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llmquant-credit

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LLMQuant Credit

LLMQuant 信用模块

This category routes credit research workflows for issuer risk, spread regimes, and high-yield stress.
该类别用于路由针对发行人风险、利差机制和高收益压力的信用研究工作流。

Routing Rules

路由规则

  1. Identify issuer, ticker, bond, index, sector, maturity bucket, credit rating, and horizon.
  2. Select the closest workflow below.
  3. Open only that workflow and any referenced local resources.
  4. Use LLMQuant Data for filings, debt schedule, fundamentals, rates, spreads, ratings, equity prices, CDS, and macro context.
  5. Report filing dates, market timestamps, rating dates, observation windows, stale notices, and missing inputs.
  1. 识别发行人、股票代码、债券、指数、行业、到期期限区间、信用评级和时间范围。
  2. 选择最匹配的下方工作流。
  3. 仅打开该工作流及所有引用的本地资源。
  4. 使用LLMQuant Data获取备案文件、债务计划表、基本面数据、利率、利差、评级、股票价格、CDS和宏观环境信息。
  5. 报告备案日期、市场时间戳、评级日期、观察窗口、过期通知以及缺失的输入信息。

Workflow Index

工作流索引

User intentWorkflow
Review an issuer's balance-sheet, cash-flow, maturity, and covenant credit risk.
workflows/issuer-credit-risk-review.md
Diagnose credit-spread regime, risk appetite, and sector pressure.
workflows/credit-spread-regime.md
Monitor high-yield stress, refinancing risk, fallen angels, and default pressure.
workflows/high-yield-stress-monitor.md
用户意图工作流
审查发行人的资产负债表、现金流、到期期限和契约信用风险。
workflows/issuer-credit-risk-review.md
分析信用利差机制、风险偏好和行业压力。
workflows/credit-spread-regime.md
监控高收益压力、再融资风险、堕落天使和违约压力。
workflows/high-yield-stress-monitor.md

LLMQuant Data Contract

LLMQuant 数据协议

Prefer LLMQuant Data when available. The workflows may need these data capabilities:
  • Retrieve issuer filings, financial statements, debt schedules, maturity ladders, segment exposure, and risk factors.
  • Retrieve bond, CDS, spread, rating, recovery, default, and sector credit data when available.
  • Retrieve rates, yield curves, equity prices, volatility, liquidity, macro, commodity, and FX context.
  • Retrieve ETF holdings or fund-flow data for credit ETFs and crowded exposures when available.
Fallback:
  • If bond-level, CDS, or rating data is unavailable, use filings, equity, rates, and macro evidence while naming missing credit-market inputs.
  • Do not estimate covenant headroom or default probability without required terms and market data.
优先使用可用的LLMQuant Data。工作流可能需要以下数据能力：
  • 获取发行人备案文件、财务报表、债务计划表、到期期限阶梯、细分业务敞口和风险因素。
  • 获取债券、CDS、利差、评级、回收率、违约率和行业信用数据（如有可用）。
  • 获取利率、收益率曲线、股票价格、波动率、流动性、宏观经济、大宗商品和外汇环境信息。
  • 获取信用ETF的持仓或资金流数据以及集中敞口信息（如有可用）。
Fallback:
  • 如果债券层面、CDS或评级数据不可用，使用备案文件、股票、利率和宏观数据作为依据，并注明缺失的信用市场输入信息。
  • 在缺少必要条款和市场数据的情况下，不得估算契约缓冲空间或违约概率。