How I Used Moonbase Station to Run Portfolio-Level Scenario Analysis Without Rebuilding Spreadsheets

Over the holidays, with fewer meetings and fewer urgent emails, I finally had time to do something I rarely get to do during the year:

slow down and test a real macro question properly.

The question was simple:

What happens to a portfolio of office assets if the next Fed rate cut actually arrives?

Not as a market comment.
Not as a theoretical discussion.
But as a real, model-driven analysis using real inputs.

In the past, this would have meant reopening multiple Excel models, copying assumptions, double-checking formulas, and hoping nothing broke along the way.

This time, I deliberately ran the entire workflow inside Moonbase Station — not as a demo, but as my actual working environment.

This article isn’t a sales pitch.
It’s a comparison between how CRE analysis is usually done and how it can be done differently when the workflow itself stops getting in the way.

The Traditional Way (That Every CRE Analyst Knows)

If you’ve worked in commercial real estate long enough, this process will feel familiar.

To test a Fed rate scenario across multiple office assets, I used to:

• Open several separate Excel models
• Check whether assumptions were still aligned
• Manually adjust discount rates or debt assumptions
• Copy outputs into a summary file
• Realize something was inconsistent
• Go back and repeat

The math was never the problem.

The problem was everything around it:

• duplicated assumptions
• fragile links
• version control
• mental overhead

Most of the effort went into maintaining the model — not thinking about the risk.

Why I Used Moonbase Station for This Experiment

Moonbase Station was built specifically to remove that friction.

For this holiday experiment, I wanted to:

• avoid rebuilding models
• keep assumptions transparent
• run portfolio-level analysis cleanly
• focus on the question, not the spreadsheet

So I committed to doing everything inside Moonbase Station — from raw data to scenario results.

Starting With Real Office Asset Data (Not Clean Demos)

All three assets in this experiment were office buildings.

Different lease profiles.
Different risk characteristics.

The raw materials looked like what CRE professionals deal with every day:

• tenancy schedules
• rent rolls in PDFs
• assumptions scattered across documents

Instead of manually re-keying everything into Excel, I processed the source files locally using a small MCP (Model Context Protocol) server running on my own machine.

The MCP server extracted the relevant information and prepared structured Excel-style templates.

Why this matters:

• the data stayed local
• sensitive tenant and lease information never left my machine
• the workflow respected real-world privacy constraints

Those prepared templates were then used directly inside Moonbase Station.

Creating Office Assets Without Rebuilding Models

Traditionally, “creating an asset” means:

• building dozens of linked Excel sheets
• carefully checking formulas
• hoping the logic still holds

In Moonbase Station, an asset is created by:

• uploading the prepared Excel template, or
• simply asking the AI to create the asset using the provided assumptions

Behind the scenes, the system builds a transparent financial model where:

• assumptions are logged
• calculations are traceable
• outputs can be reviewed and exported

The key difference from Excel is that the logic is structured and centralized, not scattered across cells.

From Individual Assets to a Portfolio

Once the three office assets were created, I grouped them into a single portfolio.

This is where the workflow really diverges from the traditional approach.

In Excel, portfolio analysis often means:

• summary tabs
• linked references
• manual aggregation

In Moonbase Station, portfolio creation is explicit.

After grouping the assets:

• assumptions could be reviewed consistently
• updates could be applied in bulk
• analysis could be run at the portfolio level by default

This alone removes a surprising amount of friction for CRE investment managers.

Running the Analysis (Without Spreadsheet Gymnastics)

With the portfolio set, running the analysis was straightforward.

Instead of:

• hunting for the right tab
• checking if formulas were overwritten
• worrying about broken links

I could simply run the analysis — or ask the AI to do it.

What matters here isn’t convenience.

It’s confidence.

When you remove manual plumbing, you spend less time wondering whether the result is correct and more time thinking about what it actually means.

Scenario Analysis: The Fed Rate Cut

With the baseline portfolio in place, I created a scenario analysis focused on a hypothetical Fed rate cut.

In the old workflow, this would have required:

• copying models
• adjusting assumptions in multiple places
• tracking versions manually

In Moonbase Station:

• I created a scenario
• selected the portfolio
• defined the target changes
• ran the analysis

The system handled consistency automatically.

This made it much easier to see:

• which office assets were most sensitive
• how valuation shifts differed across assets
• where portfolio-level risk actually concentrated

Asking Questions Instead of Digging Through Inputs

One subtle but important difference in this workflow is how questions are asked.

Instead of:

• scrolling through assumption tabs
• tracing formulas backward

I could simply ask:

• “What input is driving this change?”
• “Why does this asset react more than the others?”

This keeps the analyst focused on interpretation, not mechanics.

What This Experiment Reinforced for Me

Running this holiday experiment didn’t magically make the market clearer.

But it reinforced something important:

CRE analysis doesn’t need more complexity.
It needs cleaner workflows.

Moonbase Station doesn’t replace judgment.

It replaces:

• repetitive input
• fragile spreadsheets
• unnecessary manual coordination

That’s a meaningful difference — especially for individual analysts and small investment teams.

A Quiet Comparison to the Old Way

Looking back, the biggest contrast wasn’t speed.

It was mental clarity.

• fewer moving parts
• fewer silent errors
• easier portfolio and scenario thinking

This is what modern CRE analysis should feel like.

Closing Thought

The holidays gave me the space to test a question I’d been postponing — not because it was hard, but because the traditional workflow made it feel heavier than it needed to be.

Using Moonbase Station, the focus shifted back to what actually matters:

• assumptions
• risk
• structure
• decisions

If you’re a CRE analyst or investment manager still spending more time maintaining models than thinking about outcomes, it may be worth re-examining the workflow itself.

Happy holidays — and here’s to better analysis, not bigger spreadsheets.