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: This isn’t just theory—it’s production-ready code solving real problems. And it’s designed to be accessible whether you’re implementing these calculations for the first time or you’re a seasoned financial engineer exploring Swift.

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