A-Share Stock Volume Top 20 Ranking from Wencai
Paste the following prompt into your AI chat to install this skill:
Please follow https://skillhub.cn/install/skillhub.md to install @user_8c7f0f65/volumetop20.
About this skill
The Specific Problem
In A-share trading, trading volume is a core metric for stock liquidity and capital attention. Investors and quantitative teams need to efficiently monitor the top stocks by trading volume to capture market hotspots, track sector rotations, and formulate strategies. Traditional methods rely on manually browsing financial websites, which is cumbersome for data extraction and prone to delays, hindering real-time analysis. Thus, an automated skill for fetching top 20 volume data becomes essential, providing structured information to support decision-making workflows.
How the Skill Works
This skill is built on the Wencai platform, implementing data collection and analysis through key steps:
- Data Source Integration: Uses browser automation to visit
https://www.iwencai.com, entering query phrases like成交额TOP20in the search box to trigger data requests. User login is required for complete datasets. - Data Extraction and Cleaning: Parses each stock's rank, name, price change percentage, trading volume,
Wencai industry, current price, and stock code from query results, ensuring field alignment and data integrity. - Structured Output: Presents data in a standard Markdown table for readability and import into other tools. The table covers all key fields and supports custom format extensions.
- Sector-Level Statistics: Computes summary metrics by first-level industry, including count, proportion, total trading volume, and average price change, sorted by trading volume from highest to lowest, with representative stocks listed to highlight sector contributions.
- Intelligent Analysis: Generates sector ratings and logical analysis based on price change and trading volume data, helping users identify capital flow and potential trends—for example, high volume with price changes may signal sector rotation opportunities.
Boundaries and Notes
While convenient, this skill has limitations to consider:
- Login Requirement: A Wencai account login is mandatory; otherwise, data may be incomplete or inaccessible.
- Data Timeliness: Returns data from the previous trading day's close, not real-time, suitable for retrospective analysis and trend assessment, not intraday decisions.
- Query Dependency: Each execution requires re-fetching to ensure freshness; historical data caching is not supported for continuous tracking.
- Platform Compatibility: Based on web scraping, updates to Wencai's interface may affect stability, requiring periodic verification.
- Output Extensibility: Table output can be saved to files (e.g., JSON or Markdown) or pushed to platforms like WeChat, but automation workflows need manual configuration.
Use Cases
- After market close, a stock analyst needs to fetch top 20 volume data to generate a capital flow report and identify hot sectors for the day.
- When backtesting stock selection strategies, a quant researcher must extract industry distribution from the top 20 volume list to analyze sector rotation and refine factor models.
- An investment advisor preparing a weekly market brief for clients compares this week's top 20 volume list with the previous week's, highlighting new or exited stocks and reasons.
- A risk control team monitors abnormal trading activities by quickly obtaining a high-volume stock list, assessing potential risk concentration combined with sector classification.
Best For
- Stock Analysts: Daily parsing of volume data to track sector heat changes, providing key data support for investment strategy reports.
- Quantitative Traders: Building automated trading systems based on volume factors, requiring scheduled top 20 data fetches to update model inputs.
- Investment Advisors: Customizing market analysis briefs for clients, relying on intuitive tables and sector statistics to showcase market dynamics and stock changes.
- Financial Content Creators: Writing in-depth market analysis articles, needing structured volume data and sector ratings as content material.
Related Skills
A universal base component that automatically launches the Edge browser and connects the BrowserSkill extension, ensuring readiness for web scraping and browser automation tasks.
A fully local-run WeChat chat analysis tool with MBTI personality inference, sentiment analysis, risk detection, relationship health assessment, and conversation prediction, emphasizing privacy.
Performs project discrimination, classification, and structured extraction on bidding documents, outputting standardized data with support for manual review.
A data-model-based tool for quantitative football match analysis, offering verifiable frameworks such as win-draw-loss probabilities, upset risk assessments, and advancement path simulations.