Tradingview Quantitative

Quantitative Investment Analysis Expert

Professional quantitative investment analysis system based on TradingView MCP tools providing insights and decision recommendations.

Core Rules

Metadata First Principle

Before calling `tradingview_get_leaderboard`, you must first call `tradingview_get_metadata` to get parameter values:

1. type='markets' → Get market_code (required for stock leaderboard) 2. type='tabs' + asset_type → Get available tab values 3. type='columnsets' → Get available columnset values

Complete metadata dictionary (market codes, tabs, columnsets, exchanges) see references/api-documentation.md.

Tool Selection Quick Reference

Workflows

For detailed steps, see `workflows/ directory:

Core Analysis

• `deep-stock-analysis.md` - Deep individual stock analysis (combine quote + price multi-timeframe + ta detailed indicators + news + calendar)
• `smart-screening.md` - Smart stock screening (leaderboard multi-columnset + ta + price)
• `fundamental-screening.md` - Fundamental screening (leaderboard valuation/profitability/dividends columnsets)
• `pattern-recognition.md` - Technical pattern recognition (price + ta + pattern-library reference)
• `multi-timeframe-analysis.md` - Multi-timeframe trend confirmation (price D/W/M + ta multi-period)

Market & Sectors

• `market-review.md` - Market review (leaderboard gainers/losers + news)
• `sector-rotation.md` - Sector rotation analysis (leaderboard performance columnset + multi-sector comparison)
• `news-briefing.md` - Financial news briefing (news + news_detail, supports multi-country multi-language)

Risk & Events

• `risk-assessment.md` - Risk assessment (price historical data + quote + volatility calculation)
• `event-analysis.md` - Event-driven analysis (calendar + news + search)
• `calendar-tracking.md` - Calendar event tracking (calendar 4 types)

Quotes & Search

• `symbol-search.md` - Instrument search (search_market)
• `realtime-monitor.md` - Real-time quote monitoring (quote / quote_batch)
• `multi-symbol-analysis.md` - Multi-instrument batch analysis (quote_batch + price_batch + ta)
• `exchange-overview.md` - Exchange overview (metadata exchanges/markets/tabs)

Reference Knowledge Base

For professional methodologies and data dictionaries, see references/ directory:

• `api-documentation.md` - Complete TradingView API documentation (endpoints, parameters, metadata dictionary: market codes/tabs/columnsets/exchanges, search keywords: Market Codes, Asset Types and Tabs, Column Sets, Supported Languages)
• `mcp-tools-guide.md` - MCP tools usage guide (tool combination patterns, metadata-first rules, best practices for various scenarios)
• `technical-analysis.md` - Technical analysis methodology (comprehensive scoring model, trend/momentum/pattern/support-resistance scoring, search keywords: comprehensive scoring model, RSI, MACD, support resistance)
• `pattern-library.md` - Pattern recognition library (classic patterns, recognition algorithms, success rate statistics, search keywords: double bottom, head and shoulders, triangle, flag, candlestick patterns)
• `risk-management.md` - Risk management system (position management, stop-loss strategies, portfolio management, search keywords: Kelly formula, volatility, stop loss take profit, batch position building)
• `china-a-stock-examples.md` - China A-share practical cases (stock screening, pattern analysis, market review output examples)

Disclaimer

The analysis and recommendations provided by this Skill are for reference only and do not constitute investment advice. Investing involves risks; decisions should be made cautiously.

1.0.3 - 2026-03-04

Security

• Replace actual service domains with example domains in documentation to prevent confusion and improve security
• Remove detailed configuration instructions for example domains
• Add clarification notes that API endpoints use example domains for documentation purposes

1.0.2 - 2026-03-04

Documentation

• Update reference documentation links, change practical examples from A-shares to US stocks
• Enhance API key security instructions and configuration examples

1.0.1 - 2026-03-04

Documentation

• Add installation badges and quick install section
• Shorten SKILL.md description for skills CLI compatibility

1.0.0 - 2026-03-02

Features

• Complete TradingView quantitative investment analysis system
• Smart stock screening with multi-factor scoring
• Technical pattern recognition with confidence assessment
• Market review and hot sector tracking
• Risk management with position sizing and stop-loss recommendations
• Event-driven analysis for earnings, policies, and news
• Deep individual stock analysis with multi-timeframe technical analysis
• Fundamental screening for high dividend, low valuation stocks
• Support for multiple markets: China A-shares, US, Hong Kong, Japan, Korea, Crypto, Forex, Futures

Documentation

• Complete API documentation and metadata dictionary
• MCP tools usage guide
• Technical analysis methodology
• Pattern recognition library
• Risk management methods
• 15 workflow guides covering all major use cases
• Bilingual documentation (English and Chinese)

1.0.3 - 2026-03-04

安全性

• 将文档中的实际服务域名替换为示例域名，以防止混淆并提高安全性
• 删除示例域名的详细配置说明
• 添加说明注释，表明 API 端点使用示例域名仅供文档参考

1.0.2 - 2026-03-04

文档

• 更新参考文档链接，将实践案例从 A 股改为美股
• 增强 API 密钥安全性说明和配置示例

1.0.1 - 2026-03-04

文档

• 添加安装徽章和快速安装部分
• 缩短 SKILL.md 描述以兼容 skills CLI

1.0.0 - 2026-03-02

新功能

• 完整的 TradingView 量化投资分析系统
• 智能选股，多因子综合评分
• 技术形态识别，提供置信度评估
• 市场复盘和热点板块追踪
• 风险管理，包含仓位建议和止损止盈推荐
• 事件驱动分析，追踪财报、政策和新闻
• 个股深度分析，多时间框架技术分析
• 基本面筛选，高股息、低估值股票
• 支持多个市场：中国 A 股、美国、香港、日本、韩国、加密货币、外汇、期货

文档

• 完整的 API 文档和元数据字典
• MCP 工具使用指南
• 技术分析方法论
• 形态识别库
• 风险管理方法
• 15 个工作流指南，涵盖所有主要用例
• 双语文档（英文和中文）

TradingView Quantitative Investment Analysis Skill

English | 简体中文

 

Professional quantitative investment analysis system based on TradingView data providing intelligent stock screening, technical pattern recognition, market review, risk management, and event-driven analysis.

Installation

Install this skill with one command:

npx skills add hypier/tradingview-quantitative-skills

Features

• ✅ Smart Stock Screening - Multi-factor comprehensive scoring, dual filtering of technical + fundamental aspects
• 📊 Technical Pattern Recognition - Automatically identify classic patterns, provide confidence assessment and trading strategies
• 📈 Market Review - Track hot sectors, capital flows, discover investment opportunities
• 🛡️ Risk Management - Position suggestions, stop-loss/take-profit, volatility analysis
• 📰 Event-Driven Analysis - Track earnings, policies, news, analyze market impact
• 🔍 Deep Individual Stock Analysis - Multi-timeframe technical analysis + fundamentals + news comprehensive evaluation
• 💰 Fundamental Screening - High dividend, low valuation, profitability screening
• 🔄 Sector Rotation - Identify strong sectors and rotation trends

Quick Start

1. Configure MCP Server

Add TradingView MCP server to Cursor or Claude Desktop configuration file:

Configuration file paths:

• macOS/Linux: ~/Library/Application Support/Cursor/mcp_config.json
• Windows: %APPDATA%\Cursor\mcp_config.json

📖 Security Notice: Please read SECURITY.md for important information about API key management and data privacy.

Method 1: Use RapidAPI (Recommended, Ready to Use)

Visit https://rapidapi.com/hypier/api/tradingview-data1 to apply for a free API Key, then configure:

⚠️ SECURITY WARNING: Never commit your real API key to version control. Keep your API key secure and private. The example below uses a placeholder that you must replace with your actual key.

{
  "mcpServers": {
    "RapidAPI Hub - TradingView Data": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://mcp.rapidapi.com",
        "--header",
        "x-api-host: tradingview-data1.p.rapidapi.com",
        "--header",
        "x-api-key: <YOUR_RAPIDAPI_KEY_HERE>"
      ]
    }
  }
}

Configuration Steps: 1. Visit https://rapidapi.com/hypier/api/tradingview-data1 2. Register/login to RapidAPI account 3. Subscribe to free plan (Free tier) 4. Copy your API Key 5. Replace <YOUR_RAPIDAPI_KEY_HERE> in the configuration above with your actual API key 6. Restart Cursor/Claude Desktop

Method 2: Use Self-Built JWT Token Service

If you already have a RapidAPI Key, you can use a self-built JWT Token service:

Step 1: Generate JWT Token

⚠️ SECURITY WARNING: Replace <YOUR_RAPIDAPI_KEY_HERE> with your actual API key. Never share or commit your API key.

curl --request POST \
  --url https://tradingview-data1.p.rapidapi.com/api/mcp/generate \
  --header 'Content-Type: application/json' \
  --header 'x-rapidapi-host: tradingview-data1.p.rapidapi.com' \
  --header 'x-rapidapi-key: <YOUR_RAPIDAPI_KEY_HERE>' \
  --data '{}'

Step 2: Configure the returned JWT Token to MCP

⚠️ SECURITY WARNING: Replace <YOUR_JWT_TOKEN_HERE> with the actual JWT token from Step 1. Never commit tokens to version control.

{
  "mcpServers": {
    "tradingview": {
      "type": "streamable-http",
      "url": "https://mcp.example-mcp-server.com/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_JWT_TOKEN_HERE>",
        "Accept": "application/json, text/event-stream"
      }
    }
  }
}

Recommended Configuration

For most users, Method 1 (RapidAPI) is recommended because:

• ✅ No need to manually manage token expiration
• ✅ Simple configuration, one-time setup permanent validity
• ✅ Free quota sufficient for personal use
• ✅ Automatic authentication and retry handling

2. Verify Installation

After restart, enter in conversation:

Please call tradingview_get_metadata to get the list of supported markets

If it returns the market list (america, china, japan, etc.), the configuration is successful.

3. Start Using

Just ask questions in natural language, for example:

• "Help me select strong stocks from China A-shares"
• "Analyze the technical patterns of BTC/USDT"
• "How is the China A-share market today?"
• "I have 100k capital, want to buy a certain stock, how much should I buy?"
• "Generate today's China financial news briefing"

Usage Examples

Smart Stock Screening

Help me select stocks from China A-share technology sector that meet the following conditions:
- Technical: RSI 30-70, MACD golden cross
- Fundamental: PE < 30, ROE > 15%
- Market cap: above 5 billion

Individual Stock Analysis

Deep analysis of Puyuan Information (688118), including:
- Multi-timeframe technical analysis
- Fundamental data
- Recent news
- Buy recommendations and risk warnings

Market Review

How is the China A-share market today? Analyze hot sectors and investment opportunities

Risk Management

I have 100k capital, want to buy Puyuan Information, how much should I buy?
Give me position suggestions, stop-loss/take-profit levels and risk-reward ratio

Supported Markets

• 🇨🇳 China A-shares - SSE, SZSE, BSE
• 🇺🇸 United States - NYSE, NASDAQ
• 🇭🇰 Hong Kong - HKEX
• 🇯🇵 Japan - TSE
• 🇰🇷 South Korea - KRX
• 🪙 Cryptocurrency - Binance, Coinbase, OKX, etc.
• 💱 Forex - Major currency pairs
• 📦 Futures - Commodity, index futures

For complete market list, see references/api-documentation.md.

Frequently Asked Questions

Q: What to do if prompted "MCP server not found"?

A: Check the following points: 1. Confirm mcp_config.json path is correct 2. Confirm tradingview-mcp-server is correctly built (run npm run build) 3. Confirm paths in configuration file use absolute paths 4. Restart Windsurf/Claude Desktop

Q: What to do if authentication fails?

A: 1. Confirm TradingView account password is correct 2. Confirm account has logged into TradingView website (first time requires web login) 3. If using two-factor authentication, may need app-specific password

Q: How to get China A-share data?

A:

# First get market codes
tradingview_get_metadata(type='markets')

# Use market_code='china' to get A-share data
tradingview_get_leaderboard(
  asset_type='stocks', 
  tab='gainers',
  market_code='china'
)

Q: Which technical indicators are supported?

A: When calling tradingview_get_ta, set include_indicators=true to get:

• Trend indicators: SMA, EMA, MACD, ADX
• Momentum indicators: RSI, Stoch, CCI, Williams %R
• Volume indicators: Volume, MFI
• Support resistance: Pivot Points, Fibonacci
• Others: ATR, Beta, Bollinger Bands

Q: How to get historical K-line data?

A:

tradingview_get_price(
  symbol='SSE:600519',    # Exchange:Code
  timeframe='D',          # 1/5/15/30/60/240/D/W/M
  range=120               # Max 500 K-lines
)

Q: Which languages are supported for news data?

A: Supports 19 languages, commonly used are:

• zh-Hans - Simplified Chinese
• en - English
• ja - Japanese
• ko - Korean

Complete list: tradingview_get_metadata(type='languages')

Directory Structure

tradingview-quantitative-skills/
├── README.md                    # This file - User guide
├── SKILL.md                     # AI skill description (for AI)
├── SECURITY.md                  # Security policy and best practices
├── .gitignore                   # Git ignore patterns for sensitive files
├── references/                  # Reference materials
│   ├── api-documentation.md     # Complete API documentation and metadata dictionary
│   ├── mcp-tools-guide.md       # MCP tools usage guide
│   ├── technical-analysis.md    # Technical analysis methodology
│   ├── pattern-library.md       # Pattern recognition library
│   ├── risk-management.md       # Risk management methods
│   └── china-a-stock-examples.md # China A-share practical cases
└── workflows/                   # Workflows (15 total)
    ├── smart-screening.md       # Smart stock screening
    ├── pattern-recognition.md   # Pattern recognition
    ├── market-review.md         # Market review
    ├── risk-assessment.md       # Risk assessment
    ├── event-analysis.md        # Event analysis
    ├── deep-stock-analysis.md   # Deep individual stock analysis
    ├── fundamental-screening.md # Fundamental screening
    ├── sector-rotation.md       # Sector rotation
    └── ...                      # Other workflows

Advanced Usage

Custom Screening Criteria

Refer to workflows/smart-screening.md and workflows/fundamental-screening.md, you can combine:

• Technical indicator screening (RSI, MACD, ADX, etc.)
• Fundamental screening (PE, PB, ROE, dividend yield, etc.)
• Market cap, volume screening
• Industry sector screening

Multi-Market Comparative Analysis

Compare today's financial news from China, US, and Japan, analyze market differences

Portfolio Strategy Backtesting

Combining historical K-line data and technical indicators, simple strategy validation can be performed.

Technical Support

• API Documentation: references/api-documentation.md
• Tools Guide: references/mcp-tools-guide.md
• Practical Cases: references/us-stock-examples.md

Disclaimer

This tool is for learning and research purposes only and does not constitute any investment advice. Investing involves risks; enter the market cautiously. Any investment decisions made using this tool are at your own risk.

License

MIT License

TradingView 量化投资分析技能

English | 简体中文

 

基于 TradingView 数据的专业量化投资分析系统，提供智能选股、技术形态识别、市场复盘、风险管理、事件驱动分析等功能。

安装

一键安装此技能：

npx skills add hypier/tradingview-quantitative-skills

功能特性

• ✅ 智能选股 - 多因子综合评分，技术面+基本面双重筛选
• 📊 技术形态识别 - 自动识别经典形态，提供置信度评估和交易策略
• 📈 市场复盘 - 追踪热点板块、资金流向，发现投资机会
• 🛡️ 风险管理 - 仓位建议、止损止盈、波动率分析
• 📰 事件驱动分析 - 追踪财报、政策、新闻，分析市场影响
• 🔍 个股深度分析 - 多时间框架技术分析 + 基本面 + 新闻综合评估
• 💰 基本面筛选 - 高股息、低估值、盈利能力筛选
• 🔄 板块轮动 - 识别强势板块和轮动趋势

快速开始

1. 配置 MCP Server

将 TradingView MCP server 添加到 Cursor 或 Claude Desktop 配置文件：

配置文件路径：

• macOS/Linux: ~/Library/Application Support/Cursor/mcp_config.json
• Windows: %APPDATA%\\Cursor\\mcp_config.json

📖 安全提示：请阅读 SECURITY.md 了解 API 密钥管理和数据隐私的重要信息。

方法一：使用 RapidAPI（推荐，开箱即用）

访问 https://rapidapi.com/hypier/api/tradingview-data1 申请免费 API Key，然后配置：

⚠️ 安全警告：切勿将真实的 API 密钥提交到版本控制系统。请妥善保管您的 API 密钥。下面的示例使用占位符，您必须将其替换为实际的密钥。

{
  "mcpServers": {
    "RapidAPI Hub - TradingView Data": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://mcp.rapidapi.com",
        "--header",
        "x-api-host: tradingview-data1.p.rapidapi.com",
        "--header",
        "x-api-key: <YOUR_RAPIDAPI_KEY_HERE>"
      ]
    }
  }
}

配置步骤： 1. 访问 https://rapidapi.com/hypier/api/tradingview-data1 2. 注册/登录 RapidAPI 账号 3. 订阅免费计划（Free tier） 4. 复制你的 API Key 5. 将上面配置中的 <YOUR_RAPIDAPI_KEY_HERE> 替换为你的实际 API 密钥 6. 重启 Cursor/Claude Desktop

方法二：使用自建 JWT Token 服务

如果你已有 RapidAPI Key，可以使用自建 JWT Token 服务：

步骤 1：生成 JWT Token

⚠️ 安全警告：将 <YOUR_RAPIDAPI_KEY_HERE> 替换为你的实际 API 密钥。切勿分享或提交你的 API 密钥。

curl --request POST \
  --url https://tradingview-data1.p.rapidapi.com/api/mcp/generate \
  --header 'Content-Type: application/json' \
  --header 'x-rapidapi-host: tradingview-data1.p.rapidapi.com' \
  --header 'x-rapidapi-key: <YOUR_RAPIDAPI_KEY_HERE>' \
  --data '{}'

步骤 2：将返回的 JWT Token 配置到 MCP

⚠️ 安全警告：将 <YOUR_JWT_TOKEN_HERE> 替换为步骤 1 返回的实际 JWT token。切勿将 token 提交到版本控制系统。

{
  "mcpServers": {
    "tradingview": {
      "type": "streamable-http",
      "url": "https://mcp.example-mcp-server.com/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_JWT_TOKEN_HERE>",
        "Accept": "application/json, text/event-stream"
      }
    }
  }
}

推荐配置

对于大多数用户，推荐使用方法一（RapidAPI），因为：

• ✅ 无需手动管理 token 过期
• ✅ 配置简单，一次配置永久有效
• ✅ 免费额度足够个人使用
• ✅ 自动处理认证和重试

2. 验证安装

重启后，在对话中输入：

请调用 tradingview_get_metadata 获取支持的市场列表

如果返回市场列表（america, china, japan 等），说明配置成功。

3. 开始使用

直接用自然语言提问即可，例如：

• "帮我从 A 股科技板块中筛选强势股"
• "分析 BTC/USDT 的技术形态"
• "今天 A 股市场怎么样？"
• "我有 10 万资金，想买某只股票，应该买多少？"
• "生成今日中国财经新闻简报"

使用示例

智能选股

帮我从 A 股科技板块中筛选符合以下条件的股票：
- 技术面：RSI 30-70，MACD 金叉
- 基本面：PE < 30，ROE > 15%
- 市值：50 亿以上

个股分析

深度分析普元信息（688118），包括：
- 多时间框架技术分析
- 基本面数据
- 近期新闻
- 买入建议和风险提示

市场复盘

今天 A 股市场怎么样？分析热点板块和投资机会

风险管理

我有 10 万资金，想买普元信息，应该买多少？
给我仓位建议、止损止盈位和风险收益比

支持的市场

• 🇨🇳 中国 A 股 - 上交所、深交所、北交所
• 🇺🇸 美国 - 纽交所、纳斯达克
• 🇭🇰 香港 - 港交所
• 🇯🇵 日本 - 东京证券交易所
• 🇰🇷 韩国 - 韩国交易所
• 🪙 加密货币 - Binance、Coinbase、OKX 等
• 💱 外汇 - 主要货币对
• 📦 期货 - 商品、指数期货

完整市场列表见 references/api-documentation.md。

常见问题

Q: 提示"找不到 MCP server"怎么办？

A: 检查以下几点： 1. 确认 mcp_config.json 路径正确 2. 确认 tradingview-mcp-server 已正确构建（运行 npm run build） 3. 确认配置文件中的路径使用绝对路径 4. 重启 Windsurf/Claude Desktop

Q: 认证失败怎么办？

A: 1. 确认 TradingView 账号密码正确 2. 确认账号已登录过 TradingView 网站（首次需要网页登录） 3. 如果使用了两步验证，可能需要应用专用密码

Q: 如何获取 A 股数据？

A:

# 先获取市场代码
tradingview_get_metadata(type='markets')

# 使用 market_code='china' 获取 A 股数据
tradingview_get_leaderboard(
  asset_type='stocks',
  tab='gainers',
  market_code='china'
)

Q: 支持哪些技术指标？

A: 调用 tradingview_get_ta 时设置 include_indicators=true 可获取：

• 趋势指标：SMA、EMA、MACD、ADX
• 动量指标：RSI、Stoch、CCI、Williams %R
• 成交量指标：Volume、MFI
• 支撑阻力：Pivot Points、Fibonacci
• 其他：ATR、Beta、Bollinger Bands

Q: 如何获取历史 K 线数据？

A:

tradingview_get_price(
  symbol='SSE:600519',    # 交易所:代码
  timeframe='D',          # 1/5/15/30/60/240/D/W/M
  range=120               # 最多 500 根 K 线
)

Q: 新闻数据支持哪些语言？

A: 支持 19 种语言，常用的有：

• zh-Hans - 简体中文
• en - 英语
• ja - 日语
• ko - 韩语

完整列表：tradingview_get_metadata(type='languages')

目录结构

tradingview-quantitative-skills/
├── README.md                    # 本文件 - 用户指南
├── README.zh.md                 # 中文版用户指南
├── SKILL.md                     # AI 技能描述（给 AI 看的）
├── SECURITY.md                  # 安全策略和最佳实践
├── .gitignore                   # Git 忽略敏感文件的模式
├── references/                  # 参考资料
│   ├── api-documentation.md     # 完整 API 文档和元数据字典
│   ├── mcp-tools-guide.md       # MCP 工具使用指南
│   ├── technical-analysis.md    # 技术分析方法论
│   ├── pattern-library.md       # 形态识别库
│   ├── risk-management.md       # 风险管理方法
│   └── china-a-stock-examples.md # A 股实战案例
└── workflows/                   # 工作流（共 15 个）
    ├── smart-screening.md       # 智能选股
    ├── pattern-recognition.md   # 形态识别
    ├── market-review.md         # 市场复盘
    ├── risk-assessment.md       # 风险评估
    ├── event-analysis.md        # 事件分析
    ├── deep-stock-analysis.md   # 个股深度分析
    ├── fundamental-screening.md # 基本面筛选
    ├── sector-rotation.md       # 板块轮动
    └── ...                      # 其他工作流

高级用法

自定义筛选条件

参考 workflows/smart-screening.md 和 workflows/fundamental-screening.md，可以组合：

• 技术指标筛选（RSI、MACD、ADX 等）
• 基本面筛选（PE、PB、ROE、股息率等）
• 市值、成交量筛选
• 行业板块筛选

多市场对比分析

对比今日中美日三国财经新闻，分析市场差异

组合策略回测

结合历史 K 线数据和技术指标，可以进行简单的策略验证。

技术支持

• API 文档: references/api-documentation.md
• 工具指南: references/mcp-tools-guide.md
• 实战案例: references/china-a-stock-examples.md

免责声明

本工具仅供学习研究使用，不构成任何投资建议。投资有风险，入市需谨慎。使用本工具进行的任何投资决策，风险自负。

许可证

MIT License

TradingView Data API

Access real-time market data from TradingView with our comprehensive REST API, WebSocket support, and Model Context Protocol (MCP) integration. Get stock quotes, candlestick data, technical analysis, market leaderboards, and financial news for stocks, crypto, forex, futures, bonds, and ETFs. Includes WebSocket support for live data streaming with real-time price updates and quotes, and MCP support for AI assistant integration.

Available Endpoints

📊 Price Data

Historical and real-time OHLCV (Open, High, Low, Close, Volume) candlestick data for charting and analysis.

• GET /api/price/{symbol} - Get OHLCV candlestick data with customizable timeframes (1, 5, 15, 30, 60, 240, D, W, M)
• POST /api/price/batch - Fetch candlestick data for multiple symbols in one request (max 10)

💹 Real-time Quotes

Live market quotes with current prices, bid/ask spreads, volume, and price changes for real-time trading decisions.

• GET /api/quote/{symbol} - Get real-time quote data including price, change, volume, bid/ask
• POST /api/quote/batch - Get real-time quotes for multiple symbols in one request (max 10)

🔍 Market Search

Search and discover trading instruments across stocks, crypto, forex, and other asset types by keyword or symbol.

• GET /api/search/market/{query} - Search for stocks, crypto, forex, and other markets by keyword (supports optional filter and offset parameters)

📈 Technical Analysis

Professional technical analysis signals and indicators to identify buy/sell opportunities across multiple timeframes.

• GET /api/ta/{symbol} - Get professional technical analysis signals (Buy/Sell/Neutral) across multiple timeframes
• GET /api/ta/{symbol}/indicators - Get detailed technical indicators data (RSI, MACD, Stoch, CCI, ADX, moving averages, pivot points, etc.)

🔄 Batch API

Efficiently retrieve data for multiple symbols in a single request. Batch Get Price Data for up to 10 symbols to retrieve candlestick data, and Batch Get Quotes for up to 10 symbols to access real-time quotes.

• POST /api/price/batch - Fetch candlestick data for multiple symbols in one request (max 10)
• POST /api/quote/batch - Get real-time quotes for multiple symbols in one request (max 10)

📰 Financial News

Access financial news and market updates filtered by symbol, market type, language, and region to stay informed.

• GET /api/news - Get financial news list with optional symbol, language, market type, and market country filtering
• GET /api/news/bond - Get bond market news
• GET /api/news/crypto - Get cryptocurrency market news
• GET /api/news/economic - Get economic news
• GET /api/news/etf - Get ETF market news
• GET /api/news/forex - Get forex market news
• GET /api/news/futures - Get futures market news
• GET /api/news/index - Get index market news
• GET /api/news/stock - Get stock market news
• GET /api/news/{newsId} - Get detailed content of a news article by news ID

News Parameters:

• symbol (optional) - Filter by symbol (e.g., "HKEX:700", "NASDAQ:AAPL")
• lang (optional) - Language code (default: "en", e.g., "en", "zh-Hans", "ja")
• market (optional, only for /api/news) - Market type filter (stock, crypto, forex, futures, bond, etf, index, economic)
• market_country (optional) - Market country code filter (e.g., "US", "CN")

🏆 Market Leaderboards

Discover top performers, gainers, losers, and trending instruments across different asset types and markets.

• GET /api/leaderboard/stocks - Get stock leaderboard data (requires market_code parameter)
• GET /api/leaderboard/indices - Get indices leaderboard data
• GET /api/leaderboard/crypto - Get cryptocurrency leaderboard data
• GET /api/leaderboard/futures - Get futures leaderboard data
• GET /api/leaderboard/forex - Get forex leaderboard data
• GET /api/leaderboard/bonds - Get government bonds leaderboard data
• GET /api/leaderboard/corporate-bonds - Get corporate bonds leaderboard data
• GET /api/leaderboard/etfs - Get ETF/funds leaderboard data
• GET /api/leaderboard/data - Get leaderboard data by config ID (legacy endpoint)

Leaderboard Parameters:

• tab (required) - Tab identifier (e.g., "gainers", "all", "major")
• market_code (required for stocks) - Market code (e.g., "america", "china")
• columnset (optional) - Column set name (default: "overview")
• start (optional) - Pagination start index (default: 0)
• count (optional) - Number of results, max 150 (default: 20)
• lang (optional) - Language code (default: "en")

📋 Metadata

Retrieve API configuration data including available markets, tabs, column sets, supported languages, and exchanges.

• GET /api/metadata/markets - Get all available market codes
• GET /api/metadata/tabs - Get all available tab configurations (optional type filter)
• GET /api/metadata/columnsets - Get column set metadata by asset type
• GET /api/metadata/languages - Get supported language list
• GET /api/metadata/exchanges - Get all available exchanges list

Major Exchanges:

The API supports 353+ exchanges across different asset types. Here are some of the major exchanges:

Stock Exchanges:

Cryptocurrency Exchanges:

Note: The complete list of all 353+ exchanges can be retrieved using the /api/metadata/exchanges endpoint.

📅 Calendar Events

Access economic calendar, earnings calendar, dividends calendar, and IPO calendar data for tracking important market events.

• GET /api/calendar/economic - Get economic calendar events (supports multiple countries via market_code)
• GET /api/calendar/earnings - Get earnings calendar with earnings release dates and forecasts
• GET /api/calendar/revenue - Get dividends calendar with dividend ex-dates and payment dates
• GET /api/calendar/ipo - Get IPO calendar with IPO offer times and details

Calendar Parameters:

• from (required) - Start time (Unix timestamp in seconds, e.g., 1769356800)
• to (required) - End time (Unix timestamp in seconds, e.g., 1769961599)
• market (optional) - Market code(s), comma-separated (e.g., "america,china", default: "america")

Response Format: All calendar endpoints return data in standard JSON format:

{
  "success": true,
  "data": {
    "totalCount": 661,
    "data": [
      {
        "symbol": "NASDAQ:FLWS",
        "rank": 1,
        "earnings_release_date": 1761821100,
        "name": "FLWS",
        "description": "1-800-FLOWERS.COM, Inc.",
        ...
      }
    ]
  },
  "msg": "Success"
}

Examples:

• /api/calendar/economic?from=1769356800&to=1769961599&market=america,china - Get economic events for China and US
• /api/calendar/earnings?from=1769356800&to=1769961599&market=america,china - Get earnings calendar for multiple markets
• /api/calendar/revenue?from=1769356800&to=1769961599&market=china - Get dividends calendar for China
• /api/calendar/ipo?from=1769356800&to=1769961599&market=america,china - Get IPO calendar for multiple markets

🖼️ Logo Images

Get TradingView logo images. The logo path should be obtained from currency-logoid, base-currency-logoid, or logoid fields returned by other endpoints. These fields can be retrieved from Quote endpoints (/api/quote/{symbol} and /api/quote/batch) and Leaderboard endpoints (/api/leaderboard/*). If the path does not have an extension, .svg will be automatically added. Use the big parameter to get large size versions.

• GET /logo - Get TradingView logo images using URL query parameters

Logo Parameters:

• url (required) - Logo path (e.g., "apple.svg" or "crypto/XTVCMIDLE"). If no extension is provided, .svg will be automatically added
• big (optional) - Set to true to get large size version

Examples:

• /logo?url=apple.svg - Get Apple logo
• /logo?url=apple&big=true - Get Apple logo (big version)
• /logo?url=crypto/XTVCMIDLE&big=true - Get cryptocurrency logo (big version)

Logo Path Examples by Category:

🤖 Model Context Protocol (MCP)

Access TradingView data through the Model Context Protocol, enabling AI assistants (like Claude, Cursor) to interact with TradingView tools using a standardized protocol.

Note: This section describes the API structure for reference. The actual MCP server endpoints shown use example domains for documentation purposes.

⚡ WebSocket Real-time Data

WebSocket endpoint for real-time price updates, quotes, and market data streaming.

Note: This section describes the WebSocket API structure for reference. The actual WebSocket endpoints shown use example domains for documentation purposes.

Key Features

• Real-time Data: Live price updates and market information
• Global Coverage: Access data from major worldwide exchanges
• Batch Operations: Efficiently fetch data for multiple symbols
• Multiple Timeframes: Support for various chart intervals
• Professional Analysis: Built-in technical analysis indicators
• Market Leaderboards: Discover trending stocks and market opportunities through comprehensive leaderboards

Supported Markets

The API supports 8 different asset types:

• Stocks: 68+ markets across North America, Europe, Middle East & Africa, South America, and Asia & Oceania
• Indices: Global stock indices including major, regional, and sector indices
• Cryptocurrency: All major exchanges and trading pairs
• Futures: Commodities, energy, metals, currencies, world indices, and interest rates
• Forex: All major, minor, and exotic currency pairs
• Government Bonds: Government bonds from global markets
• Corporate Bonds: Corporate bonds with various terms and coupon types
• ETFs/Funds: Comprehensive ETF and fund coverage worldwide

Asset Types and Tabs

The following tables show all available asset types, their tabs, and column sets:

Stocks (25 tabs, 9 column sets)

Column Sets:

Indices (11 tabs, 3 column sets)

Column Sets:

Cryptocurrencies (20 tabs, 3 column sets)

Column Sets:

Futures (7 tabs, 2 column sets)

Column Sets:

Forex (10 tabs, 3 column sets)

Column Sets:

Government Bonds (17 tabs, 2 column sets)

Column Sets:

Corporate Bonds (6 tabs, 1 column set)

Column Sets:

ETFs/Funds (40 tabs, 3 column sets)

Column Sets:

Market Codes

Market codes are required for stock leaderboard queries. Available market codes:

Supported Languages

The API supports the following languages (use lang parameter):

Usage Examples

Get Stock Leaderboard

# Get top gainers for US stocks
GET /api/leaderboard/stocks?tab=gainers&market_code=america&columnset=overview&count=20

Get Cryptocurrency Leaderboard

# Get all cryptocurrencies
GET /api/leaderboard/crypto?tab=all&columnset=overview&count=50

Get News

# Get stock news for a specific symbol
GET /api/news/stock?symbol=HKEX:700&lang=zh-Hans&market_country=US

# Get cryptocurrency news
GET /api/news/crypto?lang=en

# Get general news with market filter
GET /api/news?market=stock&market_country=US&lang=en

# Get news detail by ID
GET /api/news/tag:reuters.com,2025:newsml_L1N3XK042:0?lang=en

Get Metadata

# Get all tabs for crypto
GET /api/metadata/tabs?type=crypto

# Get all available markets
GET /api/metadata/markets

# Get columnsets by asset type
GET /api/metadata/columnsets

# Get all available exchanges
GET /api/metadata/exchanges

Start building with TradingView data today!

China A-Share Practical Examples

Example 1: Smart Stock Selection - Technology Sector

User Request:

"Help me screen for strong stocks from the A-share technology sector"

Skill Execution Process:

1. Get technology sector candidate pool (150 stocks) 2. Technical screening (RSI, MACD, trend) 3. Comprehensive scoring and ranking 4. Return Top 10

Output Result:

# Smart Stock Selection Results - A-Share Technology Sector

## Qualified Stocks (Total: 10)

### 1. Primeton (688118) ⭐⭐⭐⭐⭐
**Overall Score**: 92/100

**Technical Analysis**:
- Trend: Strong uptrend 📈
- RSI(14): 65.3 (healthy range)
- MACD: Golden cross day 3, strong momentum
- Volume: 2.1x relative to average volume
- Support: ¥33.50
- Resistance: ¥37.80

**Fundamental Highlights**:
- Market Cap: ¥3.23 billion
- PE: 28.5 (reasonable)
- ROE: 18.2%
- Industry: Cloud Computing/AI

**Buy Recommendation**: ✅ Strongly Recommended
- Suggested Entry: ¥35.00-35.50
- Target Price: ¥40.00
- Stop Loss: ¥33.00
- Position Size: 10-15%

---

Example 2: Pattern Recognition - BTC/USDT

User Request:

"Analyze BTC/USDT technical patterns"

Output Result:

# BTC/USDT Technical Pattern Analysis

## Identified Patterns

### 🔍 Ascending Triangle (Confidence: 85%)
- Upper Boundary: $68,200
- Lower Boundary: Rising trendline
- Current Position: Near upper boundary

## Trading Strategy

### Strategy A: Breakout Buy
- Entry: Breakout above $68,200
- Target: $72,000
- Stop Loss: $66,500
- Risk-Reward Ratio: 1:2.4

---

Example 3: Market Review

User Request:

"Generate today's A-share market review report"

Output Result:

# A-Share Market Review - March 1, 2026

## Market Overview
- Shanghai Composite: 3,245.67 (+1.2%)
- Advance/Decline Ratio: 3,245 : 1,432 (2.27:1)
- Trading Volume: ¥987.6 billion (+15%)

## Hot Sectors
1. Cloud Computing (+3.2%) - Price increase cycle
2. Artificial Intelligence (+2.8%) - Policy support
3. New Energy (+1.5%) - Earnings improvement

MCP Tools Usage Guide

Metadata-first rules, tool combination patterns, best practices for various scenarios

---

Metadata-First Rules

Before calling tools that require parameter values, first get available values through tradingview_get_metadata. For complete metadata dictionary, see api-documentation.md (search for Market Codes, Asset Types and Tabs).

When to Call Metadata

Common market_code Quick Reference

No need to call metadata every time, here are common values:

• North America: america, canada
• Europe: uk, germany, france, switzerland, spain, italy
• Asia: china, hong-kong, japan, korea, india, taiwan, singapore
• Others: australia, brazil

Common columnset Quick Reference

---

Tool Combination Patterns

Pattern 1: Deep Individual Stock Analysis

1. search_market(query="company name") → Get accurate symbol
2. get_quote(symbol) → Real-time price, change, volume
3. get_price(symbol, timeframe='D', range=120) → Daily K-line data
4. get_ta(symbol, include_indicators=true) → Detailed technical indicators
5. get_news(symbol=symbol, lang='zh-Hans') → Related news
6. get_calendar(type='earnings', from/to) → Recent earnings dates

Pattern 2: Smart Stock Screening (Technical + Fundamental)

1. get_metadata(type='markets') → Confirm market_code
2. get_metadata(type='tabs', asset_type='stocks') → Confirm tab
3. get_leaderboard(asset_type='stocks', tab='gainers', market_code, columnset='overview') → Candidate pool
4. get_leaderboard(same, columnset='valuation') → Valuation data
5. get_leaderboard(same, columnset='profitability') → Profitability data
6. For Top candidates: get_ta(symbol, include_indicators=true) → Technical verification
7. For Top candidates: get_price(symbol, timeframe='D', range=60) → K-line verification

Pattern 3: Multi-Timeframe Trend Confirmation

1. get_price(symbol, timeframe='M', range=24) → Monthly trend
2. get_price(symbol, timeframe='W', range=52) → Weekly trend
3. get_price(symbol, timeframe='D', range=120) → Daily trend
4. get_price(symbol, timeframe='60', range=100) → 60-minute details
5. get_ta(symbol, include_indicators=true) → Multi-period TA signals

Signal consistency: Monthly/weekly/daily trend direction consistent → High confidence

Pattern 4: Sector Rotation Analysis

1. get_metadata(type='tabs', asset_type='stocks') → Get all tabs
2. get_leaderboard(tab='best-performing', columnset='performance') → Sector performance
3. Compare performance columnset data from different tabs
4. get_news(market='stock', market_country='CN') → News confirm hotspots

Pattern 5: Fundamental Screening

1. get_leaderboard(tab='high-dividend', columnset='dividends') → High dividend
2. get_leaderboard(tab='all-stocks', columnset='valuation') → Low valuation
3. get_leaderboard(tab='all-stocks', columnset='profitability') → High ROE
4. Cross-filter above results → Value stock candidates

Pattern 6: Market Review

1. get_leaderboard(tab='gainers', market_code, count=50) → Gainers
2. get_leaderboard(tab='losers', market_code, count=50) → Losers
3. get_leaderboard(tab='active', market_code) → Active stocks
4. get_leaderboard(tab='unusual-volume', market_code) → Unusual volume
5. get_news(market_country='CN', lang='zh-Hans', limit=10) → News
6. For each news: get_news_detail(news_id) → Full content

---

Key Parameter Description

get_price Timeframe Selection

get_price Chart Types

• Default: Standard K-line
• type='HeikinAshi': Heikin-Ashi, filters noise, clearer trend direction

get_ta include_indicators Return Fields

Key fields returned when setting include_indicators=true:

• RSI(14): Relative Strength Index (>70 overbought, <30 oversold)
• MACD: Trend momentum (DIF, DEA, histogram)
• Stoch: Stochastic Oscillator (K, D values)
• CCI(20): Commodity Channel Index
• ADX(14): Trend Strength (>25 trending, >50 strong trend)
• SMA/EMA: Simple/Exponential Moving Average
• Pivot Points: Pivot points (support/resistance levels)

get_news Language Codes

get_calendar Timestamps

Calendar queries require Unix timestamps (seconds), time span not exceeding 40 days:

// Current time
const now = Math.floor(Date.now() / 1000);
// 7 days later
const weekLater = now + 7 * 24 * 60 * 60;
// 14 days later
const twoWeeksLater = now + 14 * 24 * 60 * 60;

---

Multi-Asset Type Support

MCP supports 8 asset types, each with different tabs and columnsets:

Crypto-Specific Tabs

DeFi, TVL ranking, address count, volume, supply, etc. → Use get_metadata(type='tabs', asset_type='crypto') to see complete list.

ETF-Specific Tabs

By strategy: bitcoin, gold, fixed-income, leveraged, inverse, sector, etc. 40 categories.

Technical Pattern Recognition Library

Classic technical pattern recognition algorithms and trading strategies

---

📋 Pattern Classification

Reversal Patterns

• Double Bottom (W-Bottom)
• Double Top (M-Top)
• Head and Shoulders Bottom
• Head and Shoulders Top
• Rounding Bottom
• Rounding Top

Continuation Patterns

• Ascending Triangle
• Descending Triangle
• Symmetrical Triangle
• Flag Pattern
• Rectangle Pattern
• Wedge Pattern

Candlestick Patterns

• Hammer
• Inverted Hammer
• Engulfing Pattern
• Morning Star/Evening Star
• Doji

---

🔄 Reversal Patterns

1. Double Bottom (W-Bottom)

Pattern Characteristics

Price movement forms a "W" shape
Two lows are close in price
Middle high point (neckline)

Recognition Criteria

1. Price difference between two lows < 3%

const priceDiff = Math.abs(low1.price - low2.price) / low1.price;
if (priceDiff > 0.03) return false;

2. Time interval between two lows > 10 days

const timeDiff = (low2.time - low1.time) / (24 * 60 * 60);
if (timeDiff < 10) return false;

3. Neckline height > 10%

const necklineHeight = (neckline.price - low1.price) / low1.price;
if (necklineHeight < 0.1) return false;

4. Second low volume < First low volume

if (low2.volume >= low1.volume) return false;

5. Breakout volume > 1.5x average

const avgVolume = calculateAvgVolume(history, 20);
if (breakoutVolume < avgVolume * 1.5) return false;

Confidence Calculation

function calculateDoubleBottomConfidence(pattern) {
  let score = 60; // Base score

  // Smaller price difference is better
  const priceDiff = Math.abs(pattern.low1.price - pattern.low2.price) / pattern.low1.price;
  if (priceDiff < 0.02) score += 10;
  else if (priceDiff < 0.03) score += 5;

  // Longer time interval is more reliable
  const timeDiff = (pattern.low2.time - pattern.low1.time) / (24 * 60 * 60);
  if (timeDiff > 20) score += 10;
  else if (timeDiff > 15) score += 5;

  // Higher neckline is better
  const necklineHeight = (pattern.neckline - pattern.low1.price) / pattern.low1.price;
  if (necklineHeight > 0.15) score += 10;
  else if (necklineHeight > 0.12) score += 5;

  // Decreasing volume
  if (pattern.low2.volume < pattern.low1.volume * 0.8) score += 5;

  // Breakout with volume expansion
  const avgVolume = pattern.avgVolume;
  if (pattern.breakoutVolume > avgVolume * 2) score += 5;
  else if (pattern.breakoutVolume > avgVolume * 1.5) score += 3;

  return Math.min(score, 100);
}

Trading Strategy

Entry Points:

• Breakout above neckline + volume expansion
• Pullback to neckline without breaking (second entry opportunity)

Target Price:

Target = Neckline Price + (Neckline Price - Low Price)

Stop Loss:

Stop Loss = 2-3% below second low

Success Rate:

• Confidence > 85%: 75% success rate
• Confidence 70-85%: 60% success rate
• Confidence < 70%: 45% success rate

---

2. Head and Shoulders Bottom

Pattern Characteristics

Three lows: left shoulder, head, right shoulder
Head is lower than both shoulders
Both shoulders are close in price

Recognition Criteria

1. Head is > 5% lower than shoulders 2. Price difference between shoulders < 5% 3. Head has highest volume 4. Breakout with volume expansion

Confidence Calculation

function calculateHeadShouldersConfidence(pattern) {
  let score = 60;

  // Head depth
  const headDepth = (pattern.leftShoulder.price - pattern.head.price) / pattern.leftShoulder.price;
  if (headDepth > 0.1) score += 15;
  else if (headDepth > 0.07) score += 10;

  // Shoulder symmetry
  const shoulderDiff = Math.abs(pattern.leftShoulder.price - pattern.rightShoulder.price) / pattern.leftShoulder.price;
  if (shoulderDiff < 0.03) score += 10;
  else if (shoulderDiff < 0.05) score += 5;

  // Volume characteristics
  if (pattern.head.volume > pattern.leftShoulder.volume &&
      pattern.head.volume > pattern.rightShoulder.volume) {
    score += 10;
  }

  // Breakout volume
  if (pattern.breakoutVolume > pattern.avgVolume * 1.5) score += 5;

  return Math.min(score, 100);
}

Trading Strategy

Entry Point: Breakout above neckline

Target Price:

Target = Neckline Price + (Neckline Price - Head Price)

Stop Loss: Below right shoulder

---

3. Rounding Bottom

Pattern Characteristics

Price rises in arc shape
Long formation time (> 30 days)
Volume forms bowl shape

Recognition Criteria

1. Formation time > 30 days 2. Price forms arc shape 3. Left side volume > Right side volume 4. Bottom has lowest volume

Trading Strategy

Entry Point: Breakout above arc top

Target Price: 1.5-2x arc height

Stop Loss: Arc bottom

---

📐 Continuation Patterns

1. Ascending Triangle

Pattern Characteristics

Upper boundary horizontal (resistance level)
Lower boundary ascending (support line)
Volume gradually decreases
Breakout direction upward probability 70%

Recognition Criteria

1. Upper boundary horizontal (fluctuation < 2%)

const topRange = (Math.max(...tops) - Math.min(...tops)) / Math.min(...tops);
if (topRange > 0.02) return false;

2. Lower boundary ascending

const slope = calculateSlope(bottoms);
if (slope <= 0) return false;

3. Formation time 10-30 days 4. Volume contraction

Confidence Calculation

function calculateAscendingTriangleConfidence(pattern) {
  let score = 60;

  // Upper boundary horizontality
  const topRange = (Math.max(...pattern.tops) - Math.min(...pattern.tops)) / Math.min(...pattern.tops);
  if (topRange < 0.01) score += 15;
  else if (topRange < 0.02) score += 10;

  // Lower boundary slope
  const slope = calculateSlope(pattern.bottoms);
  if (slope > 0.02) score += 10;
  else if (slope > 0.01) score += 5;

  // Volume contraction
  if (pattern.recentVolume < pattern.initialVolume * 0.7) score += 10;

  // Touch count
  const touchCount = pattern.tops.length + pattern.bottoms.length;
  if (touchCount >= 6) score += 5;

  return Math.min(score, 100);
}

Trading Strategy

Entry Point: Breakout above upper boundary + volume expansion

Target Price:

Target = Upper Boundary + Triangle Height

Stop Loss: Below lower boundary

Success Rate: 70%

---

2. Flag Pattern

Pattern Characteristics

Prior significant uptrend (flagpole)
Consolidation forms parallelogram
Short consolidation time (< 20 days)
Volume contraction
Breakout direction consistent with flagpole

Recognition Criteria

1. Prior gain > 10% 2. Consolidation time < 20 days 3. Consolidation range < 50% of prior gain 4. Volume contraction

Trading Strategy

Entry Point: Breakout above flag upper boundary

Target Price:

Target = Breakout Point + Flagpole Height

Stop Loss: Flag lower boundary

---

3. Rectangle Pattern

Pattern Characteristics

Price oscillates between two horizontal lines
Both upper and lower boundaries are horizontal
Volume gradually decreases

Recognition Criteria

1. Upper and lower boundaries horizontal (fluctuation < 2%) 2. Touch boundary count ≥ 4 times 3. Consolidation time 10-40 days

Trading Strategy

Entry Point: Breakout above upper boundary + volume expansion

Target Price:

Target = Upper Boundary + Rectangle Height

Stop Loss: Below lower boundary

---

🕯️ Candlestick Patterns

1. Hammer

Pattern Characteristics

Small body
Lower shadow length > Body × 2
Very short or no upper shadow
Appears at end of downtrend

Recognition Criteria

function isHammer(candle) {
  const body = Math.abs(candle.close - candle.open);
  const lowerShadow = Math.min(candle.open, candle.close) - candle.low;
  const upperShadow = candle.high - Math.max(candle.open, candle.close);

  // Lower shadow > Body × 2
  if (lowerShadow < body * 2) return false;

  // Very short upper shadow
  if (upperShadow > body * 0.5) return false;

  // Body < 30% of total length
  const totalLength = candle.high - candle.low;
  if (body / totalLength > 0.3) return false;

  return true;
}

Signal Strength

Strong Buy:

• Appears at support level
• Volume expansion
• Next day closes bullish for confirmation

General Buy:

• Appears in downtrend
• Normal volume

---

2. Engulfing Pattern

Bullish Engulfing

Characteristics:

Previous candle: Bearish
Current candle: Bullish completely engulfs previous
Appears in downtrend
Volume expansion

Recognition Criteria:

function isBullishEngulfing(prev, curr) {
  // Previous is bearish
  if (prev.close >= prev.open) return false;

  // Current is bullish
  if (curr.close <= curr.open) return false;

  // Complete engulfing
  if (curr.open >= prev.close && curr.close <= prev.open) return false;
  if (curr.open > prev.open || curr.close < prev.close) return false;

  // Volume expansion
  if (curr.volume < prev.volume * 1.2) return false;

  return true;
}

Bearish Engulfing

Characteristics:

Previous candle: Bullish
Current candle: Bearish completely engulfs previous
Appears in uptrend
Volume expansion

---

3. Morning Star/Evening Star

Morning Star (Bullish)

Three Candle Combination:

First candle: Large bearish
Second candle: Small body (doji best)
Third candle: Large bullish

Recognition Criteria:

function isMorningStar(k1, k2, k3) {
  // First large bearish
  const body1 = k1.open - k1.close;
  if (body1 < (k1.high - k1.low) * 0.6) return false;

  // Second small body
  const body2 = Math.abs(k2.close - k2.open);
  if (body2 > (k2.high - k2.low) * 0.3) return false;

  // Third large bullish
  const body3 = k3.close - k3.open;
  if (body3 < (k3.high - k3.low) * 0.6) return false;

  // Third close > First body midpoint
  if (k3.close < (k1.open + k1.close) / 2) return false;

  return true;
}

---

🚫 Pattern Failure Recognition

False Breakout Characteristics

1. Volume not expanded after breakout

if (breakoutVolume < avgVolume * 1.3) {
  return { type: 'fake_breakout', reason: 'volume_not_confirmed' };
}

2. Quick reversal after breakout

if (closePrice < breakoutPrice * 0.97) {
  return { type: 'fake_breakout', reason: 'quick_reversal' };
}

3. Breakout magnitude < 3%

const breakoutPercent = (breakoutPrice - resistance) / resistance;
if (breakoutPercent < 0.03) {
  return { type: 'weak_breakout', reason: 'insufficient_momentum' };
}

4. Sideways movement after breakout

const daysAfterBreakout = 5;
const priceChange = (currentPrice - breakoutPrice) / breakoutPrice;
if (priceChange < 0.02 && daysPassed > daysAfterBreakout) {
  return { type: 'failed_breakout', reason: 'no_follow_through' };
}

Response Strategies

Confirm Breakout:

• Wait 2-3 days after breakout for confirmation
• Observe volume cooperation
• Set stop loss (3% below breakout point)

False Breakout Stop Loss:

• Quick stop loss, don't hesitate
• Re-evaluate pattern
• Wait for new opportunities

---

📊 Practical Examples

Example 1: BTC/USDT Ascending Triangle

Time: February 15 - March 1, 2026
Pattern: Ascending Triangle

Recognition Process:
1. Upper boundary: $68,200 (horizontal resistance)
2. Lower boundary: Rising trendline
3. Touch count: Upper boundary 3 times, lower boundary 4 times
4. Volume: Gradually contracting
5. Confidence: 85%

Trading Strategy:
- Entry: Breakout above $68,200 and hold
- Target: $72,000 (pattern height $3,800)
- Stop Loss: $66,500
- Risk-Reward Ratio: 1:2.4

Result:
- March 2: Breakout above $68,200
- March 5: Reached target $72,000
- Success: ✅

Example 2: Primeton Double Bottom Pattern

Time: January 10 - February 20, 2026
Pattern: Double Bottom (W-Bottom)

Recognition Process:
1. First low: ¥28.50 (January 10)
2. Second low: ¥28.20 (February 5)
3. Price difference: 1.05% ✅
4. Time interval: 26 days ✅
5. Neckline: ¥33.00
6. Neckline height: 15.9% ✅
7. Volume: Decreasing ✅
8. Confidence: 92%

Trading Strategy:
- Entry: Breakout above ¥33.00
- Target: ¥37.50
- Stop Loss: ¥27.50
- Risk-Reward Ratio: 1:2.7

Result:
- February 20: Breakout above neckline
- March 1: Reached ¥35.50 (target not reached but significant profit)
- Success: ✅

---

💡 Usage Recommendations

1. Pattern Recognition Priority

High Priority:

• Double Bottom/Double Top
• Head and Shoulders Bottom/Top
• Ascending Triangle

Medium Priority:

• Flag Pattern
• Rectangle Pattern
• Rounding Bottom

Low Priority:

• Single candlestick patterns (need confirmation with other signals)

2. Confirmation Mechanism

Must Confirm:

• Volume cooperation
• Breakout validity
• Time period

Optional Confirmation:

• Technical indicator support
• Fundamental cooperation
• Market environment

3. Risk Control

Strict Stop Loss:

• Exit immediately when pattern breaks
• Don't hold false hopes
• Capital protection first

Staged Position Building:

• 50% position on breakout
• 30% add after confirmation
• 20% add on trend continuation

---

📚 Advanced Learning

Recommended Books

1. "Technical Analysis of Stock Trends" - Robert D. Edwards 2. "Technical Analysis of the Futures Markets" - John J. Murphy 3. "Japanese Candlestick Charting Techniques" - Steve Nison

Practice Recommendations

1. Build pattern recognition journal 2. Backtest historical pattern success rates 3. Summarize failure cases 4. Continuously optimize recognition algorithms

Risk Management System

Professional position management, stop loss/take profit, and portfolio risk control methods

---

📊 Three Pillars of Risk Management

1. Position Management - Control single trade risk 2. Stop Loss/Take Profit - Protect profits, limit losses 3. Portfolio Management - Diversify risk, optimize returns

---

1️⃣ Position Management

1.1 Kelly Criterion

Formula

Optimal Position = (Win Rate × Profit/Loss Ratio - Loss Rate) / Profit/Loss Ratio

Where:
- Win Rate = Winning Trades / Total Trades
- Loss Rate = 1 - Win Rate
- Profit/Loss Ratio = Average Profit / Average Loss

Example Calculation

function calculateKellyPosition(winRate, profitLossRatio) {
  const loseRate = 1 - winRate;
  const kellyPercent = (winRate * profitLossRatio - loseRate) / profitLossRatio;

  // Use half Kelly for conservative approach
  const conservativeKelly = kellyPercent * 0.5;

  return Math.max(0, Math.min(conservativeKelly, 0.25)); // Max 25%
}

// Example
const winRate = 0.6;        // 60% win rate
const plRatio = 2;          // 2:1 profit/loss ratio
const position = calculateKellyPosition(winRate, plRatio);
// Result: (0.6 × 2 - 0.4) / 2 = 0.4 → Half Kelly = 0.2 (20%)

Practical Application Recommendations

Theoretical Kelly Position × 0.5 = Actual Position (conservative)
Single stock max position: 20%
Single sector max position: 40%
Total position control: Adjust based on market environment

---

1.2 Fixed Percentage Method

Method

Position = Total Capital × Fixed Percentage

Risk Level Classification

---

1.3 Volatility Adjustment Method

Formula

Adjusted Position = Base Position × (Standard Volatility / Actual Volatility)

Standard Volatility = 30%

Implementation

function adjustPositionByVolatility(basePosition, volatility) {
  const standardVol = 0.30;  // 30% standard volatility
  const adjustment = standardVol / volatility;

  return basePosition * Math.min(adjustment, 1.5); // Max 1.5x amplification
}

// Example
const basePosition = 0.15;  // 15% base position
const volatility = 0.45;    // 45% volatility (high volatility)
const adjusted = adjustPositionByVolatility(basePosition, volatility);
// Result: 0.15 × (0.30 / 0.45) = 0.10 (10%)

---

1.4 Pyramid Position Building

Normal Pyramid (Recommended)

First batch: 50% position - Buy at support level
Second batch: 30% position - Add after 5% profit
Third batch: 20% position - Add after 10% profit

Advantages:

• Controlled risk
• Lower cost
• Suitable for trend trading

Example:

function pyramidBuying(capital, currentPrice, entryPrice, position) {
  const profit = (currentPrice - entryPrice) / entryPrice;

  if (position === 0) {
    // First batch: 50%
    return { amount: capital * 0.5, reason: 'Initial position' };
  } else if (position === 1 && profit >= 0.05) {
    // Second batch: 30%
    return { amount: capital * 0.3, reason: 'Add at 5% profit' };
  } else if (position === 2 && profit >= 0.10) {
    // Third batch: 20%
    return { amount: capital * 0.2, reason: 'Add at 10% profit' };
  }

  return { amount: 0, reason: 'No addition' };
}

Inverted Pyramid (Not Recommended)

First batch: 20% position
Second batch: 30% position
Third batch: 50% position

Disadvantages:

• Excessive risk
• Higher cost
• Easy to get trapped

---

1.5 Staged Position Building

Three-Part Method

First batch: 33% - Buy at support level
Second batch: 33% - Buy at resistance breakout
Third batch: 34% - Buy after trend confirmation

Five-Part Method (More Conservative)

Each batch: 20%
Buy in 5 batches
Interval: Adjust based on market conditions

---

2️⃣ Stop Loss Strategies

2.1 Fixed Percentage Stop Loss

Standards

Conservative: -5%
Balanced: -7%
Aggressive: -10%

Implementation

function calculateFixedStopLoss(entryPrice, riskLevel = 'balanced') {
  const stopLossPercent = {
    conservative: 0.05,
    balanced: 0.07,
    aggressive: 0.10
  };

  const percent = stopLossPercent[riskLevel] || 0.07;
  return entryPrice * (1 - percent);
}

---

2.2 Technical Stop Loss

Methods

1. Support Level Stop Loss

Stop Loss = Support Level × 0.98 (2% below support)

2. Moving Average Stop Loss

Short-term: Break below 5-day MA
Medium-term: Break below 20-day MA
Long-term: Break below 60-day MA

3. Pattern Stop Loss

Double Bottom: Below second low
Triangle: Below lower boundary
Head and Shoulders: Below right shoulder

Implementation

function calculateTechnicalStopLoss(currentPrice, support, ma20, pattern) {
  const stops = [];

  // Support level stop loss
  if (support) {
    stops.push({
      price: support * 0.98,
      type: 'support',
      distance: (currentPrice - support * 0.98) / currentPrice
    });
  }

  // Moving average stop loss
  if (ma20) {
    stops.push({
      price: ma20,
      type: 'ma20',
      distance: (currentPrice - ma20) / currentPrice
    });
  }

  // Pattern stop loss
  if (pattern && pattern.stopLoss) {
    stops.push({
      price: pattern.stopLoss,
      type: 'pattern',
      distance: (currentPrice - pattern.stopLoss) / currentPrice
    });
  }

  // Choose nearest stop loss (minimum risk)
  return stops.sort((a, b) => b.price - a.price)[0];
}

---

2.3 Time-Based Stop Loss

Rules

Hold 30 days without profit → Consider exit
Hold 60 days without reaching target → Forced exit

Reasons

• Low capital efficiency
• High opportunity cost
• Possible misjudgment

---

2.4 Trailing Stop Loss

Strategy

function calculateTrailingStop(entryPrice, currentPrice, highestPrice) {
  const profit = (currentPrice - entryPrice) / entryPrice;

  if (profit < 0.05) {
    // Profit < 5%: Stop at cost
    return entryPrice;
  } else if (profit < 0.10) {
    // Profit 5-10%: Stop at cost + 3%
    return entryPrice * 1.03;
  } else if (profit < 0.20) {
    // Profit 10-20%: Stop at cost + 5%
    return entryPrice * 1.05;
  } else {
    // Profit > 20%: Stop at highest - 10%
    return highestPrice * 0.90;
  }
}

---

3️⃣ Take Profit Strategies

3.1 Staged Take Profit

Strategy

10% profit: Sell 30%
20% profit: Sell 30%
30% profit: Sell 40%

Advantages

• Lock in partial profits
• Preserve upside potential
• Reduce psychological pressure

Implementation

function calculatePartialTakeProfit(entryPrice, currentPrice, remainingPosition) {
  const profit = (currentPrice - entryPrice) / entryPrice;

  if (profit >= 0.30 && remainingPosition > 0.4) {
    return { sell: 0.4, reason: '30% profit, sell 40%' };
  } else if (profit >= 0.20 && remainingPosition > 0.7) {
    return { sell: 0.3, reason: '20% profit, sell 30%' };
  } else if (profit >= 0.10 && remainingPosition === 1.0) {
    return { sell: 0.3, reason: '10% profit, sell 30%' };
  }

  return { sell: 0, reason: 'Hold' };
}

---

3.2 Trailing Take Profit

Strategy

After profit > 15%
Exit on 5% drawback

Implementation

function calculateTrailingTakeProfit(entryPrice, currentPrice, highestPrice) {
  const profit = (currentPrice - entryPrice) / entryPrice;

  if (profit < 0.15) {
    return { action: 'hold', reason: 'Profit below 15%' };
  }

  const drawdown = (highestPrice - currentPrice) / highestPrice;

  if (drawdown >= 0.05) {
    return { action: 'sell', reason: '5% drawback, trailing take profit' };
  }

  return { action: 'hold', reason: 'Continue holding' };
}

---

3.3 Target Price Take Profit

Strategy

First target: Sell 50%
Second target: Sell 30%
Third target: Sell 20%

Target Price Calculation

function calculateTargetPrices(entryPrice, pattern, resistance) {
  const targets = [];

  // Pattern-based target
  if (pattern && pattern.target) {
    targets.push({
      price: pattern.target,
      type: 'pattern',
      sellPercent: 0.5
    });
  }

  // Resistance-based target
  if (resistance) {
    targets.push({
      price: resistance,
      type: 'resistance',
      sellPercent: 0.3
    });
  }

  // Risk-reward ratio target
  const riskRewardTarget = entryPrice * 1.20; // 20% target
  targets.push({
    price: riskRewardTarget,
    type: 'risk_reward',
    sellPercent: 0.2
  });

  return targets.sort((a, b) => a.price - b.price);
}

---

4️⃣ Risk Assessment

4.1 Individual Stock Risk Assessment

Volatility Risk

function calculateVolatility(priceHistory) {
  const returns = [];
  for (let i = 1; i < priceHistory.length; i++) {
    const ret = (priceHistory[i].close - priceHistory[i-1].close) / priceHistory[i-1].close;
    returns.push(ret);
  }

  const mean = returns.reduce((a, b) => a + b) / returns.length;
  const variance = returns.reduce((sum, ret) =>
    sum + Math.pow(ret - mean, 2), 0) / returns.length;

  const dailyVol = Math.sqrt(variance);
  const annualVol = dailyVol * Math.sqrt(252);

  return {
    daily: dailyVol,
    annual: annualVol,
    level: annualVol < 0.2 ? 'low' : annualVol < 0.4 ? 'medium' : 'high'
  };
}

Risk Levels

Low risk: Annual volatility < 20%
Medium risk: Annual volatility 20-40%
High risk: Annual volatility > 40%

---

Liquidity Risk

Good: Daily trading volume > ¥100M
Fair: Daily trading volume ¥50M-100M
Poor: Daily trading volume < ¥50M

---

Beta Coefficient

Low risk: Beta < 0.8
Medium risk: Beta 0.8-1.2
High risk: Beta > 1.2

---

4.2 Portfolio Risk Assessment

Diversification Check

function checkDiversification(portfolio) {
  const checks = {
    stockCount: portfolio.length >= 5 && portfolio.length <= 10,
    sectorCount: new Set(portfolio.map(p => p.sector)).size >= 3,
    singleStockMax: Math.max(...portfolio.map(p => p.weight)) <= 0.20,
    sectorMax: checkSectorConcentration(portfolio) <= 0.40
  };

  return {
    score: Object.values(checks).filter(Boolean).length / 4,
    checks
  };
}

Correlation Check

function calculateCorrelation(returns1, returns2) {
  const n = returns1.length;
  const mean1 = returns1.reduce((a, b) => a + b) / n;
  const mean2 = returns2.reduce((a, b) => a + b) / n;

  let numerator = 0;
  let denom1 = 0;
  let denom2 = 0;

  for (let i = 0; i < n; i++) {
    const diff1 = returns1[i] - mean1;
    const diff2 = returns2[i] - mean2;
    numerator += diff1 * diff2;
    denom1 += diff1 * diff1;
    denom2 += diff2 * diff2;
  }

  return numerator / Math.sqrt(denom1 * denom2);
}

// Correlation standards
// < 0.3: Low correlation (good)
// 0.3-0.7: Medium correlation (acceptable)
// > 0.7: High correlation (needs adjustment)

---

5️⃣ Risk-Reward Ratio

5.1 Calculation Method

function calculateRiskRewardRatio(entryPrice, targetPrice, stopLoss) {
  const potentialProfit = targetPrice - entryPrice;
  const potentialLoss = entryPrice - stopLoss;

  return {
    ratio: potentialProfit / potentialLoss,
    profit: (potentialProfit / entryPrice * 100).toFixed(2) + '%',
    loss: (potentialLoss / entryPrice * 100).toFixed(2) + '%'
  };
}

5.2 Rating Standards

5.3 Minimum Requirements

Risk-Reward Ratio ≥ 1:2
Win Rate ≥ 50%

---

6️⃣ Capital Management

6.1 Total Position Control

Market Environment Adjustment

Bull market: 70-90%
Sideways market: 50-70%
Bear market: 20-40%

Implementation

function adjustTotalPosition(marketTrend, basePosition) {
  const adjustments = {
    bull: 1.2,      // Bull market amplify 20%
    neutral: 1.0,   // Sideways unchanged
    bear: 0.6       // Bear market reduce 40%
  };

  const adjusted = basePosition * (adjustments[marketTrend] || 1.0);
  return Math.min(adjusted, 0.90); // Max 90%
}

---

6.2 Cash Reserve

Minimum Cash

Minimum cash reserve: 10%

Purpose

• Adding opportunities
• Emergency funds
• Psychological safety cushion

---

6.3 Leverage Usage

Recommendations

Not recommended to use leverage
If necessary: Leverage ≤ 1.5x

Risks

• Amplified losses
• Forced liquidation
• Psychological pressure

---

📊 Practical Examples

Example 1: Complete Risk Management Process

Stock: Primeton (688118)
Capital: ¥100,000
Current Price: ¥35.50

【Step 1: Risk Assessment】
- Volatility: 45.2% (high risk)
- Beta: 2.19 (high risk)
- Liquidity: Good

【Step 2: Position Calculation】
- Base position: 15% (balanced)
- Volatility adjustment: 15% × (30% / 45%) = 10%
- Recommended position: 8-10%

【Step 3: Staged Position Building】
First batch: 5% (¥5,000) - Price ¥35.00-35.50
Second batch: 5% (¥5,000) - Breakout ¥37.00 or pullback to ¥33.50

【Step 4: Stop Loss Setup】
- Technical stop: ¥33.00 (support level)
- Percentage stop: ¥33.00 (-7%)
- Final stop: ¥33.00

【Step 5: Take Profit Setup】
- First target: ¥40.00 (+12.7%) - Sell 50%
- Second target: ¥45.00 (+26.8%) - Sell 30%
- Trailing take profit: After profit > 15%, exit on 5% drawback

【Step 6: Risk-Reward Ratio】
- Potential profit: +12.7% (first target)
- Potential risk: -7%
- Risk-reward ratio: 1:1.8 ✅

【Execution Result】
- Entry price: ¥35.20
- Quantity: 142 shares (¥5,000)
- Stop loss: ¥33.00
- Target: ¥40.00

---

💡 Risk Management Principles

1. Never Go Full Position

Reasons:

• Loss of flexibility
• Unable to respond to opportunities
• Enormous psychological pressure

---

2. Strictly Execute Stop Loss

Principles:

• Stop loss is discipline, not suggestion
• Don't move stop loss (unless upward)
• Don't buy back immediately after stop loss

---

3. Protect Profits

Methods:

• Move stop loss up after profit
• Staged take profit
• Don't let profits turn into losses

---

4. Control Drawdown

Targets:

• Single trade max loss: < 2%
• Monthly max drawdown: < 10%
• Annual max drawdown: < 20%

---

5. Record and Review

Content:

• Record every trade
• Analyze stop loss reasons
• Summarize successes and failures
• Continuously optimize strategies

---

📚 Recommended Reading

1. "The Complete TurtleTrader" - Curtis Faith 2. "Trade Your Way to Financial Freedom" - Van K. Tharp 3. "Trading in the Zone" - Mark Douglas 4. "Trader Vic—Methods of a Wall Street Master" - Victor Sperandeo

Technical Analysis Methodology

Professional technical analysis scoring model and indicator interpretation

---

📊 Comprehensive Scoring Model

Total Score Composition (100 points)

Total Score = Trend Strength(30 points) + Momentum Indicators(25 points) + Pattern Recognition(20 points) + 
              Support Resistance(15 points) + Market Sentiment(10 points)

Rating Standards

---

1️⃣ Trend Strength Analysis (30 points)

1.1 Multi-Timeframe Moving Average Arrangement (0-15 points)

Perfect Bullish Arrangement (15 points)

5-day MA > 10-day MA > 20-day MA > 60-day MA

Scoring Criteria

• 5-day > 10-day > 20-day > 60-day: 15 points (Perfect bullish)
• 5-day > 10-day > 20-day: 12 points (Strong bullish)
• 5-day > 10-day: 8 points (Short-term bullish)
• Moving averages converging: 5 points (Direction unclear)
• Bearish arrangement: 0 points (Downward trend)

1.2 Price Relative Position (0-10 points)

Scoring Criteria

• Price > all moving averages: 10 points (Strong)
• Price > 60-day MA: 8 points (Medium-term strong)
• Price > 20-day MA: 5 points (Short-term strong)
• Price < all moving averages: 0 points (Weak)

1.3 Trend Duration (0-5 points)

Scoring Criteria

• Duration > 30 days: 5 points (Mature trend)
• Duration 20-30 days: 4 points (Established trend)
• Duration 10-20 days: 3 points (Early trend)
• Duration < 10 days: 1 point (Unstable trend)

---

2️⃣ Momentum Indicators Analysis (25 points)

2.1 RSI Relative Strength Index (0-10 points)

Health Scoring

• RSI in 40-60: 10 points (Most healthy)
• RSI in 30-40 or 60-70: 8 points (Healthy)
• RSI in 20-30 or 70-80: 5 points (Caution)
• RSI < 20 or > 80: 2 points (Overbought/oversold)

Trading Signals

Buy Signals:
- RSI breaks above 30 from below
- RSI bottom divergence (price makes new low, RSI doesn't make new low)

Sell Signals:
- RSI breaks below 70 from above
- RSI top divergence (price makes new high, RSI doesn't make new high)

2.2 MACD Indicator (0-10 points)

Status Scoring

• Golden cross + DIF > 0 + histogram expanding: 10 points (Strong buy)
• Golden cross + DIF < 0: 8 points (Buy signal)
• Golden cross + histogram contracting: 6 points (Momentum weakening)
• Death cross + DIF > 0: 3 points (Caution)
• Death cross + DIF < 0: 0 points (Sell signal)

Trading Signals

Strong Buy:
- MACD golden cross above 0 axis
- Histogram rapidly expanding

Buy:
- MACD golden cross below 0 axis
- Bottom divergence

Sell:
- MACD death cross below 0 axis
- Top divergence

2.3 Volume Coordination (0-5 points)

Volume-Price Relationship Scoring

• Rise + volume increase: 5 points (Healthy rise)
• Rise + volume decrease: 3 points (Insufficient momentum)
• Fall + volume decrease: 2 points (Selling pressure easing)
• Fall + volume increase: 0 points (Panic selling)

Relative Volume

Volume increase: Daily volume > 5-day average × 1.5
Volume decrease: Daily volume < 5-day average × 0.7

---

3️⃣ Pattern Recognition (20 points)

3.1 Classic Patterns (0-15 points)

Reversal Patterns

• Double bottom/double top: Confidence > 85% → 15 points
• Head and shoulders bottom/top: Confidence > 80% → 12 points
• Rounding bottom/top: Confidence > 75% → 10 points

Consolidation Patterns

• Ascending triangle: Confidence > 80% → 12 points
• Flag consolidation: Confidence > 75% → 10 points
• Rectangle consolidation: Confidence > 70% → 8 points

3.2 Candlestick Patterns (0-5 points)

Bullish Patterns

• Hammer: Appears at support → 5 points
• Bullish engulfing: Volume increases → 5 points
• Morning star: Three candlestick combination → 5 points

Bearish Patterns

• Shooting star: Appears at resistance → 0 points
• Bearish engulfing: Volume increases → 0 points
• Evening star: Three candlestick combination → 0 points

---

4️⃣ Support Resistance Analysis (15 points)

4.1 Distance from Support Level (0-8 points)

Scoring Criteria

Distance from support < 3%: 8 points (High safety margin)
Distance from support 3-5%: 6 points (Relatively safe)
Distance from support 5-8%: 4 points (Average)
Distance from support > 8%: 2 points (Higher risk)

4.2 Breaking Resistance Level (0-7 points)

Scoring Criteria

Effective break above resistance + volume increase: 7 points (Strong)
Break above resistance but volume decrease: 4 points (To be confirmed)
Approaching resistance without break: 2 points (Wait)
Far from resistance: 0 points (Limited space)

4.3 Support Resistance Calculation Methods

1. Historical High-Low Method

// Find important high-low points in recent 60 days
function findSupportResistance(priceHistory) {
  const highs = findLocalHighs(priceHistory);
  const lows = findLocalLows(priceHistory);
  
  // Support: Recent important low points
  const support = Math.max(...lows.slice(-3));
  
  // Resistance: Recent important high points
  const resistance = Math.min(...highs.slice(-3));
  
  return { support, resistance };
}

2. Moving Average Support Method

Short-term support: 20-day MA
Medium-term support: 60-day MA
Long-term support: 120-day MA

3. Fibonacci Retracement Method

From high point retracement:
- 0.382 retracement level (Shallow retracement)
- 0.5 retracement level (Moderate retracement)
- 0.618 retracement level (Deep retracement)

From low point rebound:
- 1.382 target level
- 1.618 target level
- 2.0 target level

---

5️⃣ Market Sentiment Analysis (10 points)

5.1 Relative Strength (0-5 points)

Scoring Criteria

Outperform market > 10%: 5 points (Strong)
Outperform market 5-10%: 4 points (Strong)
Outperform market 0-5%: 3 points (Slightly strong)
Underperform market 0-5%: 2 points (Slightly weak)
Underperform market > 5%: 0 points (Weak)

5.2 Sector Linkage (0-5 points)

Scoring Criteria

Sector leader + strong sector: 5 points
Sector follower + strong sector: 4 points
Sector leader + average sector: 3 points
Sector follower + average sector: 2 points
Sector laggard: 0 points

---

📈 Practical Application Examples

Example 1: Strong Stock Scoring

Stock: Puyuan Information (688118)
Current Price: ¥35.50

【Trend Strength】30 points → 28 points
- Moving average arrangement: 5-day>10-day>20-day>60-day(15 points)
- Price position: Above all moving averages (10 points)
- Duration: 25 days (3 points)

【Momentum Indicators】25 points → 23 points
- RSI(14): 65.3 (8 points)
- MACD: Golden cross+DIF>0+increasing (10 points)
- Volume: Volume increase on rise (5 points)

【Pattern Recognition】20 points → 18 points
- Ascending triangle: Confidence 85% (12 points)
- Bullish engulfing: Appeared yesterday (5 points)
- Pattern completeness: 90% (1 point)

【Support Resistance】15 points → 13 points
- Distance from support: 6% (4 points)
- Break above resistance: Effective break + volume increase (7 points)
- Space assessment: Good (2 points)

【Market Sentiment】10 points → 8 points
- Relative strength: Outperform market 8% (4 points)
- Sector linkage: Sector leader + strong sector (4 points)

Total Score: 90 points ⭐⭐⭐⭐⭐
Rating: Strongly Recommend

Example 2: Weak Stock Scoring

Stock: XXX (000000)
Current Price: ¥10.50

【Trend Strength】30 points → 8 points
- Moving average arrangement: Bearish arrangement (0 points)
- Price position: Below all moving averages (0 points)
- Duration: Falling for 15 days (0 points)
- Adjustment points: 8 points (Signs of rebound)

【Momentum Indicators】25 points → 10 points
- RSI(14): 25.3 (5 points - Oversold)
- MACD: Death cross+DIF<0 (0 points)
- Volume: Volume decrease on fall (5 points - Selling pressure easing)

【Pattern Recognition】20 points → 5 points
- Descending channel (0 points)
- Bearish patterns (0 points)
- Possible bottom: 5 points (RSI oversold)

【Support Resistance】15 points → 6 points
- Distance from support: 2% (6 points - Close to support)
- Resistance level: Far away (0 points)

【Market Sentiment】10 points → 0 points
- Relative strength: Underperform market 12% (0 points)
- Sector linkage: Sector laggard (0 points)

Total Score: 29 points ⭐
Rating: Not Recommend (But possible oversold rebound)

---

🎯 Usage Recommendations

1. Comprehensive Judgment

• Don't look at single indicators only
• Combine multiple dimensions for comprehensive scoring
• Pay attention to scoring change trends

2. Dynamic Adjustment

• Update scores daily
• Track scoring changes
• Adjust strategies promptly

3. Risk Control

• Set stop losses even for high-score stocks
• Low-score stocks may have oversold rebounds
• Strictly execute risk management

4. Market Environment

• Bull market: Consider above 70 points
• Sideways market: Above 80 points
• Bear market: Above 90 points or oversold rebounds

---

📚 Advanced Learning

Recommended Reading

1. 《Japanese Candlestick Charting Techniques》- Steve Nison 2. 《Reminiscences of a Stock Operator》- Edwin Lefèvre 3. 《The Turtle Trading Rules》- Curtis Faith 4. 《Technical Analysis of the Financial Markets》- Martin J. Pring

Practical Suggestions

1. Build your own scoring model 2. Backtest historical data validation 3. Keep trading logs 4. Continuously optimize and improve

US Stock Practical Examples

Case 1: Smart Stock Screening - Tech Sector

User Request:

"Help me screen for strong momentum stocks in the US tech sector"

Skill Execution Process:

1. Get tech sector candidate pool (200 stocks) 2. Technical analysis filtering (RSI, MACD, trend) 3. Comprehensive scoring and ranking 4. Return Top 10

Output Result:

# Smart Stock Screening Results - US Tech Sector

## Qualified Stocks (10 total)

### 1. NVIDIA (NVDA) ⭐⭐⭐⭐⭐
**Comprehensive Score**: 94/100

**Technical Analysis**:
- Trend: Strong uptrend 📈
- RSI(14): 67.8 (healthy range)
- MACD: Golden cross day 5, strong momentum
- Volume: 2.3x average volume
- Support: $875.00
- Resistance: $950.00

**Fundamental Highlights**:
- Market Cap: $2.15T
- P/E: 65.3 (growth premium)
- ROE: 123.5%
- Sector: AI/Semiconductors

**Buy Recommendation**: ✅ Strong Buy
- Suggested entry: $890.00-900.00
- Target price: $980.00
- Stop loss: $860.00
- Position size: 10-15%

---

### 2. Microsoft (MSFT) ⭐⭐⭐⭐
**Comprehensive Score**: 89/100

**Technical Analysis**:
- Trend: Steady uptrend 📈
- RSI(14): 62.4 (healthy range)
- MACD: Bullish momentum
- Volume: 1.8x average volume
- Support: $415.00
- Resistance: $445.00

**Fundamental Highlights**:
- Market Cap: $3.08T
- P/E: 35.2 (reasonable)
- ROE: 42.8%
- Sector: Cloud/AI/Software

**Buy Recommendation**: ✅ Buy
- Suggested entry: $425.00-430.00
- Target price: $460.00
- Stop loss: $410.00
- Position size: 10-12%

---

### 3. Advanced Micro Devices (AMD) ⭐⭐⭐⭐
**Comprehensive Score**: 86/100

**Technical Analysis**:
- Trend: Recovery uptrend 📈
- RSI(14): 58.9 (neutral-bullish)
- MACD: Turning positive
- Volume: 1.9x average volume
- Support: $145.00
- Resistance: $165.00

**Fundamental Highlights**:
- Market Cap: $245B
- P/E: 48.5 (growth)
- ROE: 15.3%
- Sector: Semiconductors/AI

**Buy Recommendation**: ✅ Buy
- Suggested entry: $152.00-155.00
- Target price: $175.00
- Stop loss: $142.00
- Position size: 8-10%

---

Case 2: Pattern Recognition - SPY (S&P 500 ETF)

User Request:

"Analyze the technical pattern for SPY"

Output Result:

# SPY Technical Pattern Analysis

## Identified Patterns

### 🔍 Bull Flag (Confidence: 82%)
- Flagpole: $505 → $525 (strong rally)
- Flag consolidation: $520-$525
- Current position: Mid-flag range
- Duration: 8 trading days

## Trading Strategies

### Strategy A: Breakout Long
- Entry: Break above $525.50
- Target: $540.00
- Stop loss: $518.00
- Risk/Reward: 1:2.0
- Position size: 15-20%

### Strategy B: Support Bounce
- Entry: Bounce at $520.00
- Target: $532.00
- Stop loss: $516.00
- Risk/Reward: 1:3.0
- Position size: 10-15%

## Key Levels
- Strong resistance: $525.50
- Support zone: $520.00-$522.00
- Major support: $515.00
- Volume profile: High volume at $522

## Market Context
- VIX: 14.2 (low volatility)
- Breadth: 65% stocks above 50-day MA
- Sector rotation: Tech leading

---

Case 3: Market Review

User Request:

"Generate today's US market review report"

Output Result:

# US Market Review - March 2, 2026

## Market Overview
- S&P 500: 5,234.56 (+0.8%)
- Nasdaq: 16,543.21 (+1.2%)
- Dow Jones: 39,876.45 (+0.5%)
- Russell 2000: 2,145.67 (+0.3%)

## Market Internals
- Advance/Decline: 2,845 : 1,234 (2.3:1)
- New Highs/Lows: 234 : 45
- Volume: Above 20-day average (+12%)
- VIX: 14.2 (-5.3%)

## Hot Sectors
1. Technology (+1.5%) - AI momentum continues
2. Communication Services (+1.2%) - Strong earnings
3. Consumer Discretionary (+0.9%) - Retail strength

## Weak Sectors
1. Energy (-0.8%) - Oil price pressure
2. Utilities (-0.5%) - Rate concerns
3. Real Estate (-0.3%) - Yield competition

## Key Movers

### Top Gainers
- NVDA: +3.2% (AI chip demand)
- META: +2.8% (Ad revenue beat)
- TSLA: +2.5% (Delivery numbers)

### Top Losers
- XOM: -2.1% (Oil price drop)
- CVX: -1.8% (Sector weakness)
- NEE: -1.5% (Utility selloff)

## Market Sentiment
- Fear & Greed Index: 68 (Greed)
- Put/Call Ratio: 0.72 (Bullish)
- AAII Bull%: 45.2% (Above average)

## Tomorrow's Watch List
- FOMC Minutes release (2:00 PM ET)
- Jobless claims data (8:30 AM ET)
- Tech earnings: ORCL, CRM

## Trading Strategy
**Bias**: Cautiously bullish
- Focus on tech leaders with momentum
- Watch for FOMC reaction
- Keep stops tight given extended levels

---

Case 4: Options Strategy - AAPL

User Request:

"Suggest an options strategy for AAPL with moderate bullish outlook"

Output Result:

# AAPL Options Strategy Analysis

## Current Market Data
- Stock Price: $178.50
- IV Rank: 32% (moderate)
- Earnings: 28 days away
- Trend: Consolidating after rally

## Recommended Strategy: Bull Call Spread

### Setup
- Buy: 180 Call @ $4.20
- Sell: 190 Call @ $1.50
- Net Debit: $2.70 per spread
- Expiration: 45 DTE (April 18, 2026)

### Risk/Reward Profile
- Max Profit: $7.30 ($730 per spread)
- Max Loss: $2.70 ($270 per spread)
- Breakeven: $182.70
- Risk/Reward: 1:2.7
- Probability of Profit: ~58%

### Greeks
- Delta: +0.42
- Theta: -0.08 (time decay)
- Vega: +0.15 (IV exposure)

### Management Rules
- Take profit: 50% max gain ($3.65)
- Stop loss: 50% max loss ($1.35)
- Adjust: Roll up if stock breaks $190

### Why This Strategy?
✅ Limited risk, defined reward
✅ Lower cost than buying stock
✅ Benefits from upward movement
✅ Time decay manageable with spread

---

Case 5: Sector Rotation Analysis

User Request:

"Analyze current sector rotation and suggest positioning"

Output Result:

# Sector Rotation Analysis - March 2026

## Current Market Phase
**Phase**: Mid-Cycle Expansion
- Economic growth: Moderate
- Fed policy: Neutral-to-accommodative
- Inflation: Moderating

## Sector Performance (30-Day)

### Leading Sectors 🚀
1. **Technology** (+8.2%)
   - AI/Cloud momentum
   - Strong earnings
   - Recommendation: Overweight

2. **Communication Services** (+6.5%)
   - Digital ad recovery
   - Streaming growth
   - Recommendation: Overweight

3. **Consumer Discretionary** (+5.1%)
   - Consumer spending resilient
   - E-commerce strong
   - Recommendation: Market weight

### Lagging Sectors 📉
1. **Energy** (-3.2%)
   - Oil price weakness
   - Demand concerns
   - Recommendation: Underweight

2. **Utilities** (-2.1%)
   - Rate sensitivity
   - Defensive rotation out
   - Recommendation: Underweight

3. **Real Estate** (-1.8%)
   - Yield competition
   - Office space concerns
   - Recommendation: Underweight

## Rotation Strategy

### Overweight Positions (60%)
- Technology: 25%
- Communication Services: 20%
- Financials: 15%

### Market Weight (30%)
- Healthcare: 15%
- Consumer Discretionary: 15%

### Underweight (10%)
- Energy: 5%
- Utilities: 3%
- Real Estate: 2%

## Key Catalysts to Watch
- Fed policy signals
- Q1 earnings season
- Economic data (GDP, employment)
- Geopolitical developments

## Tactical Recommendations
1. Add tech on pullbacks to 50-day MA
2. Trim energy on any bounce
3. Hold defensive hedges (5-10% cash)
4. Monitor sector momentum weekly

Security Policy

API Key Management

This skill requires API keys to access TradingView data through RapidAPI. Please follow these security best practices:

⚠️ Critical Security Rules

1. Never commit API keys to version control

• Do not include real API keys in configuration files that are tracked by git
• Use environment variables or secure configuration management tools
• Add configuration files with keys to .gitignore

2. Keep your API keys private

• Do not share your API keys in public forums, chat rooms, or documentation
• Do not include API keys in screenshots or screen recordings
• Treat API keys like passwords

3. Rotate keys regularly

• If you suspect your API key has been compromised, regenerate it immediately
• Consider rotating keys periodically as a security best practice

4. Use minimal permissions

• Only use API keys with the minimum required permissions
• Monitor your API usage for unexpected activity

Data Privacy

What data is sent to external APIs

When using this skill, the following data may be sent to external services:

• TradingView API: Stock symbols, market queries, and analysis requests
• RapidAPI: Authentication headers and API requests

What data is NOT sent

• Your local files and code (unless explicitly referenced in queries)
• Personal information beyond what's required for API authentication
• Conversation history (unless you explicitly include it in queries)

External Dependencies

This skill relies on the following external services:

• RapidAPI (https://rapidapi.com) - API gateway and authentication
• TradingView Data API (https://example-mcp-server.com) - Market data provider

These services have their own security policies and terms of service. Please review:

• RapidAPI Terms of Service
• RapidAPI Privacy Policy

Reporting Security Issues

If you discover a security vulnerability in this skill, please report it by:

1. Do NOT open a public GitHub issue 2. Contact the maintainer directly through GitHub private message 3. Provide detailed information about the vulnerability 4. Allow reasonable time for the issue to be addressed before public disclosure

Security Best Practices for Users

Configuration File Security

When configuring the MCP server, ensure your configuration file is secure:

# Set appropriate file permissions (Unix/Linux/macOS)
chmod 600 ~/Library/Application\ Support/Cursor/mcp_config.json

Using Environment Variables (Advanced)

For enhanced security, consider using environment variables instead of hardcoded keys:

{
  "mcpServers": {
    "RapidAPI Hub - TradingView Data": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://mcp.rapidapi.com",
        "--header",
        "x-api-host: tradingview-data1.p.rapidapi.com",
        "--header",
        "x-api-key: ${RAPIDAPI_KEY}"
      ]
    }
  }
}

Then set the environment variable:

export RAPIDAPI_KEY="your-actual-key-here"

Monitoring API Usage

Regularly check your RapidAPI dashboard to:

• Monitor API call volume
• Detect unusual activity
• Stay within rate limits
• Review billing (if applicable)

Rate Limiting and Abuse Prevention

• The free tier has rate limits to prevent abuse
• Excessive requests may result in temporary blocks
• Use caching when possible to reduce API calls
• Implement exponential backoff for retries

Disclaimer

This skill is provided "as is" without warranty of any kind. Users are responsible for:

• Securing their own API keys
• Complying with terms of service of external APIs
• Understanding the risks of using third-party services
• Any investment decisions made using this tool

Investment Risk Warning: This tool is for educational and research purposes only. It does not constitute financial advice. All investment decisions are made at your own risk.

License

This security policy is part of the TradingView Quantitative Skills project and is licensed under the MIT License.

Calendar Event Tracking Workflow

Track important market events from financial calendars, including earnings releases, dividend distributions, IPO listings, economic data releases, etc.

Execution Steps

Step 1: Determine Calendar Type

Determine the calendar type based on user needs:

• economic: Economic calendar (GDP, CPI, employment data, etc.)
• earnings: Earnings calendar (company earnings release dates)
• revenue: Dividend calendar (dividend distribution dates)
• ipo: IPO calendar (new stock listing dates)

Step 2: Determine Time Range

Calculate the query time range (Unix timestamp):

• Default query: next 7-14 days
• User can specify specific date range
• Note: Time span cannot exceed 40 days

Step 3: Determine Market Scope

Select market based on calendar type:

• Economic calendar: Supports multiple countries (america, china, japan, etc.)
• Earnings/Dividend/IPO: Default is america, can specify other markets

Step 4: Call Calendar Tool

Call tradingview_get_calendar to retrieve calendar data:

Parameter description:
- type: Calendar type (required)
  - economic: Economic events
  - earnings: Earnings releases
  - revenue: Dividend distributions
  - ipo: New stock listings
- from: Start time (required, Unix timestamp)
- to: End time (required, Unix timestamp)
- market: Market code (optional, comma-separated)

Step 5: Filter and Sort Events

Filter based on user focus:

• Sort by importance
• Filter by industry/sector
• Filter by specific securities

Step 6: Generate Calendar Report

Output formatted calendar report:

• Event list (time, event name, expected value, actual value)
• Highlight important events
• Potential impact analysis
• Recommended securities to watch

Example Conversations

User: "What important earnings are coming next week?"

Execution: 1. Calculate next week's time range (from/to timestamps) 2. Call tradingview_get_calendar with type="earnings" 3. Return earnings list, highlighting companies with high market attention 4. Suggest securities that may exceed expectations

---

User: "Check US economic data releases for the next two weeks"

Execution: 1. Calculate time range for next two weeks 2. Call tradingview_get_calendar with type="economic", market="america" 3. Return important data release times like CPI, non-farm payrolls, GDP, etc. 4. Analyze potential market impact of the data

---

User: "Check which new stocks are listing this month"

Execution: 1. Calculate time range for this month 2. Call tradingview_get_calendar with type="ipo" 3. Return new stock list including offering price, listing date, etc. 4. Analyze industry distribution of new stocks and IPO recommendations

---

User: "Are any of my holdings paying dividends soon?"

Execution: 1. Get user's stock holdings list 2. Call tradingview_get_calendar with type="revenue" 3. Filter dividend information for user's holdings 4. Return ex-dividend date, payment date, dividend amount, etc.

Deep Stock Analysis Workflow

Combine multiple MCP tools to perform comprehensive analysis on individual stocks, outputting integrated reports and trading recommendations.

Execution Steps

Step 1: Confirm Symbol

If user input is Chinese name/abbreviation, search to confirm accurate symbol:

tradingview_search_market(query="user input", filter="stock", lang="zh")

Confirm symbol format is EXCHANGE:SYMBOL (e.g., SSE:688118, NASDAQ:AAPL).

Step 2: Get Real-time Quote

tradingview_get_quote(symbol, session="regular")

Extract key data:

• Current price, change %, volume, turnover
• Bid/ask price, bid/ask volume
• 52-week high/low, market cap

Step 3: Get Multi-Timeframe Charts

Call in parallel to get data for different periods:

tradingview_get_price(symbol, timeframe='D', range=120)   # Daily - medium-term trend
tradingview_get_price(symbol, timeframe='W', range=52)    # Weekly - medium to long-term
tradingview_get_price(symbol, timeframe='60', range=100)  # 60-minute - short-term details

Optional: type='HeikinAshi' to get Heikin Ashi candles for clearer trend visualization.

Step 4: Get Detailed Technical Analysis

tradingview_get_ta(symbol, include_indicators=true)

Key Indicator Interpretation:

• Multi-timeframe signal summary (1min/5min/15min/1hour/4hour/daily/weekly/monthly)
• RSI(14): >70 overbought, <30 oversold
• MACD: Golden cross/death cross, DIF relationship with zero line
• ADX(14): >25 trending, >50 strong trend
• Moving average alignment: SMA5/10/20/60 relative relationships

See references/technical-analysis.md for detailed scoring methodology.

Step 5: Get Related News

tradingview_get_news(symbol=symbol, lang="zh-Hans", limit=5)

Get details for important news:

tradingview_get_news_detail(news_id, lang="zh-Hans")

Step 6: Query Upcoming Events

tradingview_get_calendar(type="earnings", from=now, to=now+30days, market="china")

Check for upcoming earnings, dividends, and other events.

Step 7: Generate Comprehensive Report

Output structure:

# [Stock Name] (Symbol) Deep Analysis

## Basic Information
- Current price / Change % / Volume
- Market cap / 52-week range

## Technical Analysis
- Multi-timeframe trend assessment (monthly/weekly/daily/hourly)
- Key indicator status (RSI, MACD, ADX, moving averages)
- Support levels / Resistance levels
- Overall technical score (0-100)

## Pattern Recognition
- Current pattern identification
- Confidence assessment

## News Analysis
- Recent important news summary
- Impact assessment

## Upcoming Events
- Earnings date / Dividend date

## Trading Recommendations
- Action direction (Buy/Hold/Sell)
- Suggested entry price
- Stop loss / Target price
- Position size recommendation
- Risk-reward ratio

## Risk Warnings

Example

User: "Help me analyze Primeton"

Execution: 1. search_market(query="普元信息", filter="stock") → SSE:688118 2. get_quote(symbol="SSE:688118") → Real-time quote 3. get_price × 3 timeframes → Chart data 4. get_ta(include_indicators=true) → Detailed technical indicators 5. get_news(symbol="SSE:688118", lang="zh-Hans") → Related news 6. Comprehensive scoring, generate report

Event-Driven Analysis Workflow

Track major events, analyze market impact, identify beneficiary stocks, and provide investment recommendations.

Execution Steps

Step 1: Get Financial Calendar

Call calendar based on event type (time span not exceeding 40 days):

# Earnings calendar
tradingview_get_calendar(type='earnings', from=now, to=now+14days, market='china')

# Dividend calendar
tradingview_get_calendar(type='revenue', from=now, to=now+14days, market='china')

# Economic data calendar
tradingview_get_calendar(type='economic', from=now, to=now+7days, market='america,china')

# IPO calendar
tradingview_get_calendar(type='ipo', from=now, to=now+14days, market='china')

Step 2: Get Related News

# Get specific market news
tradingview_get_news(market='stock', market_country='CN', lang='zh-Hans', limit=20)

# Get specific symbol news
tradingview_get_news(symbol='SSE:600519', lang='zh-Hans', limit=10)

# Get economic news
tradingview_get_news(market='economic', lang='zh-Hans', limit=10)

Get details for important news:

tradingview_get_news_detail(news_id, lang='zh-Hans')

Step 3: Extract Event Keywords

Extract from calendar events and news:

• Company name/symbol: Directly related stocks
• Industry keywords: Used to search for same-industry beneficiary stocks
• Policy keywords: Used to expand impact scope
• Event type: Earnings beat/policy positive/industry event/breaking news

Step 4: Search Beneficiary Stocks

Search related stocks using extracted keywords:

tradingview_search_market(query='keyword', filter='stock', limit=20)

For industry events, also find same-sector stocks via leaderboard:

tradingview_get_leaderboard(
  asset_type='stocks', tab='gainers',
  market_code='china', columnset='overview', count=50
)

Step 5: Analyze Beneficiary Stock Quotes

For identified beneficiary stocks (5-10), get quotes and technical analysis:

tradingview_get_quote_batch(symbols=[...])  # Real-time quotes
tradingview_get_ta(symbol, include_indicators=true)  # Technical confirmation

Step 6: Assess Impact Level

Assess each beneficiary stock:

Impact levels:

• Strong Positive (+3): Direct beneficiary, clear earnings improvement
• Positive (+2): Indirect beneficiary, industry prosperity improvement
• Slight Positive (+1): Sentiment positive
• Neutral (0): Limited impact
• Negative (-1/-2/-3): Symmetrical negative impact

Step 7: Generate Analysis Report

# Event-Driven Analysis Report

## Event Overview
- Event: [Event description]
- Time: [Occurrence/expected time]
- Type: [Earnings/Policy/Industry/Breaking]
- Importance: [High/Medium/Low]

## Impact Analysis
- Direct impact: ...
- Indirect impact: ...
- Impact duration: [Short-term/Medium-term/Long-term]

## Beneficiary Stock Analysis

### 1. [Stock Name] (Symbol) - Impact Level: +3
- Relevance: Direct beneficiary, [reason]
- Current price: ¥XX (Change XX%)
- Technical: RSI=XX, TA signal=[Buy/Sell]
- Trading recommendation: ...

### 2. [Stock Name] ...

## Risk Factors
- [Risk 1: Event materialization below expectations]
- [Risk 2: Market has fully priced in]

## Trading Recommendations
- Short-term strategy: ...
- Medium-term strategy: ...

Example

User: "Analyze the impact of cloud computing price increases on related companies"

Execution: 1. get_news(market='stock', market_country='CN', lang='zh-Hans') → Related news 2. get_news_detail(news_id) → News details 3. search_market(query='云计算', filter='stock') → Related stocks 4. get_leaderboard(tab='gainers', market_code='china') → Verify gainers list 5. get_quote_batch + get_ta → Quotes and technical analysis 6. Assess impact level → Generate analysis report

Exchange Overview Workflow

View the list of exchanges supported by TradingView, market configurations, and available asset types.

Execution Steps

Step 1: Determine Query Type

Determine query type based on user needs:

• exchanges: View exchange list
• markets: View market codes
• tabs: View leaderboard category tabs
• columnsets: View data column configurations
• languages: View supported languages

Step 2: Call Metadata Tool

Call tradingview_get_metadata to get configuration information:

Parameter description:
- type: Metadata type (required)
  - markets: Market code list (68+ markets)
  - tabs: Leaderboard tabs (categorized by asset type)
  - columnsets: Data column configurations (categorized by asset type)
  - languages: Supported language list
  - exchanges: Exchange list (353+ exchanges)
- asset_type: Asset type filter (optional, only for tabs)
  - stocks, indices, crypto, futures, forex, bonds, corporate_bonds, etfs

Step 3: Format Output

Format output based on query type:

Exchange List:

• Stock exchanges: NASDAQ, NYSE, HKEX, SSE, SZSE, TSE, LSE, etc.
• Cryptocurrency exchanges: Binance, Coinbase, Kraken, OKX, Bybit, etc.

Market Codes:

• North America: america, canada
• Europe: uk, germany, france
• Asia: china, japan, korea, india
• Others: australia, brazil, etc.

Leaderboard Tabs:

• Stocks: gainers, losers, large-cap, active, etc.
• Crypto: all, gainers, losers, large-cap, etc.
• Other asset type tabs

Step 4: Provide Usage Guidance

Guide users on how to use the obtained information:

• How to use market codes to query leaderboards
• How to use exchange prefixes to search symbols
• How to select appropriate leaderboard tabs

Example Conversations

User: "Which exchanges does TradingView support?"

Execution: 1. Call tradingview_get_metadata, type="exchanges" 2. Display stock exchanges and cryptocurrency exchanges by category 3. Indicate total number of exchanges (353+)

---

User: "What leaderboards are available for US stocks?"

Execution: 1. Call tradingview_get_metadata, type="tabs", asset_type="stocks" 2. Display stock leaderboard tabs: gainers, losers, large-cap, etc. 3. Explain how to use these tabs to query leaderboards

---

User: "Which countries' stock markets are supported?"

Execution: 1. Call tradingview_get_metadata, type="markets" 2. Display market code list: america, china, japan, uk, etc. 3. Explain that market codes are used for leaderboard queries

---

User: "What data columns can be displayed on leaderboards?"

Execution: 1. Call tradingview_get_metadata, type="columnsets" 2. Display available data columns by asset type:

• Stocks: overview, performance, valuation, dividends, etc.
• Crypto: overview, performance, etc.

3. Explain how to use the columnset parameter in leaderboard queries

Fundamental Screening Workflow

Use tradingview_get_leaderboard with various columnsets (valuation/profitability/dividends/balance_sheet/income_statement/cash_flow) to screen quality stocks from a fundamental perspective.

Execution Steps

Step 1: Determine Screening Strategy

Determine screening strategy based on user needs:

Step 2: Get Metadata

tradingview_get_metadata(type='markets')        # Get market_code
tradingview_get_metadata(type='columnsets')      # Confirm available columnsets

Step 3: Get Leaderboard Data (Multiple Columnsets)

Call based on strategy combination, using value investing as example:

# Get valuation data
tradingview_get_leaderboard(
  asset_type='stocks', tab='all-stocks',
  market_code='china', columnset='valuation', count=100
)

# Get profitability data
tradingview_get_leaderboard(
  asset_type='stocks', tab='all-stocks',
  market_code='china', columnset='profitability', count=100
)

# Get dividend data
tradingview_get_leaderboard(
  asset_type='stocks', tab='high-dividend',
  market_code='china', columnset='dividends', count=50
)

Step 4: Cross-Filter

Cross-filter results from multiple columnsets:

Value Investing Filter Example:

• PE < 20 (reasonable valuation)
• PB < 3 (asset discount)
• ROE > 15% (strong profitability)
• Dividend yield > 2% (dividend protection)

Growth Stock Filter Example:

• Revenue YoY growth > 20%
• Net profit growth > 15%
• ROE > 20%
• Gross margin > 40%

Step 5: Technical Validation

For top candidates (5-10), call individually:

tradingview_get_ta(symbol, include_indicators=true)

Filter out stocks with obviously weak technicals (e.g., RSI > 80 overbought, MACD death cross).

Step 6: Generate Screening Report

# Fundamental Screening Results - [Strategy Name]

## Screening Criteria
- [List all criteria]

## Qualified Stocks (Total: N)

| Rank | Stock | PE | PB | ROE | Dividend Yield | Technical Score |
|------|-------|----|----|-----|----------------|-----------------|
| 1 | ... | ... | ... | ... | ... | ... |

## Detailed Analysis (Top 5)
### 1. [Stock Name]
- Valuation: ...
- Profitability: ...
- Technical: ...
- Buy recommendation: ...

Common Screening Combinations

High Dividend Strategy

tab='high-dividend' + columnset='dividends' → Dividend yield ranking
Cross with columnset='profitability' → Confirm sustainable earnings
Cross with columnset='balance_sheet' → Confirm financial health

Low Valuation Strategy

tab='all-stocks' + columnset='valuation' → PE/PB ranking
Cross with columnset='income_statement' → Confirm revenue and profit
Cross with columnset='cash_flow' → Confirm cash flow

Blue Chip Strategy

tab='large-cap' + columnset='profitability' → Large-cap high ROE
Cross with columnset='performance' → Confirm performance trend
Cross with columnset='dividends' → Dividend protection

Multi-Symbol Batch Analysis Workflow

Batch analyze technical analysis, quote data for multiple symbols, perform horizontal comparison and comprehensive evaluation.

Execution Steps

Step 1: Collect Symbol List

Extract list of symbols to analyze from user input:

• Support up to 10 symbols for simultaneous analysis
• Symbol format: EXCHANGE:SYMBOL (e.g., NASDAQ:AAPL)

Step 2: Batch Get Real-time Quotes

Call tradingview_get_quote_batch to get real-time quotes for all symbols:

Parameter description:
- symbols: Array of symbols (1-10)
- session: Trading session (default: regular)
- fields: Return fields (default: all)

Step 3: Batch Get Historical Charts

Call tradingview_get_price_batch to get historical data for all symbols:

Parameter description:
- requests: Request array (each contains symbol, timeframe, range)
- Maximum 10 requests

Step 4: Get Technical Analysis Individually

For each symbol, call tradingview_get_ta to get technical analysis signals:

• Aggregate buy/sell/neutral signals
• Calculate comprehensive technical score

Step 5: Horizontal Comparison Analysis

Compare key metrics across symbols:

• Price change comparison: Who gained/lost the most
• Trading activity: Who has the highest volume
• Technical signal comparison: Who has the strongest technicals
• Volatility comparison: Who has the highest volatility

Step 6: Generate Comparison Report

Output comprehensive comparison report:

• Quote comparison table
• Technical score ranking
• Investment value ranking
• Risk-reward ratio comparison
• Recommended priority symbols

Example Conversations

User: "Compare and analyze AAPL, MSFT, GOOGL stocks"

Execution: 1. Call tradingview_get_quote_batch to get real-time quotes 2. Call tradingview_get_price_batch to get daily chart data 3. Call tradingview_get_ta individually to get technical analysis 4. Generate comparison table, highlighting best performers for each metric

---

User: "Batch analyze tech leader stocks"

Execution: 1. Confirm tech leader list (AAPL, MSFT, GOOGL, AMZN, META, NVDA, TSLA, etc.) 2. Batch get quotes and technical analysis 3. Sort by price change and technical score 4. Recommend symbols with strongest technicals

---

User: "Compare BTC and ETH technicals"

Execution: 1. Call tradingview_get_quote_batch, symbols=["BINANCE:BTCUSDT", "BINANCE:ETHUSDT"] 2. Call tradingview_get_price_batch to get historical charts 3. Get technical analysis signals individually 4. Compare trend strength and overbought/oversold conditions