finance-core-analysis

# 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: | 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 | --- ## 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