Bond Relative Value

anthropics/financial-services/plugins/partner-built/lseg/skills/bond-relative-value

by anthropics574ed3624aebNo license39K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 2 weeks ago

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.

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AI-generated overview

Analyzes bond relative value by decomposing spreads and running rate-shock scenarios via fixed income MCP tools.

What it does
Guides an agent through a fixed income relative value workflow: pricing bonds, pulling government and credit curves, decomposing total spread into risk-free, credit and residual components, and running parallel rate-shift scenarios. It produces spread decomposition tables, scenario P&L tables, and a rich/cheap recommendation with quantified thresholds. The skill is instructions only and relies on MCP tools to perform the calculations.
When to use it
Use when assessing whether a bond is rich, cheap or fair, comparing bonds, computing spread decomposition, or stress testing a bond position against rate shocks.
Requirements
Requires access to the referenced MCP tools: bond_price, interest_rate_curve, credit_curve, yieldbook_scenario, tscc_historical_pricing_summaries and fixed_income_risk_analytics. No scripts are shipped; it is instructions only.

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

  1. Price the Bond(s): Call bond_price for target and any comparison bonds. Extract yield, Z-spread, duration, convexity, DV01.
  2. Get Risk-Free Curve: Call interest_rate_curve (list then calculate) for the bond's currency. Interpolate at bond maturity to compute G-spread.
  3. Get Credit Curve: Call credit_curve for the issuer's country and type. Extract credit spread at the bond's maturity. Compute residual spread = G-spread minus credit curve spread.
  4. Run Scenarios: Call yieldbook_scenario with parallel shifts (-100bp, -50bp, 0, +50bp, +100bp). Extract price changes and P&L per scenario.
  5. Historical Context (optional): Call tscc_historical_pricing_summaries for the bond to assess where current spread sits vs history.
  6. Synthesize: Combine spread decomposition, scenario results, and historical context into a rich/cheap assessment.

Output Format

Spread Decomposition

ComponentSpread (bp)% of Total
G-spread (total over govt)...100%
Credit curve spread......%
Residual (liquidity + technicals)......%

Scenario P&L

ScenarioPrice ChangeP&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.

Source and attribution

Source:anthropics/financial-servicesinplugins/partner-built/lseg/skills/bond-relative-valueat commit574ed36

License: No license

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