# China A-Share Smart-Money Tracker — Institutional Score (`nexgendata/china-a-share-smart-money-tracker`) Actor Track institutional behavior for every Chinese A-share: institutional score, participation %, main-force (smart-money) cost basis vs price, super-large order net inflow, attention & popularity rank. Eastmoney data, no login. - **URL**: https://apify.com/nexgendata/china-a-share-smart-money-tracker.md - **Developed by:** [NexGenData](https://apify.com/nexgendata) (community) - **Categories:** SEO tools, Developer tools - **Stats:** 9 total users, 2 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $20.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## China A-Share Smart-Money Tracker — Institutional Score & Cost See **what institutions are doing in every Chinese A-share** in one run. For each stock this Actor returns Eastmoney's institutional-behavior signals: an **institutional score (0–100)**, **institutional participation %**, the **"main-force" (smart-money) average cost basis** versus the current price, **super-large / large order net inflow**, an attention score and the popularity rank. **No login, no account, no API key.** The standout field is `priceVsMainForceCostPct` — how far the current price sits above or below the average cost of the dominant ("main force") money in the stock. Below cost, smart money is underwater; well above, it's sitting on gains. Combined with the institutional score and participation, it's a fast read on positioning that Chinese traders watch closely (主力成本 / 机构参与度). ### What you get One row per stock per trading day: | Field | Description | |---|---| | `stockCode` / `secuCode` | 6-digit and full code | | `stockName` / `market` | Name and board (SSE / SZSE / STAR / ChiNext / BSE) | | `institutionalScore` | Eastmoney institutional score, 0–100 (higher = stronger institutional behavior) | | `institutionalParticipationPct` | Estimated institutional participation in the stock | | `mainForceCost` / `…20d` / `…60d` | Main-force (smart-money) average cost — current, 20-day, 60-day | | `close` | Latest close (CNY) | | `priceVsMainForceCostPct` | **Price vs main-force cost** — +ve = above smart-money cost, −ve = below | | `changePct` / `turnoverPct` | Daily change and turnover | | `superLargeNetInflowCny` / `largeNetInflowCny` | Net inflow from super-large / large orders (CNY) | | `superBuyRatioPct` | Share of super-large orders that were buys | | `attentionScore` / `popularityRank` / `popularityRankChange` | Retail attention and ranking | | `peDynamic` | Dynamic P/E | ### Input - **Sort by** (`sortBy`) — score / participation / attention / change / super-large net inflow. - **Min institutional score** (`minScore`) — e.g. 70 to surface only heavily-institutional names. - **Stock codes** (`securityCodes`) — restrict to specific tickers, or leave empty for the whole market. - **Include NEEQ** (`includeNEEQ`) — off by default; A-shares only. - **Max stocks** (`maxResults`). #### Example input ```json { "sortBy": "score", "minScore": 70, "maxResults": 100 } ```` #### Example output row ```json { "stockCode": "000783", "stockName": "长江证券", "market": "SZSE (Main)", "institutionalScore": 83.72, "institutionalParticipationPct": 68.44, "mainForceCost": 9.406, "close": 9.46, "priceVsMainForceCostPct": 0.57, "superLargeNetInflowCny": 1115073552, "superBuyRatioPct": 71.36, "attentionScore": 89.6 } ``` ### Use cases - **Smart-money screening** — sort by `institutionalScore` (or filter `minScore`) to find the most institutionally-active names. - **Cost-basis edge** — rank by `priceVsMainForceCostPct` to find stocks trading near/below where the main force got in. - **Flow confirmation** — combine `superLargeNetInflowCny` + `superBuyRatioPct` to see where big money is buying. - **Watchlist monitoring** — set `securityCodes` to track institutional behavior on stocks you hold. - **Dashboards / models** — feed daily institutional signals into your own app or BI tool. ### Tips - Run on a **schedule** (daily after close) and append to one dataset to build an institutional-behavior time series. - `priceVsMainForceCostPct` crossing from negative to positive can mark a shift in main-force positioning. - Mix `minScore` with `sortBy: "super_inflow"` to find high-quality names also seeing big-order buying. ### FAQ **Account or API key?** No — live from Eastmoney's public dataset. **Which markets?** All A-shares (Shanghai & Shenzhen main, STAR, ChiNext, BSE). NEEQ optional. **How current?** Daily, as published by Eastmoney after each trading session. **What are "main-force" and "super-large orders"?** Main force (主力) = the dominant institutional/large money; super-large orders are the biggest trade tranches — a common proxy for institutional activity. ### Related Actors by NexGenData Part of a China market-intelligence suite: - **China A-Share Financials** — revenue, profit, EPS, ROE per company. - **China A-Share Unlock Calendar** — upcoming lockup expiries. - **Dragon-Tiger List**, **Block Trades**, **Stock Connect Flow**, **A-Share Insider Trades** — the rest of the China flow/behavior stack. # Actor input Schema ## `sortBy` (type: `string`): Ranking metric (descending). ## `minScore` (type: `integer`): Only return stocks with an institutional score at least this high (e.g. 70 for heavy institutional interest). 0 = no filter. ## `securityCodes` (type: `array`): Restrict to specific 6-digit A-share codes (e.g. 600519, 300750). Empty = whole market. ## `includeNEEQ` (type: `boolean`): Include lower-tier 新三板 companies. Off by default — A-shares only. ## `maxResults` (type: `integer`): Maximum stocks to return. ## Actor input object example ```json { "sortBy": "score", "minScore": 0, "securityCodes": [ "600519", "300750" ], "includeNEEQ": false, "maxResults": 100 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/china-a-share-smart-money-tracker").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("nexgendata/china-a-share-smart-money-tracker").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call nexgendata/china-a-share-smart-money-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/china-a-share-smart-money-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "China A-Share Smart-Money Tracker — Institutional Score", "description": "Track institutional behavior for every Chinese A-share: institutional score, participation %, main-force (smart-money) cost basis vs price, super-large order net inflow, attention & popularity rank. Eastmoney data, no login.", "version": "0.0", "x-build-id": "GSutsAiQ87w8SH6CS" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~china-a-share-smart-money-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-china-a-share-smart-money-tracker", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~china-a-share-smart-money-tracker/runs": { "post": { "operationId": "runs-sync-nexgendata-china-a-share-smart-money-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~china-a-share-smart-money-tracker/run-sync": { "post": { "operationId": "run-sync-nexgendata-china-a-share-smart-money-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "sortBy": { "title": "Sort by", "enum": [ "score", "participation", "attention", "change", "super_inflow" ], "type": "string", "description": "Ranking metric (descending).", "default": "score" }, "minScore": { "title": "Min institutional score (0-100)", "minimum": 0, "maximum": 100, "type": "integer", "description": "Only return stocks with an institutional score at least this high (e.g. 70 for heavy institutional interest). 0 = no filter.", "default": 0 }, "securityCodes": { "title": "Stock codes (optional)", "type": "array", "description": "Restrict to specific 6-digit A-share codes (e.g. 600519, 300750). Empty = whole market.", "items": { "type": "string" } }, "includeNEEQ": { "title": "Include NEEQ (新三板)", "type": "boolean", "description": "Include lower-tier 新三板 companies. Off by default — A-shares only.", "default": false }, "maxResults": { "title": "Max stocks", "minimum": 1, "maximum": 6000, "type": "integer", "description": "Maximum stocks to return.", "default": 100 } } }, "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 } } } } } } } } } } ```