have a measurable hit rate). Above 60% puts an analyst in roughly the top third of this list; the average analyst’s rate was 53.6%.

Why it matters

Most ratings are buys, so knowing who is usually right is the only way to turn ratings into information. A star rating that combines success rate, average return and number of ratings stops a few lucky calls topping the list; the full ranking is on the analysts page.

Common pitfalls

  • Bull-market inflation: when most stocks rose, most buy calls “succeeded”. Compare with the market’s own return over the same windows.
  • Small samples: 12 calls at 80% says less than 400 calls at 62%.
  • Timid targets: a target 5% above the price is easy to hit and says little.
  • Sector mix: the same ranking shows a median hit rate of 60.5% for technology analysts but 41.9% for healthcare analysts.

How to use it

Look for analysts with a solid hit rate, a positive average return per call and hundreds of calls, in the sector you care about. The step-by-step version is in how to judge an analyst.

See analysts’ success rates with Exent

  1. Stocks Radar tracks thousands of Wall Street analysts and ranks them by past accuracy. Each profile shows success rate, average return and number of ratings.
  2. Gems flag stocks where several top‑rated (4★+) analysts agree.

Exent is our product. Educational content, not investment advice.

Frequently asked questions

In a 7-year backtest of 921,573 ratings, the average analyst’s price-target hit rate was 53.6%, so a rate above 60% over hundreds of calls puts an analyst in roughly the top third. Check sample size and average return too.

It is high, but only meaningful with many calls and a positive average return. A high rate built on small, safe targets adds little.

No. Past accuracy is evidence of skill, not a guarantee. Rates also shift as market conditions change.

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Educational content, not investment advice. Examples are illustrative; past performance does not guarantee future results.

DISCLAIMER: Exent AI is an informational research platform and does not provide investment advice, financial advice, or act as an investment adviser, broker-dealer, or fiduciary. All content, analytics, and model outputs are provided for educational and informational purposes only and should not be relied upon as a recommendation to buy, sell, or hold any financial instrument. Investing involves risk, including the possible loss of principal. Exent AI does not execute trades, hold customer funds, or provide brokerage services. Past performance and hypothetical results are not indicative of future results. Third-party data and AI-generated outputs may be incomplete or inaccurate.