# Stock Market Screener & Buy/Sell Signals (`aleksandar77/us-stock-technical-screener`) Actor BUY/SELL signals for any US stock — no API key needed, $0.02/ticker. 5 indicators: RSI, MACD, SMA/EMA crossovers & Bollinger Bands. Schedule daily for alerts, newsletters or trading bots. 6,000+ US tickers supported. - **URL**: https://apify.com/aleksandar77/us-stock-technical-screener.md - **Developed by:** [Aleksandar Petrovic](https://apify.com/aleksandar77) (community) - **Categories:** Automation, Integrations, News - **Stats:** 3 total users, 0 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $20.00 / 1,000 ticker-analyses 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 ## Stock Market Screener & Buy/Sell Signals **Get instant BUY / SELL signals for any US stock — no API key needed, just enter your tickers and go.** Powered by 5 professional technical indicators: RSI, MACD, SMA/EMA crossovers, and Bollinger Bands. Covers 6,000+ US stocks. Schedule daily to monitor your portfolio, generate newsletter content, or feed trading bots. Up to 50 tickers per run. ### Pricing **$0.02 per analyzed ticker** — that's it. No hidden fees, no platform usage charges. | Tickers | Cost | Example | |---------|------|---------| | 5 (default) | $0.10 | Quick check on your top holdings | | 20 | $0.40 | Daily portfolio scan | | 50 (max) | $1.00 | Full market screening | ### What it does For each stock ticker you provide, the Actor: 1. **Fetches historical OHLC data** (end-of-day US market data) 2. **Calculates technical indicators locally** (no extra API calls needed): - **SMA** (Simple Moving Average) — short & long period with crossover detection (Golden Cross / Death Cross) - **EMA** (Exponential Moving Average) — short & long period - **RSI** (Relative Strength Index) — overbought/oversold detection - **MACD** (Moving Average Convergence Divergence) — with signal line crossovers - **Bollinger Bands** — volatility and price position analysis 3. **Generates an overall signal**: STRONG BUY, BUY, NEUTRAL, SELL, or STRONG SELL ### Output example ```json { "ticker": "AAPL", "date": "2026-04-04", "currentPrice": 185.42, "priceChange": 2.15, "priceChangePct": 1.17, "volume": 54238912, "overallSignal": "BUY", "signalStrength": 2, "smaShort": 182.35, "smaLong": 178.90, "smaCrossover": "bullish", "smaCrossoverDetail": "SMA(20) above SMA(50)", "rsi": 58.42, "rsiSignal": "neutral", "macd": 1.2345, "macdSignal": "bullish", "macdDetail": "MACD(1.2345) above Signal(0.8901)", "bollingerSignal": "neutral", "bollingerDetail": "%B=62.3% | Upper=192.10, Lower=174.50" } ```` ### Input parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `tickers` | string\[] | required | Stock ticker symbols (e.g., AAPL, MSFT, TSLA). Up to 50. | | `lookbackDays` | integer | 200 | Days of history (max 730) | | `smaShortPeriod` | integer | 20 | Short SMA period | | `smaLongPeriod` | integer | 50 | Long SMA period | | `rsiPeriod` | integer | 14 | RSI calculation period | | `rsiOverbought` | integer | 70 | RSI overbought threshold | | `rsiOversold` | integer | 30 | RSI oversold threshold | | `macdFastPeriod` | integer | 12 | MACD fast EMA period | | `macdSlowPeriod` | integer | 26 | MACD slow EMA period | | `macdSignalPeriod` | integer | 9 | MACD signal line period | | `bollingerPeriod` | integer | 20 | Bollinger Bands period | | `bollingerStdDev` | number | 2.0 | Bollinger Bands std deviation | ### Limits - Up to **50 tickers per run** - End-of-day data (updated after market close) - Up to 2 years of historical data for analysis ### Use cases - **Daily stock screening** — schedule the Actor to run daily and get technical signals - **Portfolio monitoring** — track your holdings' technical health - **Trading signal alerts** — integrate with Zapier/Make to get notifications - **Research & backtesting** — export historical analysis data - **Newsletter content** — generate daily market analysis automatically ### Getting started 1. Click **Start** (or call via API) 2. Enter your stock tickers (e.g., AAPL, TSLA, NVDA) 3. Adjust indicator settings if needed (or use defaults) 4. Get your results in the dataset — export as JSON, CSV, or connect to 1,000+ apps via integrations # Actor input Schema ## `tickers` (type: `array`): List of US stock ticker symbols to analyze (e.g., AAPL, MSFT, GOOGL, TSLA, NVDA). Up to 50 tickers per run. ## `lookbackDays` (type: `integer`): Number of days of historical data to fetch. Free tier supports up to 730 days (2 years). ## `smaShortPeriod` (type: `integer`): Short-term Simple Moving Average period (e.g., 20 days). ## `smaLongPeriod` (type: `integer`): Long-term Simple Moving Average period (e.g., 50 days). ## `rsiPeriod` (type: `integer`): Relative Strength Index period. ## `rsiOverbought` (type: `integer`): RSI level considered overbought. ## `rsiOversold` (type: `integer`): RSI level considered oversold. ## `macdFastPeriod` (type: `integer`): MACD fast EMA period. ## `macdSlowPeriod` (type: `integer`): MACD slow EMA period. ## `macdSignalPeriod` (type: `integer`): MACD signal line EMA period. ## `bollingerPeriod` (type: `integer`): Bollinger Bands moving average period. ## `bollingerStdDev` (type: `number`): Bollinger Bands standard deviation multiplier. ## Actor input object example ```json { "tickers": [ "AAPL", "MSFT", "GOOGL", "AMZN", "TSLA" ], "lookbackDays": 200, "smaShortPeriod": 20, "smaLongPeriod": 50, "rsiPeriod": 14, "rsiOverbought": 70, "rsiOversold": 30, "macdFastPeriod": 12, "macdSlowPeriod": 26, "macdSignalPeriod": 9, "bollingerPeriod": 20, "bollingerStdDev": 2 } ``` # 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 = { "tickers": [ "AAPL", "MSFT", "GOOGL", "AMZN", "TSLA" ] }; // Run the Actor and wait for it to finish const run = await client.actor("aleksandar77/us-stock-technical-screener").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 = { "tickers": [ "AAPL", "MSFT", "GOOGL", "AMZN", "TSLA", ] } # Run the Actor and wait for it to finish run = client.actor("aleksandar77/us-stock-technical-screener").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 '{ "tickers": [ "AAPL", "MSFT", "GOOGL", "AMZN", "TSLA" ] }' | apify call aleksandar77/us-stock-technical-screener --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=aleksandar77/us-stock-technical-screener", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Stock Market Screener & Buy/Sell Signals", "description": "BUY/SELL signals for any US stock — no API key needed, $0.02/ticker. 5 indicators: RSI, MACD, SMA/EMA crossovers & Bollinger Bands. Schedule daily for alerts, newsletters or trading bots. 6,000+ US tickers supported.", "version": "1.0", "x-build-id": "fTweUZer3W8cacjaj" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/aleksandar77~us-stock-technical-screener/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-aleksandar77-us-stock-technical-screener", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/aleksandar77~us-stock-technical-screener/runs": { "post": { "operationId": "runs-sync-aleksandar77-us-stock-technical-screener", "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/aleksandar77~us-stock-technical-screener/run-sync": { "post": { "operationId": "run-sync-aleksandar77-us-stock-technical-screener", "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", "required": [ "tickers" ], "properties": { "tickers": { "title": "Stock Tickers", "type": "array", "description": "List of US stock ticker symbols to analyze (e.g., AAPL, MSFT, GOOGL, TSLA, NVDA). Up to 50 tickers per run.", "items": { "type": "string" } }, "lookbackDays": { "title": "Lookback Days", "minimum": 30, "maximum": 730, "type": "integer", "description": "Number of days of historical data to fetch. Free tier supports up to 730 days (2 years).", "default": 200 }, "smaShortPeriod": { "title": "SMA Short Period", "minimum": 5, "maximum": 200, "type": "integer", "description": "Short-term Simple Moving Average period (e.g., 20 days).", "default": 20 }, "smaLongPeriod": { "title": "SMA Long Period", "minimum": 10, "maximum": 200, "type": "integer", "description": "Long-term Simple Moving Average period (e.g., 50 days).", "default": 50 }, "rsiPeriod": { "title": "RSI Period", "minimum": 5, "maximum": 50, "type": "integer", "description": "Relative Strength Index period.", "default": 14 }, "rsiOverbought": { "title": "RSI Overbought Level", "minimum": 50, "maximum": 90, "type": "integer", "description": "RSI level considered overbought.", "default": 70 }, "rsiOversold": { "title": "RSI Oversold Level", "minimum": 10, "maximum": 50, "type": "integer", "description": "RSI level considered oversold.", "default": 30 }, "macdFastPeriod": { "title": "MACD Fast Period", "minimum": 5, "maximum": 50, "type": "integer", "description": "MACD fast EMA period.", "default": 12 }, "macdSlowPeriod": { "title": "MACD Slow Period", "minimum": 10, "maximum": 100, "type": "integer", "description": "MACD slow EMA period.", "default": 26 }, "macdSignalPeriod": { "title": "MACD Signal Period", "minimum": 3, "maximum": 30, "type": "integer", "description": "MACD signal line EMA period.", "default": 9 }, "bollingerPeriod": { "title": "Bollinger Bands Period", "minimum": 5, "maximum": 100, "type": "integer", "description": "Bollinger Bands moving average period.", "default": 20 }, "bollingerStdDev": { "title": "Bollinger Bands Std Dev", "minimum": 1, "maximum": 4, "type": "number", "description": "Bollinger Bands standard deviation multiplier.", "default": 2 } } }, "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 } } } } } } } } } } ```