Single-name model

Stock macro sensitivity review

Explain how a selected equity historically moved with rates, inflation, growth, credit stress, and commodity inputs using transparent model diagnostics.

Regression ready

Guided intake

Start with a decision, not a blank prompt

The workshop guide uses these intake points to ask sharper questions before producing structured output.

Goal

What decision should stock analysis support?

Inputs

Which dataset, ticker, scenario, or assumption set should be trusted?

Constraint

What risk limit, horizon, or caveat should shape the output?

Output contract

Every useful answer becomes a card stack

Recommendation

What the workflow suggests and why it is not automatic advice.

Evidence

The metrics, chart movement, or model signal supporting the view.

Caveat

The assumption, missing data, or model risk that could change the result.

Next step

The most useful follow-up action before exporting or sharing.

Rate beta

-0.42

Demo coefficient versus real 10-year yield changes

CPI sensitivity

-0.18

Lower is better for inflation shock resilience

Model fit

0.64 R2

Enough to inform questions, not enough to automate trades

Professional review checklist

OKUse split-adjusted prices and consistent return frequency.
OKFlag coefficients that change sign across rolling windows.
OKDocument excluded events such as mergers, splits, or crisis periods.

Empty state behavior

Enter a ticker and macro factor set to generate the first sensitivity table.

Correlation is not causation. Results are model-dependent and assume regime stability.

Placeholders only. No payment gate.