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Earnings Estimates & Actuals

Overview

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The Finvera Consensus Earnings Estimates API provides point-in-time and latest consensus for EPS, revenue, and key line items across quarterly and annual periods. It’s built for developers who need clean, backtest-ready estimates for screens, models, and research dashboards—without vendor-specific quirks.

What you get

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Consensus Stats: mean, median, high, low, standard deviation, coverage count.

Periods: quarterly (FQ1–FQ4) and annual (FY), rolling and fiscal-calendar views.
Point-in-Time (PIT): retrieve the consensus as it existed on a historical date (survivorship-bias safe).
Latest Snapshots: fast access to the most recent consensus.
Revisions History: day-by-day changes in consensus with as_of timestamps.
Adjustments: GAAP / Non-GAAP EPS flags, currency and split adjustments.
Identifiers: ticker, CIK, FIGI/ISIN (when available).

Use Cases

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Pre-earnings screens (rising/declining revision momentum)

Factor backtests (estimate dispersion, surprise set-ups)
Dashboards showing estimate trends vs. price
Risk checks on low-coverage names or high-dispersion periods

Endpoints

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GET /estimates/consensus/{ticker}
# Latest consensus for upcoming and recent periods

GET /estimates/consensus/{ticker}/history?period=FQ&fiscal_year=2025&fiscal_period=Q3
# PIT series of consensus over time for a specific period

GET /estimates/consensus/{ticker}/revisions?start=2024-01-01&end=2025-09-22
# Daily revisions window with as_of timestamps

GET /estimates/coverage/{ticker}
# What measures/periods are available for this name

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GET /estimates/consensus/{ticker}
# Latest consensus for upcoming and recent periods

GET /estimates/consensus/{ticker}/history?period=FQ&fiscal_year=2025&fiscal_period=Q3
# PIT series of consensus over time for a specific period

GET /estimates/consensus/{ticker}/revisions?start=2024-01-01&end=2025-09-22
# Daily revisions window with as_of timestamps

GET /estimates/coverage/{ticker}
# What measures/periods are available for this name

Schema

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Note: Fields omitted with ... for brevity.

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curl --request GET \
  --url https://api.finvera.news/delivery/api/v1/estimates/consensus/AAPL

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curl --request GET \
  --url https://api.finvera.news/delivery/api/v1/estimates/consensus/AAPL

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{
  "ticker": "AAPL",
  "cik": "0000320193",
  "as_of": "2025-09-22T14:00:00Z",
  "currency": "USD",
  "measures": [
    {
      "measure": "EPS",
      "gaap_flag": "Non-GAAP",
      "frequency": "FQ",
      "fiscal_year": 2025,
      "fiscal_period": "Q1",
      "period_end_date": "2024-12-28",
      "latest": {
        "mean": 2.11,
        "median": 2.10,
        "high": 2.25,
        "low": 1.96,
        "stddev": 0.07,
        "analyst_count": 38,
        "updated_at": "2025-09-22T13:58:20Z"
      },
      "point_in_time": {
        "available": true,
        "first_seen": "2024-10-01",
        "last_seen": "2025-09-22"
      }
    },
    {
      "measure": "REVENUE",
      "frequency": "FQ",
      "fiscal_year": 2025,
      "fiscal_period": "Q1",
      "period_end_date": "2024-12-28",
      "latest": {
        "mean": 118500000000,
        "median": 118200000000,
        "high": 121000000000,
        "low": 114900000000,
        "stddev": 1600000000,
        "analyst_count": 36,
        "updated_at": "2025-09-22T13:58:20Z"
      }
    }
  ]
}

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{
  "ticker": "AAPL",
  "cik": "0000320193",
  "as_of": "2025-09-22T14:00:00Z",
  "currency": "USD",
  "measures": [
    {
      "measure": "EPS",
      "gaap_flag": "Non-GAAP",
      "frequency": "FQ",
      "fiscal_year": 2025,
      "fiscal_period": "Q1",
      "period_end_date": "2024-12-28",
      "latest": {
        "mean": 2.11,
        "median": 2.10,
        "high": 2.25,
        "low": 1.96,
        "stddev": 0.07,
        "analyst_count": 38,
        "updated_at": "2025-09-22T13:58:20Z"
      },
      "point_in_time": {
        "available": true,
        "first_seen": "2024-10-01",
        "last_seen": "2025-09-22"
      }
    },
    {
      "measure": "REVENUE",
      "frequency": "FQ",
      "fiscal_year": 2025,
      "fiscal_period": "Q1",
      "period_end_date": "2024-12-28",
      "latest": {
        "mean": 118500000000,
        "median": 118200000000,
        "high": 121000000000,
        "low": 114900000000,
        "stddev": 1600000000,
        "analyst_count": 36,
        "updated_at": "2025-09-22T13:58:20Z"
      }
    }
  ]
}

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[
  {
    "ticker": "AAPL",
    "measure": "EPS",
    "gaap_flag": "Non-GAAP",
    "frequency": "FQ",
    "fiscal_year": 2025,
    "fiscal_period": "Q1",
    "as_of": "2025-08-01",
    "stats": { "mean": 2.07, "median": 2.06, "high": 2.20, "low": 1.94, "stddev": 0.06, "analyst_count": 37 }
  },
  {
    "ticker": "AAPL",
    "measure": "EPS",
    "gaap_flag": "Non-GAAP",
    "frequency": "FQ",
    "fiscal_year": 2025,
    "fiscal_period": "Q1",
    "as_of": "2025-09-22",
    "stats": { "mean": 2.11, "median": 2.10, "high": 2.25, "low": 1.96, "stddev": 0.07, "analyst_count": 38 }
  }
]

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[
  {
    "ticker": "AAPL",
    "measure": "EPS",
    "gaap_flag": "Non-GAAP",
    "frequency": "FQ",
    "fiscal_year": 2025,
    "fiscal_period": "Q1",
    "as_of": "2025-08-01",
    "stats": { "mean": 2.07, "median": 2.06, "high": 2.20, "low": 1.94, "stddev": 0.06, "analyst_count": 37 }
  },
  {
    "ticker": "AAPL",
    "measure": "EPS",
    "gaap_flag": "Non-GAAP",
    "frequency": "FQ",
    "fiscal_year": 2025,
    "fiscal_period": "Q1",
    "as_of": "2025-09-22",
    "stats": { "mean": 2.11, "median": 2.10, "high": 2.25, "low": 1.96, "stddev": 0.07, "analyst_count": 38 }
  }
]

Design Notes

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Low Latency: sub-200ms targets via indexed time-series storage.

Developer-First JSON: consistent keys across measures and periods.
Backtest-Ready: PIT queries to avoid look-ahead bias; stable identifiers.
Quality Controls: outlier trimming options (trim_pct, optional z-score caps).

If you’d like, I can tailor this to your exact routing (paths, auth), add pagination notes, and include an OpenAPI snippet.

Overview

What you get

Example Use Cases

Endpoint Examples

Schema

Design Notes