{ "openapi": "3.0.1", "info": { "title": "👁️🔥 Insider Cluster Buy Detector — 3+ Insiders Same Stock", "description": "Detects CLUSTERS of insider buying — 3+ insiders (CEO/CFO/Directors/10%-owners) buying the same stock inside a 30/60/90-day window. Cluster signals outperform single-insider trades by 4-7% (Lakonishok-Lee). Pay-per-cluster. Bloomberg / TipRanks / OpenInsider Pro alternative.", "version": "0.0", "x-build-id": "Mph07fk20I2QFJpaT" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~insider-cluster-detector/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-insider-cluster-detector", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~insider-cluster-detector/runs": { "post": { "operationId": "runs-sync-nexgendata-insider-cluster-detector", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~insider-cluster-detector/run-sync": { "post": { "operationId": "run-sync-nexgendata-insider-cluster-detector", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "min_cluster_size": { "title": "Minimum cluster size (insiders)", "minimum": 2, "maximum": 20, "type": "integer", "description": "Minimum number of DISTINCT insiders that must have bought the same stock inside the rolling window for a cluster to qualify. 3 is the academic-research threshold (Lakonishok-Lee 2001, Cohen-Malloy-Pomorski 2012) — clusters of 3+ insiders outperform single-insider signals by 4-7% annually. 2 catches early-stage signals (CEO+CFO duos). 5+ is the rare mega-cluster (whole board piling in) — historically the strongest reversal signal at distressed names. Anything under 3 is NOT a cluster, just two friends.", "default": 3 }, "date_range": { "title": "Cluster lookback window", "enum": [ "last_30d", "last_60d", "last_90d" ], "type": "string", "description": "How far back to scan for clustered insider buying. last_30d is the canonical academic-research window — insiders rarely act independently on the same thesis if their decisions are spaced more than a month apart. last_60d catches slower-developing clusters (quarterly board cycles). last_90d catches the rare cross-quarter accumulation pattern at deep-value names. Shorter windows = fresher signal but fewer hits. Longer windows = more hits but lower per-cluster strength.", "default": "last_30d" }, "min_value_usd": { "title": "Minimum cluster value (USD)", "minimum": 0, "maximum": 100000000, "type": "integer", "description": "Skip clusters where the total combined dollar value of all insider buys is below this threshold. Filters out trivial token buys (1-2K share Director gifts/exercises). Common thresholds: 25000 (OpenInsider default — material-trade screen), 100000 (mid-cap conviction floor), 500000 (large-cap whale-magnet), 1000000 (only mega-clusters). Note: very high thresholds drastically reduce hit count — most quality cluster signals run 50K-300K combined.", "default": 25000 }, "exclude_sells": { "title": "Pure-buy clusters only", "type": "boolean", "description": "If true, only return clusters where EVERY insider transaction in the window was a buy (no sells, no exercises, no dispositions mixed in). The is_all_buy=true flag isolates the highest-signal pattern — when no insider is taking money off the table while 3+ are putting it in. Setting to false lets through mixed-direction clusters (e.g., 3 buys + 1 sell — still bullish-leaning but diluted). Pure-buy clusters historically outperform mixed clusters by 2-3% in the 6-month window.", "default": true }, "limit": { "title": "Max cluster records to return", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of cluster records to push to the dataset (one row per stock — already aggregated, so a stock with 8 insiders piling in is ONE record not eight). Typical hedge-fund-analyst usage: 10-50 clusters per refresh — that's the full universe of actionable smart-money signals on any given day. Backtesters pull 200+. Each cluster record is a pay-per-result charge of $0.25.", "default": 25 }, "tickers": { "title": "Restrict to specific tickers (optional)", "type": "array", "description": "Optional list of stock tickers to restrict the cluster scan to. Useful when you already track a watchlist and only want cluster alerts for those names. Leave empty to scan the full universe of US-listed stocks with recent insider activity. Examples: ['AAPL', 'MSFT', 'NVDA'] or ['MYGN', 'BABA', 'INTC']. Case-insensitive, max 100 tickers.", "default": [], "items": { "type": "string" } }, "include_industry": { "title": "Include industry/sector classification", "type": "boolean", "description": "If true, include the OpenInsider-supplied industry classification (e.g., 'Pharmaceutical Preparations', 'Semiconductors', 'Commercial Banks') as the sector field on each cluster record. Used by quant funds to group cluster signals by sector — a cluster wave across multiple regional banks is a different signal than one isolated bank cluster. Set to false to skip and save a tiny amount of bandwidth.", "default": true } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } }