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. 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