README.md

metadata

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).

🎯 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

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.

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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