Monte Carlo Simulator
Run Monte Carlo simulations with probability distributions, confidence intervals, and statistical analysis
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Source preview
cli-tool/components/commands/simulation/monte-carlo-simulator.md
--- allowed-tools: Read, Write, Edit, WebSearch argument-hint: [simulation-target] | --financial-projections | --project-timelines | --market-scenarios | --risk-assessment description: Run Monte Carlo simulations with probability distributions, confidence intervals, and statistical analysis --- # Monte Carlo Simulator Run comprehensive Monte Carlo simulations with advanced statistical analysis: **$ARGUMENTS** ## Current Analysis Context - Simulation target: Based on $ARGUMENTS (financial projections, project timelines, market scenarios, risk assessment) - Key variables: Uncertain parameters that drive outcome variability - Available data: Historical data, expert estimates, and probability distributions - Decision requirements: Confidence levels and risk tolerance for decision-making ## Task Execute sophisticated Monte Carlo simulations with comprehensive uncertainty quantification: **Simulation Target**: Use $ARGUMENTS to simulate financial projections, project timelines, market scenarios, or risk assessments **Monte Carlo Framework**: 1. **Variable Definition** - Uncertain parameter identification, probability distribution selection, and correlation modeling 2. **Simulation Engine** - Random sampling, scenario generation, and statistical convergence analysis 3. **Output Analysis** - Probability distributions, confidence intervals, and sensitivity analysis 4. **Risk Quantification** - Value at Risk (VaR), extreme scenario analysis, and tail risk assessment 5. **Scenario Clustering** - Pattern recognition, outcome categorization, and decision-relevant grouping 6. **Decision Integration** - Risk-adjusted recommendations, optimization strategies, and contingency planning **Advanced Features**: Latin hypercube sampling, copula modeling, importance sampling, and variance reduction techniques. **Statistical Rigor**: Convergence testing, goodness-of-fit validation, and robust statistical inference with comprehensive uncertainty bounds. **Output**: Complete Monte Carlo analysis with probability distributions, risk metrics, scenario analysis, and statistically-grounded decision recommendations with quantified confidence levels.
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MIT License Copyright (c) 2025 Daniel (San) Ávila Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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