skills/fixed-income/SKILL.md
[STUB] Bond pricing, yield curves, duration and convexity analysis, and DeFi lending rate modeling
npx skillsauth add agiprolabs/claude-trading-skills fixed-incomeInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Status: STUB — This skill provides a basic bond calculator and an overview of planned capabilities. Full implementation is awaiting community contribution.
Fixed income analysis bridges traditional bond mathematics with DeFi lending rate modeling. Bond pricing fundamentals — present value of cash flows, yield curves, duration, and convexity — translate directly to analyzing DeFi lending protocols where depositors earn variable or fixed rates on crypto assets.
On Solana, lending protocols like Marginfi, Kamino, and Solend offer variable-rate lending/borrowing. Understanding term structure and rate dynamics helps optimize yield farming strategies and compare opportunities across protocols.
This skill is informational and analytical only. It does not provide financial advice or trading recommendations.
This stub includes a working bond calculator with price, yield-to-maturity, duration, and convexity computations. See scripts/bond_calculator.py for the implementation.
def bond_price(
face: float, coupon_rate: float, ytm: float, periods: int, freq: int = 2
) -> float:
"""Calculate bond price as present value of all cash flows.
Args:
face: Face (par) value of the bond.
coupon_rate: Annual coupon rate (decimal, e.g., 0.05 for 5%).
ytm: Yield to maturity (annual, decimal).
periods: Number of coupon periods remaining.
freq: Coupon frequency per year (2 = semi-annual).
Returns:
Bond price (dirty price).
"""
coupon = face * coupon_rate / freq
y = ytm / freq
pv_coupons = sum(coupon / (1 + y) ** t for t in range(1, periods + 1))
pv_face = face / (1 + y) ** periods
return pv_coupons + pv_face
Run the demo:
python scripts/bond_calculator.py --demo
When fully implemented, this skill will cover:
| Concept | Description | |---------|-------------| | Clean/Dirty Price | Price excluding/including accrued interest | | Accrued Interest | Interest earned since last coupon date | | Day Count Conventions | 30/360, ACT/360, ACT/365, ACT/ACT | | Zero-Coupon Bonds | Discount bonds with no periodic coupons |
| Yield Measure | Use Case | |---------------|----------| | Yield to Maturity (YTM) | Total return if held to maturity | | Current Yield | Annual coupon / price | | Yield to Call | Return if called at first call date | | Spread to Benchmark | Credit risk premium over risk-free rate |
| Metric | Measures | |--------|----------| | Macaulay Duration | Weighted average time to cash flows | | Modified Duration | Price sensitivity to yield changes | | Effective Duration | Duration for bonds with embedded options | | Convexity | Second-order price sensitivity | | Dollar Duration (DV01) | Dollar change per 1bp yield move |
| Method | Description | |--------|-------------| | Bootstrap | Extract spot rates from par bond prices | | Nelson-Siegel | Parametric model with level, slope, curvature | | Nelson-Siegel-Svensson | Extended model with additional curvature term | | Cubic Spline | Non-parametric interpolation |
| Protocol | Chain | Type | |----------|-------|------| | Marginfi | Solana | Variable rate | | Kamino | Solana | Variable rate | | Solend | Solana | Variable rate | | Aave | Ethereum/Multi | Variable + stable rate | | Compound | Ethereum | Variable rate |
Planned DeFi features:
# For full implementation
uv pip install numpy scipy
# For visualization
uv pip install matplotlib
The included scripts/bond_calculator.py uses only the Python standard library and runs without any dependencies.
Compare DeFi lending rates across protocols using fixed income analytics. Annualize variable rates, compute effective yields accounting for compounding frequency, and identify the most capital-efficient opportunities.
Track lending rates over time to understand rate dynamics. Identify periods of rate compression (low utilization) vs rate expansion (high utilization) to time deposits optimally.
Borrow at lower rates on one protocol and lend at higher rates on another. Duration and convexity concepts help assess the risk of rate changes during the arbitrage holding period.
Use duration to estimate how lending positions change in value as rates move. Higher duration means greater sensitivity to rate changes.
Bond price (present value of cash flows):
P = Σ [C / (1+y)^t] + F / (1+y)^n
t=1..n
Where:
C = periodic coupon payment = Face * coupon_rate / frequency
y = periodic yield = YTM / frequency
F = face value
n = total number of periods
Macaulay Duration:
D_mac = (1/P) * Σ [t * C / (1+y)^t] + (n * F) / ((1+y)^n * P)
Modified Duration:
D_mod = D_mac / (1 + y)
Convexity:
Convexity = (1/P) * Σ [t*(t+1) * C / (1+y)^(t+2)] + [n*(n+1)*F] / [(1+y)^(n+2) * P]
Price change approximation:
ΔP/P ≈ -D_mod * Δy + 0.5 * Convexity * (Δy)²
| File | Description |
|------|-------------|
| references/planned_features.md | Planned features, bond formulas, DeFi protocols, and implementation priorities |
| scripts/bond_calculator.py | Bond price, YTM, duration, and convexity calculator |
This skill is a stub awaiting full implementation. To contribute:
See references/planned_features.md for the full feature list and implementation priorities.
This skill provides analytical tools and mathematical models for informational purposes only. It does not constitute financial advice. Fixed income and DeFi lending involve risk of loss.
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