BusinessMath
Your roadmap to mastering financial calculations, statistical analysis, and optimization in Swift
Welcome! Over the next twelve weeks, we’re going on a journey together—from calculating the basics of time value of money to building sophisticated portfolio optimizers and real-time trading systems. Whether you’re a Swift developer curious about financial mathematics, a business analyst looking to bring your calculations into code, or someone who just loves solving practical problems with elegant tools, this series is for you.
What is BusinessMath?
BusinessMath is a comprehensive Swift library that brings financial calculations, statistical analysis, and optimization algorithms to your fingertips. Need to calculate loan amortization schedules? Run Monte Carlo simulations? Optimize a portfolio under constraints? BusinessMath has you covered—with clean, type-safe APIs that work across all Apple platforms.But this library is more than just a collection of functions. It’s built on principles that matter: test-driven development, comprehensive documentation, and real-world applicability. Every calculation is tested, every API is documented, and every feature is designed to solve actual business problems.
What to Expect
This series spans 12 weeks with 3-4 posts per week, mixing technical deep-dives with real-world case studies:Weeks 1-2: Foundation We’ll start with the essentials—time series data, time value of money, and financial ratios. By the end of week 1, you’ll build a complete retirement planning calculator.
Weeks 3-5: Financial Modeling Learn to build growth models, revenue projections, and complete financial statements. We’ll tackle real scenarios like capital equipment decisions and lease accounting.
Weeks 6-8: Simulation & Optimization Monte Carlo simulations, scenario analysis, and portfolio optimization. The midpoint case study combines everything you’ve learned into a $10M portfolio optimizer.
Weeks 9-12: Advanced Topics Integer programming, particle swarm optimization, parallel processing, and performance tuning. We’ll close with reflections on building production-quality software and a complete investment strategy DSL.
Every few posts, we’ll pause for a case study—a complete, real-world scenario that combines multiple topics into a practical solution. By the end, you’ll have tackled 6 substantial business problems, from retirement planning to real-time portfolio rebalancing.
Why Follow Along?
Each post is self-contained but builds on previous concepts. You’ll get:- Runnable code examples you can try immediately
- Complete playgrounds to experiment and modify
- Links to comprehensive API documentation when you want to dive deeper
- Real business context that explains why each technique matters
Ready to Begin?
We’ll publish new posts Monday, Wednesday, Thursday, and Friday, with case studies every other Friday. Bookmark this series, follow along at your own pace, and don’t hesitate to experiment with the code. The best way to learn is by doing.Let’s get started.
Series Overview: 12 weeks | ~40 posts | 6 case studies | 11 major topics
First Post: Week 1 – Getting Started with BusinessMath
Ready to dive in? Check out the first post where we cover installation, basic concepts, and your first calculations.
Getting Started with BusinessMath
Jan 5, 2026
7 min read
Test-First Development with AI
Jan 6, 2026
8 min read
Time Series Foundation
Jan 7, 2026
8 min read
Case Study: Retirement Planning Calculator
Jan 9, 2026
14 min read
Data Table Analysis for Sensitivity Testing
Jan 12, 2026
10 min read
Documentation as Design
Jan 13, 2026
8 min read
Financial Ratios and Metrics Guide
Jan 14, 2026
17 min read
Risk Analytics and Stress Testing
Jan 16, 2026
13 min read
Growth Modeling and Forecasting
Jan 19, 2026
13 min read
The Master Plan: Organizing Complexity
Jan 20, 2026
9 min read
The Supporting Cast: Coding Rules, DocC Guidelines, and Testing Standards
Jan 21, 2026
13 min read
Building a Revenue Forecasting Model
Jan 22, 2026
14 min read
Case Study: Capital Equipment Purchase Decision
Jan 23, 2026
17 min read
Welcome to BusinessMath: A 12-Week Journey
Jan 26, 2026
3 min read
Building Multi-Period Financial Reports
Jan 26, 2026
13 min read
Building Financial Statements
Jan 28, 2026
14 min read
Lease Accounting with IFRS 16 / ASC 842
Jan 29, 2026
15 min read
Loan Amortization Analysis
Feb 2, 2026
14 min read
Investment Analysis with NPV and IRR
Feb 3, 2026
17 min read
Equity Valuation: From Dividends to Residual Income
Feb 5, 2026
18 min read
Bond Valuation and Credit Analysis
Feb 6, 2026
18 min read
Monte Carlo Simulation for Financial Forecasting
Feb 10, 2026
23 min read
GPU-Accelerated Monte Carlo: Expression Models and Performance
Feb 10, 2026
23 min read
Scenario and Sensitivity Analysis
Feb 12, 2026
24 min read
Case Study #3: Option Pricing with Monte Carlo Simulation
Feb 14, 2026
20 min read
Bonus Post: Reverse-Engineering API Pricing from Usage Data with BusinessMath
Feb 15, 2026
18 min read
Optimization Foundations: From Goal-Seeking to Multivariate
Feb 16, 2026
12 min read
Portfolio Optimization: Building Optimal Investment Portfolios
Feb 17, 2026
14 min read
Core Optimization APIs: Goal-Seeking and Error Handling
Feb 18, 2026
12 min read
Vector Operations: Foundation for Multivariate Optimization
Feb 19, 2026
15 min read
Multivariate Optimization: Gradient Descent to Newton-Raphson
Feb 22, 2026
13 min read
Constrained Optimization: Lagrange Multipliers and Real-World Constraints
Feb 25, 2026
15 min read
Business Optimization Patterns: From Theory to Practice
Mar 2, 2026
15 min read
Integer Programming: Optimal Decisions with Whole Numbers
Mar 3, 2026
17 min read
Adaptive Selection: Let BusinessMath Choose the Best Algorithm
Mar 4, 2026
20 min read
Parallel Multi-Start Optimization: Finding Global Optima
Mar 5, 2026
19 min read
"Newton-Raphson: When Fast Convergence Becomes a Liability"
Mar 6, 2026
11 min read
Performance Benchmarking: Measure, Compare, Optimize
Mar 9, 2026
18 min read
L-BFGS Optimization: Memory-Efficient Large-Scale Optimization
Mar 10, 2026
14 min read
Conjugate Gradient: Efficient Optimization Without Hessians
Mar 11, 2026
15 min read
Simulated Annealing: Global Optimization Without Gradients
Mar 12, 2026
23 min read
Nelder-Mead Simplex: Robust Gradient-Free Optimization
Mar 16, 2026
15 min read
Particle Swarm Optimization: Collective Intelligence for Global Search
Mar 18, 2026
20 min read
Case Study: Real-Time Portfolio Rebalancing with Async Optimization
Mar 20, 2026
27 min read
What Worked: Practices That Delivered Results
Mar 23, 2026
8 min read
What Didn't Work: Lessons from Failures and Dead Ends
Mar 24, 2026
9 min read
Final Statistics: By the Numbers
Mar 25, 2026
8 min read
Case Study: Investment Strategy DSL with Result Builders
Mar 26, 2026
11 min read
Happy Birthday, Apple
Apr 1, 2026
5 min read
How We Stopped Losing Context and Started Shipping Faster with AI
Apr 1, 2026
7 min read
Three New Auditors for quality-gate-swift, or Why Modular Linters Win
Apr 8, 2026
10 min read