--- title: TVOG Analysis Dashboard emoji: ๐Ÿข 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 ๐Ÿ“Š 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) ## ๐ŸŽฏ 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. ## โœจ Key Features ### ๐Ÿ”ง 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 ### ๐Ÿ“ˆ 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 ### ๐Ÿ“Š 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 ## ๐Ÿš€ 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 ``` ## ๐Ÿ”ฌ Technical Background ### Mathematical Foundation The dashboard implements: - **Geometric Brownian Motion** for account value simulation: `dS/S = rยทdt + ฯƒยทฮตยทโˆšdt` - **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 ## ๐Ÿ‘ฅ 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 ## ๐Ÿ“š 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 ## ๐ŸŽ›๏ธ 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) ## ๐Ÿ“– 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 ## ๐Ÿค 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 ## ๐Ÿ“„ License This project is open source and available under the MIT License. ## ๐Ÿ™ Acknowledgments Based on the lifelib savings library example, which demonstrates advanced actuarial modeling techniques for variable annuity products. --- **Built with โค๏ธ 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