China Pptx Author

china-pptx-author

Purpose

Generate professional A股投资分析PPT for any listed company. This skill is a generic engine — every output is driven by two parameters:

All financial figures, price data, peer valuations, and company descriptions are fetched live from iFind / AkShare / public APIs. Nothing is hardcoded.

Data Pipeline

Step 1: Resolve Company Info

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# MCP tool: search_stock
search_stock(keyword="{{COMPANY_NAME}}")
# → confirms ticker, exchange (SH/SZ), full legal name

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# MCP tool: get_quote
get_quote(ticker="{{TICKER}}")
# → live price, PE, PB, market cap, turnover, 52-week range

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# MCP tool: get_financials
get_financials(ticker="{{TICKER}}", statement_type="income", period="annual")
# → annual income statement: revenue, net profit, margins, EPS, etc.
get_financials(ticker="{{TICKER}}", statement_type="balance", period="annual")
# → balance sheet: assets, liabilities, equity
get_financials(ticker="{{TICKER}}", statement_type="cashflow", period="annual")
# → cash flow statement

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# MCP tool: get_historical_data
get_historical_data(ticker="{{TICKER}}", frequency="weekly", start_date="{{START_DATE}}", end_date="{{END_DATE}}")
# → OHLCV price history for trend charts

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# MCP tool: get_industry_stocks
get_industry_stocks(industry="{{INDUSTRY_NAME}}")
# → peer companies in the same sector for comps analysis

Step 2: Fetch Peer Data

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# For each peer returned by get_industry_stocks, call get_quote to get PE/PB
# Focus on top 5-8 comparable companies by revenue/market cap

Step 3: Generate Charts

Use matplotlib to create:

1. Revenue & Profit trend — from get_financials(income)
2. Margin trends — gross margin, net margin, ROE over time
3. Growth rates — YoY revenue and profit growth
4. Peer comparison — horizontal bar chart of PE and PB vs peers
5. Price trend — from get_historical_data
6. Valuation range — football field based on peer PE distribution

All chart titles and labels must include {{COMPANY_NAME}} dynamically.

Presentation Structure

The default deck is 12 slides. Adjust sections based on deck_type parameter.

Template (parameterized)

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Slide 1:  Cover
    {{COMPANY_NAME}} ({{TICKER}}.{{EXCHANGE}})
    {{REPORT_TITLE}}  |  {{DATE}}
    机密文件 | 仅供内部参考

Slide 2:  投资摘要 (Investment Highlights)
    • {{HIGHLIGHT_1}}
    • {{HIGHLIGHT_2}}
    • {{HIGHLIGHT_3}}
    目标价: ¥{{TARGET_PRICE_LOW}} - ¥{{TARGET_PRICE_HIGH}}
    评级: {{RATING}}

Slide 3:  公司概览 (Company Overview)
    {{COMPANY_DESCRIPTION}}
    主营业务: {{MAIN_BUSINESS}}
    成立时间 | 上市板块 | 控股股东 (all from search_stock / get_quote)

Slide 4:  行业分析 (Industry Overview)
    {{INDUSTRY_NAME}} — market size, trends, policy
    Data from: get_industry_stocks result analysis

Slide 5:  财务分析 (Financial Summary)
    [Chart: Revenue & Profit]  [Chart: Margin Trends]
    [Chart: Growth Rates]
    All data from get_financials(income, annual)

Slide 6:  运营指标 (Operating Metrics)
    Segment breakdown, KPIs (if available from financials)

Slide 7:  可比公司估值 (Trading Comparables)
    [Chart: Peer PE/PB comparison]
    Table: Peer | Market Cap | P/E | P/B | EV/EBITDA

Slide 8:  估值分析 (Valuation)
    [Chart: Football field]
    DCF / PE / PB ranges derived from peer analysis

Slide 9:  投资逻辑 (Investment Thesis)
    3-5 key investment bullets derived from data analysis

Slide 10: 风险提示 (Risk Factors)
    Generic risk categories, customized from industry context

Slide 11: 投资建议 (Recommendation)
    评级 + 目标价 range + upside calculation

Slide 12: 免责声明 (Disclaimer)
    Standard A-share research disclaimer

Deck Type Variants

Design Standards

Content Rules

A-Share Terminology

Quality Checklist

Before delivering the PPT:

• All {{PLACEHOLDER}} replaced with live data
• Charts readable, labeled, sourced
• Numbers consistent across slides (revenue matches across chart/table/text)
• Company name and ticker correct throughout
• Peer data reflects actual industry comparables
• Disclaimer slide included
• File named: {{COMPANY_NAME}}_{{TICKER}}_{{REPORT_TITLE}}.pptx

Usage

Invoke the generation script (from project root):

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cd {{PROJECT_ROOT}} && python3 scripts/generate_a_share_ppt.py \
  --company "{{COMPANY_NAME}}" \
  --ticker "{{TICKER}}" \
  --industry "{{INDUSTRY_NAME}}" \
  --output "{{OUTPUT_PATH}}" \
  --type {{DECK_TYPE}} \
  --title "{{REPORT_TITLE}}"

Required args: --company, --ticker Optional: --industry (for peer lookup), --output, --type (pitch/deep_dive/initiation), --title

If --industry is omitted, the script attempts to infer it from the company's sector classification.

Data Source Mode Switch: Set env var IFIND_DATA_SOURCE_MODE to control data source preference.

• ifind-only (strict): Use iFind only, error if unavailable
• ifind-fallback (default): iFind preferred, fallback to AkShare
• akshare-only, wind-only (Wind only), wind-fallback (Wind first, fallback to iFind → AkShare): Skip iFind, use AkShare only