Tutorials ========= This tutorial series walks you through the Ergodic Insurance Limits framework, from installation to advanced optimization. The goal is to help you understand how time-average (ergodic) analysis changes insurance purchasing decisions compared to traditional expected-value approaches. .. note:: **New here?** Start with :doc:`01_getting_started` for installation and a first simulation. Tutorial Overview ----------------- The tutorials are split into two groups. **Foundations (Tutorials 1--2):** 1. **Getting Started** -- Installation, environment setup, and running your first simulation 2. **Basic Simulation** -- The Widget Manufacturer model, step-by-step year simulation, and loss processing **Applied Workflow (Tutorials 3--6):** Tutorials 3 and 4 follow **NovaTech Plastics**, a fictional $10M plastics manufacturer with an 8% operating margin, as the running example. The same manufacturer parameters carry through Tutorials 5 and 6. 3. **Configuring Insurance** -- Building single-layer and multi-layer insurance towers for NovaTech 4. **Optimization Workflow** -- Using ``BusinessOptimizer`` to find data-driven insurance strategies as NovaTech plans its expansion 5. **Analyzing Results** -- Comparing time-average vs. ensemble-average growth rates with ``ErgodicAnalyzer`` 6. **Advanced Scenarios** -- Monte Carlo simulations, market cycle modeling, and scenario analysis Quick Start Paths ----------------- You do not need to complete every tutorial. Pick a path based on what you want to learn: **Actuaries and Risk Managers:** Start with the foundations, then focus on insurance structure and results interpretation. 1. :doc:`01_getting_started` 2. :doc:`03_configuring_insurance` 3. :doc:`05_analyzing_results` **Financial Analysts and CFOs:** Focus on the business case for insurance and the optimization workflow. 1. :doc:`01_getting_started` 2. :doc:`04_optimization_workflow` 3. :doc:`05_analyzing_results` **Developers and Researchers:** Dive into the simulation engine and advanced techniques. 1. :doc:`02_basic_simulation` 2. :doc:`04_optimization_workflow` 3. :doc:`06_advanced_scenarios` Tutorials --------- .. toctree:: :numbered: :maxdepth: 2 :caption: Step-by-Step Tutorials: 01_getting_started 02_basic_simulation 03_configuring_insurance 04_optimization_workflow 05_analyzing_results 06_advanced_scenarios Support Resources ----------------- .. toctree:: :maxdepth: 1 :caption: Help & Support: troubleshooting Learning Objectives ------------------- After working through these tutorials you should be able to: * Install the framework and run a simulation end-to-end * Configure multi-layer insurance programs with deductibles, attachment points, and limits * Use the optimizer to search for insurance strategies that maximize time-average growth * Interpret the difference between ensemble-average and time-average growth rates * Run Monte Carlo simulations and analyze survival probabilities, ROE, and final equity distributions Prerequisites ------------- **Required:** * Python 3.12 or higher * Comfort with Python basics: importing packages, running scripts, reading tracebacks * Familiarity with probability concepts (distributions, expected value, variance) at the level of Actuarial Exam P **Helpful:** * Working knowledge of insurance terms -- deductible, retention, limit, attachment point, premium * Exposure to financial metrics such as ROE, operating margin, and asset turnover * Experience with NumPy arrays and Matplotlib (used throughout the code examples) Getting Help ------------ If you get stuck: 1. Check the :doc:`troubleshooting` guide for common errors and fixes 2. Consult the :doc:`../api/modules` for detailed function and class documentation 3. Open an issue on `GitHub `__