/finance-core-analysis

name: finance-core-analysis
description: 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.

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.

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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:

| Field | What to capture | |---|---| | Report date | Date used for file naming and source alignment | | Key facts | 3-5 source-backed facts from daily-finance | | Numbers | Actual, expected/previous, unit, direction, close/intraday status | | Sources | Inherited source names/links and any reliability limits | | Open questions | Facts that require current re-check or must be excluded |

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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】`.

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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`

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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

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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

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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。

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File output

If environment allows:

Save to:

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

Rules:

• Use the same report date