Business Statistics & Forecasting for Accountants (Track D)

Chapter 22 — Financial statement analysis toolkit (ratios, trends, variance, common-size)

PyPI workbook run (Track D)

From inside your Track D workbook folder (created by pystatsv1 workbook init --track d --dest ...), run:

pystatsv1 workbook run |trackd_run|

Outputs are written under outputs/track_d/ by default. If you’re unsure what a file is for, start with Track D Outputs Guide.

To see the full chapter-by-chapter run map (D00–D23), see Track D chapter index (PyPI).

Optional: write to a custom output folder:

pystatsv1 workbook run |trackd_run| --outdir outputs/track_d_custom

Interpretation prompts (quick self-check):

What is the accounting or business measurement goal in this chapter?
Which invariant/check would catch a “numbers look fine but are wrong” mistake here?

This chapter is the “accountant’s explainer pack”: a small set of repeatable analyses that turn monthly statements into decision support:

Ratios — liquidity, leverage, profitability, and efficiency
Trends — levels + percent changes (with rolling summaries)
Common-size statements — normalize the income statement to revenue and the balance sheet to total assets so comparisons are apples-to-apples
Variance bridges — a simple “what drove the change” decomposition month-over-month

The goal is not to “win” with a single metric. It’s to build a defensible story that avoids overclaiming.

By the end of Chapter 22 you should be able to:

Compute and interpret a core ratio set (liquidity, leverage, profitability, efficiency).
Use common-size statements to explain composition changes, not just level changes.
Build a simple variance bridge for net income (revenue vs costs).
Identify “cosmetic” improvements (profit up, but working capital or cash risk worse).

This chapter uses the NSO v1 synthetic tables:

statements_is_monthly.csv — income statement (Sales Revenue, COGS, Operating Expenses, Net Income)
statements_bs_monthly.csv — balance sheet (Cash, AR, Inventory, AP, taxes payable, notes payable, equity)
statements_cf_monthly.csv — cash flow bridge (Net Change in Cash)

From the repo root:

# (Re)generate NSO v1 synthetic data (if needed)
make business-nso-sim

# Run Chapter 22
make business-ch22

Artifacts are written under outputs/track_d/:

ch22_ratios_monthly.csv — monthly ratio panel (liquidity, leverage, margins, working-capital days)
ch22_common_size_is.csv — income statement common-size (percent of revenue)
ch22_common_size_bs.csv — balance sheet common-size (percent of total assets)
ch22_variance_bridge_latest.csv — last month vs prior month net-income bridge components
ch22_assumptions.csv — definitions + guardrails (what each metric means)
ch22_design.json — reproducibility metadata (inputs + definitions)
ch22_memo.md — short interpretation memo
ch22_figures_manifest.csv + figures/ch22_fig_*.png — figure list + plots

Don’t overclaim: ratios summarize relationships in the data; they don’t prove causes.
Watch denominators: small revenue months can inflate percentages.
Use context: if net income improves but AR days rise, you may have a collections problem.
Check cash: profits can improve while cash gets tighter due to working capital.

Ratio set: Compute a ratio panel (liquidity, leverage, profitability, efficiency) for two periods and identify tradeoffs and red flags.
Common-size comparison: Produce common-size statements for two periods and explain what changed strategically (mix, cost structure, or investment).
Variance explanation tree: Build a simple net income bridge (revenue, COGS, opex) and write a short explanation of the change with operational driver hypotheses.