Aggregate Transactions

Introduction

This endpoint computes a per-bucket median multiple for a single cohort of deals.

You choose one metric (such as ev_revenue or valuation), slice the cohort by time_bucket (month, quarter, year, or a single overall bucket), and scope it with the same filters vocabulary as the transactions list.

The response returns {bucket, n, median, q1, q3} arrays plus the methodology constants used, so you can chart valuation trends or benchmark a comparable set without pulling and reducing the raw deals yourself.

Set up

Endpoint

POST https://multiples.vc/api/private/v1/transactions/aggregate

Request

Send a JSON body with the metric to aggregate, an optional time bucket, and an optional filters object that defines the cohort. Only metric is required. Without filters, the cohort is every deal in the default date window.

Median EV/Revenue per quarter across M&A deals:

{
  "metric": "ev_revenue",
  "time_bucket": "quarter",
  "filters": {
    "deal_type": ["M&A"],
    "date_from": "2021-01-01",
    "date_to": "2025-12-31"
  }
}

Median EV/Revenue per year for European Growth/Venture rounds:

{
  "metric": "ev_revenue",
  "time_bucket": "year",
  "filters": {
    "deal_type": [
      "Growth",
      "Venture"
    ],
    "target_region": [
      "Western Europe",
      "Northern Europe"
    ],
    "date_from": "2020-01-01",
    "date_to": "2024-12-31"
  }
}

Top-level parameters:

field	type	description
`metric`	string (required)	The value aggregated per bucket. One of `ev_revenue`, `ev_ebitda`, `valuation`, `raised`, `revenue`, `ebitda`.
`time_bucket`	string	How deals are grouped over time: `month`, `quarter`, `year`, or `none`. Defaults to `none` (one overall bucket).
`filters`	object	Cohort definition. Accepts the full `/transactions` filter vocabulary (below).

filters fields (all optional):

field	type	description
`id`	array of uuid	Match specific deals by ID.
`target_id`	array of uuid	Restrict to deals whose target is one of these companies.
`investor_id`	array of uuid	Match deals where any of these companies took part in any role: lead investor, other investor or buyer.
`deal_type`	array of string	One or more of `Early`, `Growth`, `M&A`, `Public listing`, `Secondary`, `Venture`. `Write-down` and its subtypes `Impairment` and `Insolvency` are accepted but match nothing: a write-down is a valuation event, not a transaction (see Transaction filters and vocabulary).
`deal_subtype`	array of string	One or more of `Angel`, `ICO`, `PE buyout`, `Pre-seed`, `Secondary - private`, `Secondary - public`, `Seed`, `Series A`-`Series J`, `Strategic M&A`, `Strategic investment`, `Undisclosed stage`.
`date_from`	date (`YYYY-MM-DD`)	Earliest deal date to include. Defaults to 5 years before today when omitted.
`date_to`	date (`YYYY-MM-DD`)	Latest deal date to include. Defaults to today when omitted.
`valuation_min` / `valuation_max`	number	Bound deal valuation (millions USD).
`raised_min` / `raised_max`	number	Bound amount raised.
`revenue_min` / `revenue_max`	number	Bound deal revenue.
`ebitda_min` / `ebitda_max`	number	Bound deal EBITDA.
`ev_revenue_min` / `ev_revenue_max`	number	Bound the EV/Revenue multiple.
`ev_ebitda_min` / `ev_ebitda_max`	number	Bound the EV/EBITDA multiple.
`target_country`	array of string	Target country (ISO 3166-1 alpha-3 codes).
`target_region`	array of string	Target region (e.g. `North America`, `Western Europe`).
`target_verticals`	array of string	Match deals whose target operates in any of these verticals.
`target_themes`	array of string	Match deals whose target maps to any of these themes.
`target_client_focus`	array of string	Match by target client focus (e.g. `B2C`).
`target_revenue_model`	array of string	Match by target revenue model.
`target_company_type`	array of string	Match by target company type.
`updated_at`	date-time	Change-feed checkpoint: only deals updated at or after this timestamp. Setting it also includes soft-deleted deals.
`include_deleted`	boolean	Include soft-deleted deals. Defaults to `false`.

Tag filters accept the same {"all": ["A", "B"]} shape as POST /transactions: the target must carry every listed value. A plain array still matches any listed value. An unknown value returns 400 and names the closest matches.

The accepted filter fields, metric enums, time buckets, and methodology constants are also discoverable at runtime via GET /lookup/transactions.

Response

Each data entry is one bucket. Buckets with no deals (n: 0) are returned so charts have explicit gaps. A bucket with fewer than 5 deals after outlier trimming (small_n_threshold) is returned exactly like an empty one: n: 0, with median, q1 and q3 set to null. Example for median EV/Revenue per year for European Growth/Venture rounds (the second request above):

{
  "data": [
    {
      "bucket": "2020",
      "n": 42,
      "median": 10.7718120805369,
      "q1": 5.55991124260355,
      "q3": 17.9166666666667,
      "warning": null
    },
    {
      "bucket": "2021",
      "n": 90,
      "median": 9.88470557582074,
      "q1": 5,
      "q3": 18.7724830128347,
      "warning": null
    },
    {
      "bucket": "2022",
      "n": 68,
      "median": 12.5009557522124,
      "q1": 6.70950704225352,
      "q3": 22.0485210171251,
      "warning": null
    },
    {
      "bucket": "2023",
      "n": 24,
      "median": 6.76799805385352,
      "q1": 4.93762963252847,
      "q3": 11.3538205980066,
      "warning": null
    },
    {
      "bucket": "2024",
      "n": 37,
      "median": 9.5,
      "q1": 4.46632478632479,
      "q3": 17,
      "warning": null
    }
  ],
  "meta": {
    "metric": "ev_revenue",
    "time_bucket": "year",
    "total_deals": 284,
    "outliers_trimmed": 23,
    "methodology": {
      "small_n_threshold": 5,
      "outlier_rule": "iqr_1.5",
      "default_date_range_years": 5,
      "empty_buckets_returned": true,
      "date_range": {
        "from": "2020-01-01",
        "to": "2024-12-31"
      }
    }
  }
}

When time_bucket is none, data holds a single entry whose bucket is null, covering the whole cohort:

{
  "data": [
    { "bucket": null, "n": 211, "median": 390, "q1": 100.05, "q3": 1000, "warning": null }
  ],
  "meta": {
    "metric": "valuation",
    "time_bucket": "none",
    "total_deals": 242,
    "outliers_trimmed": 31,
    "methodology": {
      "small_n_threshold": 5,
      "outlier_rule": "iqr_1.5",
      "default_date_range_years": 5,
      "empty_buckets_returned": true,
      "date_range": { "from": "2021-06-15", "to": "2026-06-15" }
    }
  }
}

Fields

data[] - one object per bucket:

field	type	description
`bucket`	string \| null	The bucket label: `YYYY-MM` (month), `YYYY-Qn` (quarter), or `YYYY` (year). `null` when `time_bucket` is `none`.
`n`	integer	Number of deals in the bucket after outlier trimming. `0` when the bucket is empty or below `small_n_threshold`.
`median`	number \| null	Median of the chosen metric for the bucket. `null` when `n` is `0`.
`q1`	number \| null	First quartile (25th percentile) of the metric. `null` under the same conditions as `median`.
`q3`	number \| null	Third quartile (75th percentile) of the metric. `null` under the same conditions as `median`.
`warning`	string \| null	Currently always `null`.

meta - context and methodology:

field	type	description
`metric`	string	The metric that was aggregated (echoes the request).
`time_bucket`	string	The time bucket that was applied (echoes the request).
`total_deals`	integer	Matching deals across reported buckets, before outlier trimming. Buckets below `small_n_threshold` are not counted.
`outliers_trimmed`	integer	Deals removed by the outlier rule in reported buckets. Buckets below `small_n_threshold` are not counted.
`methodology`	object	Constants used for this aggregation (see below).
`usage`	object	Always `{ "records_billable": 0, "records_charged": 0 }`: aggregates are not charged. See Rate Limits.

meta.methodology:

field	type	description
`small_n_threshold`	integer	Buckets with fewer than this many deals after trimming are returned like empty ones: `n: 0` and `null` statistics.
`outlier_rule`	string	The outlier-trimming rule applied, e.g. `iqr_1.5` (values outside 1.5×IQR of the quartiles are dropped).
`default_date_range_years`	integer	Lookback window (in years) used when `date_from`/`date_to` are omitted.
`empty_buckets_returned`	boolean	Whether zero-deal buckets are emitted in `data` (so time series have explicit gaps).
`date_range`	object	The effective date window applied, with `from` and `to` (`YYYY-MM-DD`).
`date_range.from`	string (date)	Start of the effective window (inclusive).
`date_range.to`	string (date)	End of the effective window (inclusive).

Introduction

Set up

On this page