📅 Earnings Calendar — Upcoming Earnings + EPS Estimates

Stop paying $24,000 a year for a Bloomberg seat just to see who reports tomorrow. This actor returns a clean, structured earnings calendar for US-listed companies with consensus EPS estimates, fiscal periods, prior-year comparables, market caps, and (optionally) the most recent reported surprise for each name. Pay only for the records you pull — no annual contracts, no Refinitiv enterprise license, no Estimize floor.

If you trade earnings, sit on a sell-side desk, run an options vol book, or work in IR — this is the data you actually use. Cron it nightly, pin it to your dashboard, or stream the upcoming week into your backtest harness.

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What you get per record

Every dataset item is one upcoming (or just-reported) earnings event:

Field	Example	Description
symbol	NVDA	US listing ticker
company_name	NVIDIA Corporation	Full issuer name
sector	Technology	GICS-style sector (inferred when not provided)
earnings_date	2026-05-14	ISO date of the scheduled release
time_of_day	AMC	BMO (before market open) / AMC (after market close) / null when not supplied
fiscal_period	Q1 2026	Calendar-anchored fiscal quarter being reported
fiscal_quarter_ending_raw	Mar/2026	The raw period label from the data source
consensus_eps_estimate	0.92	Wall Street consensus EPS in USD
consensus_revenue_estimate_usd	null	Revenue consensus (null in free tier)
n_analysts	38	Number of analysts contributing to the consensus
prior_period_eps	0.61	Year-ago comparable EPS
eps_growth_yoy_pct	50.82	(consensus / prior_year - 1) × 100
market_cap_usd	2150000000000	Raw USD market cap snapshot
prior_year_report_date	5/14/2025	The year-ago report date for context
last_eps_actual	1.85	Most recently reported EPS (hydration)
last_eps_consensus	1.73	Consensus for that quarter (hydration)
last_eps_surprise_pct	6.94	Surprise % of the most recent report (hydration)
last_quarter_period	Mar 2026	Period of the most recent report
last_reported_date	4/30/2026	Date of the most recent report
actual_eps	2.01	Populated when the event is in the past
eps_surprise_pct	4.69	Surprise on the event row when reported
nasdaq_url	https://www.nasdaq.com/...	Issuer earnings page
stockanalysis_url	https://stockanalysis.com/...	Issuer fundamentals page
data_source	nasdaq_earnings_calendar	Provenance

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Input parameters

• limit — max records to return. 0 returns everything in the date window.
• date_range — today / this_week / next_week / this_month / all (45-day forward window).
• min_market_cap_billion — minimum market cap in $B. Use 10 for large-cap only, 50 for mega-cap, 0 for everything.
• sector — filter to a single GICS sector or all.
• with_estimates_only — exclude names without a published consensus EPS estimate. Sell-side typically true; IR teams often false.
• hydrate_surprises — make one extra API call per symbol to attach last-reported surprise data. On by default. Turn off for the fastest pull.

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Sample input

{
  "limit": 200,
  "date_range": "this_week",
  "min_market_cap_billion": 5,
  "sector": "Technology",
  "with_estimates_only": true,
  "hydrate_surprises": true
}

That request pulls the current trading week's tech earnings calendar, $5B+ market cap, only names with analyst coverage, with the prior-quarter surprise stamped on each row.

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Who pays for this

• Earnings traders — pre-event positioning around the BMO / AMC clock. Filter time_of_day to focus on the post-close batch.
• Sell-side analysts — coverage prep for client notes. The n_analysts and prior_period_eps fields tell you who's competing on the call.
• Options vol desks — pricing IV crush. Combine consensus_eps_estimate with last_eps_surprise_pct to size moves.
• IR teams — peer-window awareness. Pull your sector, see who reports the same week, and time your release to avoid clashes.
• Quant / systematic funds — backtest fuel. Pull the 45-day forward window nightly, snapshot, accumulate.
• Fintech apps — "what's reporting this week" widgets without a Refinitiv contract.

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Versus the incumbents

Source	Earnings calendar	EPS estimates	Surprise history	Market cap	Cost (US-only, retail-equivalent)
Bloomberg Terminal (EE / ECO)	yes	yes	yes	yes	~$24,000 / year / seat
FactSet	yes	yes	yes	yes	~$12,000+ / year / seat
Refinitiv Eikon	yes	yes	yes	yes	~$22,000 / year / seat
Zacks Premium	yes (web)	yes	yes	yes	$249–$549 / year
Estimize (consensus + crowd)	yes	yes	yes	partial	$99–$2,400+ / month
NexGenData Earnings Calendar (this actor)	yes	yes	yes (opt-in hydration)	yes	$0.05 / record, no subscription

For a single trader pulling 200 names a week, this actor runs ~$10/week — roughly 1/50th of a Zacks Premium subscription and 1/200th of a Bloomberg seat.

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Pricing — pay-per-event

Event	Price
Actor start	$0.01 (charged once per run)
Earnings record (primary event)	$0.05 per record returned

A pull of 100 upcoming earnings = $0.01 + 100 × $0.05 = $5.01. A pull of 10 names for a quick smoke test = $0.51.

No subscription. No minimum. No annual contract. Cron it once a day or once a year.

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How it works under the hood

1. The actor resolves your date_range to a concrete list of trading-week or calendar dates.
2. For each date, it pulls the NASDAQ public earnings-calendar JSON endpoint — the same feed that powers nasdaq.com/market-activity/earnings.
3. Rows are normalized: market cap is decoded from "$131,271,743,181" strings, EPS like "($0.59)" is parsed to negative floats, Mar/2026 becomes Q1 2026, "time-pre-market" becomes BMO.
4. Year-over-year EPS growth is computed from the prior-year comparable when both values exist and the denominator isn't near-zero.
5. Sector is inferred from issuer name when the source doesn't supply one (a conservative keyword classifier; null when ambiguous).
6. If hydrate_surprises = true, the actor fans out one additional per-symbol call to the NASDAQ earnings-surprise endpoint and attaches the most recent reported EPS, consensus that quarter, and surprise percentage. For events whose earnings_date matches the last reported date within 5 days, those values also populate the actual_eps / eps_surprise_pct fields directly.
7. Dedupe is on (symbol, earnings_date) — necessary because the same name can appear on adjacent days when the source moves a confirmed report.
8. Results sort by date ascending, then market cap descending — the biggest names of each day rise to the top.

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Operational notes

• No proxy needed. The NASDAQ JSON endpoint is unauthenticated and tolerates moderate concurrency. The actor caps day-fanout at 4 and surprise-fanout at 6.
• Backfill. Want the next quarter's earnings? Use date_range: "all" for 45 forward days. To go further, run the actor on a daily cron and accumulate to your own warehouse.
• Already-reported events. When your window includes past dates (e.g. when running mid-day after the market opens), already-reported names will carry actual_eps and eps_surprise_pct if hydration is on.
• Revenue estimates. Consensus revenue is intentionally null in this tier — the free NASDAQ feed doesn't carry it. We surface the field for forward compatibility; a premium tier may hydrate from IBES-style sources.
• Surprises by day. To slice "biggest beats this week," pull date_range: "this_week" and sort the result by last_eps_surprise_pct (for upcoming weighting) or eps_surprise_pct (for already-reported events).

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The full NexGenData market-intelligence fleet

This actor is one of several pieces in a coordinated fleet — combine them to build a full Bloomberg-on-Apify stack at a fraction of the cost.

• 🚀 IPO Tracker — recent + upcoming IPOs with lockup expirations, post-IPO performance, and SEC EDGAR prospectus links. Pair with the earnings calendar to catch first earnings reports of recently-IPO'd names.
• 📋 SEC Form 4 Insider Tracker — real-time insider buys and sells. Cross-reference insider activity in the 30 days before earnings — historically one of the highest-signal pre-earnings indicators.
• 🚨 SEC Form 8-K Material Events Scraper — surprise filings between scheduled earnings. Companies sometimes pre-announce or guide via 8-K; this actor surfaces those.
• 📊 Finviz Stock Screener — fundamentals and technicals screener for the full US market. Use it to build watchlists, then feed those watchlists back into the earnings calendar.
• 🇨🇳 Chinese ADRs Stock Screener — US-listed Chinese ADRs (BABA, JD, BIDU, PDD, NIO, etc.). These names dominate certain earnings weeks and have unique fiscal calendars.
• 🤖 Finance MCP Server — the same data, exposed as a Model Context Protocol server for Claude Desktop, Cursor, and other LLM clients. Ask "what's reporting next week with a market cap over $10B" in natural language.

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Affiliate / referral

If this actor saves you a Bloomberg seat or a Zacks Premium subscription, consider supporting NexGenData by using our affiliate link when you sign up for Apify:

https://apify.com/nexgendata?fpr=2ayu9b

Every signup helps keep the fleet maintained, the endpoints fresh, and the prices honest.