/insider-module/api/insiders/aggregation/by-sector

Aggregate insider activity by sector or industry.

Aggregate insider activity by sector or industry. Returns metrics per group: transaction count, filing count, unique insiders (counted as distinct canonical owners — one per economic transaction, not raw distinct ReportingOwner names; matches /clusters.insider_count semantics), unique issuers, buy/sell counts, buy/sell values, net value, buy/sell shares, and net shares.

5 tokensSince v1.5.0

Why use this

Sector-level insider sentiment analysis and heatmap data.

Common use case

Building a sector heatmap showing where insider buying/selling is concentrated, or comparing insider activity across Technology vs Healthcare vs Energy sectors.

Sector / industry insider-activity heatmap aggregator — partitions all qualifying transactions in a lookback window into Sharadar-classified buckets and emits one row per bucket with 13 metrics covering count, value, share, breadth, and direction.

The most-used filter combinations:

Sector heatmap — group_by=sector + filed_at_days=30 + sort_by=abs_net_value returns the top-N sectors by absolute net flow (largest mover regardless of direction).
C-suite-only conviction — add is_c_suite=true + exclude_10b5_1=true + min_value=1000000 to strip out routine 10b5-1 sales and surface only material discretionary activity.
Sector rotation — group_by=sector + acquired_disposed_code=A to find sectors with concentrated insider BUYING (vs the default which mixes both directions into net_value).
Industry drill-down — group_by=industry + sector=Technology to break Technology-sector activity into its constituent industries (Software—Application, Semiconductors, Consumer Electronics).

v3.x changed unique_insiders semantics to count UNIQUE BENEFICIAL OWNERS (post-canonical-owner dedup) — multiple LLC/trust vehicles of the same person now count as one (the previous behavior over-counted by 5-15% on average). This makes unique_insiders / unique_issuers a sharper breadth metric.

For the per-ticker rolled-up sentiment use GET /insider-module/api/insiders/summary/by-ticker/{ticker}; for the global all-market dashboard use GET /insider-module/api/insiders/stats/global.

Parameters

Name	In	Required	Default	Allowed	Description	Example
group_by	query	optional	sector	—	Group by 'sector' or 'industry'	—
sector	query	optional	—	—	Filter to a specific sector	Technology
industry	query	optional	—	—	Filter to a specific industry	Consumer Electronics
filed_at_days	query	optional	30	—	Lookback window in days (1-3650)	—
transaction_days	query	optional	—	—	Filter by transaction date (days ago, 1-365)	30
min_value	query	optional	—	—	Minimum transaction value	1000000
max_value	query	optional	—	—	Maximum transaction value	100000000
transaction_code	query	optional	—	—	Filter by transaction code (P, S, M, etc.)	P
acquired_disposed_code	query	optional	—	—	Filter by A (Acquired) or D (Disposed)	A
is_officer	query	optional	—	—	Filter to officers only	true
is_director	query	optional	—	—	Filter to directors only	false
is_ten_percent_owner	query	optional	—	—	Filter to 10%+ owners only	false
is_c_suite	query	optional	—	—	Filter to C-suite executives only	true
exclude_10b5_1	query	optional	false	—	Exclude pre-planned 10b5-1 trades	—
exclude_cashless	query	optional	false	—	Exclude cashless exercise sales	—
limit	query	optional	50	—	Max groups to return (max 500)	20
offset	query	optional	0	—	Pagination offset	0
sort_by	query	optional	abs_net_value	—	Sort by: abs_net_value, net_value, total_value, transaction_count, or unique_insiders	filed_at

Response schema

Field	Type	Nullable	Description
status	string	no	Always `success` on 2xx.
data	array	no	Array of one row per `(group_by)` partition meeting the filter set. Sorted by `sort_by` parameter (default `abs_net_value DESC` — largest absolute net flow first, regardless of direction). When `sector` or `industry` filter is set, the array contains a single row.
data[].group	string	yes	Sector name (when `group_by=sector`) or industry name (when `group_by=industry`). Null for tickers without a Sharadar classification — these accumulate into a single 'unclassified' bucket so the ratios remain consistent.
data[].transaction_count	integer	no	Total qualifying transactions in the group (post-filter). Excludes 10b5-1 trades when `exclude_10b5_1=true`; excludes cashless-exercise sales when `exclude_cashless=true`.
data[].filing_count	integer	no	Distinct Form 4 filings represented in the group (one filing can have many transactions; this is the unique-filing count).
data[].unique_insiders	integer	no	Distinct count of reporting persons in the group (post-canonical-owner dedup — multiple LLC/trust vehicles of the same beneficial owner count as one). Use as a breadth metric — high `unique_insiders / unique_issuers` ratio = signal spread across many insiders rather than concentrated in a few.
data[].unique_issuers	integer	no	Distinct count of issuer companies in the group. Combined with `unique_insiders` and `transaction_count`, gives a 3-way density view of the group's activity.
data[].buy_count	integer	no	Count of acquisition transactions (`acquired_disposed_code='A'`).
data[].sell_count	integer	no	Count of disposition transactions (`acquired_disposed_code='D'`).
data[].buy_value	number	no	Sum of `shares × price_per_share` across all buy-side transactions in the group, USD. Always non-negative.
data[].sell_value	number	no	Sum of `shares × price_per_share` across all sell-side transactions in the group, USD. Always non-negative.
data[].net_value	number	no	`buy_value - sell_value` (signed USD). The headline magnitude metric — positive = net buying, negative = net selling. Sort by `abs_net_value` to get the most-active groups regardless of direction.
data[].buy_shares	number	no	Sum of shares acquired (split-adjusted). Always non-negative.
data[].sell_shares	number	no	Sum of shares disposed. Always non-negative.
data[].net_shares	number	no	`buy_shares - sell_shares` (signed).
meta	object	yes	Result metadata block — pagination + applied filters echo.
meta.total	integer	no	Total distinct groups matching the filter set (full count, not just the returned page).
meta.limit	integer	no	Effective page size (capped at 500 server-side).
meta.offset	integer	no	Echo of the requested offset.
meta.has_more	boolean	no	`true` when another page is available.
meta.group_by	string	no	Echo of the resolved `group_by` parameter (`'sector'` or `'industry'`). Source of truth for clients rendering 'Grouped by Sector'-style headings.
meta.filed_at_days	integer	yes	Echo of the resolved lookback window (defaults to 30 when unset). Useful for clients to render 'Last 30 days' annotations.
request_id	string	yes	Per-request UUID for log correlation.
timestamp	string	no	ISO-8601 UTC response timestamp.

Sample response

"status": "success"
"data":
]
"meta":
- "total": 11
- "limit": 50
- "offset": 0
- "has_more": false
- "group_by": "sector"
- "filed_at_days": 30
}

}

Errors

Status	Label	Description
200	OK	Request succeeded.
400	Bad Request	Invalid query, body, or path parameter.
401	Unauthorized	Missing or invalid Authorization header / api_Token.
402	Payment Required	Insufficient token balance for this call. Top up
429	Too Many Requests	Rate limit exceeded for your tier (see /pricing for tier limits). Tier limits
500	Server Error	Unexpected server-side failure. Retry with backoff; report if persistent.

Code samples

Reveal credentials

curl "https://api.finradar.ai/insider-module/api/insiders/aggregation/by-sector?api_Token=YOUR_API_KEY" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN"

Generate an API key in /account/credentials to run live queries (literal YOUR_API_KEY placeholder shown until then).