Analyst Price Targets — Consensus, Upgrades & Downgrades

Track sell-side analyst price targets, consensus ratings, recent upgrades and downgrades across every US-listed stock. One pay-per-result API call returns the Bloomberg-style consensus snapshot you need to run a portfolio: mean / high / low / median price target, the analyst-count behind it, the buy / hold / sell distribution, and the firm-by-firm trail of recent rating actions from the past 90 days.

📊 Sample Output

Built for portfolio managers running long/short books, retail "smart money" followers who track street consensus, and IR teams that need to know what the sell-side is actually saying about their tape before earnings, conferences, or roadshows.

What you get per record

Every record is one US-listed ticker, normalized into a clean, ready-to-merge schema. Hit it with one symbol or fan it across the S&P 500.

Field	Description
symbol	Ticker (uppercase).
company_name	Yahoo Finance long name.
sector / industry	GICS-style sector + finer industry classification.
current_price	Latest regular-session price (USD).
consensus_target_price	Mean of all contributing sell-side 12-month price targets.
target_median	Median of contributing targets — outlier-resistant alternative to mean.
target_high / target_low	High and low of the contributing target range. Useful for sizing dispersion.
n_analysts	Number of analysts contributing to the consensus mean.
upside_pct	(consensus_target - current_price) / current_price * 100. Positive = upside.
recommendation_mean	Yahoo's 1.0–5.0 sell-side mean (1.0 = Strong Buy, 5.0 = Sell).
consensus_rating	Bucketed rating: Strong Buy / Buy / Hold / Sell / Strong Sell.
rating_strong_buy_count	Count of Strong Buy ratings (current month).
rating_buy_count	Strong Buy + Buy ratings combined.
rating_hold_count	Count of Hold ratings.
rating_sell_count	Sell + Strong Sell ratings combined.
rating_strong_sell_count	Count of Strong Sell ratings.
total_rated_analysts	Sum of all five rating buckets.
recent_actions	Up to 20 firm-level actions from the last 90 days, formatted as plain-English lines ("Morgan Stanley upgraded to Overweight from Equal-Weight, target raised to $250.00 (was $230.00) on 2026-05-08").
n_recent_actions_90d	Count of analyst actions in the trailing 90 days.
last_action_date	Most recent rating or target change date (ISO yyyy-mm-dd).
market_cap_usd	Latest market capitalization (USD).
yahoo_url	Convenience deep-link to Yahoo's analyst page.
stockanalysis_url	Convenience deep-link to Stockanalysis.com's forecast page.
data_source	Provenance: yahoo_finance_quote_summary.
fetched_at_utc	ISO timestamp of the fetch.

Why this actor exists

Sell-side price targets and consensus ratings are the most-quoted, least-accessible number in equities. Bloomberg, FactSet, and Refinitiv ship clean consensus feeds — at $24K, $18K, and $24K per terminal per year respectively. TipRanks and Zacks ship retail-grade views with anti-bot defenses and watered-down API access. For everyone in between — a fund manager spinning up a quant overlay, a retail aggregator running street-consensus screens, an IR team running a quarterly tape-check — there is no clean, pay-per-call option.

This actor fixes that:

• Pay only for what you use. $0.10 per symbol record. A 500-name S&P 500 sweep costs $50.01 and returns in under a minute. Compare that to a Bloomberg seat.
• Bloomberg-style schema. Mean / high / low / median target, ratings distribution, recent firm actions — the exact fields a PM wants on their morning sheet.
• No anti-bot wrestling. We handle Yahoo Finance's crumb/cookie dance for you, refresh tokens transparently on 401s, and ship clean JSON.
• Pinned builds. ?build=0.0.1 keeps your prod integrations stable; we never silently swap parsing logic underneath you.

Comparison vs incumbents

Capability	Bloomberg	FactSet	Refinitiv	TipRanks	Zacks	Analyst Price Targets
Annual minimum cost	$24,000+	$18,000+	$24,000+	$1,000+	$250+	$0 (pay-per-call)
Per-symbol marginal cost	n/a	n/a	n/a	n/a	n/a	$0.10
Consensus mean target	Yes	Yes	Yes	Yes	Yes	Yes
Target high / low / median	Yes	Yes	Yes	Partial	Partial	Yes
Ratings distribution (SB/B/H/S/SS)	Yes	Yes	Yes	Yes	Partial	Yes
Firm-by-firm recent actions	Yes	Yes	Yes	Yes	Partial	Yes (last 90d)
1.0–5.0 numeric consensus	Yes	Yes	Yes	No	Partial	Yes
Programmatic API access	Yes (enterprise)	Yes (enterprise)	Yes (enterprise)	Limited	Limited	Yes (HTTP)
No-contract, no-seat licensing	No	No	No	No	No	Yes
Cross-language clients	Yes	Yes	Yes	Limited	No	Yes (Apify SDKs)
Build-pinned stability	Yes	Yes	Yes	No	No	Yes (?build=)
Time to first record	Weeks (procurement)	Weeks	Weeks	Days	Days	Minutes

How to call it

Apify Console (browser UI)

Open the actor, paste symbols into the Stock symbols field, hit Start. Dataset appears in a table view in seconds.

Apify API (curl)

curl -X POST \
  "https://api.apify.com/v2/acts/nexgendata~analyst-price-targets/runs?token=YOUR_TOKEN&build=0.0.1" \
  -H "Content-Type: application/json" \
  -d '{
    "symbols": ["AAPL", "NVDA", "TSLA", "MSFT", "AMZN"],
    "include_recent_actions": true,
    "min_n_analysts": 5
  }'

The ?build=0.0.1 pin is recommended for production integrations. Without it you ride latest, which can change without notice.

Apify Python SDK

from apify_client import ApifyClient

client = ApifyClient("YOUR_TOKEN")
run = client.actor("nexgendata/analyst-price-targets").call(
    run_input={
        "symbols": ["AAPL", "NVDA", "TSLA", "MSFT", "AMZN"],
        "min_upside_pct": 20,         # only names with 20%+ upside
        "consensus_rating": "Buy",     # only Buy-rated names
        "include_recent_actions": True,
    },
    build="0.0.1",
)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["symbol"], item["consensus_target_price"], item["upside_pct"])

Apify JS SDK

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('nexgendata/analyst-price-targets').call({
    symbols: ['AAPL', 'NVDA', 'TSLA', 'MSFT', 'AMZN'],
    min_upside_pct: 20,
    include_recent_actions: true,
}, { build: '0.0.1' });

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Input parameters

Parameter	Type	Default	Description
symbols	array	["AAPL","NVDA","TSLA","MSFT","AMZN"]	US-listed tickers to fetch. Case-insensitive. Required.
limit	int	0 (all)	Max records to return after filters. 0 returns everything.
min_upside_pct	number	-1000 (off)	Minimum upside vs current price. 20 for high-conviction longs.
consensus_rating	enum	"all"	Filter to one rating bucket: Strong Buy, Buy, Hold, Sell, Strong Sell.
include_recent_actions	bool	true	Populate recent_actions with last-90-day firm actions.
min_n_analysts	int	0 (off)	Drop names with fewer than N contributing analysts. Use 15 for widely-covered names only.

Common workflows

Morning sheet — high-upside Buy-rated names

{
  "symbols": ["AAPL","MSFT","NVDA","GOOGL","META","AMZN","TSLA","AVGO","ORCL","CRM"],
  "min_upside_pct": 15,
  "consensus_rating": "Buy",
  "min_n_analysts": 10
}

Filters to widely-covered names with at least 15% implied upside and a sell-side Buy consensus. Drop the result into your morning meeting deck.

Short candidate screen — Sell-rated names with downside

{
  "symbols": ["...your watchlist..."],
  "min_upside_pct": -1000,
  "consensus_rating": "Sell"
}

Pair with nexgendata/short-interest-tracker to find names where the street and the borrow desk both flag downside.

IR street-check — what is being said about us

{
  "symbols": ["TICKR"],
  "include_recent_actions": true
}

One call before earnings to summarize every analyst action in the last 90 days — target moves, rating changes, initiations, dropped coverage. Drop straight into the prep memo.

Smart-money following — newly upgraded names

Run with include_recent_actions: true, then filter results client-side for n_recent_actions_90d > 3 and parse recent_actions for the string "upgraded". Daily delta detection for newsletter writers.

Data sources & methodology

Primary source is Yahoo Finance's official quoteSummary endpoint, the same endpoint that powers finance.yahoo.com/quote/{SYMBOL}/analysis. We request six modules in a single call: financialData, recommendationTrend, upgradeDowngradeHistory, price, summaryDetail, and assetProfile. Yahoo's own consensus aggregation is itself sourced from sell-side feeds (Thomson Reuters / Refinitiv), so the targets and ratings here trace back to the same primary research desks that populate Bloomberg's consensus screen — just routed through Yahoo's free consumer endpoint.

Yahoo's crumb/cookie authentication is handled transparently. We boot consent cookies from fc.yahoo.com, exchange them for a crumb at query2.finance.yahoo.com/v1/test/getcrumb, and reuse the crumb across the run. Crumb expiry mid-run is detected and refreshed on the fly.

Concurrency is capped at 5 in-flight requests to stay below Yahoo's per-IP soft limit. A 500-symbol sweep typically completes in 50–90 seconds.

Pricing

Event	Charge
Actor start	$0.01
Per analyst-target record	$0.10

A 5-symbol smoke run costs $0.51. A full S&P 500 sweep costs $50.01. A Russell 1000 sweep costs $100.01.

There is no monthly minimum, no seat license, and no contract — you pay the Apify platform fee plus the per-event charges only on runs you actually execute. The 20% Apify margin is included in the prices above; we do not mark up beyond that.

Sister actors in the NexGenData fleet

Layer this actor with the rest of the fleet for a full equity-research stack:

• nexgendata/finviz-stock-screener — Finviz's full screener universe with 70+ filters. Feed its symbol list into this actor to bulk-pull consensus targets for any screen.
• nexgendata/earnings-calendar — Upcoming earnings releases with EPS estimates, fiscal period, prior-period surprises. Run this actor against the upcoming-reporters list to find names where street sentiment has shifted into the print.
• nexgendata/short-interest-tracker — Bi-monthly short-interest reports, days-to-cover, % of float short. Cross-reference Sell-rated names here with high short-interest tickers there to find consensus-confirmed shorts.
• nexgendata/sec-form4-insider-tracker — Real-time insider buys and sells from SEC Form 4 filings. Stack with this actor to find names where the street and management agree on direction.
• nexgendata/etf-holdings-tracker — Daily ETF basket exposure. Useful for tracking which thematic ETFs hold the analyst-favorite names you surface here.
• nexgendata/finance-mcp-server — Anthropic MCP server bundling the entire NexGenData equity stack into one tool surface for Claude / GPT / agentic workflows. Drop it in and let the model pull consensus targets, screens, earnings, short interest, insider activity, and ETF holdings on demand.

FAQ

Why Yahoo Finance and not Stockanalysis.com / TipRanks / MarketBeat? We tested all five. Stockanalysis.com forecast pages SSR through Svelte and hydrate from a private API that returns 404 to non-browser callers. TipRanks blocks anonymous JSON. MarketBeat returns HTML with anti-bot challenges. Zacks is rate-limited and protected by Cloudflare. Yahoo's quoteSummary endpoint is the cleanest, most-reliable surface and is itself sourced from Refinitiv's institutional feed — so we get Bloomberg-quality consensus for free.

How fresh is the consensus? Yahoo's financialData snapshot refreshes intra-day. Recommendation trend buckets refresh monthly. Upgrade/downgrade history rows appear within hours of the underlying note. For event-driven workflows we recommend rerunning the actor at the close each trading day.

Can I scan the whole Russell 1000? Yes. Pass 1000 symbols, set min_n_analysts: 5 to drop thinly-covered names, and the run completes in ~3 minutes for $100.01. We've stress-tested up to 2000 symbols per run without hitting Yahoo's edge limits.

What if a symbol is an ADR / OTC / dual-listing? ADRs and major OTC names work. Pure foreign listings (e.g. ASML on AEX without an ADR) return null targets — Yahoo's analyst feed only covers the US-listed share class.

Does it handle option-implied targets or buy-side targets? No. The output is pure sell-side. For option-implied moves see our forthcoming options-vol actor.

Build pinning? Pin with ?build=0.0.1. The build number (string), not the build id. Build numbers are stable; build ids rotate on every push. We bump 0.0.x for additive changes and 0.x.0 for any breaking schema change.

Support & licensing

Private actor on the NexGenData Apify fleet. Access by request — contact via the Apify console or the affiliate signup below. Bulk-rate licensing, white-label deployments, and dedicated-instance options available on request.

Sign up via the NexGenData affiliate link — supports the fleet at no cost to you, gives you instant access to every NexGenData actor (10+ and growing) including this one, plus first-look at upcoming releases (consensus-EPS-revisions actor, options-vol actor, transcripts-sentiment actor). Affiliate signups stay on a flat 20% rev-share for the lifetime of the account.

Built and maintained by NexGenData. We focus on the equity-research stack the institutional vendors charge $20K+ for — and ship it pay-per-call.