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Skillslongbridge-invest-analysis-us

longbridge-invest-analysis-us

Data & analytics

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Updated 10-15 20:12

About this skill

Longbridge Weekly Investment Analysis

This skill is designed to automatically fetch the user's multidimensional investment data on Longbridge Securities (Longbridge) and generate Markdown and HTML reports that integrate professional candlestick charts and in-depth quantitative analysis.

Core Process

  1. Fetch Data:
    • Run script scripts/fetch_weekly_data.py。
    • Required Data:
      • portfolio.json: Holdings and assets.
      • orders.json: This week's transaction records.
      • market_temp.json: Market sentiment.
      • benchmarks/: Fetch QQQ.US and VOO.US candlestick data as benchmarks.
      • kline/: Fetch the past 200 days of daily candlestick data for held tickers, used to calculate moving averages.
      • metrics/: Fetch calc-index (PE/PB/turnover rate) and capital --flow (capital flow).

  1. Quantitative Analysis:

    • Technical Aspect: Calculate MA(5, 20, 120, 200) and EMA indicators.
    • Performance Aspect: Calculate the portfolio's excess return (Alpha) vs QQQ/VOO.
    • Capital Aspect: Summarize this week's large-order/net inflow trends.
    • Risk Aspect: Assess individual stocks' deviation from moving averages.

  2. Generate Results:

    • Generate a structured weekly_report_<DATE>.md。
    • Use assets/report_template.html to render and generate HTML, which must integrate Lightweight Charts to display dynamic candlestick charts and moving averages.

Report Structure Requirements

1. Assets and Benchmark Comparison

  • Total assets, weekly profit and loss, risk level.
  • Portfolio return vs QQQ vs VOO comparison curve or table.

2. Core Holdings Technical Analysis (with charts)

  • Each core holding must be equipped with a Lightweight Charts candlestick chart.
  • The chart includes: candlesticks, MA(5, 20, 120, 200), and this week's buy/sell point markers.
  • Financial indicators: PE, PB, this week's net capital inflow.

3. In-Depth AI Strategy Reflection

  • Analysis of excess performance based on benchmark comparison.
  • Assessment of support/resistance levels based on technical indicators.
  • Next week's operational recommendations and hedging strategies.

Constraints

  • Always prioritize using local scripts and maintain JSON data persistence.
  • Charts must support interactivity, with a visual pursuit of the ultimate Premium feel.
  • Fabricating data is strictly prohibited; if the API is missing, it must be noted.