Bond Valuation and Credit Analysis

BusinessMath Quarterly Series

15 min read

Part 19 of 12-Week BusinessMath Series

What You’ll Learn

  • Pricing bonds and calculating yield to maturity (YTM)
  • Measuring interest rate risk using duration and convexity
  • Converting credit metrics (Z-Scores) to default probabilities and spreads
  • Valuing callable bonds and calculating Option-Adjusted Spread (OAS)
  • Building credit curves to analyze default risk over time
  • Calculating expected losses for bond portfolios
  • Making informed fixed income investment decisions

The Problem

Bond markets dwarf equity markets ($100T+ globally), yet bond valuation is surprisingly complex:

  • How do you price a bond? It’s not just “divide coupon by yield”—that’s current yield, not price.
  • What’s the interest rate risk? If rates rise 1%, how much does your bond portfolio lose?
  • How do you value credit risk? A BBB-rated bond should yield more than AAA, but how much?
  • What about callable bonds? Issuers can refinance if rates drop—how do you value that option?

Manual bond analysis in spreadsheets is tedious when managing portfolios with hundreds of positions.

The Solution

BusinessMath provides comprehensive bond valuation and credit analysis: Bond pricing, duration/convexity calculation, credit spread modeling, callable bond valuation with OAS, and credit curve construction.

Basic Bond Pricing

Price a simple corporate bond:

import BusinessMath
import Foundation

// 5-year corporate bond
// - Face value: $1,000
// - Annual coupon: 6%
// - Semiannual payments
// - Current market yield: 5%

let calendar = Calendar.current
let today = Date()
let maturity = calendar.date(byAdding: .year, value: 5, to: today)!

let bond = Bond(
    faceValue: 1000.0,
    couponRate: 0.06,
    maturityDate: maturity,
    paymentFrequency: .semiAnnual,
    issueDate: today
)

let marketPrice = bond.price(yield: 0.05, asOf: today)

print("Bond Pricing")
print("============")
print("Face Value: $1,000")
print("Coupon Rate: 6.0%")
print("Market Yield: 5.0%")
print("Price: \(marketPrice.currency(2))")

let currentYield = bond.currentYield(price: marketPrice)
print("Current Yield: \(currentYield.percent(2))")

Output:

Bond Pricing
============
Face Value: $1,000
Coupon Rate: 6.0%
Market Yield: 5.0%
Price: $1,043.82

Current Yield: 5.75%

The pricing rule: When coupon > yield, bond trades at premium (> $1,000). When yield > coupon, trades at discount (< $1,000). This is the inverse price-yield relationship.

Yield to Maturity (YTM)

Given a market price, solve for the internal rate of return:

// Find YTM given observed market price

let observedPrice = 980.00  // Trading below par

do {
    let ytm = try bond.yieldToMaturity(price: observedPrice, asOf: today)

    print("\nYield to Maturity Analysis")
    print("===========================")
    print("Market Price: \(observedPrice.currency())")
    print("YTM: \(ytm.percent(2))")

    // Verify round-trip: Price → YTM → Price
    let verifyPrice = bond.price(yield: ytm, asOf: today)
    print("Verification: \(verifyPrice.currency(2))")
    print("Difference: \(abs(verifyPrice - observedPrice).currency(2))")

} catch {
    print("YTM calculation failed: \(error)")
}

Output:

Yield to Maturity Analysis
===========================
Market Price: $980.00
YTM: 6.48%

Verification: $980.00
Difference: $0.00

The definition: YTM is the total return if you buy at current price, hold to maturity, and reinvest all coupons at the YTM rate. It’s the bond’s IRR.

Duration and Convexity

Measure interest rate risk:

let yield = 0.05

let macaulayDuration = bond.macaulayDuration(yield: yield, asOf: today)
let modifiedDuration = bond.modifiedDuration(yield: yield, asOf: today)
let convexity = bond.convexity(yield: yield, asOf: today)

print("\nInterest Rate Risk Metrics")
print("==========================")
print("Macaulay Duration: \(macaulayDuration.number(2)) years")
print("Modified Duration: \(modifiedDuration.number(2))")
print("Convexity: \(convexity.number(2))")

// Estimate price change from 1% yield increase
let yieldChange = 0.01  // 100 bps
let priceChange = -modifiedDuration * yieldChange

print("\nIf yield increases by 100 bps:")
print("Duration estimate: \(priceChange.percent(2))")

// More accurate estimate with convexity
let convexityAdj = 0.5 * convexity * yieldChange * yieldChange
let improvedEstimate = priceChange + convexityAdj

print("With convexity adjustment: \(improvedEstimate.percent(2))")

// Actual price change
let newPrice = bond.price(yield: yield + yieldChange, asOf: today)
let originalPrice = bond.price(yield: yield, asOf: today)
let actualChange = ((newPrice / originalPrice) - 1.0)

print("Actual change: \(actualChange.percent(2))")

Output:

Interest Rate Risk Metrics
==========================
Macaulay Duration: 4.41 years
Modified Duration: 4.30
Convexity: 22.07

If yield increases by 100 bps:
Duration estimate: -4.30%
With convexity adjustment: -4.19%
Actual change: -4.19%

The interpretation:

  • Macaulay Duration (4.41 years): Weighted average time to receive cash flows
  • Modified Duration (4.30): Price sensitivity—a 1% yield increase causes ~4.3% price drop
  • Convexity (22.07): Curvature—improves duration estimate for large yield changes

The insight: Duration is a linear approximation. Convexity captures the curve. Together, they predict price changes accurately.

Credit Risk Analysis

Convert company fundamentals to bond pricing:

// Step 1: Start with credit metrics (Altman Z-Score)
let zScore = 2.3  // Grey zone (moderate credit risk)

// Step 2: Convert Z-Score to default probability
let creditModel = CreditSpreadModel()
let defaultProbability = creditModel.defaultProbability(zScore: zScore)

print("\nCredit Risk Analysis")
print("====================")
print("Z-Score: \(zScore.number(2))")
print("Default Probability: \(defaultProbability.percent(2))")

// Step 3: Determine recovery rate by seniority
let seniority = Seniority.seniorUnsecured
let recoveryRate = RecoveryModel.standardRecoveryRate(seniority: seniority)

print("Seniority: Senior Unsecured")
print("Expected Recovery: \(recoveryRate.percent(0))")

// Step 4: Calculate credit spread
let creditSpread = creditModel.creditSpread(
    defaultProbability: defaultProbability,
    recoveryRate: recoveryRate,
    maturity: 5.0
)

print("Credit Spread: \((creditSpread * 10000).number(0)) bps")

// Step 5: Price the bond
let riskFreeRate = 0.03  // 3% Treasury yield
let corporateYield = riskFreeRate + creditSpread

let corporateBond = Bond(
    faceValue: 1000.0,
    couponRate: 0.05,
    maturityDate: maturity,
    paymentFrequency: .semiAnnual,
    issueDate: today
)

let corporatePrice = corporateBond.price(yield: corporateYield, asOf: today)

print("\nCorporate Bond Pricing:")
print("Risk-Free Rate: \(riskFreeRate.percent(2))")
print("Corporate Yield: \(corporateYield.percent(2))")
print("Bond Price: \(corporatePrice.currency(2))")

Output:

Credit Risk Analysis
====================
Z-Score: 2.30
Default Probability: 3.92%
Seniority: Senior Unsecured
Expected Recovery: 50%
Credit Spread: 206 bps

Corporate Bond Pricing:
Risk-Free Rate: 3.00%
Corporate Yield: 5.06%
Bond Price: $997.39

The workflow: Z-Score → Default Probability → Credit Spread → Bond Yield → Bond Price

The formula: Credit Spread ≈ (Default Probability × Loss Given Default) / (1 - Default Probability)

Credit Deterioration Impact

See how credit quality affects bond values:

print("\nCredit Deterioration Impact")
print("===========================")

let scenarios = [
    (name: "Investment Grade", zScore: 3.5),
    (name: "Grey Zone", zScore: 2.0),
    (name: "Distress", zScore: 1.0)
]

print("\nScenario           | Z-Score | PD     | Spread | Price")
print("-------------------|---------|--------|--------|--------")

for scenario in scenarios {
    let pd = creditModel.defaultProbability(zScore: scenario.zScore)
    let spread = creditModel.creditSpread(
        defaultProbability: pd,
        recoveryRate: recoveryRate,
        maturity: 5.0
    )
    let yld = riskFreeRate + spread
    let price = corporateBond.price(yield: yld, asOf: today)

    print("\(scenario.name.padding(toLength: 18, withPad: " ", startingAt: 0)) | \(scenario.zScore.number(1))     | \(pd.percent(1)) | \((spread * 10000).number(0)) bps | \(price.currency(2))")
}

Output:

Credit Deterioration Impact
===========================

Scenario           | Z-Score | PD     | Spread     | Price
-------------------|---------|--------|------------|----------
Investment Grade   |     3.5 |   0.0% |      2 bps | $1,091.44
Grey Zone          |     2.0 |  11.9% |    708 bps |   $804.45
Distress           |     1.0 |  88.1% | 18,421 bps |    $28.14

The pattern: As credit deteriorates (lower Z-Score), default probability rises, spreads widen, and bond prices fall. The relationship is non-linear—distressed bonds see massive spread widening.

Callable Bonds and OAS

Value bonds with embedded call options:

// High-coupon callable bond (issuer can refinance)

let highCouponBond = Bond(
    faceValue: 1000.0,
    couponRate: 0.07,  // 7% coupon (above market)
    maturityDate: calendar.date(byAdding: .year, value: 10, to: today)!,
    paymentFrequency: .semiAnnual,
    issueDate: today
)

// Callable after 3 years at $1,040 (4% premium)
let callDate = calendar.date(byAdding: .year, value: 3, to: today)!
let callSchedule = [CallProvision(date: callDate, callPrice: 1040.0)]

let callableBond = CallableBond(
    bond: highCouponBond,
    callSchedule: callSchedule
)

let volatility = 0.15  // 15% interest rate volatility

// Step 1: Price non-callable bond
let straightYield = riskFreeRate + creditSpread
let straightPrice = highCouponBond.price(yield: straightYield, asOf: today)

// Step 2: Price callable bond
let callablePrice = callableBond.price(
    riskFreeRate: riskFreeRate,
    spread: creditSpread,
    volatility: volatility,
    asOf: today
)

// Step 3: Calculate embedded option value
let callOptionValue = callableBond.callOptionValue(
    riskFreeRate: riskFreeRate,
    spread: creditSpread,
    volatility: volatility,
    asOf: today
)

print("\nCallable Bond Analysis")
print("======================")
print("Non-Callable Price: \(straightPrice.currency(2))")
print("Callable Price: \(callablePrice.currency(2))")
print("Call Option Value: \(callOptionValue.currency(2))")
print("Investor gives up: \((straightPrice - callablePrice).currency(2))")

// Step 4: Calculate Option-Adjusted Spread (OAS)
do {
    let oas = try callableBond.optionAdjustedSpread(
        marketPrice: callablePrice,
        riskFreeRate: riskFreeRate,
        volatility: volatility,
        asOf: today
    )

    print("\nSpread Decomposition:")
    print("Nominal Spread: \((creditSpread * 10000).number(0)) bps")
    print("OAS (credit only): \((oas * 10000).number(0)) bps")
    print("Option Spread: \(((creditSpread - oas) * 10000).number(0)) bps")

} catch {
    print("OAS calculation failed: \(error)")
}

// Step 5: Effective duration (accounts for call option)
let effectiveDuration = callableBond.effectiveDuration(
    riskFreeRate: riskFreeRate,
    spread: creditSpread,
    volatility: volatility,
    asOf: today
)

let straightDuration = highCouponBond.macaulayDuration(yield: straightYield, asOf: today)

print("\nDuration Comparison:")
print("Non-Callable Duration: \(straightDuration.number(2)) years")
print("Effective Duration: \(effectiveDuration.number(2)) years")
print("Duration Reduction: \(((1 - effectiveDuration / straightDuration) * 100).number(0))%")

Output:

Callable Bond Analysis
======================
Non-Callable Price: $1,150.82
Callable Price: $1,048.51
Call Option Value: $102.31
Investor gives up: $102.31

Spread Decomposition:
Nominal Spread: 206 bps
OAS (credit only): 206 bps
Option Spread: 0 bps

Duration Comparison:
Non-Callable Duration: 7.56 years
Effective Duration: 1.80 years
Duration Reduction: 76%

The callable bond mechanics:

  1. Callable price < Non-callable price: Investor compensates issuer for refinancing option
  2. OAS isolates credit risk: Strips out option risk for apples-to-apples comparison
  3. Effective duration < Macaulay duration: Call option limits price appreciation when rates fall (negative convexity)

The insight: Callable bonds exhibit negative convexity—when rates fall, price gains are capped at the call price.

Credit Curves

Build term structures of credit spreads:

// Credit curve from market observations

let periods = [
    Period.year(1),
    Period.year(3),
    Period.year(5),
    Period.year(10)
]

// Observed spreads (typically upward sloping)
let marketSpreads = TimeSeries(
    periods: periods,
    values: [0.005, 0.012, 0.018, 0.025]  // 50, 120, 180, 250 bps
)

let creditCurve = CreditCurve(
    spreads: marketSpreads,
    recoveryRate: recoveryRate
)

print("\nCredit Curve Analysis")
print("=====================")

// Interpolate spreads
for years in [2.0, 7.0] {
    let spread = creditCurve.spread(maturity: years)
    print("\(years.number(0))-Year Spread: \((spread * 10000).number(0)) bps")
}

// Cumulative default probabilities
print("\nCumulative Default Probabilities:")
for year in [1, 3, 5, 10] {
    let cdp = creditCurve.cumulativeDefaultProbability(maturity: Double(year))
    let survival = 1.0 - cdp
    print("\(year)-Year: \(cdp.percent(2)) default, \(survival.percent(2)) survival")
}

// Hazard rates (forward default intensities)
print("\nHazard Rates (Default Intensity):")
for year in [1, 5, 10] {
    let hazard = creditCurve.hazardRate(maturity: Double(year))
    print("\(year)-Year: \(hazard.percent(2)) per year")
}

Output:

Credit Curve Analysis
=====================
2-Year Spread: 85 bps
7-Year Spread: 208 bps

Cumulative Default Probabilities:
1-Year: 1.00% default, 99.00% survival
3-Year: 6.95% default, 93.05% survival
5-Year: 16.47% default, 83.53% survival
10-Year: 39.35% default, 60.65% survival

Hazard Rates (Default Intensity):
1-Year: 1.00% per year
5-Year: 3.60% per year
10-Year: 5.00% per year

The credit curve: Shows how default risk evolves over time. Upward-sloping curves indicate increasing uncertainty at longer horizons.

Hazard rate: Instantaneous default intensity—useful for pricing credit derivatives like CDSs.

Try It Yourself

Click to expand full playground code 
import BusinessMath
import Foundation


// MARK: - Basic Bond Pricing

// 5-year corporate bond
// - Face value: $1,000
// - Annual coupon: 6%
// - Semiannual payments
// - Current market yield: 5%

let calendar = Calendar.current
let today = Date()
let maturity = calendar.date(byAdding: .year, value: 5, to: today)!

let bond = Bond(
	faceValue: 1000.0,
	couponRate: 0.06,
	maturityDate: maturity,
	paymentFrequency: .semiAnnual,
	issueDate: today
)

let marketPrice = bond.price(yield: 0.05, asOf: today)

print("Bond Pricing")
print("============")
print("Face Value: $1,000")
print("Coupon Rate: 6.0%")
print("Market Yield: 5.0%")
print("Price: \(marketPrice.currency(2))")

let currentYield = bond.currentYield(price: marketPrice)
print("Current Yield: \(currentYield.percent(2))")

// MARK: - Yield to Maturity

// Find YTM given observed market price

let observedPrice = 980.00  // Trading below par

do {
	let ytm = try bond.yieldToMaturity(price: observedPrice, asOf: today)

	print("\nYield to Maturity Analysis")
	print("===========================")
	print("Market Price: \(observedPrice.currency())")
	print("YTM: \(ytm.percent(2))")

	// Verify round-trip: Price → YTM → Price
	let verifyPrice = bond.price(yield: ytm, asOf: today)
	print("Verification: \(verifyPrice.currency(2))")
	print("Difference: \(abs(verifyPrice - observedPrice).currency(2))")

} catch {
	print("YTM calculation failed: \(error)")
}

// MARK: - Duration and Convexity

let yield = 0.05

let macaulayDuration = bond.macaulayDuration(yield: yield, asOf: today)
let modifiedDuration = bond.modifiedDuration(yield: yield, asOf: today)
let convexity = bond.convexity(yield: yield, asOf: today)

print("\nInterest Rate Risk Metrics")
print("==========================")
print("Macaulay Duration: \(macaulayDuration.number(2)) years")
print("Modified Duration: \(modifiedDuration.number(2))")
print("Convexity: \(convexity.number(2))")

// Estimate price change from 1% yield increase
let yieldChange = 0.01  // 100 bps
let priceChange = -modifiedDuration * yieldChange

print("\nIf yield increases by 100 bps:")
print("Duration estimate: \(priceChange.percent(2))")

// More accurate estimate with convexity
let convexityAdj = 0.5 * convexity * yieldChange * yieldChange
let improvedEstimate = priceChange + convexityAdj

print("With convexity adjustment: \(improvedEstimate.percent(2))")

// Actual price change
let newPrice = bond.price(yield: yield + yieldChange, asOf: today)
let originalPrice = bond.price(yield: yield, asOf: today)
let actualChange = ((newPrice / originalPrice) - 1.0)

print("Actual change: \(actualChange.percent(2))")

// MARK: - Credit Risk Analysis

// Step 1: Start with credit metrics (Altman Z-Score)
let zScore = 2.3  // Grey zone (moderate credit risk)

// Step 2: Convert Z-Score to default probability
let creditModel = CreditSpreadModel()
let defaultProbability = creditModel.defaultProbability(zScore: zScore)

print("\nCredit Risk Analysis")
print("====================")
print("Z-Score: \(zScore.number(2))")
print("Default Probability: \(defaultProbability.percent(2))")

// Step 3: Determine recovery rate by seniority
let seniority = Seniority.seniorUnsecured
let recoveryRate = RecoveryModel.standardRecoveryRate(seniority: seniority)

print("Seniority: Senior Unsecured")
print("Expected Recovery: \(recoveryRate.percent(0))")

// Step 4: Calculate credit spread
let creditSpread = creditModel.creditSpread(
	defaultProbability: defaultProbability,
	recoveryRate: recoveryRate,
	maturity: 5.0
)

print("Credit Spread: \((creditSpread * 10000).number(0)) bps")

// Step 5: Price the bond
let riskFreeRate = 0.03  // 3% Treasury yield
let corporateYield = riskFreeRate + creditSpread

let corporateBond = Bond(
	faceValue: 1000.0,
	couponRate: 0.05,
	maturityDate: maturity,
	paymentFrequency: .semiAnnual,
	issueDate: today
)

let corporatePrice = corporateBond.price(yield: corporateYield, asOf: today)

print("\nCorporate Bond Pricing:")
print("Risk-Free Rate: \(riskFreeRate.percent(2))")
print("Corporate Yield: \(corporateYield.percent(2))")
print("Bond Price: \(corporatePrice.currency(2))")


// MARK: - Credit Deterioration Impact

print("\nCredit Deterioration Impact")
print("===========================")

let scenarios = [
	(name: "Investment Grade", zScore: 3.5),
	(name: "Grey Zone", zScore: 2.0),
	(name: "Distress", zScore: 1.0)
]

print("\nScenario           | Z-Score | PD     | Spread     | Price")
print("-------------------|---------|--------|------------|----------")

for scenario in scenarios {
	let pd = creditModel.defaultProbability(zScore: scenario.zScore)
	let spread = creditModel.creditSpread(
		defaultProbability: pd,
		recoveryRate: recoveryRate,
		maturity: 5.0
	)
	let yld = riskFreeRate + spread
	let price = corporateBond.price(yield: yld, asOf: today)

	print("\(scenario.name.padding(toLength: 18, withPad: " ", startingAt: 0)) | \(scenario.zScore.number(1).paddingLeft(toLength: 7)) | \(pd.percent(1).paddingLeft(toLength: 6)) | \((spread * 10000).number(0).paddingLeft(toLength: 6)) bps | \(price.currency(2).paddingLeft(toLength: 9))")
}

// MARK: - Callable Bonds and OAS

	// High-coupon callable bond (issuer can refinance)

	let highCouponBond = Bond(
		faceValue: 1000.0,
		couponRate: 0.07,  // 7% coupon (above market)
		maturityDate: calendar.date(byAdding: .year, value: 10, to: today)!,
		paymentFrequency: .semiAnnual,
		issueDate: today
	)

	// Callable after 3 years at $1,040 (4% premium)
	let callDate = calendar.date(byAdding: .year, value: 3, to: today)!
	let callSchedule = [CallProvision(date: callDate, callPrice: 1040.0)]

	let callableBond = CallableBond(
		bond: highCouponBond,
		callSchedule: callSchedule
	)

	let volatility = 0.15  // 15% interest rate volatility

	// Step 1: Price non-callable bond
	let straightYield = riskFreeRate + creditSpread
	let straightPrice = highCouponBond.price(yield: straightYield, asOf: today)

	// Step 2: Price callable bond
	let callablePrice = callableBond.price(
		riskFreeRate: riskFreeRate,
		spread: creditSpread,
		volatility: volatility,
		asOf: today
	)

	// Step 3: Calculate embedded option value
	let callOptionValue = callableBond.callOptionValue(
		riskFreeRate: riskFreeRate,
		spread: creditSpread,
		volatility: volatility,
		asOf: today
	)

	print("\nCallable Bond Analysis")
	print("======================")
	print("Non-Callable Price: \(straightPrice.currency(2))")
	print("Callable Price: \(callablePrice.currency(2))")
	print("Call Option Value: \(callOptionValue.currency(2))")
	print("Investor gives up: \((straightPrice - callablePrice).currency(2))")

	// Step 4: Calculate Option-Adjusted Spread (OAS)
	do {
		let oas = try callableBond.optionAdjustedSpread(
			marketPrice: callablePrice,
			riskFreeRate: riskFreeRate,
			volatility: volatility,
			asOf: today
		)

		print("\nSpread Decomposition:")
		print("Nominal Spread: \((creditSpread * 10000).number(0)) bps")
		print("OAS (credit only): \((oas * 10000).number(0)) bps")
		print("Option Spread: \(((creditSpread - oas) * 10000).number(0)) bps")

	} catch {
		print("OAS calculation failed: \(error)")
	}

	// Step 5: Effective duration (accounts for call option)
	let effectiveDuration = callableBond.effectiveDuration(
		riskFreeRate: riskFreeRate,
		spread: creditSpread,
		volatility: volatility,
		asOf: today
	)

	let straightDuration = highCouponBond.macaulayDuration(yield: straightYield, asOf: today)

	print("\nDuration Comparison:")
	print("Non-Callable Duration: \(straightDuration.number(2)) years")
	print("Effective Duration: \(effectiveDuration.number(2)) years")
	print("Duration Reduction: \(((1 - effectiveDuration / straightDuration) * 100).number(0))%")


// MARK: - Credit Curves

	// Credit curve from market observations

	let periods = [
		Period.year(1),
		Period.year(3),
		Period.year(5),
		Period.year(10)
	]

	// Observed spreads (typically upward sloping)
	let marketSpreads = TimeSeries(
		periods: periods,
		values: [0.005, 0.012, 0.018, 0.025]  // 50, 120, 180, 250 bps
	)

	let creditCurve = CreditCurve(
		spreads: marketSpreads,
		recoveryRate: recoveryRate
	)

	print("\nCredit Curve Analysis")
	print("=====================")

	// Interpolate spreads
	for years in [2.0, 7.0] {
		let spread = creditCurve.spread(maturity: years)
		print("\(years.number(0))-Year Spread: \((spread * 10000).number(0)) bps")
	}

	// Cumulative default probabilities
	print("\nCumulative Default Probabilities:")
	for year in [1, 3, 5, 10] {
		let cdp = creditCurve.cumulativeDefaultProbability(maturity: Double(year))
		let survival = 1.0 - cdp
		print("\(year)-Year: \(cdp.percent(2)) default, \(survival.percent(2)) survival")
	}

	// Hazard rates (forward default intensities)
	print("\nHazard Rates (Default Intensity):")
	for year in [1, 5, 10] {
		let hazard = creditCurve.hazardRate(maturity: Double(year))
		print("\(year)-Year: \(hazard.percent(2)) per year")
	}

→ Full API Reference: BusinessMath Docs – 3.10 Bond Valuation

Modifications to try:

  1. Price corporate bonds across the credit spectrum (AAA to CCC)
  2. Calculate portfolio duration for a bond ladder
  3. Model callable bond strategies in different rate environments
  4. Build credit curves for multiple issuers

Real-World Application

Fixed income is the largest asset class globally:

  • Pension funds: Managing $100B+ bond portfolios
  • Insurance companies: Asset-liability matching with bonds
  • Central banks: Setting monetary policy via bond markets
  • Corporates: Issuing bonds to finance operations

Portfolio manager use case: “We hold $5B in corporate bonds. Calculate portfolio duration, DV01 (dollar duration per basis point), and aggregate credit exposure by rating bucket.”

BusinessMath makes this analysis programmatic, real-time, and portfolio-wide.

★ Insight ─────────────────────────────────────

Why Do Bonds Have Inverse Price-Yield Relationship?

It’s counter-intuitive: when yields rise, bond prices fall. Why?

The mechanism: A bond is a stream of fixed cash flows. When yields rise:

  • New bonds issue with higher coupons
  • Your old bond (with lower coupon) is less attractive
  • To compete, your bond must trade at a discount

Example:

  • You buy a 5% coupon bond for $1,000 (yield = 5%)
  • Rates rise, new bonds pay 6% coupons
  • Your 5% bond must drop to ~$957 so its yield rises to 6%

The math: Bond price = PV(future coupons + principal). When discount rate (yield) increases, PV decreases.

The lesson: Duration measures this price sensitivity. Higher duration = greater price volatility when yields change.

─────────────────────────────────────────────────

📝 Development Note

The most challenging implementation was callable bond pricing with binomial trees. We had to:

  1. Build interest rate trees with specified volatility
  2. Implement backward induction (value at maturity, work backward)
  3. Check at each node: Is bond callable? If yes, value = min(continuation value, call price)
  4. Calculate OAS by iterating to find spread that matches market price

Trade-off: Binomial trees are slower than closed-form solutions but handle path-dependent options (callable, putable, convertible bonds).

We chose accuracy over speed—bond portfolios are repriced daily, not millisecond-by-millisecond.

Related Methodology: Test-First Development (Week 1) - We wrote tests comparing our binomial tree to Bloomberg’s pricing for callable bonds before implementation.

Next Steps

Coming up next week: Week 6 explores Monte Carlo simulation and scenario analysis for risk modeling.

Monday: Monte Carlo Basics - Building stochastic models for forecasting under uncertainty.

Series Progress:

  • Week: 5/12
  • Posts Published: 19/~48
  • Topics Covered: Foundation + Analysis + Operational + Financial Statements + Advanced Modeling (complete)
  • Playgrounds: 18 available

Tagged with: businessmath, swift, bonds, fixed-income, credit-risk, duration, convexity, callable-bonds, oas