monte-carlo-return-simulator

Name: monte-carlo-return-simulator
Availability: InStock
Author: chibus0368-pixel

Simulates CRE return distributions from three-point estimates using Monte Carlo trials.

Updated Apr 1, 2026

Search Tags:#risk-analysis #monte-carlo #cash-flow #var #cvar #cre-investment #irrs

Ready to run

npx skills add https://github.com/chibus0368-pixel/om-analyzer --skill monte-carlo-return-simulator

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: monte-carlo-return-simulator
Source: https://github.com/chibus0368-pixel/om-analyzer/tree/main/skills/monte-carlo-return-simulator
Command: npx skills add https://github.com/chibus0368-pixel/om-analyzer --skill monte-carlo-return-simulator

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Probabilistic CRE return analysis by converting three-point uncertainty into a full, simulated return distribution across hold periods and deal types.

Core Features & Use Cases

End-to-end Monte Carlo engine for CRE returns using distributional inputs and correlation matrices
Generates year-by-year NOI, debt service, terminal value, levered cash flows, and key metrics (IRR, equity multiple, cash-on-cash)
Supports scenario overlays and sensitivity analysis with a consistent uncertainty framework

Quick Start

Provide your three-point estimates and run the calculator with the default 5,000-trial setup to generate the probabilistic return distribution.

Frequently Asked Questions about monte-carlo-return-simulator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I run a Monte Carlo simulation for CRE investment returns?▼

To run a Monte Carlo simulation for CRE investment returns, provide three-point uncertainty estimates for your inputs and execute the 5,000-trial setup to generate a probabilistic distribution of levered cash flows, IRR, and equity multiples.

What is VaR and CVaR in commercial real estate risk analysis?▼

VaR and CVaR in commercial real estate risk analysis are tail-risk metrics quantifying potential losses within a simulated return distribution. They are calculated alongside IRR and equity multiples by converting uncertainty inputs into probabilistic cash flow outcomes.

Can I model value-add and opportunistic CRE deals with different hold periods?▼

You can model value-add and opportunistic CRE deals with different hold periods. The simulator converts three-point uncertainties into year-by-year NOI, debt service, and terminal value to generate levered cash flows across various deal structures and timelines.

How do you handle correlation between inputs in a Monte Carlo cash flow model?▼

To handle correlation between inputs in a Monte Carlo cash flow model, the simulator applies Cholesky decomposition to the correlation matrix. This ensures correlated variables maintain realistic dependencies during the 5,000-trial distribution fitting process.

What is the best way to underwrite CRE tail risk using probabilistic returns?▼

The best way to underwrite CRE tail risk using probabilistic returns is converting three-point estimates into a full simulated distribution. This calculates cash-on-cash, IRR, equity multiple, VaR, and CVaR while applying scenario overlays for sensitivity analysis.

Why does my IRR convergence fail during stochastic real estate modeling?▼

IRR convergence during stochastic real estate modeling can fail due to unstable simulated cash flow sequences. The simulator addresses this with robust IRR convergence handling to ensure reliable metrics across the generated distribution of returns.