Stock Valuation

Stock Valuation 报告 生成器 v3.0

生成 professional valuation 报告s with ONE command. The 流水线 auto-检测s peers, 运行s all 8 data scripts in parallel, and produces a polished HTML 报告.

Quick 启动 (One Prompt) User: "生成 a valuation 报告 for AAPL"

代理 steps:

Step 1: 运行 Data 流水线 uv 运行 --with yfinance,matplotlib,lxml python3 $技能_DIR/scripts/运行_流水线.py TICKER # 输出s: /tmp/TICKER_data.json

Options:

# Specify peers manually uv 运行 --with yfinance,matplotlib,lxml python3 $技能_DIR/scripts/运行_流水线.py AAPL --peers MSFT GOOG META

Step 2: Qualitative Re搜索 (MANDATORY)

运行 these 搜索es in parallel and collect the 结果s into /tmp/TICKER_re搜索.json:

2a. Seeking Alpha Re搜索 网页_搜索 "{TICKER} seekingalpha analysis 2025 2026" 网页_搜索 "seekingalpha {TICKER} strong buy OR turning bullish OR high growth"

提取 3-5 articles: title, date, rating (Strong Buy/Buy/Hold/Sell), one-sentence thesis.

2b. X/Twitter Sentiment # If bird 命令行工具 avAIlable: bird 搜索 '$TICKER' -n 15 --plAIn # Otherwise: 网页_搜索 "{TICKER} stock twitter sentiment price tar获取"

提取 3-5 notable posts: username, bull/bear stance, key argument, any specific price tar获取.

2c. Analyst Consensus 网页_搜索 "{TICKER} analyst price tar获取 consensus 2026"

提取: consensus rating, average/low/high price tar获取s.

2d. Earnings & Revenue 网页_搜索 "{TICKER} latest earnings call revenue composition segments" 网页_fetch "BEST_EARNINGS_URL" --maxChars 6000

提取: revenue by segment (amount, % of total, YoY growth), geographic breakdown, funded accounts/AUM/key KPIs, management 图形界面dance.

2e. Catalysts & Risks

Synthesize from all re搜索 above. AIm for 5-7 catalysts and 5-7 risks (with mitigants).

Save as Re搜索 JSON

Save to /tmp/TICKER_re搜索.json:

{ "sa_articles": [ {"title": "Article Title", "date": "Dec 2025", "rating": "Strong Buy", "summary": "Key thesis in one sentence"} ], "twitter_sentiment": [ {"user": "FinanceGuy", "stance": "Bullish", "summary": "Key argument or price tar获取"} ], "analyst_consensus": {"rating": "Strong Buy", "avg_pt": 200.0, "low_pt": 150.0, "high_pt": 250.0}, "catalysts": [ "Q4 earnings beat could trigger re-rating (报告ing Mar 19)", "Geographic expansion into new markets reducing concentration risk" ], "risks": [ "Regulatory risk in key markets. Mitigant: diversified across 6+ jurisdictions", "Trading volume cy命令行工具cality. Mitigant: interest income provides stable base" ], "revenue_composition": [ {"流": "Product Sales", "amount": "$50B", "pct": "52%", "trend": "Strong growth", "notes": "Core hardware"} ], "geographic_data": [ {"market": "Americas", "new_accounts_pct": "45%", "avg_deposit": "$50K", "highlights": "Largest market"} ] }

Step 3: 生成 报告 uv 运行 python3 $技能_DIR/scripts/生成_报告.py /tmp/TICKER_data.json --re搜索 /tmp/TICKER_re搜索.json # 输出s: /tmp/TICKER_报告.html

Step 4: Convert to PDF & Deliver /应用s/Google\ Chrome.应用/Contents/MacOS/Google\ Chrome \ --headless --disable-gpu --print-to-pdf=/tmp/TICKER_报告.pdf \ --no-pdf-header-footer /tmp/TICKER_报告.html

Deliver the PDF (and optionally HTML) to the user.

Script Reference Script Deps 输出 运行_流水线.py TICKER [--peers P1 P2] [--输出] yfinance,matplotlib,lxml Merged JSON → file 生成_报告.py DATA.json [--输出] [--re搜索] (none) HTML 报告 fetch_fundamentals.py TICKER [PEERS...] yfinance Financials, ratios, peer data fetch_technicals.py TICKER yfinance SMAs, RSI, MACD, 52W range fetch_historical_valuation.py TICKER yfinance,lxml 5yr P/E 历史, percentile dcf_模型.py TICKER [--wacc] [--growth-*] yfinance 10yr DCF bear/base/bull fetch_insiders.py TICKER yfinance Insider txns + institutional holders fetch_options.py TICKER yfinance P/C ratio, IV, unusual vol fetch_earnings_calendar.py TICKER yfinance Next earnings date 生成_图表s.py TICKER yfinance,matplotlib 4 PNGs → /tmp/ 检测_peers.py TICKER [--count N] yfinance Auto-检测ed peers 过滤器_tweets.py (stdin) (none) 过滤器ed tweet JSON 报告 Sections

The 生成d 报告 includes all of these (in order):

Header (company name, ticker, date, data sources) Earnings Badge (next earnings date) KPI Cards (price, MCap, P/E, margins — 2 rows of 4) Quarterly Trends (with QoQ growth arrows ↑↑/↑/→/↓) Revenue Composition (segment breakdown table + insight callout) Geographic Expansion (market-by-market table) Technical Analysis (6-panel: RSI, SMAs, MACD, 52W range) 图表s (2×2 grid: price+SMA, revenue, margins, PE 历史) Historical Valuation (5Y PE avg, range, percentile + mean reversion callout) Peer Comparison (full table with highlight row + discount callout) Options Sentiment (4 KPI cards + interpretation) Insider Activity Seeking Alpha Re搜索 (bullish/cautious grouping + consensus callout) X/Twitter Sentiment (notable takes + consensus callout) Catalysts (5-7 items, most 导入ant first) Risks