API Documentation

List entities with optional filtering.

Query Parameters

kind=snapshot (default) — the daily-captured consensus: EPS and revenue avg/low/high, analyst counts, growth, the EPS trend 7/30/60/90 days ago and revision counts. One row per target fiscal period (estimate_date) per capture day (captured_at, the honest as-of). Snapshots exist from 2026-02-19 only. Daily capture began then, and no licensed vendor sells historical consensus snapshots — that floor is a real ceiling, not a backfill gap.

kind=pre_report — the consensus at each report, as an as-of-dated observation series: as_of = report date, target_period = the reported quarter, eps_estimate beside eps_actual. Quarterly, one observation per report, history to roughly 2004. It is not a forward-year snapshot and not a daily series.

as_of, start and end bound the observation date (captured_at for snapshots, the report date for pre-report); target_period keeps one target fiscal period. Every response's meta states both floors and which series you are holding. Pages never split an observation date, so the date cursors are safe to walk.

Stock splits, dividends, and other corporate actions.

Query Parameters

Get ETF or mutual fund holdings.

{
  "data": [
    {
      "name": "Apple Inc",
      "ticker": "AAPL",
      "shares": 169547850,
      "market_value": 33659841250,
      "percentage": 7.12
    }
  ],
  "meta": {
    "fund_ticker": "SPY",
    "report_date": "2026-01-15"
  }
}

Compare multiple entities on key metrics.

Parameters

Filters (all optional): fund_type (etf | mutual_fund), category, fund_family, asset_class, max_expense_ratio, q (name or ticker), status (active | dead | all — default active; pass dead or all for the survivorship-free universe), limit (default 50, max 200), offset.

Expense ratios are fractions — max_expense_ratio=0.001 means 0.10%, and every response echoes meta.expense_ratio_units. The filter caps the ETF net_expense_ratio and the mutual-fund expense_ratio, while the expense_ratio shown on each row is the gross figure — so a fund with acquired-fund fees can display a value above your cap. Unknown parameters are never silently ignored: they come back in meta.ignored_params.

For a full walk of the universe pass order=id and follow meta.next_cursor — stable keyset paging that will not skip or repeat rows.

{
  "data": {"funds": [
    {"ticker": "SPY", "name": "SPDR S&P 500 ETF Trust", "type": "etf",
     "category": "Large Blend", "expense_ratio": 0.000945,
     "total_assets": 624318000000.0}
  ]},
  "meta": {"count": 1, "has_more": true,
           "expense_ratio_units": "fraction (0.001 = 0.1%)"}
}

Returns family, category, expense ratios (gross, net, and net-of-acquired-fund-fees), yield, inception, AUM from SEC N-PORT, plus style_box, synapse_category and N-CEN structural_flags (money-market, target-date, leveraged/inverse, fund-of-funds).

These classifications are our own. synapse_category, style_box and synapse_star_rating are computed in-house from SEC filings and our own prices. They are first-party — ours, computed from our own inputs, and not interchangeable with any industry-standard classification.

GET /funds/{identifier}/classification   portfolio weight breakdowns
GET /funds/{identifier}/distributions   dividends + capital gains
GET /funds/categories                   the category vocabulary + counts

Parameters

adjustment: raw (NAV only) · adjusted (default, vendor total return) · total_return / pit (self-computed, no look-ahead). frequency=monthly resamples to month-end server-side. start, end, limit (default 10000, max 100000; 0 = all rows within your tier's historical window — Free 1 year, Developer 5 years, Quant full history), offset, order. meta.tier_clipped and meta.tier_floor_date report when that window truncated your result.

Windowing

The window anchors to the end you pinned. With start, limit bounds the earliest N rows in range and you page forward with meta.next_start. Without start, you get the most-recent N and page backward with meta.next_end. order only re-arranges the page — it never changes which rows are selected.

Exception: adjustment=total_return|pit withholds both cursors. The PIT index re-bases at the filtered start, so following a cursor would splice two different bases; page that mode with offset instead.

{
  "data": [{"date": "2024-01-02", "nav": 100.0, "nav_raw": 100.0}],
  "meta": {"ordering": "date_asc", "window_anchor": "start",
           "next_start": "2024-02-15", "next_end": null,
           "has_more": true, "frequency": "daily"}
}

as_of=YYYY-MM-DD returns the latest portfolio that was public on or before that date — cut on filing date, not report date, so a backtest never sees a portfolio before it was filed. limit default 500 (max 5000), offset.

Each position carries the issuer ticker, country, shares/par, market value, pct_of_nav, and sector — the issuer's synapse_sector (first-party, derived from the issuer's SEC SIC code) for equities, a deterministic bond segment for fixed income and cash, and null where we cannot classify the position honestly. The first page also carries meta.sector_allocation, whole-portfolio weights. Fixed income and cash resolve to their own segments (Treasury, Agency, Corporate Bond, Municipal, Sovereign, Bank Loan, Cash) from the position's own N-PORT fields, so a bond fund gets a meaningful breakdown rather than one blob; only positions we genuinely cannot classify roll into Unclassified, keeping the weights a true fraction of NAV.

Units differ between the two holdings endpoints — do not copy values between them. Here pct_of_nav is a fraction (0.0712 = 7.12%). The legacy /holdings/{identifier} returns the same quantity as percentage, multiplied by 100 (7.12).

{
  "data": [{"name": "Apple Inc", "ticker": "AAPL", "sector": "Information Technology",
            "shares_or_par": 178000000, "market_value": 33900000000.0,
            "pct_of_nav": 0.0712}],
  "meta": {"report_date": "2021-06-30", "filing_date": "2021-08-27",
           "point_in_time": true, "total_holdings": 503,
           "sector_allocation": [{"sector": "Information Technology", "weight": 0.2841}]}
}

Returns, volatility and max drawdown are decimals (0.12 = 12%; max_drawdown is negative, so -0.34 is a 34% drawdown). Sharpe is a plain dimensionless ratio, not a percentage. expense_percentile is a fraction 0–1 within category, where lower is cheaper.

synapse_star_rating is our own: the within-category percentile of the Sharpe ratio from our NAV history. It is a first-party rating — ours, computed from our own data, and not interchangeable with any industry-standard score. It is honestly null for young funds and thin categories — meta.coverage tells you which, so render “—” rather than zero. A fund with no ratings row at all returns data: null and meta.available: false (with no coverage block) — check that first.

Use POST /funds/ratings/batch to fetch many funds in one call.

Parameters: action_type, limit (default 100, max 500), offset.

Splits are served only when arithmetically verified against the raw price series — a real 1-for-N reverse makes the per-share value jump about N×. Regex or model confidence alone is never enough. That is a deliberate precision floor: recall is bounded by that series' coverage, so a real split we cannot verify is withheld rather than served wrong.

Ratios are (ratio_num, ratio_den) = (new, old) shares; a reverse split is ratio_num < ratio_den. Today only splits are extracted as structured actions. Liquidations, mergers and name/ticker/fee changes exist so far as captured raw filings and are not yet in this feed.

Filters

Required — at least one of ticker (issuer) or insider (CIK, or a name). Optional: code · is_10b5_1 · start / end · limit (default 50, max 200) · offset.

Transaction codes

The common ones: S open-market sale · P open-market purchase · A grant or award · M option exercise · F shares withheld for tax · G gift · C conversion. Other SEC codes appear in the data and are returned unfiltered; the parameter accepts any single letter and is not validated against a whitelist.

Two things that will bite you

start/end and the ordering apply to transaction_date — the trade date, not filing_date, the date the market learned of it. For a point-in-time study, filter on the filing_date field in the returned rows.

Rows are newest-first and there is no order parameter — the opposite of /prices and /funds/{id}/nav, which are oldest-first. Sort before computing anything sequential.

is_10b5_1 is tri-state: true, false, or null. Null is honest and means the SEC checkbox did not exist for that filing — it is never silently reported as false. The flag was introduced in 2023, so it is null for essentially everything before then. It is declared at the filing level and denormalized onto every row of that form — it tells you the filing asserted Rule 10b5-1(c) reliance, not that this specific line did.

Current beneficial ownership of non-derivative (Table I) positions only — options and RSUs are not included. One row per (insider, security class, direct/indirect), so someone holding common stock directly and also through a trust appears as two rows; sum them yourself for a person-level total. Ordered by shares_owned descending, limit default 100 (max 500).

shares_owned is a raw share count, not a percentage of the company. as_of is per-row staleness — the transaction date of the most recent non-superseded filing for that position, falling back to period-of-report then filing date. It is a trade date, not a query date. This endpoint is current-state only; it has no as_of parameter.

IPO lock-up expiry calendar extracted from SEC 424B4 final prospectuses — the dates on which insider shares become sellable. The lock-up period is model-extracted from the prospectus body and every row carries extraction_confidence; expiry = prospectus date + lock-up days. Coverage is recent IPOs with live or upcoming lock-ups.

as_of=YYYY-MM-DD (default today), limit (default 0 = the full book, max 5000), offset.

This route rejects unknown parameters with a 400 rather than ignoring them, which is stricter than the rest of the API. Two consequences: authenticate with the X-API-Key header (a ?api_key= query parameter is a 400 here), and ?envelope=false is rejected as unrecognized — send Accept: application/json+raw instead if you want an unenveloped response here.

weight is a fraction (0.002914 = 0.2914%) and is the weight at addition, not a live weight. It is populated for SD2000 only — SPX, NDX and DJI return weight: null and, despite meta.ordering = weight_desc, fall through to alphabetical ticker order.

GET /indexes lists which symbols actually carry membership data, with each index's provenance. SD2000 is our own rules-based US small-cap index, reconstituted annually with real add and remove history — it is not the Russell 2000 and is not derived from it.

{
  "data": [{"ticker": "ACLS", "synapse_id": "…", "weight": 0.002914,
            "added_date": "2021-06-25", "is_synthetic_added_date": false}],
  "meta": {"index_symbol": "SD2000", "asof": "2022-06-30",
           "ordering": "weight_desc"}
}

List all available economic series with optional category filter.

Treasury yield curve with spreads and inversion detection.

{
  "data": {
    "date": "2026-01-24",
    "yields": {
      "1M": 5.25, "3M": 5.30, "6M": 5.20,
      "1Y": 5.00, "2Y": 4.50, "5Y": 4.20,
      "10Y": 4.10, "30Y": 4.30
    },
    "spread_2_10": -40,
    "is_inverted": true
  }
}

Aggregated market indicators for a specific date. Perfect for backtesting context.

Rate Limit Headers