API documentation.

Alphanume exposes every dataset through a single, query-parameter–based REST API. This page walks through account setup, authentication, and the request pattern shared by all endpoints.

Get Pro or Enterprise Access

For new API access, subscribe to Pro at the sign-up page, or contact the data team for Enterprise access. After registering for Pro and setting your password, your API key will be emailed to you automatically. Existing users can upgrade through their account.

Base URL

All Alphanume API requests are made against:

https://api.alphanume.com/v1

Example Request

The API follows a simple, query-parameter–based request structure. Below is a sample request to the Historical Market Cap endpoint:

import requests

url = "https://api.alphanume.com/v1/historical-market-cap"
params = {
    "ticker": "AAPL",
    "date": "2026-02-06",
    "api_key": "alp_abc123"
}

response = requests.get(url, params=params)
data = response.json()

print(data)

curl "https://api.alphanume.com/v1/historical-market-cap?ticker=AAPL&date=2026-02-06&api_key=alp_abc123"

Header-Based Auth

You can also pass your API key via the X-API-Key header instead of a query parameter.

curl "https://api.alphanume.com/v1/historical-market-cap?ticker=AAPL&date=2026-02-06" \
  -H "X-API-Key: alp_abc123"

Response Format

Responses are returned in JSON and are designed to be immediately usable in research pipelines.

{
  "count": 1,
  "data": [
    {
      "date": "2026-02-06",
      "ticker": "AAPL",
      "market_cap": 4109599296360.0,
      "shares_outstanding": 14776353000.0
    }
  ]
}

General Pattern

All Alphanume endpoints follow the same structure:

GET /v1/{endpoint}?param1=value&param2=value&api_key=alphanume_api_key

This makes it easy to programmatically construct requests across datasets without learning new schemas.

Rate Limits

• Pro tier: 600 requests per minute
• Enterprise: limits agreed by contract
• Exceeding the limit returns HTTP 429

Next Steps

• Choose a dataset from the documentation library
• Review authentication and API key setup
• Integrate directly into your backtests or production systems

Alphanume runs a hosted MCP (Model Context Protocol) server that exposes the dataset catalog through callable tools. Connect it to Claude, Codex, Cursor, or any MCP client and query the datasets conversationally; the model constructs the calls, the server returns the same point-in-time data as the REST API.

In Claude and Codex there is no key to copy. Paste the server URL, sign in with the same Alphanume account you subscribe with, and the server resolves your key and tier for you.

Server URL

https://mcp.alphanume.com/mcp

The server speaks streamable HTTP, the current MCP transport standard, and authenticates over OAuth. Clients that cannot open a browser use the API key endpoint described further down.

Connect from Claude

This is the recommended path and takes about a minute.

1. Open Settings in Claude, then Connectors.
2. Click Add custom connector.
3. Paste https://mcp.alphanume.com/mcp as the remote MCP server URL and confirm.
4. Click Connect. Claude opens a browser window; sign in with your Alphanume account.
5. The Alphanume dataset tools are now available. Ask a question in plain language and the model calls them directly.

Connect from Codex

The Codex CLI adds the server and runs the same browser sign-in from two commands:

codex mcp add alphanume --url https://mcp.alphanume.com/mcp
codex mcp login alphanume

login opens your browser for the Alphanume sign-in and stores the token, so restarts and new sessions stay authorized. Confirm the server is registered with codex mcp list.

Connect from Cursor

Cursor connects with an API key rather than a browser sign-in. Add the server to ~/.cursor/mcp.json (or .cursor/mcp.json inside a project) and point it at the key endpoint:

{
  "mcpServers": {
    "alphanume": {
      "url": "https://mcp.alphanume.com/key/mcp",
      "headers": { "X-API-Key": "alp_YOUR_KEY" }
    }
  }
}

Other clients and scripts

Anything that cannot run a browser flow, including CI jobs, custom agents, and self-hosted tooling, uses the same key endpoint. Point the client at the URL and attach your key as an X-API-Key header; Authorization: Bearer alp_... is also accepted.

https://mcp.alphanume.com/key/mcp

Keys are issued at sign-up and are the same keys the REST API uses.

Endpoint Reference

Authentication

OAuth does not create a second account system. Signing in resolves the API key already attached to your Alphanume account, and every tool call runs under that key, so tiering, rate limits, and error messages are identical to the REST API. There is no separate MCP subscription.

• Signing in with a different Alphanume account uses that account's key and tier
• If your account has no key yet, tool calls return a clear error pointing you to alphanume.com rather than failing silently
• Revoking access in your client does not affect your REST API key

Access and Limits

• Pro tier: full history and the latest session, 600 requests per minute
• Enterprise: access and limits agreed by contract

Available Tools

One tool per dataset, matching the references in the documentation library:

• Equity selection: next-day movers, Quant Galore Momentum Index
• Index & volatility: SPX 0-DTE strike band, S&P 500 risk regime, IV/HV premium, IV/HV rank (52-week), vol-of-vol
• Earnings: implied vs realized move history
• Corporate events: dilution filings, shelf registrations, enriched de-SPAC events, corporate default events
• Regulatory & enforcement: SEC trading suspensions, cyber incidents, crypto enforcement actions
• Biotech & FDA: FDA response events, advisory committee votes
• Dividends: dividend capture
• Reference data: historical market cap (plus ticker coverage list), optionable tickers, ticker classification
• Alternative data: Wikipedia views, SEC filing intensity
• Utility: API status

Response Conventions

• Responses mirror the REST API: {"count": N, "data": [...]}
• Every data tool accepts max_rows (default 500); prefer narrowing date or ticker filters over raising it
• Volatility tools update intraday and settle after the close; pass only_final=true to restrict to settled values
• Large datasets paginate with cursor_date and cursor_ticker, returned as next_cursor when has_more is set

Short Locates tracks quoted fees and share availability for hard-to-borrow US stocks. A locate checks whether shares can be borrowed before a short sale. Each row represents one stock in one daily snapshot.

Why it's useful

• Estimate locate fees for a planned share quantity.
• Find stocks whose locate costs rose or available shares fell.
• Include observed locate costs and availability in short-selling research.

Endpoint

GET /v1/short-locates

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

Find morning quotes costing at least $5 to locate 100 shares:

import requests

url = "https://api.alphanume.com/v1/short-locates"
params = {"date": "2026-10-15", "slot": "am", "status": "offered", "min_cost_per_100": 5}
headers = {"X-API-Key": "YOUR_API_KEY"}
r = requests.get(url, params=params, headers=headers)
r.raise_for_status()
print(r.json())

curl "https://api.alphanume.com/v1/short-locates?date=2026-10-15&slot=am&status=offered&min_cost_per_100=5" \
  -H "X-API-Key: YOUR_API_KEY"

The hosted MCP tool is get_short_locates. It accepts the same filters and cursor values, plus max_rows to limit the MCP result. max_rows is not a REST parameter.

Request Parameters

• api_key: required unless supplied through the X-API-Key header.
• ticker: exact stock symbol, normalized to uppercase.
• slot: am or pm. Omit for both snapshots.
• status: one of the six results listed below.
• min_cost_per_100: inclusive minimum locate cost in USD per 100 shares, at least zero. Excludes rows without a price.

Filters are optional and combine with AND. Slot and status values are case-insensitive. Invalid values, conflicting date filters, and incomplete cursors return 400.

Date Filtering

• date: exact snapshot trading date, in YYYY-MM-DD format.
• date_gte / date_lte: inclusive date bounds.
• date_gt / date_lt: exclusive date bounds.

Dates use America/New_York. Do not combine date with range bounds. With no date filters, the endpoint returns history from October 8, 2026 onward.

Locate Status

• offered: shares were available with a quoted price.
• no_shares: no shares were available; quantity is zero. An indicative price may still be present.
• threshold: a Reg SHO threshold-list restriction prevented a locate in this snapshot.
• unavailable: no locate quote was available.
• corporate_action: a corporate action prevented a quote.
• error: another refusal prevented a quote.

Response Fields

Example Response

The ticker and values below are illustrative, not a live quote.

{
  "count": 1,
  "has_more": false,
  "next_cursor": null,
  "data": [
    {
      "date": "2026-10-15",
      "slot": "am",
      "snapshot_time_utc": "2026-10-15 11:45",
      "ticker": "EXAMPLE",
      "status": "offered",
      "price_per_share": 0.075,
      "cost_per_100": 7.5,
      "available_qty": 12000
    }
  ]
}

Response and Pagination

count is the number of rows on this page. REST pages contain up to 50,000 rows, ordered by newest date first, pm before am, then ticker alphabetically. There is no configurable REST page size.

When has_more is true, repeat the request with the same filters and all three values from next_cursor: cursor_date, cursor_slot, and cursor_ticker. The final page has has_more=false and next_cursor=null.

while r.json().get("has_more"):
    params.update(r.json()["next_cursor"])
    r = requests.get(url, params=params, headers=headers)
    r.raise_for_status()
    print(r.json())

Notes on Data Behavior

• Snapshots are scheduled at 11:45 UTC (am) and 17:30 UTC (pm) on trading days. These are 07:45 / 13:30 Eastern during daylight saving time and 06:45 / 12:30 during standard time.
• snapshot_time_utc records the actual snapshot time to the minute. Early snapshots can fall outside the regular schedule. It is shared across the snapshot, not a separate quote time for each stock.
• History begins October 8, 2026, with no earlier backfill. Use only snapshots already observed at your research decision time.
• Prices are null when no price is available. A null price is not a free locate. A price alone does not mean shares are available: use status=offered for available quotes. Quantity is zero for no_shares and null when no quantity was returned.
• Quotes can differ across brokers and change between snapshots. They do not reserve shares, confirm a borrow, or represent annual borrow rates or all short-selling costs.
• Coverage is limited to tracked hard-to-borrow stocks. An absent ticker does not establish that shares are available or free to locate.

The Next-Day Movers dataset provides a daily, model-ranked collection of equities most likely to experience large price moves in the following trading session.

Each observation contains one of the top names selected from a universe of liquid optionable equities, based on a predictive model designed to identify securities with elevated next-day realized movement potential. Behind the scenes, the model evaluates features such as implied volatility, realized volatility, and related volatility structure information to rank candidates by expected next-day movement.

All observations are stored historically and remain fixed once published, allowing the dataset to be used safely in systematic research and backtesting workflows without lookahead bias.

Why it's useful

• Identify equities most likely to experience outsized next-day moves
• Build directional or non-directional volatility trading strategies
• Screen for high-movement candidates before the next session opens
• Study the relationship between implied volatility, realized volatility, and future movement
• Backtest systematic workflows built around next-day mover selection

Endpoint

GET /v1/next-day-movers

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

import requests

url = "https://api.alphanume.com/v1/next-day-movers"
params = {"api_key": "alp_abc123"}

r = requests.get(url, params=params)
print(r.json())

curl "https://api.alphanume.com/v1/next-day-movers?api_key=alp_abc123"

Request Parameters

• api_key (required): your Alphanume API key.
• date: observations for a single trading date (YYYY-MM-DD).
• date_gte / date_lte / date_gt / date_lt: filter by date range. Any logically valid combination is accepted.

If no date filters are provided, all available historical observations are returned.

Response Format

{
  "count": 2,
  "data": [
    { "date": "2026-03-09", "ticker": "AAOI", "return": 8.92, "absolute_move": 8.92 },
    { "date": "2026-03-09", "ticker": "FIGR", "return": 21.29, "absolute_move": 21.29 }
  ]
}

Forward Return Availability

For the most recent observation date, return and absolute_move will appear as null. These fields represent realized movement during the following trading session. Until a full trading day has completed after the selection date, the outcome cannot yet be calculated. Once the next session has closed, the values are populated automatically and remain fixed thereafter.

// Most recent date
{ "date": "2026-03-10", "ticker": "NVDA", "return": null, "absolute_move": null }

// Historical observation
{ "date": "2026-03-09", "ticker": "FIGR", "return": 21.29, "absolute_move": 21.29 }

Response Fields

Notes on Data Behavior

• New selections are generated daily at 3:30 PM (America/New_York Time)
• Historical observations are stored point-in-time
• Once published, observations are not retroactively altered
• Dates are returned as YYYY-MM-DD
• Results are ordered by date DESC

Pre-Market Drop Risk is a daily model-ranked list of US microcaps with elevated probability of falling at least 5% from the regular-session open to the close. Only names that traded actively before 09:00 ET and were classified as microcaps are eligible to be scored.

Each row carries the model probability and daily rank, the pre-market price and return path available at the cutoff, lagged return context, point-in-time market cap, and outcomes that fill after the relevant horizon matures. Sub-$1 names are included and labeled rather than removed.

Why it's useful

• Prioritize a short or risk-review queue before the opening auction
• Compare hit rates across probability, rank, price, and market-cap cuts
• Study sub-$1 and $1-and-up cohorts separately
• Measure how the signal behaves at the close and over later sessions
• Join a pre-open ranking to independent news, liquidity, and borrow systems

Endpoint

GET /v1/premarket-drop-risk

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

import requests

url = "https://api.alphanume.com/v1/premarket-drop-risk"
params = {
    "date": "2026-08-28",
    "min_prob": 0.70,
    "max_rank": 5,
    "api_key": "alp_abc123"
}

r = requests.get(url, params=params)
print(r.json())

curl "https://api.alphanume.com/v1/premarket-drop-risk?date=2026-08-28&min_prob=0.70&max_rank=5&api_key=alp_abc123"

Request Parameters

• api_key (required): a Pro Alphanume API key.
• ticker (optional): ticker symbol, case-insensitive exact match.
• date (optional): exact signal date in YYYY-MM-DD format. It cannot be combined with date range parameters.
• min_prob (optional): minimum prob_drop from 0 through 1.
• min_price / max_price (optional): inclusive bounds on px_at_trading, each at least 0. max_price must be greater than or equal to min_price.
• sub_dollar (optional): 1 keeps names below $1 at the cutoff; 0 keeps $1 and above.
• max_rank (optional): positive integer upper bound on rank_for_date. For example, 5 returns the top five names per day.
• cursor_date / cursor_rank (optional, together): values from the prior response's next_cursor. Both must be provided or neither.

Date Filtering

Date filters apply to the model's signal date. Supported range parameters are:

• date_gte
• date_lte
• date_gt
• date_lt

Any logically valid combination is accepted.

Response Fields

Example Response

{
  "count": 1,
  "has_more": false,
  "next_cursor": null,
  "data": [
    {
      "date": "2026-08-28",
      "ticker": "XYZ",
      "rank_for_date": 1,
      "prob_drop": 0.781432,
      "px_at_trading": 0.83,
      "sub_dollar": 1,
      "premarket_return_at_cutoff": 18.57,
      "t_0": 0.0,
      "t_1": 0.0,
      "t_2": 4.29,
      "t_3": 7.14,
      "t_4": 9.43,
      "t_5": 11.86,
      "t_6": 13.57,
      "t_7": 16.14,
      "t_8": 17.43,
      "t_9": 18.57,
      "return_lag_1y": -63.21,
      "return_lag_1m": -1.84,
      "return_lag_5d": 22.06,
      "market_cap": 17640000.0,
      "intraday_return_pct": -8.43,
      "return_lead_1d": -6.18,
      "return_lead_5d": -14.72,
      "return_lead_30d": null
    }
  ]
}

Notes on Data Behavior

• Results are ordered by date DESC, rank_for_date ASC
• Responses are capped at 50,000 rows. When has_more is true, pass next_cursor's date and rank back as cursor_date and cursor_rank
• The target is an unadjusted open-to-close return of -5% or worse, not any negative return
• t_0 through t_9 are cumulative, not separate 30-minute buckets. When no print exists at or before a mark, the value is 0 rather than null
• premarket_return_at_cutoff is identical to t_9
• Outcome fields remain null until their horizons mature, and can stay null after maturity when a halt or delisting leaves no required exchange print
• Borrow availability, locate fees, execution costs, internal model metadata, publication timestamps, print counts, and pre-market dollar volume are not served fields

The Quant Galore Momentum Index provides the historical and live constituents of a rules-based, cross-sectional equity momentum strategy.

Each observation represents a stock included in the 10-stock monthly basket on a specific rebalance date, along with its rank within that basket. This dataset is designed for systematic traders, researchers, and allocators who want clean, point-in-time access to a maintained momentum index without reconstructing the full ranking pipeline.

Why it's useful

• Replicate or track the Quant Galore Momentum strategy
• Run independent performance attribution or turnover analysis
• Study cross-sectional momentum concentration effects
• Measure post-rebalance drift and decay
• Build overlays (options, hedging, leverage) on top of a rules-based equity core

Index Overview

• Universe: Deeply liquid U.S. equities with at least six consecutive weeks of listed weekly option expirations
• Construction: Cross-sectional momentum ranking
• Basket Size: Top 10 stocks
• Rebalance Frequency: Monthly
• Ranking: Highest momentum = rank 1

The dataset reflects the actual basket at that specific date, not a reconstructed or retroactively altered list.

Endpoint

GET /v1/quant-galore-momentum-index

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

import requests

url = "https://api.alphanume.com/v1/quant-galore-momentum-index"
params = {"api_key": "alp_abc123"}

r = requests.get(url, params=params)
print(r.json())

curl "https://api.alphanume.com/v1/quant-galore-momentum-index?api_key=alp_abc123"

Request Parameters

• api_key (required): your Alphanume API key.
• date (optional): return basket constituents for a single rebalance date (YYYY-MM-DD). Cannot be combined with range parameters.
• date_gte / date_lte / date_gt / date_lt (optional): filter by rebalance date range. Any logically valid combination is accepted.

Validation rules:

• date_lte must be ≥ date_gte
• date_lte must be > date_gt
• date_lt must be > date_gte

If no date filters are provided, all available historical observations are returned (subject to tier-based limits).

Response Format

{
  "count": 970,
  "data": [
    { "date": "2026-02-02", "ticker": "BE", "rank": 10 },
    { "date": "2026-02-02", "ticker": "IREN", "rank": 9 }
  ]
}

Response Fields

Notes on Data Behavior

• Constituents update monthly upon rebalance at 4:05 PM (America/New_York Time)
• Each rebalance date contains exactly 10 stocks
• Rankings are deterministic and stored historically
• Historical baskets remain fixed once published
• Results are ordered by date DESC
• Dates are returned in YYYY-MM-DD format
• Invalid date formats return a 400 response
• Mixing date with range parameters returns a 400

The S&P 500 0-DTE Strike Band dataset provides a daily, model-derived strike range representing the expected intraday price bounds for the S&P 500 index during the current trading session.

Each observation contains a lower and upper strike level that define the range in which the index is expected to remain with high probability through the close of the same-day (0-DTE) options cycle. The band is calculated using forward-looking implied probability distributions and broader market risk factors, and is designed to assist traders in strike selection and risk management for intraday option strategies.

All observations are point-in-time and stored historically. Once published, values are never retroactively altered, allowing the dataset to be used safely in systematic research and backtesting workflows.

Why it's useful

• Identify statistically informed strike levels for same-day SPX options
• Structure intraday spreads, condors, or volatility-selling strategies
• Quantify expected index movement using implied probability information
• Filter or validate discretionary strike selection decisions
• Analyze historical containment probabilities for intraday index ranges

Endpoint

GET /v1/spx-0dte-strike-band

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

import requests

url = "https://api.alphanume.com/v1/spx-0dte-strike-band"
params = {"api_key": "alp_abc123"}

r = requests.get(url, params=params)
print(r.json())

curl "https://api.alphanume.com/v1/spx-0dte-strike-band?api_key=alp_abc123"

Request Parameters

• api_key (required): your Alphanume API key.
• date: strike band for a single trading date (YYYY-MM-DD).
• date_gte / date_lte / date_gt / date_lt: filter by date range. Any logically valid combination is accepted.

If no date filters are provided, all available historical observations are returned (subject to tier-based limits).

Response Format

{
  "count": 1,
  "data": [
    {
      "date": "2026-03-05",
      "lower_strike": 6740,
      "upper_strike": 6880,
      "instrument": "SPX"
    }
  ]
}

Response Fields

Strike Band Definition

The lower_strike and upper_strikevalues represent the model-derived strike range within which the S&P 500 index is expected to remain through the close of the same-day options session. The band is calculated using forward-looking implied probability distributions, realized volatility data, and broader market risk factors. Strikes are rounded to the nearest listed SPX option increment.

Notes on Data Behavior

• New observations are published daily at 10:30 AM (America/New_York Time)
• Values are point-in-time and reflect information available at calculation time
• Historical strike bands remain fixed once published
• Dates are returned as YYYY-MM-DD
• Results are ordered by date DESC

The S&P 500 Risk Regime dataset provides a daily, point-in-time binary classification of prevailing equity market conditions.

Each observation reflects whether the S&P 500 was classified as being in a risk-off (1) or risk-on (0) regime on that date. The dataset is designed for systematic traders and researchers who require a stable, reproducible market state signal for filtering, sizing, or regime-aware modeling.

Why it's useful

• Filter strategies during elevated volatility or selloff regimes
• Dynamically scale position size based on market conditions
• Improve risk-adjusted returns via regime-aware allocation
• Segment backtests into bull vs stress environments
• Study behavioral or factor performance across volatility states

Endpoint

GET /v1/sp500-risk-regime

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

import requests

url = "https://api.alphanume.com/v1/sp500-risk-regime"
params = {"api_key": "alp_abc123"}

r = requests.get(url, params=params)
print(r.json())

curl "https://api.alphanume.com/v1/sp500-risk-regime?api_key=alp_abc123"

Request Parameters

• api_key (required): your Alphanume API key.
• date (optional): return regime classification for a single date (YYYY-MM-DD).
• date_gte / date_lte / date_gt / date_lt (optional): filter by date range. Any logically valid combination is accepted.

If no date filters are provided, all available historical observations are returned (subject to tier-based limits).

Response Format

{
  "count": 522,
  "data": [
    { "date": "2026-02-23", "risk_regime": 1 }
  ]
}

Response Fields

Regime Definition

1 → Risk-Off: elevated volatility and/or stress conditions. Historically associated with defensive positioning and higher downside risk.

0 → Risk-On: lower volatility and constructive equity conditions. Historically associated with trend persistence and risk-seeking behavior.

The classification is derived from forward-looking implied volatility metrics and is stored as a fixed daily regime label. Historical values are not retroactively altered.

Notes on Data Behavior

• New observations are updated daily at 10:10 AM (America/New_York Time)
• Dates are returned as YYYY-MM-DD
• Values are point-in-time
• Historical regime labels remain fixed once published
• Results are ordered by date DESC

The IV/HV Premium dataset answers a single recurring question for every liquid US equity: are this name's options rich or cheap right now? For each ticker and trading day it pairs the annualized at-the-money implied volatility of the listed expiry nearest ~30 calendar days (iv) against the annualized 30-trading-day close-to-close realized volatility (hv).

From that pair it derives the volatility risk premium two ways, the spread (iv − hv) and the ratio (iv / hv, where > 1 = rich and < 1 = cheap), and adds daily cross-sectional ranks and z-scores so a value can be read both against the name's own history and against the rest of the universe that day.

Every past date is settled and fixed, so the series can be used in systematic research and backtesting without lookahead bias. Volatilities are annualized; notional_volume (underlying volume × VWAP) is carried as a liquidity reference.

Why it's useful

• Screen the universe for the richest or cheapest options by iv_hv_ratio on any given day
• Rank names cross-sectionally with the daily percentile and z-score fields for relative-value vol trades
• Size a vol-selling or vol-buying book by how far implied sits above or below realized
• Backtest premium-capture strategies on a point-in-time, no-lookahead history

Endpoint

GET /v1/iv-hv-premium

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

import requests

url = "https://api.alphanume.com/v1/iv-hv-premium"
params = {
    "date": "2026-06-12",
    "min_ratio_rank": 0.9,
    "api_key": "alp_abc123"
}

r = requests.get(url, params=params)
print(r.json())

curl "https://api.alphanume.com/v1/iv-hv-premium?date=2026-06-12&min_ratio_rank=0.9&api_key=alp_abc123"

Request Parameters

• api_key (required): your Alphanume API key.
• ticker (optional): equity ticker filter (case-insensitive, exact match). If omitted, all tickers are returned.
• date (optional): exact trading date (YYYY-MM-DD). Cannot be combined with date range parameters.
• min_iv_hv_ratio / max_iv_hv_ratio (optional, float): screen on the iv / hv ratio.
• min_ratio_rank (optional, float 0–1): floor on iv_hv_ratio_ranked; e.g. 0.9 returns the richest decile that day.
• only_final (optional, true/1/yes): return settled rows only. Default false.

Date Filtering

All dates must be provided in YYYY-MM-DD format. Supported parameters:

• date_gte
• date_lte
• date_gt
• date_lt

Any logically valid combination is accepted.

Response Fields

Example Response

{
  "count": 1,
  "data": [
    {
      "date": "2026-06-12",
      "ticker": "AAPL",
      "iv": 0.1795,
      "hv": 0.2333,
      "iv_hv_spread": -0.0538,
      "iv_hv_ratio": 0.769,
      "iv_ranked": 0.22,
      "hv_ranked": 0.61,
      "iv_hv_spread_ranked": 0.18,
      "iv_hv_ratio_ranked": 0.31,
      "iv_z": -0.42,
      "hv_z": 0.55,
      "iv_hv_spread_z": -0.60,
      "iv_hv_ratio_z": -0.48,
      "notional_volume": 8410000000,
      "notional_volume_ranked": 0.99,
      "notional_volume_z": 4.1,
      "days_to_exp": 31,
      "exp_date": "2026-07-17",
      "atm_strike": 290,
      "spot": 291.36,
      "is_final": 0,
      "last_updated": "2026-06-12 15:31:04"
    }
  ]
}

Notes on Data Behavior

• One row per ticker per trading date over a point-in-time liquid US-equity universe
• Today's row is provisional intraday (is_final = 0) and settled after the close (is_final = 1, ~16:30 ET)
• Volatilities are annualized; typical iv/hv ≈ 0.15–0.80
• Cross-sectional ranks and z-scores are computed across that day's universe
• Once a date settles, its values are fixed and not retroactively altered
• Results are ordered by date DESC, ticker ASC

The IV/HV Rank dataset answers is volatility high or low for this name?For each ticker and trading day it places the current ~30-day implied vol and 30-day realized vol within that name's own trailing 52-week (strict 252-observation) range, as both a 0–100 rank and a 0–100 percentile.

Rank measures position within the year's high–low band; percentile measures the share of the trailing year that traded below the current value:

• *_rank = (value − 52w_low) / (52w_high − 52w_low) × 100
• *_percentile = share of trailing-year observations below the current value × 100

The dataset is derived from the same iv/hv series as IV/HV Premium, over the same universe and update cadence. A ticker appears only once it has a full year of history; daily cross-sectional rank and z-score fields add context against the rest of the universe.

Why it's useful

• Find names whose implied vol is historically cheap (low IV Rank) or expensive (high IV Rank) for premium timing
• Compare IV Rank against HV Rank to spot where implied is stretched relative to a name's own realized regime
• Screen for high-percentile vol candidates with min_iv_percentile
• Build mean-reversion or breakout signals on a name-relative, point-in-time vol measure

Endpoint

GET /v1/iv-rank

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

import requests

url = "https://api.alphanume.com/v1/iv-rank"
params = {
    "ticker": "AAPL",
    "min_iv_rank": 80,
    "api_key": "alp_abc123"
}

r = requests.get(url, params=params)
print(r.json())

curl "https://api.alphanume.com/v1/iv-rank?ticker=AAPL&min_iv_rank=80&api_key=alp_abc123"

Request Parameters

• api_key (required): your Alphanume API key.
• ticker (optional): equity ticker filter (case-insensitive, exact match). If omitted, all tickers are returned.
• date (optional): exact trading date (YYYY-MM-DD). Cannot be combined with date range parameters.
• min_iv_rank / max_iv_rank (optional, float 0–100): screen on 52w IV Rank.
• min_hv_rank / max_hv_rank (optional, float 0–100): screen on 52w HV Rank.
• min_iv_percentile (optional, float 0–100): floor on 52w IV Percentile.
• only_final (optional, true/1/yes): return settled rows only. Default false.

Date Filtering

All dates must be provided in YYYY-MM-DD format. Supported parameters:

• date_gte
• date_lte
• date_gt
• date_lt

Any logically valid combination is accepted.

Response Fields

Example Response

{
  "count": 1,
  "data": [
    {
      "date": "2026-06-12",
      "ticker": "AAPL",
      "iv": 0.1795,
      "iv_rank": 31.4,
      "iv_percentile": 28.0,
      "iv_52w_high": 0.42,
      "iv_52w_low": 0.135,
      "iv_52w_median": 0.21,
      "hv": 0.2333,
      "hv_rank": 58.2,
      "hv_percentile": 61.0,
      "hv_52w_high": 0.39,
      "hv_52w_low": 0.11,
      "hv_52w_median": 0.20,
      "n_obs_52w": 252,
      "notional_volume": 8410000000,
      "iv_rank_cs_ranked": 0.34,
      "iv_rank_cs_z": -0.41,
      "hv_rank_cs_ranked": 0.62,
      "hv_rank_cs_z": 0.39,
      "is_final": 0,
      "last_updated": "2026-06-12 15:31:04"
    }
  ]
}

Notes on Data Behavior

• A ticker appears only once it has a full year (252 observations) of iv-hv-premium history
• Today's row is provisional intraday (is_final = 0) and settled after the close (is_final = 1, ~16:30 ET)
• Rank uses the high–low band; percentile uses the share of the trailing year below the current value
• Once a date settles, its values are fixed and not retroactively altered
• Results are ordered by date DESC, ticker ASC

The Vol-of-Vol Index answers whose volatility is most unstable? For each ticker and trading day it measures the coefficient of variation (standard deviation ÷ mean) of that name's own ~30-day implied vol and 30-day realized vol over a trailing 21 observations (~1 month). Higher values mean the name's volatility is itself more variable.

The measure is dimensionless, so it is directly comparable across names, and a daily cross-sectional ranking surfaces the most vol-unstable names on any given day. It is derived from the same iv/hv series as IV/HV Premium, over the same universe and update cadence.

The first ~month of each ticker's history is absent while the 21-observation window warms up.

Why it's useful

• Rank the universe by which names have the most unstable implied or realized vol on a given day
• Filter for stable-vol names (low vol-of-vol) when a strategy depends on a steady vol regime
• Flag names whose vol is churning ahead of catalysts or regime shifts
• Combine with IV/HV Premium and IV/HV Rank for a fuller picture of a name's vol behavior

Endpoint

GET /v1/vol-of-vol

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

import requests

url = "https://api.alphanume.com/v1/vol-of-vol"
params = {
    "min_iv_vov_rank": 0.9,
    "api_key": "alp_abc123"
}

r = requests.get(url, params=params)
print(r.json())

curl "https://api.alphanume.com/v1/vol-of-vol?min_iv_vov_rank=0.9&api_key=alp_abc123"

Request Parameters

• api_key (required): your Alphanume API key.
• ticker (optional): equity ticker filter (case-insensitive, exact match). If omitted, all tickers are returned.
• date (optional): exact trading date (YYYY-MM-DD). Cannot be combined with date range parameters.
• min_iv_vov / max_iv_vov (optional, float ≥ 0): screen on raw implied vol-of-vol.
• min_hv_vov / max_hv_vov (optional, float ≥ 0): screen on raw realized vol-of-vol.
• min_iv_vov_rank / min_hv_vov_rank (optional, float 0–1): daily percentile floor on the implied / realized vol-of-vol rank.
• only_final (optional, true/1/yes): return settled rows only. Default false.

Date Filtering

All dates must be provided in YYYY-MM-DD format. Supported parameters:

• date_gte
• date_lte
• date_gt
• date_lt

Any logically valid combination is accepted.

Response Fields

Example Response

{
  "count": 1,
  "data": [
    {
      "date": "2026-06-12",
      "ticker": "AAPL",
      "iv": 0.1795,
      "iv_vov": 0.084,
      "iv_mean_21": 0.1822,
      "iv_std_21": 0.0153,
      "hv": 0.2333,
      "hv_vov": 0.121,
      "hv_mean_21": 0.2210,
      "hv_std_21": 0.0267,
      "n_obs_vov": 21,
      "notional_volume": 8410000000,
      "iv_vov_cs_ranked": 0.41,
      "iv_vov_cs_z": -0.22,
      "hv_vov_cs_ranked": 0.73,
      "hv_vov_cs_z": 0.64,
      "is_final": 0,
      "last_updated": "2026-06-12 15:31:04"
    }
  ]
}

Notes on Data Behavior

• The first ~month of each ticker's history is absent while the 21-observation window warms up
• Vol-of-vol is the coefficient of variation (std ÷ mean), so it is dimensionless and comparable across names
• Today's row is provisional intraday (is_final = 0) and settled after the close (is_final = 1, ~16:30 ET)
• Once a date settles, its values are fixed and not retroactively altered
• Results are ordered by date DESC, ticker ASC

The Earnings Implied vs Realized dataset is a per-ticker track record of how each company's earnings move was priced versus how it actually moved. For every earnings event, it captures the pre-earnings at-the-money straddle (the market's implied move) and compares it to the realized post-earnings move.

Alongside each event it carries running, point-in-time statistics for the ticker: how often the straddle over- or under-priced the move, and the trailing averages of implied move, realized move, and over/under-pricing. This answers the recurring question: does this name usually over- or under-price its earnings?

All observations are stored historically and remain fixed once the post-earnings session has resolved, so the dataset can be used safely in systematic research and backtesting without lookahead bias.

Why it's useful

• Answer “does TICKER usually over- or under-price its earnings?” with a running hit rate
• Rank or screen names by their straddle over/under-pricing tendency ahead of an earnings season
• Study the implied-vs-realized edge for earnings vol selling or buying
• Backtest earnings strategies conditioned on a ticker's historical move ratio and hit rate
• Compare straddle-implied moves to consensus EPS surprises and realized reactions

Endpoint

GET /v1/earnings-move-history

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

import requests

url = "https://api.alphanume.com/v1/earnings-move-history"
params = {
    "ticker": "AAPL",
    "api_key": "alp_abc123"
}

r = requests.get(url, params=params)
print(r.json())

curl "https://api.alphanume.com/v1/earnings-move-history?ticker=AAPL&api_key=alp_abc123"

Request Parameters

• api_key (required): your Alphanume API key.
• ticker (optional): equity ticker filter (case-insensitive, exact match). If omitted, events across all tickers are returned.
• date (optional): earnings date filter (YYYY-MM-DD). Cannot be combined with date range parameters.

If no date filters are provided, all available historical events are returned (subject to your tier's visible window).

Date Filtering

All dates must be provided in YYYY-MM-DD format. Supported parameters:

• date_gte
• date_lte
• date_gt
• date_lt

Any logically valid combination is accepted.

Response Fields

Example Response

{
  "count": 1,
  "data": [
    {
      "date": "2026-01-29",
      "ticker": "AAPL",
      "time": "amc",
      "capture_date": "2026-01-29",
      "reaction_date": "2026-01-30",
      "spot": 232.14,
      "atm_strike": 232.5,
      "exp_date": "2026-01-30",
      "days_to_exp": 1,
      "atm_call_px": 4.85,
      "atm_put_px": 4.70,
      "straddle": 9.55,
      "implied_move_pct": 4.11,
      "implied_move_dollars": 9.55,
      "atm_iv": 0.68,
      "realized_return_pct": -2.34,
      "realized_abs_move_pct": 2.34,
      "over_under_pct": 1.77,
      "move_ratio": 0.57,
      "overpriced": true,
      "eps_estimated": 2.35,
      "eps_actual": 2.41,
      "notional_volume": 184320000,
      "n_events_to_date": 18,
      "hit_rate_to_date": 0.67,
      "avg_implied_move_to_date": 4.42,
      "avg_realized_abs_to_date": 3.61,
      "avg_over_under_to_date": 0.81
    }
  ]
}

Notes on Data Behavior

• Updated daily after the market close (EOD)
• For an event whose post-earnings session has not yet closed, the realized fields (realized_return_pct, realized_abs_move_pct, over_under_pct, move_ratio, overpriced) are not yet populated
• Running statistics (n_events_to_date, hit_rate_to_date, the trailing averages) are point-in-time: they reflect only events up to and including each row
• Once an event resolves, its values are fixed and not retroactively altered
• Dates are returned as YYYY-MM-DD
• Results are ordered by date DESC, ticker ASC

Track new stock buyback announcements from SEC 8-K filings and attached press releases. Each row describes one action: a new program, a change to a program, or its completion, termination, or suspension.

The dataset records announced plans and terms. It does not measure shares actually repurchased.

Why it's useful

• Find new buyback programs and compare their size with company market value.
• Separate new authorizations from increases, extensions, and endings.
• Build event histories using the source filing time and track later row updates.

Endpoint

GET /v1/capital/buybacks

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

Find new programs announced since January 2026 with a stated dollar size of at least 5% of market cap:

import requests

url = "https://api.alphanume.com/v1/capital/buybacks"
params = {
    "event_type": "new_authorization",
    "date_gte": "2026-01-01",
    "min_pct_of_market_cap": 5,
}
r = requests.get(url, params=params, headers={"X-API-Key": "YOUR_API_KEY"})
r.raise_for_status()
print(r.json())

curl -G "https://api.alphanume.com/v1/capital/buybacks" \
  -H "X-API-Key: YOUR_API_KEY" \
  --data-urlencode "event_type=new_authorization" \
  --data-urlencode "date_gte=2026-01-01" \
  --data-urlencode "min_pct_of_market_cap=5"

The hosted MCP tool is get_buybacks. It accepts the same filters and cursor components, plus max_rows to limit MCP output. max_rows is not a REST parameter.

Request Parameters

• api_key: required unless supplied in the X-API-Key header.
• ticker: optional exact symbol, normalized to uppercase.
• event_type: one of the six values described below.
• min_amount_usd: minimum announced dollar amount, at least 0. Excludes rows without a dollar amount.
• min_pct_of_market_cap: minimum percentage of market cap, from 0 to 100. Excludes rows without a ratio.
• min_confidence: minimum quality score, from 0 to 1. Values below 0.75 have no effect because lower-scoring rows are never served.
• updated_since: rows changed at or after this New York date or timestamp, using last_updated. Accepts YYYY-MM-DD, YYYY-MM-DD HH:MM:SS, or the same timestamp with a T separator.

Event Types

• new_authorization: a new board-authorized share repurchase program.
• increase_or_extension: a program increase, extension, renewal, or raised buyback target.
• accelerated_share_repurchase: an accelerated share repurchase agreement, commonly called an ASR.
• tender_offer: an issuer offer to buy shares from holders, including Dutch auctions, or its reported results.
• 10b5_1_plan: a company repurchase trading plan under an existing authorization.
• completion_or_termination: completion, termination, or suspension of a program.

Date Filtering

date selects an exact event_date. Alternatively, use inclusive date_gte and date_lte, or strict date_gt and date_lt. Dates use YYYY-MM-DD. Do not combine date with a range. These filters do not use filing time or expiry.

Response and Pagination

The response contains count, has_more, next_cursor, and data. The count is for the current page. REST pages contain at most 50,000 rows; there is no configurable page-size parameter.

Rows sort by newest event_date, then ticker ascending (missing symbols first), then record_id ascending. When has_more is true, keep the same filters and pass all three values from next_cursor: cursor_date, cursor_ticker, and integer cursor_id. Preserve an empty cursor_ticker for an unmapped symbol. The final page has next_cursor: null.

Response Fields

Example Response

This fictional company and its values illustrate all 17 public fields. This is not a live record.

{
  "count": 1,
  "has_more": false,
  "next_cursor": null,
  "data": [
    {
      "record_id": 1001,
      "accession_no": "0000123456-26-000042",
      "ticker": "EXAMPLE",
      "cik": 123456,
      "company_name": "Example Industries Inc.",
      "event_type": "new_authorization",
      "event_date": "2026-09-10",
      "filed_at": "2026-09-10 16:15:00",
      "event_description": "The board authorized a new $500 million share repurchase program.",
      "authorized_amount_usd": 500000000,
      "authorized_shares": null,
      "pct_of_market_cap": 5,
      "expiry_date": null,
      "replaces_prior_program": 1,
      "remaining_prior_amount_usd": 25000000,
      "confidence": 0.95,
      "last_updated": "2026-09-19 05:05:00"
    }
  ]
}

Notes on Data Behavior

• History starts January 2024. Updates run daily, with the final stage scheduled for 09:05 UTC.
• event_date falls back from the stated announcement date to the 8-K report date, then filing date. It is never after filing or more than 45 days before it.
• filed_at is when EDGAR received the filing, not when the API published the row. Historical rows were backfilled, and enrichment or corrections may arrive later. This endpoint does not reconstruct past API snapshots.
• For increases, authorized_amount_usd is the increment when stated, otherwise the new total. Check the filing before adding it to an earlier program.
• Null means unavailable or unstated, not zero. Percentages above 100% are suppressed. The denominator is market cap on the last session before filing, not necessarily before the announcement.
• Repeated announcements, routine quarterly activity, stale mentions, and low-quality rows are excluded. New programs, increases, ASRs, and tender offers need at least a stated dollar amount, share count, or expiry to be included.
• Only one action is retained per filing. An authorization takes priority over a trading plan or ASR announced with it. Some announcements buried in long earnings releases can be missed.
• Coverage excludes 6-K filings, tender offers disclosed only on Schedule TO-I, fund redemption plans, private repurchases from one holder, and repurchases of debt or other non-common-stock securities.
• Use cik and accession_no to find the source at https://www.sec.gov/Archives/edgar/data/<cik>/<accession-without-dashes>/.

Toxic Financing covers PIPEs (private investments in public equity) and other private-placement financing events disclosed in 8-K and 8-K/A filings. Compare ordinary fixed-price deals with market-linked pricing, resets, warrants, and committed purchase facilities. One row represents a disclosed event, not a unique financing deal.

Why it's useful

• Screen market-linked financing and inspect discounts, floors, and resets.
• Compare stated proceeds with issuer market cap, keeping commitments separate from cash received.
• Follow linked resale-registration filings and effectiveness dates.

Endpoint

GET /v1/capital/private-placements

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

import requests

url = "https://api.alphanume.com/v1/capital/private-placements"
params = {"min_toxicity": 3, "spac": "false", "api_key": "alp_abc123"}
r = requests.get(url, params=params)
r.raise_for_status()
print(r.json())

curl "https://api.alphanume.com/v1/capital/private-placements?min_toxicity=3&spac=false&api_key=alp_abc123"

MCP tool: get_private_placements. It accepts the same filters and cursors, plus the MCP client's max_rows response bound. REST has no configurable page-size parameter.

Request Parameters

• api_key: your API key. ticker: one issuer symbol, normalized to uppercase.
• structure: common, units_with_warrants, convertible_note, convertible_preferred, equity_line, sepa_prepaid_advance, other.
• event_kind: announcement, closing, amendment_or_reset, termination, unstated.
• min_toxicity: integer 0 through 3, inclusive minimum. Even 0 excludes null scores.
• variable_price: true selects variable_discount_to_market and lesser_of; false selects fixed only. Omit to include unstated pricing.
• has_warrants: true means warrant_coverage_pct > 0; false means null or zero coverage. It does not establish absence of warrants, especially for convertibles whose coverage is null.
• spac: true or false on is_spac_related, the SIC 6770 flag. Omit for both.
• min_confidence: minimum quality signal, 0 through 1.
• updated_since: inclusive lower bound on last_updated, as YYYY-MM-DD or YYYY-MM-DD HH:MM:SS (also accepts T between date and time).

Optional filters combine with AND. Boolean and enum values are case-insensitive. Invalid values, conflicting exact-date and range filters, and incomplete cursors return 400.

Date Filtering

• date: exact announce_date, YYYY-MM-DD; cannot combine with range bounds.
• date_gte and date_lte: inclusive bounds.
• date_gt and date_lt: exclusive bounds.

These filter the 8-K filing date, not signing, closing, publication, or resale effectiveness. event_date can encode a month or year as its first day. closing_date can be expected on an announcement.

Toxicity score

The first matching rule wins. This is a structural screen, not a return forecast or a measure of issuer solvency.

• 3: variable_discount_to_market or lesser_of pricing, or an equity line / prepaid facility with a stated variable reference.
• 2: full_ratchet or price_reset_on_dilutive_issuance; coverage at least 100% with a prior-close discount at least 15%; or original-issue discount at least 10%. weighted_average alone does not trigger this grade.
• 1: any investor common warrants, a prior-close discount at least 10%, positive original-issue discount, or an equity line / prepaid facility without a stated reference.
• Null: after the higher rules, unstated pricing with terms_in_exhibit_flag=1 and no identified common warrants. Otherwise 0.

Some scoring inputs, including common-warrant counts for convertibles, are not public fields. The served columns explain the main components but do not guarantee exact recomputation of every score. A zero can still have missing terms or a discount below the scoring threshold.

Response and Pagination

The envelope contains count (rows in this response), has_more, next_cursor, and data. REST pages contain at most 50,000 rows. Order is announce_date descending, then ticker ascending with missing symbols first, then record_id ascending.

When has_more is true, resend the same filters with all three next_cursor values: cursor_date, cursor_ticker, and integer cursor_id. Preserve an empty cursor_ticker for a missing symbol. The last page has next_cursor=null.

while r.json().get("has_more"):
    params.update(r.json()["next_cursor"])
    r = requests.get(url, params=params)
    r.raise_for_status()
    print(r.json())

Response Fields

Example Response

This fictional company and accession illustrate all 45 public fields. This is not a live record.

{
  "count": 1,
  "has_more": false,
  "next_cursor": null,
  "data": [
    {
      "record_id": 1001,
      "accession_no": "0000000000-26-000001",
      "ticker": "EXAMPLE",
      "cik": 0,
      "company_name": "Illustrative Company",
      "event_kind": "announcement",
      "announce_date": "2026-09-10",
      "event_date": "2026-09-09",
      "closing_date": null,
      "structure": "convertible_note",
      "securities_summary": "Privately placed convertible notes",
      "gross_proceeds_usd": 2000000,
      "committed_capacity_usd": null,
      "shares_sold": null,
      "price_per_share_usd": null,
      "discount_to_prior_close_pct": null,
      "price_basis": "variable_discount_to_market",
      "variable_discount_pct": 20,
      "lookback_days": 10,
      "floor_price_usd": 0.25,
      "floor_exists_flag": 1,
      "reset_provision": "none_stated",
      "warrant_coverage_pct": null,
      "warrant_exercise_price_usd": null,
      "warrant_term_months": null,
      "has_prefunded_warrants": 0,
      "original_issue_discount_pct": null,
      "investor_names_stated": null,
      "investor_type_stated": "institutional_investors",
      "placement_agent": null,
      "exemption_stated": "regulation_d",
      "registration_deadline_days": null,
      "resale_registration_form": null,
      "resale_registration_date": null,
      "resale_effective_date": null,
      "is_spac_related": 0,
      "concurrent_registered_offering_flag": 0,
      "terms_in_exhibit_flag": 0,
      "toxicity_score": 3,
      "market_cap_at_announce_usd": 10000000,
      "proceeds_pct_of_market_cap": 20,
      "confidence": 0.9,
      "first_seen_at": "2026-09-10 16:15:00",
      "published_at": "2026-09-13 08:20:00",
      "last_updated": "2026-09-13 08:20:00"
    }
  ]
}

Notes on Data Behavior

• History begins in 2024. Daily discovery starts at 07:40 UTC, storage is scheduled at 08:20 UTC, and status/enrichment updates at 10:15 UTC. Processing is not intraday streaming.
• The feed reads filing bodies; terms only in exhibits can remain unavailable. Missing amounts, investors, prices, and market caps stay null rather than dropping rows. confidence is a quality signal, not guaranteed accuracy.
• Separate announcement, closing, and amendment filings can describe the same financing. There is no public deal ID linking them; avoid summing repeated proceeds across events.
• Resale linkage searches the first eligible issuer registration within 180 days after announce_date. It uses CIK for shelf registrations and ticker for S-1s. It is not an exact deal join, and effectiveness does not confirm selling.
• first_seen_at uses the filing timestamp as a proxy, not a verified live observation time. Backfilled timestamps are synthetic. Republishing can refresh published_at and subsequent enrichment changes current rows; this feed is not a historical snapshot service.
• Money is USD, percentages use percent units (20 means 20%), dates are YYYY-MM-DD, and timestamps are YYYY-MM-DD HH:MM:SS. Raw prior-close inputs and internal production provenance are not served.

The Dilution dataset captures U.S. equity dilution risk at the moment it enters the market. It is a point-in-time record of S-1 registration statements, enriched with market context and lifecycle tracking, designed for traders and researchers who need to identify and manage dilution-driven risk with precision.

Each record represents a filing as it was known on the filing date, labeled for its dilutive impact and later resolved as the filing becomes effective or is withdrawn.

Why it's useful

• Identify dilution risk at inception, not in hindsight
• Filter or size exposure around secondary offerings and resale pressure
• Build short-biased or risk-aware strategies in small- and mid-cap equities
• Study post-filing outcomes, including time-to-effectiveness or withdrawal

Endpoint

GET /v1/dilution

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

import requests

url = "https://api.alphanume.com/v1/dilution"
params = {
    "date_gte": "2026-02-06",
    "api_key": "alp_abc123"
}

r = requests.get(url, params=params)
print(r.json())

curl "https://api.alphanume.com/v1/dilution?date_gte=2026-02-01&api_key=alp_abc123"

Request Parameters

• api_key (optional): your API key. Enables full dataset access and reduces per-request limits. If omitted, a limited subset is returned.
• ticker (optional): stock ticker filter (case-insensitive, exact match). If omitted, data across all tickers are returned.
• date (optional): filing date filter (YYYY-MM-DD). If omitted, a ticker must be provided.

Date Filtering

All dates must be provided in YYYY-MM-DD format. Supported parameters:

• date_gte
• date_lte
• date_gt
• date_lt

Any logically valid combination is accepted.

Example Response

{
  "count": 1,
  "data": [
    {
      "date": "2026-02-02",
      "filing_timestamp": "2026-02-02T16:05:51-05:00",
      "ticker": "IVDA",
      "company_name": "Iveda Solutions, Inc.",
      "market_cap_at_filing": 2557918.88,
      "dilutive": 1,
      "resale": 0,
      "shares_offered": 5434782.0,
      "became_effective": 0,
      "effective_date": "",
      "days_to_effective": null,
      "offering_withdrawn": 0,
      "withdrawal_date": "",
      "days_to_withdrawal": null,
      "root_file_number": "333-293126",
      "accession_number": "0001493152-26-004743",
      "filing_url": "https://www.sec.gov/Archives/edgar/data/1397183/000149315226004743/0001493152-26-004743-index.htm",
      "last_updated": "2026-02-02 23:01:15.364519-05:00"
    }
  ]
}

Core Filing Fields (Point-in-Time)

Market Context (Point-in-Time)

Dilution Classification

Lifecycle Resolution

Metadata

Notes on Data Behavior

• Records are never removed once published
• Point-in-time fields remain fixed
• Only lifecycle fields update as events occur
• All dates are returned as YYYY-MM-DD strings

The Shelf Registrations dataset is a point-in-time capacity ledger of S-3 and F-3 shelf registration statements. A shelf registration is a company's pre-approval to sell securities in the future: it says how much the company may sell, in what forms, before any actual sale happens. Every base filing, amendment, and automatic (WKSI) shelf is one row, labeled with the registered dollar capacity, the securities covered, and the resale flag.

Each row is then tracked forward: when the shelf became effective (the SEC's EFFECT notice, or effective on filing for automatic shelves), how many days that took, an estimated expiry three years from effectiveness, and any 424B5 takedown activity linked by file number. Market cap and shares outstanding as of the session before the filing are attached for context, so capacity can be compared to company size without a second lookup.

Important framing: authorization is not issuance. This dataset records what a shelf registers, not what was sold. It is the upstream signal behind dilution screeners, not a record of completed offerings.

Why it's useful

• Screen for fresh shelf capacity filed in recent weeks, before any offering prices
• Compare capacity_amount to market_cap_at_filing to find small caps with outsized authorized dilution
• Separate primary dilution risk (shelf_type=new, is_resale=0) from resale registrations and routine WKSI shelves
• Study the timeline from filing to effectiveness to first takedown
• Pull one ticker's full shelf history as background for a position

Endpoint

GET /v1/capital/shelf-registrations

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

import requests

url = "https://api.alphanume.com/v1/capital/shelf-registrations"
params = {
    "ticker": "PLUG",
    "date_gte": "2026-06-01",
    "api_key": "alp_abc123"
}

r = requests.get(url, params=params)
print(r.json())

curl "https://api.alphanume.com/v1/capital/shelf-registrations?ticker=PLUG&date_gte=2026-06-01&api_key=alp_abc123"

Request Parameters

• api_key (required): your Alphanume API key.
• ticker (optional): equity ticker filter (case-insensitive, exact match). If omitted, filings across all tickers are returned.
• cik (optional): SEC CIK number, digits only.
• form (optional): exact form type. One of S-3, F-3, S-3/A, F-3/A, S-3ASR, F-3ASR.
• shelf_type (optional): one of new, amendment, automatic.
• date (optional): filing date filter (YYYY-MM-DD). Cannot be combined with date range parameters.
• updated_since (optional, YYYY-MM-DD): only rows whose last_updated is on or after this date. Useful for catching EFFECT and takedown refreshes without re-pulling history.
• cursor_date / cursor_accession (optional, together): keyset pagination cursor. Pass the date and accession_number from a previous response's next_cursor to fetch the next page. Both must be provided or neither.

If no date filters are provided, all available historical filings are returned (subject to your tier's visible window).

Date Filtering

All dates must be provided in YYYY-MM-DD format and filter on the filing date. Supported parameters:

• date_gte
• date_lte
• date_gt
• date_lt

Any logically valid combination is accepted.

Response Fields

Example Response

{
  "count": 1,
  "has_more": false,
  "next_cursor": null,
  "data": [
    {
      "record_id": "0001140361-26-028514",
      "date": "2026-08-14",
      "filing_timestamp": "2026-08-14 17:12:44",
      "ticker": "PLUG",
      "cik": "1093691",
      "company_name": "Plug Power Inc.",
      "accession_number": "0001140361-26-028514",
      "form": "S-3",
      "file_number": "333-281204",
      "shelf_type": "new",
      "capacity_amount": 1000000000.0,
      "securities": "common stock, preferred stock, debt securities, warrants",
      "is_well_known_seasoned": 0,
      "is_resale": 0,
      "became_effective": 1,
      "effective_at": "2026-08-21",
      "days_to_effective": 7,
      "expiry_estimate": "2029-08-21",
      "takedown_count": 0,
      "first_takedown_at": null,
      "market_cap_at_filing": 1284000000.0,
      "outstanding_shares_at_filing": 812500000,
      "filing_url": "https://www.sec.gov/Archives/edgar/data/1093691/000114036126028514/0001140361-26-028514-index.htm",
      "refused": 0,
      "last_updated": "2026-08-22 11:20:05"
    }
  ]
}

Notes on Data Behavior

• New filings are picked up nightly after the EDGAR filing day closes; effectiveness (EFFECT) and takedown status are refreshed daily
• Authorization is not issuance. capacity_amount is what the shelf registers, not what was sold; takedown_count is linkage evidence, not a usage ledger
• Automatic (WKSI) shelves and other indeterminate registrations have capacity_amount = null by design, never a guessed number
• Rows where the extraction model refused to label the filing are still served with refused = 1 and NULL extraction fields; the filing event itself is real
• Amendments are separate rows (shelf_type = amendment), not merged into the base filing's row
• expiry_estimate is an estimate (effectiveness plus 3 years); actual expiry can differ under Rule 415(a)(5)/(6) transition rules or early replacement
• Takedown counts are refreshed for shelves filed in the trailing 400 days; older shelves' counts freeze at their last refresh
• Dates are returned as YYYY-MM-DD
• Results are ordered by date DESC, accession_number ASC
• Responses are capped at 50,000 rows. When has_more is true, pass next_cursor's date and accession_number back as cursor_date and cursor_accession to fetch the next page

Enriched Reverse Splits is a historical and forward calendar of US reverse stock splits. Each row represents one ticker and execution date. Future execution dates stay in the same schema as completed events, so one endpoint supports both event monitoring and backtests.

The raw split terms are joined to listing-deficiency context, point-in-time market-cap tier, optionability, sector, and counts of recent S-1 dilution filings and S-3 or F-3 shelf registrations. The feed is designed for short screening and long-side risk controls, but it does not contain borrow availability or locate cost.

Why it's useful

• Monitor announced reverse splits before their execution dates
• Separate deep consolidations from near-1.0 share adjustments
• Rank post-split short screens by size, sub-dollar status, and optionability
• Find reverse splits preceded by recent dilution or shelf-registration activity
• Remove fresh reverse splitters from long-only microcap universes

Endpoint

GET /v1/capital/reverse-splits

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

import requests

url = "https://api.alphanume.com/v1/capital/reverse-splits"
params = {
    "date_gte": "2026-01-01",
    "ratio_lte": 0.1,
    "cap_tier": "nano",
    "deficiency_only": "true",
    "api_key": "alp_abc123"
}

r = requests.get(url, params=params)
print(r.json())

curl "https://api.alphanume.com/v1/capital/reverse-splits?date_gte=2026-01-01&ratio_lte=0.1&cap_tier=nano&deficiency_only=true&api_key=alp_abc123"

Request Parameters

• api_key (required): a Pro Alphanume API key.
• ticker (optional): ticker symbol, case-insensitive exact match.
• date (optional): exact execution date in YYYY-MM-DD format. It cannot be combined with date range parameters.
• upcoming (optional): true returns execution dates today or later; false returns completed events.
• ratio_gte / ratio_lte (optional): normalized split ratio from above 0 through 1. A 1-for-10 consolidation has ratio 0.1.
• cap_tier (optional): one of nano, micro, small, or mid_plus.
• deficiency_only (optional): true keeps ratio 0.5 or lower.
• sub_dollar (optional): true keeps names whose unadjusted close before execution was below $1; false keeps $1 and above.
• updated_since (optional): only rows updated at or after a YYYY-MM-DD date or YYYY-MM-DD HH:MM:SS timestamp.
• cursor_date / cursor_ticker (optional, together): values from the prior response's next_cursor. Both must be provided or neither.

Date Filtering

Date filters apply to the split execution date, which may be in the future. Supported range parameters are:

• date_gte
• date_lte
• date_gt
• date_lt

Any logically valid combination is accepted.

Response Fields

Example Response

{
  "count": 1,
  "has_more": false,
  "next_cursor": null,
  "data": [
    {
      "record_id": 842,
      "ticker": "XYZ",
      "date": "2026-08-28",
      "execution_date": "2026-08-28",
      "first_seen_at": "2026-08-12 06:31:04",
      "split_from": 10.0,
      "split_to": 1.0,
      "ratio": 0.1,
      "is_deficiency_candidate": 1,
      "sub_dollar_flag": 1,
      "market_cap_before": 18420000.0,
      "market_cap_tier": "nano",
      "sector": "technology",
      "optionable_flag": 0,
      "dilution_link_flag": 1,
      "dilution_link_count": 2,
      "shelf_link_flag": 1,
      "shelf_link_count": 1,
      "published_at": "2026-08-12 06:31:04",
      "last_updated": "2026-08-29 06:30:22"
    }
  ]
}

Notes on Data Behavior

• Results are ordered by date DESC, ticker ASC
• Responses are capped at 50,000 rows. When has_more is true, pass both values from next_cursor back as cursor_date and cursor_ticker
• Future rows carry null price and market-cap enrichment until the execution date arrives
• first_seen_at is a genuine observation time for live and forward rows; backfilled past rows use the execution date as a disclosed synthetic value
• market_cap_before and market_cap_tier are null before January 2024
• sector is current-state, while optionable_flag is point-in-time
• Polygon can revise or withdraw an announced event. Revisions update the row, but a future event removed entirely from the vendor feed is not currently deleted
• Open-end mutual fund share adjustments are excluded; ETFs and closed-end funds remain
• Raw pre-split price, its source, vendor split id, borrow data, and historical return studies are not served fields

Lockup Expirations tracks when insider and pre-offering shares become eligible for sale after a US-listed operating-company IPO or follow-on offering. Each row is one release tranche from a final prospectus, with the total locked block, offering float, and release conditions.

Why it's useful

• Build a forward calendar of share releases, nearest expiration first
• Compare the locked block with offering float and shares outstanding
• Separate staged releases and inspect conditions that may permit earlier selling
• Follow updates or build historical cohorts with availability timestamps

Endpoint

GET /v1/capital/lockup-expirations

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

Find upcoming lockups whose total locked block is at least twice the offering float:

import requests

url = "https://api.alphanume.com/v1/capital/lockup-expirations"
params = {
    "upcoming": "true",
    "min_locked_to_float": 2,
    "api_key": "alp_abc123"
}

r = requests.get(url, params=params)
r.raise_for_status()
print(r.json())

curl "https://api.alphanume.com/v1/capital/lockup-expirations?upcoming=true&min_locked_to_float=2&api_key=alp_abc123"

The hosted MCP tool is get_lockup_expirations. It accepts the same filters and cursor components, plus max_rows for the MCP result limit. max_rows is not a REST parameter.

Request Parameters

• api_key: required unless supplied through the X-API-Key header.
• ticker: optional exact symbol match, normalized to uppercase.
• lockup_type: ipo or follow_on.
• upcoming: true selects expiration today or later in America/New_York; false selects earlier dates. Omit for both.
• status: upcoming or expired as of the last daily status sweep. Use upcoming for a calendar check against the current ET date.
• early_release: true selects any early_release_type other than none, including staggered schedules. false selects plain fixed-period lockups.
• min_locked_to_float: inclusive minimum total locked-block-to-offering-float ratio, a number at least 0.
• min_confidence: inclusive minimum quality score from 0 to 1.
• updated_since: rows with last_updated at or after a date or timestamp. Accepts YYYY-MM-DD, YYYY-MM-DD HH:MM:SS, or YYYY-MM-DDTHH:MM:SS, without a timezone suffix.

Filters are optional and combine with AND. Boolean and enum values are case-insensitive. Invalid supported values, conflicting exact-date/range filters, and incomplete cursors return 400.

Date Filtering

• date: exact expiration date in YYYY-MM-DD format. Cannot be combined with date bounds.
• date_gte / date_lte: inclusive expiration-date bounds.
• date_gt / date_lt: exclusive expiration-date bounds.

These parameters filter expiration, not the offering date, first sellable session, or publication timestamp. Future dates are supported. With no filters, both upcoming and historical rows are returned.

Response and Pagination

The envelope is {"count": N, "has_more": false, "next_cursor": null, "data": [...]}. count is the number of rows in this response. REST pages are capped at 50,000 rows; there is no configurable page-size parameter.

When has_more is true, resend the same filters with all three values from next_cursor: cursor_date, cursor_ticker, and cursor_id. Preserve an empty cursor_ticker for an unmapped IPO; cursor_id is the integer row ID.

while r.json().get("has_more"):
    params.update(r.json()["next_cursor"])
    r = requests.get(url, params=params)
    r.raise_for_status()
    print(r.json())

Upcoming expirations sort nearest today first, followed by expired rows newest first. Ties sort by ticker (missing symbols first), then row ID. Ordering uses the ET date at request time; a page walk crossing midnight ET can repeat or skip a row at the upcoming/expired boundary.

Example Response

This fictional company and its values illustrate all 30 served fields. The example is not a live record.

{
  "count": 1,
  "has_more": false,
  "next_cursor": null,
  "data": [
    {
      "record_id": 1001,
      "ticker": "EXAMPLE",
      "cik": 1234567,
      "company_name": "Example Industries (illustrative)",
      "exchange": "Nasdaq Global Market",
      "accession_no": "0001234567-26-000001",
      "lockup_type": "ipo",
      "offering_date": "2026-04-23",
      "first_trade_date": "2026-04-24",
      "shares_offered": 10000000,
      "shares_outstanding_post_offering": 40000000,
      "locked_shares": 30000000,
      "locked_pct_of_outstanding": 75,
      "float_shares_at_offering": 10000000,
      "locked_to_float_ratio": 3,
      "tranche_seq": 1,
      "tranche_count": 1,
      "tranche_pct": 100,
      "lockup_days": 180,
      "date": "2026-10-20",
      "expiration_date": "2026-10-20",
      "shares_sellable_from": "2026-10-20",
      "early_release_type": "none",
      "early_release_terms": null,
      "status": "upcoming",
      "market_cap_at_offering": null,
      "confidence": 0.9,
      "first_seen_at": "2026-04-24 07:00:00",
      "published_at": "2026-09-12 07:25:00",
      "last_updated": "2026-09-12 07:25:00"
    }
  ]
}

Notes on Data Behavior

• Sources are final prospectuses, Forms 424B4 and 424B1, with prospectus history from 2021. New filings and enrichment are processed daily; status refreshes at 11:40 UTC.
• The expiration is the contractual anchor plus calendar-day lockup length. The anchor is usually the prospectus date; closing language uses the next session after that date, while first-listed-for-trading language uses the first trade date.
• shares_sellable_from rolls expiration to the first NYSE session on or after it. Eligibility does not confirm sales or predict returns.
• For earnings, price, staggered, mixed, or other release conditions, read early_release_terms. The displayed expiration is the contractual outside date; earlier conditional release dates are not computed.
• locked_shares and locked_to_float_ratio describe the full locked block. For one staged release, multiply by tranche_pct / 100 when known. Do not sum the full block across its tranches or assume all staged percentages are disclosed.
• Offering float can understate tradable shares when over-allotment exercise is unknown. ADS offerings use the listed unit. Missing counts and ratios mean unavailable, not zero; ratios above 200 are withheld.
• Market cap is the first available observation on or after the offering, not necessarily available at pricing. Coverage starts in 2024 and can lag a new ticker. Other enrichment can also arrive later.
• Rows can change. Pre-launch backfilled first_seen_at values are synthetic filing timestamps; inspect published_at and later updates when evaluating historical availability. This endpoint is not an as-of snapshot service.
• SPAC IPOs, de-SPAC sponsor lockups, resale-only prospectuses, and non-equity offerings are excluded. Deals without identified lockup language produce no row. Re-filed prospectuses can appear under separate accessions.
• Use cik and accession_no to open https://www.sec.gov/Archives/edgar/data/<cik>/<accession-without-dashes>/. Dates use YYYY-MM-DD; availability timestamps use YYYY-MM-DD HH:MM:SS.

Enriched De-SPAC Events tracks SPAC business combinations from the definitive-agreement announcement through registration, shareholder voting, listing, and completion, or termination and trust liquidation. Each current row represents one deal, with both ticker identities, dated milestones, and disclosed transaction economics.

The latest view follows the deal as new SEC filings arrive. A separate history view records filing events and the status after each one, allowing researchers to distinguish a deal's current state from its earlier disclosures.

Why it's useful

• Follow pending combinations before the operating company starts trading
• Track shareholder meetings, expected closings, and expected first trading dates
• Connect the SPAC's ticker to the new company and its listed warrants
• Compare completed deals by redemptions, remaining trust cash, and PIPE financing
• Separate completed, terminated, and liquidated deals when building event cohorts
• Inspect filing history and availability timestamps for historical research

Endpoint

GET /v1/de-spac-events

Base URL

https://api.alphanume.com/v1

Authentication

All requests require an API key. Pass it as a query parameter (?api_key=your_key) or via header (X-API-Key: your_key).

New REST API and MCP access requires Pro or Enterprise. Public dashboard previews are separate from a subscription.

Sample Request

Find pending deals with a milestone today or later:

import requests

url = "https://api.alphanume.com/v1/de-spac-events"
params = {
    "status": "pending",
    "upcoming": "true",
    "api_key": "alp_abc123"
}

r = requests.get(url, params=params)
r.raise_for_status()
print(r.json())

curl "https://api.alphanume.com/v1/de-spac-events?status=pending&upcoming=true&api_key=alp_abc123"

For the completed-deal workflow, select completions explicitly:

curl "https://api.alphanume.com/v1/de-spac-events?status=completed&date_gte=2026-01-01&date_lte=2026-03-31&api_key=alp_abc123"

Request Parameters

• api_key (required): your Alphanume API key. Header-based authentication is also supported.
• view (optional): latest (default) returns the current row for each deal; history returns the filing-event log.
• status (optional): one or more comma-separated statuses below. all (default) selects every status; pending expands to the six non-terminal statuses. Values are case-insensitive. When included in a list, all removes the status filter.
• ticker (optional): case-insensitive exact match against prior_ticker or new_ticker; latest also matches ticker.
• date (optional): exact filing date in YYYY-MM-DD format. Cannot be combined with date-range parameters.
• date_gte / date_lte / date_gt / date_lt (optional): inclusive or exclusive filing-date bounds. In latest, these filter the filing that set the current status; in history, they filter each entry's filing date.
• upcoming (optional, latest only): true selects pending deals with next_event_date today or later. false selects everything else, including resolved deals and pending deals with no future milestone. Omit to include both.
• next_event_lte (optional, latest only): require the next milestone to fall on or before a YYYY-MM-DD date. Combine with upcoming=true for a forward calendar.
• updated_since (optional, latest only): include rows with last_updated at or after a date or timestamp. Accepts YYYY-MM-DD, YYYY-MM-DD HH:MM:SS, or YYYY-MM-DDTHH:MM:SS, without a timezone suffix.

With no filters, the API returns all latest deal rows accessible to the key. Date filters do not reconstruct the latest view as it looked on a past date. Unknown statuses or views, invalid parameter formats, conflicting date filters, and latest-only filters with view=history return 400.

Lifecycle Statuses

Filings can skip stages. Later filings that describe an earlier stage do not move the current status backward. A deal may first appear at a later stage when its announcement has not been identified.

Response Format

Both views return {"count": N, "data": [...]}, without cursor pagination. These fictional examples illustrate the response schema; the company names, symbols, and abbreviated filing links are not live records.

{
  "count": 1,
  "data": [
    {
      "deal_id": "1234567-20260701",
      "status": "vote_scheduled",
      "event_status": "vote_scheduled",
      "date": "2026-08-28",
      "filing_url": "https://www.sec.gov/Archives/edgar/data/1234567/...",
      "ticker": "AURA",
      "prior_ticker": "AURA",
      "new_ticker": "MRLN",
      "warrant_ticker": null,
      "exchange": null,
      "spac_cik": 1234567,
      "pubco_cik": null,
      "prior_spac_name": "Aurora Acquisition Corp.",
      "new_company_name": "Marlin Technologies, Inc.",
      "target_business_name": "Marlin Technologies, LLC",
      "business_description": null,
      "sponsor_name": null,
      "announced_date": "2026-07-01",
      "registration_effective_date": null,
      "meeting_date": "2026-09-15",
      "record_date": null,
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{
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  "data": [
    {
      "deal_id": "2345678-20260105",
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}