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creating-financial-models This skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisions
npx skills add chen-zexi/open-ptc-agent --skill creating-financial-models agent daytona langchain langraph llm mcp
Financial Modeling Suite
A comprehensive financial modeling toolkit for investment analysis, valuation, and risk assessment using industry-standard methodologies.
Core Capabilities
1. Discounted Cash Flow (DCF) Analysis
Build complete DCF models with multiple growth scenarios
Calculate terminal values using perpetuity growth and exit multiple methods
Determine weighted average cost of capital (WACC)
Generate enterprise and equity valuations
2. Sensitivity Analysis
Test key assumptions impact on valuation
Create data tables for multiple variables
Generate tornado charts for sensitivity ranking
Identify critical value drivers
3. Monte Carlo Simulation
Run thousands of scenarios with probability distributions
Model uncertainty in key inputs
Generate confidence intervals for valuations
Calculate probability of achieving targets
4. Scenario Planning
Build best/base/worst case scenarios
Model different economic environments
Test strategic alternatives
Compare outcome probabilities
Input Requirements
For DCF Analysis
Historical financial statements (3-5 years)
Revenue growth assumptions
Operating margin projections
Capital expenditure forecasts
Working capital requirements
Terminal growth rate or exit multiple
Discount rate components (risk-free rate, beta, market premium)
For Sensitivity Analysis
Base case model
Variable ranges to test
Key metrics to track
For Monte Carlo Simulation
Probability distributions for uncertain variables
Correlation assumptions between variables
Number of iterations (typically 1,000-10,000)
For Scenario Planning
Scenario definitions and assumptions
Probability weights for scenarios
Key performance indicators to track
Output Formats
DCF Model Output
Complete financial projections
Free cash flow calculations
Terminal value computation
Enterprise and equity value summary
Valuation multiples implied
Excel workbook with full model
Sensitivity Analysis Output
Sensitivity tables showing value ranges
Tornado chart of key drivers
Break-even analysis
Charts showing relationships
Monte Carlo Output
Probability distribution of valuations
Confidence intervals (e.g., 90%, 95%)
Statistical summary (mean, median, std dev)
Risk metrics (VaR, probability of loss)
Scenario Planning Output
Scenario comparison table
Probability-weighted expected values
Decision tree visualization
Risk-return profiles
Model Types Supported
Corporate Valuation
Mature companies with stable cash flows
Growth companies with J-curve projections
Turnaround situations
Project Finance
Infrastructure projects
Real estate developments
Energy projects
M&A Analysis
Acquisition valuations
Synergy modeling
Accretion/dilution analysis
LBO Models
Leveraged buyout analysis
Returns analysis (IRR, MOIC)
Debt capacity assessment
Best Practices Applied
Modeling Standards
Consistent formatting and structure
Clear assumption documentation
Separation of inputs, calculations, outputs
Error checking and validation
Version control and change tracking
Valuation Principles
Use multiple valuation methods for triangulation
Apply appropriate risk adjustments
Consider market comparables
Validate against trading multiples
Document key assumptions clearly
Risk Management
Identify and quantify key risks
Use probability-weighted scenarios
Stress test extreme cases
Consider correlation effects
Provide confidence intervals
Example Usage "Build a DCF model for this technology company using the attached financials"
"Run a Monte Carlo simulation on this acquisition model with 5,000 iterations"
"Create sensitivity analysis showing impact of growth rate and WACC on valuation"
"Develop three scenarios for this expansion project with probability weights"
Scripts Included
dcf_model.py: Complete DCF valuation enginesensitivity_analysis.py: Sensitivity testing framework
Limitations and Disclaimers
Models are only as good as their assumptions
Past performance doesn't guarantee future results
Market conditions can change rapidly
Regulatory and tax changes may impact results
Professional judgment required for interpretation
Not a substitute for professional financial advice
Quality Checks The model automatically performs:
Balance sheet balancing checks
Cash flow reconciliation
Circular reference resolution
Sensitivity bound checking
Statistical validation of Monte Carlo results
Updates and Maintenance
Models use latest financial theory and practices
Regular updates for market parameter defaults
Incorporation of regulatory changes
Continuous improvement based on usage patterns
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
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Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.
CLI to manage emails via IMAP/SMTP. Use `himalaya` to list, read, write, reply, forward, search, and organize emails from the terminal. Supports multiple accounts and message composition with MML (MIME Meta Language).
