analyzing-structured-note-payoffs
Deconstructs structured note payoffs with embedded option identification, issuer credit risk, and all-in cost analysis. Use when analyzing structured notes, evaluating embedded options, or assessing structured product costs.
Best use case
analyzing-structured-note-payoffs is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Deconstructs structured note payoffs with embedded option identification, issuer credit risk, and all-in cost analysis. Use when analyzing structured notes, evaluating embedded options, or assessing structured product costs.
Teams using analyzing-structured-note-payoffs should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/analyzing-structured-note-payoffs/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How analyzing-structured-note-payoffs Compares
| Feature / Agent | analyzing-structured-note-payoffs | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Deconstructs structured note payoffs with embedded option identification, issuer credit risk, and all-in cost analysis. Use when analyzing structured notes, evaluating embedded options, or assessing structured product costs.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Analyzing Structured Note Payoffs Deconstructs structured note payoffs with embedded option identification, issuer credit risk, and all-in cost analysis. ## When To Use - Evaluating a structured note term sheet or offering document before purchase - Reverse-engineering the payoff profile to identify embedded derivatives - Comparing all-in cost of a structured note against replicating the position with vanilla instruments - Assessing issuer credit risk embedded in unsecured note obligations - Reviewing suitability of a structured product for a portfolio or hedging program ## Inputs To Gather - **Term sheet or offering supplement** — maturity, coupon structure, underlier(s), barrier levels, participation rates, caps/floors - **Underlier data** — current spot price, dividend yield, historical and implied volatility for relevant tenors - **Issuer credit profile** — CDS spread or credit rating, senior unsecured spread curve - **Risk-free rate curve** — swap or Treasury curve matching the note's currency and tenor - **Comparable vanilla pricing** — broker quotes or model prices for the component options (calls, puts, digital options, knock-in/knock-out barriers) - **Fee disclosures** — stated issuance fees, placement agent commissions, estimated hedging costs if available ## Workflow 1. **Map the payoff formula.** Parse the term sheet to express the note's return as a piecewise function of the underlier at maturity (and at observation dates for autocallables or barrier-monitoring notes). Identify all scenarios: full principal return, enhanced upside, partial protection, full loss. 2. **Decompose into component instruments.** Break the payoff into a combination of: - Zero-coupon bond (issuer credit) - Long/short vanilla calls or puts at stated strikes - Digital (binary) options for fixed coupon triggers - Barrier options (knock-in puts, knock-out calls) with specified levels - Worst-of or basket features if multi-underlier 3. **Price each component independently.** - Value the bond component by discounting at the issuer's credit spread over the risk-free curve - Price option components using Black-Scholes, local volatility, or Monte Carlo as appropriate for the payoff complexity - For barrier and autocall features, use Monte Carlo with correlation assumptions for multi-asset notes [VERIFY correlation inputs against market data] - Sum component values to derive a theoretical fair value for the note 4. **Calculate the all-in cost.** - Compare fair value to par (issue price): the difference represents the total embedded cost to the investor - Express as annualized cost drag (bps/year) over the note's expected life - Decompose cost into identifiable buckets: issuer funding advantage, option premium markup, placement fees 5. **Assess issuer credit risk.** - Quantify the credit spread component — how much yield is the investor forgoing by holding unsecured issuer paper vs. a risk-free instrument - Evaluate whether the note's coupon or enhanced return adequately compensates for issuer default risk - Flag if issuer CDS spread has moved materially since issuance [VERIFY current CDS levels] 6. **Scenario and sensitivity analysis.** - Run payoff under spot moves of -30%, -15%, flat, +15%, +30% at maturity - Test sensitivity to implied volatility shifts (+/- 5 vol points) - For autocallables, model probability of early call at each observation date - For worst-of notes, stress correlation assumptions (e.g., correlation drops from 0.7 to 0.3) 7. **Compare to replication portfolio.** Estimate the cost of replicating the note's payoff using exchange-traded or OTC options plus a money-market position. If replication is cheaper, quantify the savings. ## Output Structure the analysis report with these sections: - **Note Summary** — issuer, maturity, underlier(s), key terms (barrier, participation rate, cap, coupon) - **Payoff Diagram** — describe or tabulate the piecewise payoff across underlier price ranges - **Embedded Option Decomposition** — table listing each component, notional, strike/barrier, and individual fair value - **Fair Value vs. Issue Price** — total note fair value, cost to investor in dollar and annualized basis-point terms - **Issuer Credit Assessment** — credit spread, implied default probability over note tenor, rating - **Scenario Table** — payoff under each scenario with probability-weighted expected return - **Replication Comparison** — cost and feasibility of replicating via vanilla instruments - **Key Risks** — maximum loss scenario, barrier proximity, correlation risk, early call risk, liquidity risk (secondary market) ## Quality Checks - Verify the sum of decomposed component values approximates the issue price (residual = embedded cost); flag if residual exceeds 5% of notional without explanation - Confirm barrier levels and strike prices match the term sheet exactly — transcription errors here invalidate the entire analysis - Ensure the discount rate used for the bond component reflects the issuer's actual credit curve, not a generic spread [VERIFY] - For multi-underlier notes, confirm correlation assumptions are sourced from market data, not assumed - Check that scenario analysis covers the maximum-loss case (e.g., underlier drops below knock-in barrier) - Validate that annualized cost calculation uses the correct day count convention and expected life (not stated maturity for autocallables) [VERIFY day count convention per term sheet] - Flag any terms that create asymmetric issuer optionality (e.g., issuer call provisions, discretionary coupon features)
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