bond-relative-value
anthropics/financial-services
Analyze bond richness/cheapness via spread decomposition, yield curves, credit spreads, and scenario stress testing.
What is bond-relative-value?
Perform relative value analysis on bonds by decomposing total spread into risk-free, credit, and residual components, then stress-test under rate scenarios. Use this when comparing bonds, assessing whether spreads adequately compensate for risk, or evaluating bond value relative to curves.
- Decompose bond spreads into G-spread, credit curve, and residual (liquidity/technicals) components
- Price bonds and extract yield, duration, convexity, DV01, and Z-spread
- Retrieve government and swap yield curves to compute risk-free benchmarks
- Access credit spread curves by issuer country and type
- Run parallel rate-shock scenarios (-100bp to +100bp) to model price and P&L impact
- Retrieve historical pricing data for Z-score and percentile context
How to install bond-relative-value
npx skills add https://github.com/anthropics/financial-services --skill bond-relative-value- Access to MCP tools: bond_price, interest_rate_curve, credit_curve, yieldbook_scenario, tscc_historical_pricing_summaries, and fixed_income_risk_analytics
- Bond identifiers (ISIN, RIC, or CUSIP) for the securities being analyzed
- Familiarity with spread decomposition and relative value concepts
How to use bond-relative-value
- 1.Call bond_price with the target bond's identifier to extract yield, Z-spread, duration, and DV01
- 2.Retrieve the government or swap yield curve for the bond's currency and interpolate at maturity to compute G-spread
- 3.Query the credit_curve tool for the issuer's country and type, then extract credit spread at the bond's maturity
- 4.Calculate residual spread as G-spread minus credit curve spread to isolate liquidity and technical factors
- 5.Run yieldbook_scenario with parallel rate shifts (-100bp, -50bp, 0, +50bp, +100bp) and record price changes
- 6.Optionally retrieve historical pricing summaries to assess current spread percentile and Z-score
- 7.Synthesize results into a spread decomposition table, scenario P&L table, and rich/cheap recommendation with quantified breakeven spread moves
Use cases
- Determine if a corporate bond's spread is rich or cheap relative to its credit risk and rate environment
- Compare two bonds in the same sector to identify relative value opportunities
- Assess how a bond's value changes under different interest rate scenarios before committing capital
- Isolate the residual spread component to identify technicals or liquidity premiums
- Benchmark current spreads against historical ranges to contextualize valuation
- Fixed income analysts and portfolio managers
- Credit traders evaluating bond opportunities
- Risk managers stress-testing bond portfolios
- Investment committees assessing bond recommendations
bond-relative-value FAQ
Residual spread is total G-spread minus the credit curve spread. It captures liquidity premiums, technicals, and other factors beyond rates and credit. A wide residual suggests the bond may be cheap (good value) or illiquid (bad for trading).
Scenario P&L shows how the bond's price changes under different parallel rate shifts. Positive P&L under rate declines (bullish scenarios) and negative under rate rises (bearish) is typical. Compare P&L across bonds to assess relative rate sensitivity.
A rich bond has spreads that do not adequately compensate for its risks—it is overvalued. The recommendation is to avoid or underweight. Typically indicated by spreads tighter than historical averages or credit curve benchmarks.
Yes. Use the fixed_income_risk_analytics tool to extract OAS and effective duration for callable bonds, which account for embedded optionality. Then proceed with spread decomposition and scenario analysis as normal.
Refresh when market conditions change significantly (rate moves, credit events, liquidity shifts) or when the bond's spread moves materially from your last assessment. Daily or weekly updates are typical for active portfolios.
Full instructions (SKILL.md)
Source of truth, from anthropics/financial-services.
name: bond-relative-value description: Perform relative value analysis on bonds by combining pricing, yield curve context, credit spreads, and scenario stress testing. Use when analyzing bond richness/cheapness, computing spread decomposition, comparing bonds, assessing bond value vs curves, or running rate shock scenarios.
Bond Relative Value Analysis
You are an expert fixed income analyst specializing in relative value. Combine bond pricing, yield curves, credit curves, and scenario analysis from MCP tools to assess whether bonds are rich, cheap, or fair. Focus on routing tool outputs into spread decomposition and scenario tables — let the tools compute, you synthesize and recommend.
Core Principles
Relative value is about whether a bond's spread adequately compensates for its risks relative to comparable instruments. Always decompose total spread into risk-free + credit + residual components. The residual (what's left after rates and credit) reveals true richness or cheapness. Stress test with scenarios to confirm the view holds under different rate environments.
Available MCP Tools
bond_price— Price bonds. Returns clean/dirty price, yield, duration, convexity, DV01, Z-spread. Accepts ISIN, RIC, or CUSIP.interest_rate_curve— Government and swap yield curves. Two-phase: list then calculate. Use to compute G-spreads.credit_curve— Credit spread curves by issuer type. Two-phase: search by country/issuerType, then calculate. Use to isolate credit component.yieldbook_scenario— Scenario analysis with parallel rate shifts. Returns price change and P&L under each scenario.tscc_historical_pricing_summaries— Historical pricing data. Use for historical spread context and Z-score analysis.fixed_income_risk_analytics— OAS, effective duration, key rate durations. Use for callable bonds and deeper risk decomposition.
Tool Chaining Workflow
- Price the Bond(s): Call
bond_pricefor target and any comparison bonds. Extract yield, Z-spread, duration, convexity, DV01. - Get Risk-Free Curve: Call
interest_rate_curve(list then calculate) for the bond's currency. Interpolate at bond maturity to compute G-spread. - Get Credit Curve: Call
credit_curvefor the issuer's country and type. Extract credit spread at the bond's maturity. Compute residual spread = G-spread minus credit curve spread. - Run Scenarios: Call
yieldbook_scenariowith parallel shifts (-100bp, -50bp, 0, +50bp, +100bp). Extract price changes and P&L per scenario. - Historical Context (optional): Call
tscc_historical_pricing_summariesfor the bond to assess where current spread sits vs history. - Synthesize: Combine spread decomposition, scenario results, and historical context into a rich/cheap assessment.
Output Format
Spread Decomposition
| Component | Spread (bp) | % of Total |
|---|---|---|
| G-spread (total over govt) | ... | 100% |
| Credit curve spread | ... | ...% |
| Residual (liquidity + technicals) | ... | ...% |
Scenario P&L
| Scenario | Price Change | P&L (per 100 notional) |
|---|---|---|
| -100bp | ... | ... |
| -50bp | ... | ... |
| Base | ... | ... |
| +50bp | ... | ... |
| +100bp | ... | ... |
Rich/Cheap Summary
State the primary spread metric, its historical context (percentile, comparison to averages), the residual spread signal, and a clear recommendation: rich (avoid/underweight), cheap (buy/overweight), or fair (neutral). Quantify how many bp of spread move would change the recommendation.
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