# 🤖 Trading Performance Analyst (`easyapi/trading-performance-analyst-1`) Actor Transform your trading performance data into actionable insights with AI! Get comprehensive analysis of your trading metrics, strategies, and risk management approach. Perfect for day traders, investors, and portfolio managers seeking data-driven recommendations to optimize their trading. 📊🚀 - **URL**: https://apify.com/easyapi/trading-performance-analyst-1.md - **Developed by:** [EasyApi](https://apify.com/easyapi) (community) - **Categories:** Agents, AI, Other - **Stats:** 4 total users, 0 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $9.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## 🤖 Trading Performance Analyst(Rental) Transform your trading performance data into actionable insights with AI! This powerful analyst tool provides comprehensive evaluation of your trading metrics, strategies, and risk management approach, delivering professional recommendations to enhance your trading results. Two versions for choice: | **Pay Model** | **Pricing** | |--------------------------------------------------------------------------------------|-------------------------| | [**Rental**](https://apify.com/easyapi/trading-performance-analyst-rental) | $29.99/month(no limit) | | [**Pay-per-event**](https://apify.com/easyapi/trading-performance-analyst) | $3.99/event | ### ✨ Key Features - 📊 Comprehensive performance metrics analysis (ROI, Sharpe ratio, drawdown) - 📈 Trading strategy evaluation and optimization - 🛡️ Risk management assessment - 💡 Actionable recommendations for improvement - 📑 Multi-format reports (PDF, HTML, Markdown) - 🎯 Personalized insights based on trading style - 📚 Educational resource recommendations - 🔄 Continuous improvement suggestions ### 💪 Why Choose This Actor? - **Data-Driven**: Get objective analysis based on your actual trading performance - **Comprehensive**: Evaluate multiple aspects of your trading approach - **Professional**: Receive expert-level insights and recommendations - **Time-Saving**: Generate detailed reports in minutes - **Multi-Format**: Access your analysis in three different formats - **Actionable**: Get practical steps for improvement - **Educational**: Learn from personalized recommendations ### 🎯 Perfect For - 📈 Day Traders - 💼 Portfolio Managers - 🏦 Investment Professionals - 📊 Financial Analysts - 🎓 Trading Education Providers - 💰 Retail Investors - 🏢 Trading Firms ### 📈 Use Cases 1. **Performance Review**: Regular evaluation of trading strategies and results 2. **Strategy Optimization**: Identify areas for improvement in trading approach 3. **Risk Assessment**: Analyze and optimize risk management practices 4. **Educational Support**: Guide trading education and skill development 5. **Portfolio Analysis**: Evaluate overall trading portfolio performance ### 📝 Input Requirements Provide your trading information: - Trading performance data (metrics like ROI, Sharpe ratio) - Typical trading strategies - Risk management approach - Educational background in trading ### 📊 Output Receive comprehensive reports in three formats: 1. **HTML Report**: Web-friendly format with interactive elements 2. **PDF Report**: Professional document for sharing and printing 3. **Markdown Report**: Easy-to-edit format for further customization #### Input Example ```json { "tradingPerformanceData": "15% ROI, 1.2 Sharpe ratio, 25% maximum drawdown, 60/40 win/loss ratio", "typicalTradingStrategies": "Momentum trading, Swing trading, Use of technical analysis", "riskManagementApproach": "Utilizing stop-loss orders, Risking no more than 2% of account balance per trade", "educationalBackground": "Bachelor's degree in Finance, Certified Financial Technician (CFTe)" } ```` #### Output Example The results will be wrapped into a dataset which you can always find in the **Storage** tab. Here's an excerpt from the data you'd get if you apply the input parameters above: ```json { "input": { "tradingPerformanceData": "15% ROI, 1.2 Sharpe ratio, 25% maximum drawdown, 60/40 win/loss ratio", "typicalTradingStrategies": "Momentum trading, Swing trading, Use of technical analysis", "riskManagementApproach": "Utilizing stop-loss orders, Risking no more than 2% of account balance per trade", "educationalBackground": "Bachelor's degree in Finance, Certified Financial Technician (CFTe)" }, "htmlFile": "https://api.apify.com/v2/key-value-stores/null/records/trading-performance-analysis-2025-04-03-15-30-50.html", "pdfFile": "https://api.apify.com/v2/key-value-stores/null/records/trading-performance-analysis-2025-04-03-15-30-50.pdf", "markdownFile": "https://api.apify.com/v2/key-value-stores/null/records/trading-performance-analysis-2025-04-03-15-30-50.md" } ``` ##### Example Screenshots ![Example](https://i.imgur.com/Tf6S8Fy.png) ### 🔗 Related Actors You Might Like - 📊 [Binance Futures Leaderboard Scraper](https://apify.com/easyapi/binance-futures-leaderboard-scraper) - Scrape top crypto traders' performance metrics - 🤖 [AI Idea Generator](https://apify.com/easyapi/ai-idea-generator) - Transform challenges into innovative solutions - 🔍 [AI-powered Search](https://apify.com/easyapi/ai-powered-search) - Get structured, AI-powered summaries - 📈 [Google RealTime Trends Data Scraper](https://apify.com/easyapi/google-realtime-trends-data-scraper) - Monitor trending search keywords - 📊 [Keyword Discovery Tool](https://apify.com/easyapi/keyword-discovery-tool) - Uncover valuable search insights - 📱 [All-in-One Social Media Phone Number Scraper](https://apify.com/easyapi/all-in-one-social-media-phone-number-scraper) - Extract contact info across platforms - 📧 [All-in-One Social Media Email Scraper](https://apify.com/easyapi/all-in-one-social-media-email-scraper) - Discover emails across social platforms - 🔍 [Reddit Comments Scraper](https://apify.com/easyapi/reddit-comments-scraper) - Extract Reddit comments with thread structure - 📊 [Social Media Influencer Scraper](https://apify.com/easyapi/social-media-influencer-scraper) - Discover top influencers across platforms - 🎯 [Keyword Discovery Tool](https://apify.com/easyapi/keyword-discovery-tool) - Get valuable search insights - 📈 [LinkedIn Ads Library Scraper](https://apify.com/easyapi/linkedin-ads-library-scraper) - Scrape LinkedIn's Ad Library data - 🔍 [Google News Scraper](https://apify.com/easyapi/google-news-scraper) - Collect up to 5000 news articles - 📊 [PubMed Search Scraper](https://apify.com/easyapi/pubmed-search-scraper) - Extract research papers and articles - 🎯 [Article Content Extractor](https://apify.com/easyapi/article-content-extractor) - Extract clean article content - 📈 [IP Intelligence Aggregator](https://apify.com/easyapi/ip-intelligence-aggregator) - Get comprehensive IP data # Actor input Schema ## `tradingPerformanceData` (type: `string`): Your trading performance metrics including ROI, Sharpe ratio, drawdown, win/loss ratio ## `typicalTradingStrategies` (type: `string`): Description of your typical trading strategies and approaches ## `riskManagementApproach` (type: `string`): Your approach to managing trading risks ## `educationalBackground` (type: `string`): Your educational background and certifications in trading ## Actor input object example ```json { "tradingPerformanceData": "15% ROI, 1.2 Sharpe ratio, 25% maximum drawdown, 60/40 win/loss ratio", "typicalTradingStrategies": "Momentum trading, Swing trading, Use of technical analysis", "riskManagementApproach": "Utilizing stop-loss orders, Risking no more than 2% of account balance per trade", "educationalBackground": "Bachelor's degree in Finance, Certified Financial Technician (CFTe)" } ``` # 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("easyapi/trading-performance-analyst-1").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("easyapi/trading-performance-analyst-1").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 easyapi/trading-performance-analyst-1 --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=easyapi/trading-performance-analyst-1", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "🤖 Trading Performance Analyst", "description": "Transform your trading performance data into actionable insights with AI! Get comprehensive analysis of your trading metrics, strategies, and risk management approach. Perfect for day traders, investors, and portfolio managers seeking data-driven recommendations to optimize their trading. 📊🚀", "version": "0.0", "x-build-id": "7up81aoJQAoYqBfX3" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/easyapi~trading-performance-analyst-1/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-easyapi-trading-performance-analyst-1", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/easyapi~trading-performance-analyst-1/runs": { "post": { "operationId": "runs-sync-easyapi-trading-performance-analyst-1", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/easyapi~trading-performance-analyst-1/run-sync": { "post": { "operationId": "run-sync-easyapi-trading-performance-analyst-1", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "tradingPerformanceData", "typicalTradingStrategies", "riskManagementApproach", "educationalBackground" ], "properties": { "tradingPerformanceData": { "title": "Trading Performance Data", "type": "string", "description": "Your trading performance metrics including ROI, Sharpe ratio, drawdown, win/loss ratio", "default": "15% ROI, 1.2 Sharpe ratio, 25% maximum drawdown, 60/40 win/loss ratio" }, "typicalTradingStrategies": { "title": "Trading Strategies", "type": "string", "description": "Description of your typical trading strategies and approaches", "default": "Momentum trading, Swing trading, Use of technical analysis" }, "riskManagementApproach": { "title": "Risk Management Approach", "type": "string", "description": "Your approach to managing trading risks", "default": "Utilizing stop-loss orders, Risking no more than 2% of account balance per trade" }, "educationalBackground": { "title": "Educational Background", "type": "string", "description": "Your educational background and certifications in trading", "default": "Bachelor's degree in Finance, Certified Financial Technician (CFTe)" } } }, "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 } } } } } } } } } } ```