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Financial statement analysis

BAR Chapter 1 · Area I · Blueprint I.A.1

BAR opens where real finance jobs start: with a set of statements, a budget and a manager asking 'why?'. The Blueprint wants you to gather the right data, compare this year with last year and with the budget, read ratios, use analytics outputs and work out what a transaction does to the numbers. One retailer, Harbor Lane Outfitters, runs through the whole chapter so every ratio comes from the same statements.

In this chapter

  1. Getting the data ready
  2. Comparing with last year and with the budget
  3. Profitability ratios and the DuPont model
  4. Liquidity, activity and the cash conversion cycle
  5. Solvency and market ratios
  6. Reading analytics outputs
  7. What a transaction does to the numbers
  8. Limits of ratios and writing it up

This chapter has 8 lessons, 51 practice MCQs with explanations and 20 simulations, plus flashcards and a recall sheet.

What this chapter covers

Chapter 1 is free to read in full. Here are its lessons.

Getting the data ready

Every analysis starts with data, and bad data gives confident wrong answers. Before calculating anything, decide which attributes you need: the fields, their type and format, and where each one comes from.

Structured data sits in rows and columns with fixed fields, like the general ledger or a sales table. Unstructured data has no fixed fields: emails, contracts, customer reviews, images. Unstructured data must be transformed, for example by tagging reviews as positive or negative, before it can be counted.

Transforming data means preparing, cleaning and scrubbing it: removing duplicates, fixing formats, filling or flagging blanks, and joining tables on a common key such as a product code.

Then test the two things the Blueprint names. Completeness: are all records there? Agree record counts and totals to the source. Accuracy: are the amounts right? Agree a sample of lines to source documents and the totals to the general ledger.

Example. A sales file has 5,000 rows totalling $812,000. The ledger shows sales of $812,000 and the till system logged 5,000 sales. Counts and totals agree, so the file is complete for analysis. If dates were stored as text in two formats, they would be converted to one date format before grouping sales by month.

Step up. An extract of 10,000 invoice lines contains 120 lines dated in the next year, 45 duplicates and 30 lines with a blank store number. Cleaning means removing the 120 out-of-period lines and the 45 duplicates and investigating the 30 blanks. The clean file has 10,000 - 120 - 45 = 9,835 lines, of which 30 still need a store assigned.

Exam level. Harbor Lane's sales extract totals $3,987,500 against a ledger balance of $4,000,000. The point-of-sale log shows 50 transactions missing from the extract, with an average sale of $250. The missing lines explain 50 x $250 = $12,500, exactly the gap, so the extract is incomplete rather than inaccurate. Re-run the extract, then agree record count and total to the ledger before any ratio is computed. Had the gap been $40,000, the missing lines would not explain it and accuracy (wrong amounts) would also need testing.

Watch out. An extract that agrees in total can still be wrong line by line. Completeness (counts and totals) and accuracy (amounts on each line) are separate checks.

Comparing with last year and with the budget

Numbers mean little alone. Analysts compare them with the prior period, with the budget and with competitors.

Horizontal analysis shows the change in each line from one period to the next, in dollars and in percent: (this year - last year) / last year.

Vertical analysis expresses every line as a percent of a base: sales for the income statement, total assets for the balance sheet. The result is a common-size statement, which lets you compare a small company with a large one, or this year with last year, on the same scale.

A budget variance is actual minus budget. Call it favorable (F) when it helps profit: revenue above budget or cost below budget. Call it unfavorable (U) when it hurts profit. Then explain it: was it volume, price, cost per unit, a one-off event or a timing difference?

Example. Harbor Lane's operating expenses were $1,000,000 against $950,000 last year: up $50,000, or 5.3%. As a percent of sales they fell from 27.1% to 25.0%, because sales grew faster than expenses. That is a sign of operating leverage.

Step up. Sales rose from $3,500,000 to $4,000,000. Horizontal analysis: ($4,000,000 - $3,500,000) / $3,500,000 = 14.3%. Cost of goods sold rose from $2,030,000 to $2,400,000, or 18.2%. Because costs grew faster than sales, the gross margin fell from 42% to 40%.

Exam level. The budget assumed sales of $4,200,000 at a 42% gross margin. Actual sales were $4,000,000 at 40%. Split the $164,000 gross profit shortfall: the volume effect is ($4,000,000 - $4,200,000) x 42% = $84,000 U, and the margin effect is (40% - 42%) x $4,000,000 = $80,000 U. Together $164,000 U. Operating expenses came in $50,000 under budget, which is favorable, but management should check whether the saving is real (efficiency) or just timing (a delayed marketing campaign).

Watch out. A favorable cost variance is not always good news. Spending less on maintenance or training this year can show as favorable and cost far more next year.

Profitability ratios and the DuPont model

Profitability ratios ask how much profit the business makes from its sales, its assets and its owners' money.

Gross margin is gross profit divided by sales. Profit margin is net income divided by sales.

Return on assets (ROA) is net income divided by average total assets. Use the average of the opening and closing balances, because income is earned over the whole year.

Return on equity (ROE) is net income divided by average shareholders' equity.

The DuPont model breaks ROE into three drivers: profit margin x asset turnover x equity multiplier. Margin measures pricing and cost control, turnover measures how hard the assets work, and the multiplier measures leverage. ROE = ROA x equity multiplier.

Example. Net income $375,000; sales $4,000,000; average assets $2,500,000; average equity $1,050,000. Margin 9.375%, turnover 1.6, ROA 15%. Multiplier $2,500,000 / $1,050,000 = 2.38. ROE = 15% x 2.38 = 35.7%, the same as $375,000 / $1,050,000.

Step up. Average total assets are ($2,400,000 + $2,600,000) / 2 = $2,500,000. ROA = $375,000 / $2,500,000 = 15%. The DuPont split: profit margin 9.375% x asset turnover 1.6 = 15%. Harbor Lane earns about nine cents on each sales dollar and turns its assets over 1.6 times a year.

Exam level. A competitor reports ROE of 30% with a profit margin of 12%, asset turnover of 1.25 and an equity multiplier of 2.0. Harbor Lane's ROE is 35.7%: margin 9.375% x turnover 1.6 x multiplier 2.38. Harbor Lane wins on ROE not because it is more profitable per sale (its margin is lower) but because it uses its assets harder and carries more debt. The extra leverage lifts ROE in a good year and deepens losses in a bad one. A good analysis says which driver explains the gap.

Watch out. Use averages when the question gives opening and closing balances. Using year-end assets ($2,600,000) gives an ROA of 14.4%, a classic wrong option.

Liquidity, activity and the cash conversion cycle

Liquidity ratios ask whether the business can pay its bills over the next year. The current ratio is current assets divided by current liabilities. The quick ratio (acid test) keeps only the most liquid assets: cash, marketable securities and receivables. It leaves out inventory and prepaid expenses.

Activity ratios measure how quickly working capital turns into cash. Receivable turnover is sales divided by average receivables, and 365 divided by it gives days sales outstanding. Inventory turnover is cost of goods sold divided by average inventory, and 365 divided by it gives days in inventory.

Payable turnover is purchases divided by average payables. Days payables outstanding tell you how long the company takes to pay suppliers.

The cash conversion cycle = days in inventory + days sales outstanding - days payables outstanding. It is the number of days cash is tied up between paying for stock and collecting from customers.

The operating cash flow ratio, cash from operations divided by current liabilities, checks liquidity with cash rather than balances.

Example. Average receivables ($350,000 + $450,000) / 2 = $400,000. Receivable turnover $4,000,000 / $400,000 = 10, so customers take 36.5 days to pay. Average inventory ($440,000 + $520,000) / 2 = $480,000. Inventory turnover $2,400,000 / $480,000 = 5, so stock sits 73 days.

Step up. Purchases are not on the income statement, so derive them: cost of goods sold + ending inventory - beginning inventory = $2,400,000 + $520,000 - $440,000 = $2,480,000. Average payables are ($270,000 + $350,000) / 2 = $310,000, so payable turnover is 8.0 and days payables outstanding are 365 / 8 = 45.6 days.

Exam level. Last year Harbor Lane's current ratio was 2.5 and its quick ratio 1.33. This year they are 2.3 and 1.2. Inventory grew from $440,000 to $520,000 and cash fell from $180,000 to $150,000. The quick ratio fell more than the current ratio because inventory is excluded from the quick ratio and inventory is where the money went. With a 63.9-day cycle, each extra day ties up about $4,000,000 / 365 = $10,959 of sales. Cutting inventory days from 73 to 60 would free roughly 13 x ($2,400,000 / 365) = $85,479 of cash.

Watch out. Inventory turnover uses cost of goods sold, not sales. Receivable turnover uses sales. Mixing them up is the most common wrong option.

Solvency and market ratios

Solvency ratios ask whether the business can meet its long-term obligations. Debt to equity is total liabilities divided by total equity. The total debt ratio is total liabilities divided by total assets.

Times interest earned is earnings before interest and taxes (EBIT) divided by interest expense. It shows how many times operating profit covers interest. Lenders often set a minimum in a loan covenant.

Market ratios matter to shareholders. Earnings per share (EPS) is net income less preferred dividends, divided by the weighted average common shares. The price-earnings ratio is the share price divided by EPS. Dividend payout is dividends divided by net income.

Many analysts also watch EBITDA, earnings before interest, taxes, depreciation and amortization, as a rough measure of operating cash generation. Chapter 2 looks at such non-GAAP measures more closely.

Example. EBIT is $600,000 and interest is $100,000, so times interest earned is 6.0. EBITDA is $600,000 + $120,000 depreciation = $720,000. With 100,000 shares and a price of $45, EPS is $3.75 and the P/E is 12.

Step up. Debt to equity was $1,400,000 / $1,000,000 = 1.40 in Year 1 and $1,500,000 / $1,100,000 = 1.36 in Year 2. Liabilities rose, but retained earnings rose a little faster, so leverage eased slightly.

Exam level. A loan covenant requires times interest earned of at least 5.0 and debt to equity of no more than 1.5. Harbor Lane plans to borrow another $300,000 at 8% to open a store that adds $40,000 of operating income. New interest: $100,000 + $24,000 = $124,000. New EBIT: $640,000. TIE = $640,000 / $124,000 = 5.16: still above 5.0. Debt to equity becomes $1,800,000 / $1,100,000 = 1.64: covenant broken. The store looks profitable but the financing fails the covenant; equity or a smaller loan would be needed.

Watch out. Times interest earned uses income before interest and taxes. Using net income ($375,000 / $100,000 = 3.75) understates coverage.

Reading analytics outputs

Analytics outputs are reports and visualizations built from data. The Blueprint expects you to read them and explain results, not to build the software.

Descriptive analytics tells you what happened. Diagnostic analytics digs into why. Predictive analytics estimates what will happen, often with regression. Prescriptive analytics recommends what to do.

Pick the right picture: a line chart for a trend over time, a bar chart to compare categories, a scatter plot to show how two variables move together, a pie chart only for parts of a whole.

A regression line has the form y = a + bx. The intercept a is y when x is zero; the slope b is the change in y for each unit of x. R-squared (between 0 and 1) is the share of the change in y explained by x. The correlation coefficient (between -1 and +1) shows direction and strength.

Correlation is not causation. Two numbers can move together because a third factor drives both, or by chance.

Example. A bar chart shows December sales of $620,000 against an average month of $333,333. Descriptive: December is the busiest month. Diagnostic: drill down and 70% of the extra is gift cards sold, which are a liability until redeemed, so December revenue under GAAP is lower than the till total.

Step up. The regression is monthly sales = $50,000 + $12 x visitors. A store expecting 25,000 visitors next month predicts $50,000 + $12 x 25,000 = $350,000 of sales. The $50,000 is the intercept (sales with zero visitors, mostly online orders), and $12 is the slope (extra sales per extra visitor).

Exam level. R-squared is 0.81, so the correlation coefficient is the square root, 0.90. A new store expects 60,000 visitors, while the data used to build the model ranged from 10,000 to 35,000. The prediction of $50,000 + $12 x 60,000 = $770,000 is an extrapolation outside the data, so it is unreliable: a crowded store may convert fewer visitors. An analyst would flag the estimate and look for comparable large stores before relying on it.

Watch out. A high R-squared does not mean the model will predict well outside the range of data it was built on.

What a transaction does to the numbers

The Blueprint asks you to derive the impact of transactions on the statements and the notes. Work in three steps: write the journal entry, see which lines move, then recompute the ratio.

For any ratio, check what happens to the numerator and the denominator. A transaction that changes only one of them moves the ratio in that direction. A transaction that changes both by the same amount depends on whether the ratio is above or below 1.

Transactions that swap one current asset for another, like collecting a receivable, leave the current ratio unchanged but can change the quick ratio (buying inventory with cash lowers it).

Do not forget the notes: a new loan brings a debt maturity disclosure, a sale of a major asset may need disclosure, and a covenant breach can change how debt is classified.

Example. Harbor Lane buys $60,000 of inventory for cash. Current assets are unchanged, so the current ratio stays at 2.3. Quick assets fall from $600,000 to $540,000, so the quick ratio falls from 1.2 to 1.08.

Step up. When a ratio is above 1, taking the same amount off the top and the bottom raises it: ($1,150,000 - $100,000) / ($500,000 - $100,000) = 2.63. Adding the same amount to both lowers it. When a ratio is below 1, the opposite happens.

Exam level. Harbor Lane is considering selling an old warehouse (carrying amount $300,000) for $360,000 cash and paying $200,000 of long-term debt with part of the proceeds. Effects: cash +$160,000 net, so current ratio = $1,310,000 / $500,000 = 2.62; gain of $60,000 (ignore income tax here); total assets $2,600,000 - $300,000 + $160,000 = $2,460,000; liabilities $1,300,000; equity $1,160,000; debt to equity falls to $1,300,000 / $1,160,000 = 1.12. The note on property would describe the sale, and the gain is not part of recurring operating income.

Watch out. Paying a current liability raises a current ratio above 1 but lowers a current ratio below 1. Always check which side of 1 you start on.

Limits of ratios and writing it up

Ratios point you to questions; they do not answer them. Know their limits.

Ratios use historical cost figures. Different accounting methods (FIFO or LIFO, straight-line or accelerated depreciation) make companies look different when they are not. A year-end date at a seasonal low or high distorts balance sheet ratios. Window dressing, such as paying suppliers just before year end, can flatter a ratio for one day.

Inflation distorts comparisons over time. A single unusual item, such as a lawsuit settlement, can swing a year's margin.

A good write-up states the question, the data and its checks, the key findings with numbers, the limits of the analysis and a recommendation. Lead with the answer; managers read the first paragraph.

Example. Harbor Lane missed budgeted net income by $93,000. Gross profit was $164,000 short ($84,000 from lower sales volume, $80,000 from a two-point drop in margin), partly offset by $50,000 of lower operating expenses. Interest was $10,000 over budget. Tax at 25% absorbed a quarter of the shortfall.

Step up. Harbor Lane uses FIFO and a competitor uses LIFO. In a period of rising prices the competitor's cost of goods sold is higher and its inventory lower, so its gross margin looks worse and its inventory turnover looks faster even if the two businesses are identical. Comparisons across companies need the same accounting methods, or an adjustment.

Exam level. Harbor Lane's year end is January 31, after the holiday season; a competitor's is October 31, before it. At January 31 Harbor Lane's inventory is low and its cash high, so its current ratio and inventory turnover look strong. At October 31 the competitor holds peak stock. The gap is caused by timing, not performance. Use average balances, compare to the competitor's quarterly figures, or compare each company with its own history.

Watch out. Comparing with an industry average assumes the average company is a sensible benchmark. Check who is in the average and how it was calculated.

Chapter 2: Non-financial and non-GAAP measures