Market measure by dimension breakdown

Request Body

application/json

TypeScript Definitions

Use the request body type in TypeScript.

advancedFilters?|||

filters?|||

flatFilters?

measure?MarketChartMeasure

Which metric to compute. Every field-backed measure is sentinel-guarded: the source encodes unknown values as an out-of-range fill, so values outside the measure's plausible range are dropped before it is aggregated. Ranges: volume 0–100,000,000; avgRate 0–25; avgLoanAmount 0–100,000,000; avgCreditScore 300–850; avgLTV 0–1,000; avgDTI 0–1,000; avgIncome 0–100,000,000; avgAppraisedValue 0–100,000,000; avgPurchasePrice 0–100,000,000; avgDtiFront 0–1,000; avgCombinedLtv 0–1,000; avgLoanTerm 0–1,200; originatedVolume 0–100,000,000. units and originatedUnits are document counts and are not guarded. Each response reports how many documents its guard excluded, so a mean taken over 98% of the data can be told apart from one taken over 60%. NOTE on population: units and volume cover loan APPLICATIONS of every outcome — denials, withdrawals and secondary-market purchases included — while originatedUnits and originatedVolume cover originations only. Which metric each bar reports — and, with one exception, NOT what the bars are ranked by. Ranking is by transaction count unless you explicitly pass volume, which ranks by dollars instead. Defaults to units, so "top originators" means the busiest rather than the biggest. The average measures deliberately rank by count too: ordering a high-cardinality slice by its own mean returns whichever one-transaction buckets happened to score highest, so "top zips by average rate" would mean "zips with one weird loan" — ranked by count it means "the busiest zips, with their rates". Every bucket publishes its own count, so the sample size behind a value is never implicit.

Default"units"

Value in

"volume" | "units" | "avgRate" | "avgLoanAmount" | "avgCreditScore" | "avgLTV" | "avgDTI" | "avgIncome" | "avgAppraisedValue" | "avgPurchasePrice" | "avgDtiFront" | "avgCombinedLtv" | "avgLoanTerm" | "originatedUnits" | "originatedVolume"

period?Period

Value in

"2017" | "2018" | "2019" | "2020" | "2021" | "2022" | "2023" | "2024" | "2025" | "2026" | "last3Months" | "last6Months" | "last12Months" | "last14Months" | "last16Months" | "last18Months" | "last24Months" | "yearToDate" | "allTime"

slice*MarketSliceDimension

Value in

"state" | "county" | "metro" | "zip" | "loanPurpose" | "loanType" | "propertyType" | "occupancyType" | "amortizationType" | "channel" | "borrowerGeneration" | "firstTimeHomebuyer" | "veteranIndicator" | "hmdaActionTaken" | "selfEmployed" | "currentHomeOwner"

Response Body

`application/json`

curl -X POST "https://example.com/v1/market/analytics/chart" \  -H "Content-Type: application/json" \  -d '{    "slice": "state"  }'

{
  "data": [
    {
      "count": 0,
      "excluded": 0,
      "id": "string",
      "label": "string",
      "segments": [
        {
          "label": "string",
          "value": 0
        }
      ],
      "value": 0
    }
  ],
  "measure": "string",
  "segment": "string",
  "slice": "string"
}

{
  "error": "string"
}

{
  "error": "string"
}

{
  "error": "string"
}

{
  "error": "string"
}

{
  "error": "string",
  "limit": 0,
  "size": 0
}

Market measure by dimension breakdown

Authorization

Request Body

Response Body

200application/json

400application/json

401application/json

403application/json

404application/json

413application/json

`application/json`

`application/json`

`application/json`

`application/json`

`application/json`

`application/json`