Overview: A clear description of the Advanced Portfolio Simulation Engine project using Monte Carlo analysis
Objectives:
- Build a robust Monte Carlo simulation framework
- Enable stress-testing and scenario analysis
- Provide accurate risk metrics and performance projections
- Support multi-asset portfolio modeling
- Deliver high-performance computation
Key Features:
- Monte Carlo Simulation Engine - Multi-threaded framework with 10,000+ iterations, custom random number generation, and various probability distributions
- Portfolio Modeling - Multi-asset construction, correlation matrices, rebalancing strategies
- Risk Analysis Metrics - VaR, CVaR, Sharpe ratio, maximum drawdown, volatility calculations
- Performance Forecasting - Time-horizon projections with confidence intervals
- Stress Testing & Scenarios - Market scenarios, custom scenario creation, sensitivity analysis
Technical Requirements:
- Performance target: <5 seconds for standard portfolios
- Scalability: Handle 100+ assets
- RESTful API endpoints
- JSON, CSV, and visualization-ready outputs
Proposed API Endpoints:
- POST /api/portfolio/simulate
- GET /api/portfolio/simulation/{id}
- POST /api/portfolio/scenarios
- GET /api/portfolio/metrics/{id}
Acceptance Criteria: 7 checkboxes covering performance, accuracy, testing, documentation, and validation
Success Metrics: Validation against industry-standard tools, performance targets, and user satisfaction
Overview: A clear description of the Advanced Portfolio Simulation Engine project using Monte Carlo analysis
Objectives:
Key Features:
Technical Requirements:
Proposed API Endpoints:
Acceptance Criteria: 7 checkboxes covering performance, accuracy, testing, documentation, and validation
Success Metrics: Validation against industry-standard tools, performance targets, and user satisfaction