README.md

---
title: TVOG Analysis Dashboard
emoji: 🐢
colorFrom: purple
colorTo: yellow
sdk: gradio
sdk_version: 5.31.0
app_file: app.py
pinned: false
license: mit
short_description: 'TVOG pricing: Monte Carlo vs. Black-Scholes tools.'
---

# TVOG Analysis Dashboard 📊

An interactive dashboard for analyzing Time Value of Options and Guarantees (TVOG) in Variable Annuity products with Guaranteed Minimum Accumulation Benefits (GMAB).

[![Open in Spaces](https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm.svg)](https://huggingface.co/spaces/alidenewade/tvog-analysis-dashboard)

## 🎯 Overview

This dashboard provides a comprehensive comparison between **Monte Carlo simulation** and **Black-Scholes-Merton analytical solutions** for pricing variable annuity guarantees. It's designed specifically for actuaries, finance professionals, economists, and academics working in insurance and financial risk management.

## ✨ Key Features

### 🔧 Interactive Controls
- **Monte Carlo Parameters**: Adjustable scenario counts (1K-50K), risk-free rates, volatility levels
- **Product Configuration**: Customizable sum assured, policy counts, and maturity periods  
- **Model Point Analysis**: Flexible premium ranges with configurable test points

### 📈 Four Analysis Modules

1. **TVOG Comparison**: Side-by-side Monte Carlo vs Black-Scholes results with convergence ratios
2. **Simulation Paths**: Account value trajectory visualization with guarantee levels
3. **Distribution Analysis**: Statistical distributions of final values and GMAB payouts
4. **Convergence Analysis**: Monte Carlo convergence validation against analytical solutions

### 📊 Professional Output
- **Results Table**: Detailed numerical comparison data
- **Real-time Updates**: Dynamic recalculation with parameter changes
- **Statistical Overlays**: Theoretical distributions and error metrics
- **Export-Ready Visualizations**: High-quality plots for presentations

## 🚀 Getting Started

### Online Usage
Simply click the "Open in Spaces" badge above to access the live dashboard - no installation required!

### Local Installation
```bash
git clone https://huggingface.co/spaces/alidenewade/tvog-analysis-dashboard
cd tvog-analysis-dashboard
pip install -r requirements.txt
python app.py
```

## 🔬 Technical Background

### Mathematical Foundation
The dashboard implements:
- **Geometric Brownian Motion** for account value simulation: `dS/S = r·dt + σ·ε·√dt`
- **Black-Scholes-Merton Formula** for European put option pricing
- **Risk-Neutral Valuation** with Monte Carlo scenarios

### Key Assumptions
- No policy decrements (mortality/lapse rates = 0)
- No management fees for clean comparison
- Constant risk-free rate environment
- Log-normal asset return distribution

## 👥 Target Audience

### Primary Users
- **Actuaries**: Pricing and reserving analysis for variable annuity products
- **Risk Managers**: Quantifying guarantee costs and capital requirements
- **Product Developers**: Designing and testing new guarantee features
- **Academics**: Teaching and researching financial guarantee valuation

### Use Cases
- **Product Pricing**: Determine fair value of GMAB guarantees
- **Model Validation**: Compare simulation results with analytical benchmarks
- **Sensitivity Analysis**: Test impact of parameter changes on guarantee costs
- **Educational Tool**: Demonstrate Monte Carlo vs analytical pricing methods

## 📚 Methodology

### Monte Carlo Simulation
- Generates thousands of risk-neutral scenarios
- Simulates account value paths using geometric Brownian motion
- Calculates present value of guarantee payouts at maturity
- Provides statistical confidence through large sample sizes

### Black-Scholes-Merton Benchmark
- Analytical solution for European put option pricing
- Provides exact theoretical value for comparison
- Validates Monte Carlo convergence and accuracy
- Offers computational efficiency for sensitivity analysis

## 🎛️ Parameter Guide

### Critical Parameters
- **Scenarios**: Higher counts improve accuracy but increase computation time
- **Volatility**: Key driver of option value - higher volatility increases TVOG
- **Risk-Free Rate**: Affects both drift and discounting of future payouts
- **Moneyness**: Initial account value relative to guarantee level

### Recommended Settings
- **For Quick Analysis**: 5,000-10,000 scenarios
- **For Production**: 50,000+ scenarios
- **For Presentations**: 10,000 scenarios (good balance of accuracy/speed)

## 📖 Educational Value

This dashboard serves as an excellent educational tool for:
- **Understanding Monte Carlo Methods** in financial modeling
- **Comparing Simulation vs Analytical** approaches
- **Visualizing Financial Risk** through interactive plots
- **Learning Option Pricing Theory** in insurance contexts

## 🤝 Contributing

Found a bug or have suggestions? Feel free to:
- Open an issue on the repository
- Submit a pull request with improvements
- Share feedback through the Hugging Face community tab

## 📄 License

This project is open source and available under the MIT License.

## 🙏 Acknowledgments

Based on the lifelib savings library example, which demonstrates advanced actuarial modeling techniques for variable annuity products.

---

**Built with ❤️ for the actuarial and finance community**

*For technical support or collaboration opportunities, connect through Hugging Face!*

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference