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finance-core-analysis

Generate stage-2 publishable deep financial analysis markdown from a daily-finance brief plus current web verification, using liquidity, interest rates, risk appetite, capital flows, policy, and balance-sheet constraints. Use when user wants a deeper 公众号-style markdown analysis based on daily-finance output, core macro/market mechanism analysis, or the second step of the daily finance pipeline before finance-explosive-article.

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Core Financial Analysis

Overview

Generate a deep mechanism analysis from the stage-1 daily finance brief.

This is stage 2 of the daily finance pipeline:

daily-finance → finance-core-analysis → finance-explosive-article

Use the stage-1 file as the factual base, verify/update key data from current external sources, then produce a standalone publishable markdown analysis that can also feed the final 德哥风格爆款文章.


Input

Prefer reading:

markdown/daily-finance-YYYY-MM-DD.md

If the file is not provided:

  • Use the newest matching file by filename/date only when the user clearly asks for the latest report; state this assumption in the output metadata
  • Ask which report date or file to use when multiple plausible dates exist and "latest" is not implied
  • If the user gives raw daily-finance content in chat, use that content
  • Do not invent missing facts

Extract a reusable fact table before analysis:

FieldWhat to capture
Report dateDate used for file naming and source alignment
Key facts3-5 source-backed facts from daily-finance
NumbersActual, expected/previous, unit, direction, close/intraday status
SourcesInherited source names/links and any reliability limits
Open questionsFacts that require current re-check or must be excluded

External data step

Always access current external data when producing a current analysis.

Use web search, browser, finance tools, or available MCP tools to:

  • Re-check major market prices, yields, exchange rates, commodities, and volatility indicators
  • Verify policy statements, macro data, earnings data, and geopolitical facts
  • Update stale numbers from the stage-1 brief when newer reliable data exists
  • Add only source-verifiable data

Use source hierarchy:

  • Primary: official releases, central banks, exchanges, regulators, company filings, Reuters, Bloomberg, FT, WSJ
  • Chinese reliable sources: 财新, 第一财经, 财经, 21世纪经济报道, 经济观察报
  • Secondary sources require backtracking to original data

Current-data pull should be narrow and decision-relevant. Prioritize:

  • Rates: US 10Y/2Y, China 10Y, major central-bank signal
  • Liquidity: DXY, CNH, SHIBOR/DR007 or equivalent local liquidity indicator when relevant
  • Risk appetite: major equity index, VIX or local volatility/breadth proxy
  • Commodities: oil, gold, copper only when linked to the day's thesis

If a value cannot be verified, remove it or mark it as 【待】; never build the core judgment on 【待】.


Core model

Explain market behavior through these variables:

  • Liquidity
  • Interest rates
  • Risk appetite
  • Capital flows
  • Policy direction
  • Balance-sheet pressure
  • Incentive constraints

Use first-principles reasoning:

事件 → 约束变化 → 资金行为 → 定价结果 → 风险信号


Analysis rules

  • Separate confirmed facts from interpretation
  • Reuse source-backed numbers from daily-finance
  • Add new data only when it is necessary and source-verifiable
  • Mark uncertainty clearly
  • Write as a serious publishable 公众号 deep-analysis article; save the strongest viral packaging for finance-explosive-article
  • Do not give explicit buy/sell recommendations
  • For every major conclusion, name the constraint that changed and the observable signal that would prove it wrong
  • Avoid analyzing every lens mechanically; select the 3-5 lenses that actually explain the fact base

Validation checklist

Before final output, check:

  • Data correctness: dates, units, directions, actual vs expected, intraday vs close
  • Source consistency: important claims have reliable sources
  • Logic integrity: each conclusion follows from a mechanism, not from mood words
  • Causal chain: event, constraint, capital behavior, pricing result, risk signal
  • Counter-case: include what would make the judgment wrong
  • Publication readiness: title, subheadings, short paragraphs, clear conclusion

Required structure

1. Title

  • Use a clear 公众号-style title
  • Prefer tension and mechanism over clickbait

2. Executive judgment

  • State the single most important market judgment
  • Explain what changed today
  • Include one "what would change my mind" sentence

3. Fact base

  • Summarize the 3-5 key facts inherited from daily-finance
  • Preserve important numbers and source labels
  • Add newly verified external data when necessary
  • Use a compact table with columns: 标签, 事实, 数值, 来源, 状态

4. Mechanism analysis

Analyze through 3-5 lenses as relevant:

  • Liquidity
  • Interest rates
  • Risk appetite
  • Capital flows
  • Policy
  • Balance sheets

For each lens, explain:

  • What changed
  • Why it matters
  • How it transmits into asset prices
  • What data would confirm or falsify this lens

5. Core contradiction

Identify the main tension, for example:

  • Growth vs inflation
  • Policy easing vs currency pressure
  • Risk appetite vs earnings pressure
  • Liquidity repair vs balance-sheet contraction

6. Scenario deduction

Provide:

  • Base case
  • Alternative case
  • Falsification signal

Each scenario must specify:

  • Trigger condition
  • Asset-pricing implication
  • Observable confirmation signal

7. Key variables to watch

List 3-6 observable indicators for the next update.

8. Non-advisory implication

Explain directional exposure and risk, not ticker calls.

9. Sources

List inherited sources and any new verified sources.

10. Disclaimer

本文仅供参考,不构成投资建议。


File output

If environment allows:

Save to:

markdown/finance-core-analysis-YYYY-MM-DD.md

Rules:

  • Use the same report date as the input daily-finance file
  • Create directory if missing
  • Use UTF-8 encoding
  • Output a complete publishable markdown article, not notes
  • If write fails → fallback to chat output

Writing style

  • Use 公众号-readable structure: strong title, short paragraphs, numbered sections
  • Keep the tone sharp but rational
  • Explain mechanisms in plain Chinese
  • Use contrast where helpful: "不是A,而是B"
  • Avoid empty emotional phrases and unexplained jargon

Goal

Produce a reusable deep-analysis document that answers:

  • What changed
  • Why it changed
  • What mechanism connects facts to asset pricing
  • What would prove the analysis wrong
Repository
digoal/blog
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