Where the analysts with the best track records agree, what the accuracy data says about analysts, how quality‑at‑a‑discount and momentum screens work, and how to test any idea against your own portfolio before acting.
The useful answer is not a single consensus list but the small set of stocks where the analysts with the strongest track records agree. Any such list changes as new ratings come in, so it is more useful to understand how it is built. Then you can judge the method rather than take the names on trust.
How a convergence list is typically built:
Convergence matters because each analyst covers a different set of companies and makes different mistakes. When several strong records point the same way, a single analyst’s error carries less weight. It is still research, not a guarantee: top analysts are wrong a large share of the time.
Read a worked example in how Gems are built and whether following top analysts’ consensus picks has worked. Individual analyst records are on the analyst rankings, and the star scale is explained in what a 5-star analyst is.
About as accurate as a coin flip on average, with a minority that did meaningfully better. The backtest below replayed every rating with a price target over a 7-year lookback: was the target reached, how fast, and what the stock did over the next 12 months.
| Group | Analysts | Price-target hit rate (median) | Stock higher 12 months later (median) | Median 12-month return |
|---|---|---|---|---|
| All ratings (628,792 calls) | — | 52.4% (all calls) | 64.0% (all calls) | +13.4% (all calls) |
| 5★ analysts | 141 | 60.8% | 68.6% | +19.9% |
| 4★ analysts | 853 | 52.8% | 62.8% | +12.0% |
| Group | All ratings (628,792 calls) | 5★ analysts | 4★ analysts |
|---|---|---|---|
| Analysts | — | 141 | 853 |
| Price-target hit rate (median) | 52.4% (all calls) | 60.8% | 52.8% |
| Stock higher 12 months later (median) | 64.0% (all calls) | 68.6% | 62.8% |
| Median 12-month return | +13.4% (all calls) | +19.9% | +12.0% |
Source: Exent’s 7-year backtest of analyst ratings, as of Jun 24, 2026. Targets that were hit took a median of 91 days. Accuracy also varied by sector: the median analyst hit 62.3% of targets in materials and 61.8% in technology, but 37.7% in healthcare and 37.3% in real estate. Past accuracy does not guarantee future accuracy.
| Go deeper | What it answers |
|---|---|
| Are Wall Street analysts accurate? | The median analyst’s hit rate, in detail. |
| Is the average analyst a coin flip? | The headline finding of the aggregate study. |
| Are price targets accurate? | Hit rates, days to hit and implied vs realized upside. |
| Which analysts are most accurate? | How to rank analysts and what separates the best. |
| Analyst accuracy by sector | Where analysts were most and least reliable. |
| Which bank has the best analysts? | Accuracy aggregated by firm. |
| Do analysts beat the market? | Returns of analysts’ picks vs the S&P 500. |
| How to judge an analyst | Hit rate, sample size and recency before you follow a call. |
| Analyst success rate | The definition and its pitfalls. |
| Famous analyst calls | Well-known right and wrong calls, sourced. |
Treat “buy” as the default, not a strong signal. In the last 12 months of the same data, 115,183 ratings were buys, 42,272 holds and 4,537 sells: 71.1% buy, 26.1% hold and 2.8% sell. A “hold” often works as a polite sell, and banks use different words for the same view (outperform, overweight, buy).
Four habits make ratings more useful:
| Go deeper | What it answers |
|---|---|
| What a buy rating means | Buy, outperform and overweight compared. |
| What overweight means | Rating scales by bank. |
| What a price target is | How targets are set and the 12-month horizon. |
| Consensus rating and price target | Median vs mean, and dispersion. |
| How to read analyst consensus | What “analysts think” about a stock really tells you. |
| What a strong-buy consensus is worth | The evidence on unanimous ratings. |
| Why analysts rarely say sell | Incentives and the share of sell ratings. |
| Are analyst ratings biased? | Conflicts and optimism bias. |
| Sell-side vs buy-side analysts | Who they work for and why it matters. |
| Analyst upgrades | What happened after upgrades, from studies. |
| Analyst downgrades | What happened after downgrades. |
| Price target changes | Whether target raises predicted gains. |
| Analyst initiations | What a new coverage call means. |
| Analyst coverage | How many analysts cover a stock and why it matters. |
| Estimate revisions | Changes to earnings forecasts as a signal. |
| Analyst vs AI stock ratings | How human ratings compare with AI scores. |
| Free analyst ratings | Where to see ratings for free, and what is missing. |
| How to follow Wall Street analysts | A practical routine, filtered by track record. |
| TipRanks alternatives | Other analyst trackers and how they rank analysts. |
Start from a quality filter, then look for a price drop, never the other way round. A typical quality‑at‑a‑discount screen keeps only stocks that pass a quality test, such as a record of steady returns with moderate drawdowns, and then shows those trading 15% or more below their 52-week high, deepest discount first.
The order matters. Screening for big drops first mostly finds stocks that fell for good reasons. A fall of 15% in a business with a strong record can be noise; the same fall in a weak business is often the start of a value trap. A discount screen shows candidates, not bargains: the next step is to read why the price fell.
To build your own version, see stock screener settings for long-term investors and the quality factor. Some screeners also accept plain-English filters; see how the AI stock screener works.
Momentum leaders are stocks in a strong, steady uptrend that is not yet stretched. A common momentum‑leader screen requires a relative strength index (RSI) between 55 and 75, a price above both the 50-day and the 200-day moving average, and a positive 3-month return, then ranks by RSI.
Momentum is one of the most studied return factors, and it comes with sharp reversals. In Exent’s 10-year backtest, a momentum factor ETF (MTUM) returned 16.2% a year against 15.2% for the S&P 500, but with a deeper maximum drawdown (−30.2% against −23.9%) and a lower Sharpe ratio (0.81 against 0.88). It beat the index in 5 of 9 calendar years. Backtested (hypothetical) results; past performance does not guarantee future results.
| Go deeper | What it answers |
|---|---|
| Momentum vs the S&P 500 backtest | Year by year, with drawdowns. |
| Momentum factor | What it is and why it has worked. |
| Mean reversion vs momentum | The two opposite effects, defined. |
| Pair trade | Betting on one stock against another. |
From anyone with a verifiable record or a disclosed position: large funds’ 13F filings, company insiders’ Form 4 trades, sector leadership and scheduled catalysts. Each source has a lag or a bias you should know about.
| Source | What to know | Go deeper |
|---|---|---|
| Hedge funds and famous investors | 13F filings show long US positions, filed weeks after each quarter ends | How to track smart money, 13F filing |
| Company insiders | Purchases with their own money are read as more informative than sales | Insider buying |
| Sector leadership | Which parts of the market are leading, week by week | Sector leadership |
| Catalysts and events | Earnings, index additions and macro releases move prices around known dates | Catalyst, trading earnings, S&P 500 inclusion effect |
| What other investors hold | Popular is not the same as good; crowding raises correlation | Most-held stocks among self-directed investors |
| A neutral list of sources | Pros and cons of each place to look | Where to find stock ideas |
Judge the idea on two levels: is the stock sound, and does it improve your portfolio? The second question is the one most investors skip. In an anonymized sample of 144 self‑directed portfolios (October 2026; see the retail portfolio study), the median portfolio held 15 positions but had 77.2% of its value in the top five, and 54.2% held at least one Magnificent 7 stock. A new idea that moves with what you already own adds risk without adding diversification.
| Go deeper | What it answers |
|---|---|
| Evaluate a stock idea | A checklist including portfolio fit. |
| Does this stock fit my portfolio? | Its effect on Sharpe ratio, correlation and concentration. |
| How to write an investment thesis | A template with examples. |
| How to build a watchlist | A simple process. |
| Trading vs investing | What academic evidence says works for most people. |
| Do day traders make money? | What the studies found. |
Any idea list is research to support your own decisions, not a personal recommendation. For the bigger picture on picking stocks against the index, read why beating the S&P 500 is so hard.
Look for stocks where several analysts with strong past accuracy independently rate a buy, rather than the plain consensus. Exent tracks this as Gems, a list that changes as new ratings come in.
Across 628,792 ratings over 7 years in Exent’s data to June 2026, 52.4% of price targets were reached. The median 5★ analyst hit 60.8%, so track records differ a lot.
Filter for quality first, then look for stocks well below their 52-week high, and read why the price fell. Exent’s Survivors on Discount screen uses a 15% threshold on stocks with its quality labels.
Stocks in a steady uptrend that is not overbought. Exent’s screen looks for an RSI between 55 and 75, a price above the 50-day and 200-day moving averages, and a positive 3-month return.
Banks want access to companies and their business, and rating scales lean positive. In Exent’s data only 2.8% of ratings in the last 12 months were sells.
It can be a useful filter for research, not a guarantee. Even the most accurate analysts missed a large share of their targets, so position size and portfolio fit still decide the outcome.
Exent Stocks Radar ranks Wall Street analysts by past accuracy and flags Gems, the stocks where several 4★+ analysts agree.
Educational content, not investment advice. Examples are illustrative; past performance does not guarantee future results.