Financial Analysis puzzles, solved step by step

Put the lease liability inside EV whenever the rent is outside EBITDA. After capitalisation the leaser's EBITDA is Rs 100 crore, like the owner's. Its shares and debt are worth Rs 723 crore, so dividing those alone gives 7.2x and makes it look cheaper. Add the Rs 77 crore lease and it is 8.0x, the owner's multiple. The numerator and denominator must describe the same claims.

Why does a lease behave like debt?

Think of two families in identical flats. One bought with a home loan; the other rents on a ten year agreement it cannot walk away from. Both owe fixed payments for years. A long lease is a loan from the landlord, repaid in rent, so the rent contains both the use of the asset and the financing of it. Under IFRS 16, and Ind AS 116 in India, the leaser now shows that promise as a lease liabilityThe present value of the rent the company is contractually committed to pay over the lease term, carried on the balance sheet like a borrowing.: Rs 12 crore a year for ten years, discounted at 9%, is about Rs 77 crore.

What changes in the numbers, and what does not?

Capitalisation moves the rent out of operating costs. It comes back as depreciation on a right-of-use asset and interest on the lease, both below EBITDA. So the leaser's EBITDA jumps by the full Rs 12 crore while nothing about its stores, customers or cash has changed. The same move puts about Rs 77 crore of lease on the balance sheet. The two changes are a pair, and a fair multiple has to use both halves or neither.

Where does this bite in real comparables work?

Data providers and peer tables do not always treat leases the same way, and a peer set can mix companies reporting under different standards. Before trusting a multiple, check whether its EV includes lease liabilities and whether its EBITDA is before or after rent, then make every company in the table match. A retailer, airline or restaurant chain that leases most of its sites can look 11% cheaper than an owner purely from this mismatch, which is the whole of the gap in this example.

Say the limitation too. The capitalised figure depends on the discount rate and the lease term the company chose, so two leasers with the same rent can carry different liabilities. Lease-adjusted multiples are better, not exact.

X carries more debt and owns a stake in an associate. Debt of Rs 750 crore at 8% costs 5.6% after tax, less than the 6.7% its operations earn on their value, so levering lowers the P/E. The associate adds Rs 22 crore to net income but nothing to EBITDA, while its Rs 300 crore value sits inside EV. Strip it out and X is 7.0x, like its peers.

Why can two multiples on the same company disagree?

Picture a house with a mortgage. Its price compared with the rent it earns is one ratio; your equity in it compared with the rent left after the mortgage payment is another. The two only agree if there is no loan. EV/EBITDA looks at the whole business before financing, while P/E looks at the shareholders' slice after interest, tax and anything non-operating. Every gap between them is explained by something that sits between EBITDA and net income, or between EV and equity value.

What numbers make both facts true?

Give both companies the same operations: EBITDA Rs 150 crore, depreciation Rs 50 crore, operating profit Rs 100 crore, tax 30%. The peer has no debt, earns Rs 70 crore and is worth Rs 1,050 crore: 15.0x earnings and 7.0x EBITDA. X borrows Rs 750 crore at 8%, so interest of Rs 60 crore leaves Rs 28 crore from operations, and it books Rs 22 crore as its share of an associateA company in which the group holds a significant minority stake, usually 20% to 50%. The group books its share of that company profit below operating profit, never in revenue or EBITDA.'s profit. Net income of Rs 50 crore at 12x is equity of Rs 600 crore, and with the debt that is an EV of Rs 1,350 crore, 9.0x EBITDA.

Which reason moves which multiple?

Separate them, because the follow-up always asks. Debt lowers the P/E when its after-tax cost is below the earnings yield of the operations. Here debt costs 8% times 0.7, which is 5.6%, while the operations earn 70 on 1,050, or 6.7%. Swapping expensive equity for cheaper debt leaves the operating slice at about 10.7x earnings. The associate does the other job: its Rs 300 crore of value sits inside EV while its profit sits below EBITDA, which lifts EV/EBITDA from 7.0x to 9.0x.

Name a third candidate if you have time: a lower tax rate than peers raises net income without touching EBITDA, so it also lowers P/E alone. Say what you would check to choose between them: the notes on debt, associates and the effective tax rate.

The cost of equity is 13.6% at debt-to-equity of 0.5, and 15.4% at 1.0. Relevering puts your own debt back onto the peer's business risk: 0.8 times (1 plus 0.75 times 0.5) gives a beta of 1.10, and 7% plus 1.10 times 6% is 13.6%. At 1.0 the beta is 1.40, so the cost of equity is 15.4%.

Why unlever the peer's beta and then relever it?

Two friends buy identical flats. One pays cash; the other borrows 60% of the price. When flat prices move 10%, the cash buyer's wealth moves 10%, while the borrower's stake moves far more, because the loan does not shrink with the price. A peer's observed beta mixes two things, the risk of its business and the risk its own debt adds, so you strip out its debt before borrowing its business risk. Then you add back your own debt, because your shareholders carry your leverage, not the peer's.

This is the Hamada relation, which assumes debt carries no market risk of its own. Then the capital asset pricing model does the rest: cost of equity is the risk-free rate plus beta times the equity risk premium, so 7% plus 1.10 times 6% is 13.6%. At debt-to-equity of 1.0, beta becomes 0.8 times 1.75, or 1.40, and the cost of equity is 15.4%.

Does more debt make the company more expensive to fund overall?

Not by this alone. Equity gets dearer as debt rises, but debt is cheaper than equity and its interest is tax-deductible, so the weighted cost of capital can fall even while the cost of equity climbs. Where it turns is where lenders start charging more and distress becomes real, which this formula does not capture. Say that limit out loud: the straight line only holds while debt is safe.

About Rs 2.16 lakh. The cow earns Rs 1,20,000 of milk a year and costs Rs 70,000, leaving Rs 50,000 of net cash for six years. At 12% that stream is worth about Rs 2,05,570, and the Rs 20,000 sale in year 6 adds about Rs 10,133. Paying more than about Rs 2,16,000 means earning less than 12% on the purchase.

How do you value something that is not a company?

The same way you value a company. A shop, a flat you rent out and a cow are all machines that turn money in now into money out later. Anything that produces cash can be valued as the present value of the cash it will hand you, after the costs of keeping it running. So the first job is to find the net cash each year, then the life, then the value left at the end.

Net cash: 10 litres a day for 300 days is 3,000 litres, worth Rs 1,20,000 at Rs 40. Upkeep of Rs 70,000 leaves Rs 50,000 a year. The six years and the Rs 20,000 sale at the end complete the cash flows.

What would make you pay less?

Every assumption in this answer is a risk to price: yield falling with age, illness, milk price, feed cost. If milk yield drops 10% a year, net cash falls fast because upkeep does not fall with it, and the value drops sharply. A higher required return for a risky asset does the same. The interviewer who asks you to value an animal is checking that you name the cash, the life, the end value and the risk, in that order, and do not stop at the milk bill.

Flip twice: heads then tails counts as heads, tails then heads counts as tails, and anything else is thrown away and flipped again. The two mixed orders each have probability 2/9, so they are equally likely whatever the bias. A pair succeeds 4/9 of the time, so each fair result takes 9/4 pairs, or 4.5 flips. Knowing the bias is exactly 1/3 lets you cut that to 2.25.

Why are heads-tails and tails-heads always equally likely?

Picture two friends flipping the same lopsided coin, one after the other. The chance the first gets heads and the second tails is the heads chance times the tails chance. The chance of the reverse is the tails chance times the heads chance. Multiplication does not care about order, so the two mixed outcomes are exactly equally likely, whatever the bias. That symmetry is the whole trick, known as the von Neumann method. Here each mixed pair has probability 1/3 times 2/3, which is 2/9.

How do you get the average of 4.5 flips?

Each pair either works or does not, independently of the last. Waiting for a success that happens with probability q takes 1/q tries on average, the same reason a die takes six rolls on average to show a six. A pair works with probability 4/9, so you need 9/4 pairs, and two flips a pair makes 4.5 flips. The method pays for its fairness with waste: 5 pairs in 9 are thrown away.

Can you do better if you know the bias exactly?

Yes, and this is usually the follow-up. With p exactly 1/3, tails-tails has probability 4/9, the same as the two mixed pairs together. Call tails-tails one side and either mixed pair the other, and only heads-heads, 1/9 of pairs, is wasted, so each fair result costs 2 times 9/8, or 2.25 flips. The von Neumann method is still the better answer when nobody tells you the bias, because it works for any p. The limit for any scheme is set by how much randomness one flip carries: about 0.92 of a fair bit here, so no method can beat roughly 1.09 flips per fair result on average.

About 2,000 sit-down cafés, as a range of roughly 1,000 to 4,000. Take about 1.3 crore people, 70% of them aged 15 to 64, and assume 20% of those visit a café twice a week. That is about 5.2 lakh cups a day; at 250 cups a café a day, about 2,080 cafés. A supply check, 150 commercial clusters with 10 cafés each plus 500 neighbourhood ones, gives about 2,000.

What exactly are you counting?

Say the definition before any number. In Bengaluru the answer changes several times over depending on whether small standing filter coffee counters count, so define a coffee shop as a sit-down café selling espresso-style coffee and say you are leaving the counters out. Then state the population as an assumption, about 1.3 crore for the metro area, and tell the interviewer you would confirm it. In a market sizing nobody is marking the population figure; they are marking whether your chain of reasoning holds.

How do you build it from demand?

Think of a single café first: how many cups does it need to sell to pay its rent? Then ask how many cups the city drinks. Of 1.3 crore people, about 70% are aged 15 to 64, so 91 lakh. Assume 20% of them use cafés, 18.2 lakh people, at two cups a week each: 36.4 lakh cups a week, or about 5.2 lakh a day. A café open 12 hours selling around 20 cups an hour serves about 250 cups a day, so the city supports about 2,080 cafés.

How do you check it, and which assumption matters most?

Count from the other side: supply. Picture the tech parks, malls and busy high streets, say 150 of them, with about 10 cafés each, plus about 500 standalone neighbourhood cafés. That is about 2,000, close to the demand answer. Then name the swing factor. The 20% share of café users is the softest input: halve it and the answer falls to about 1,040. Say the range out loud, roughly 1,000 to 4,000, because a single precise number from soft inputs sounds less credible, not more.

Roughly 21,800 to 26,200. Scale the 16% annual volatility by the square root of the time, not the time itself: four months is a third of a year, the square root of a third is about 0.58, and 16% times 0.58 is about 9.2%. That is about 2,217 points either side of 24,000, a band that holds the close about two times in three.

Why can you not just say where the index will close?

You cannot, and saying so is part of a good answer. The honest reply to a where-will-it-close question is a central point and a range, with the range doing most of the work. Today's level is the natural centre over a few months, since the expected drift is small next to the spread. The interviewer reported here asked a sales and trading candidate exactly this, and what they are testing is whether you can turn a volatility number into a range in your head.

Why does volatility scale with the square root of time?

Picture someone walking along a lane, taking each step forward or back at random. After four steps they are not usually four steps away; good and bad steps partly cancel, and the typical distance is about two steps, the square root of four. Price moves behave the same way: variance adds up with time, so the standard deviation grows with the square root of time. A third of a year is not a third of the annual volatility; it is the square root of a third, about 58% of it.

How do you check it, and what are you leaving out?

Check by another route. Monthly volatility is 16% over the square root of 12, about 4.6%, and four months is the square root of 4, which is 2, times that: about 9.2%. Same answer. Two standard deviations, about 19,600 to 28,400, covers roughly 95% of outcomes, and naming that wider band shows you know a one standard deviation range will be wrong a third of the time. Say the limits too: prices compound, so the upper side is slightly wider, about 21,900 to 26,300 on a log basis; the drift is ignored; and real index returns have fatter tails than a bell curve.

Net income falls Rs 60 crore, cash falls Rs 10 crore and debt rises Rs 50 crore. All Rs 100 crore of interest is an expense, so pre-tax profit drops 100 and tax drops 40. On the cash flow statement, add back the Rs 50 crore paid in kind because no cash left, so cash from operations falls 10. On the balance sheet, cash is down 10, debt up 50 and retained earnings down 60: both sides fall 10.

What does paid in kind actually mean?

Think of a credit card bill where you pay half the interest and the bank adds the other half to what you owe. You have still been charged the full interest; you just have not paid all of it in cash. PIK interestPaid-in-kind interest: interest that is settled by adding it to the loan principal instead of paying cash, so the debt grows each period. is a real expense that is settled by growing the loan instead of draining the bank account. That single sentence tells you where each half goes: the expense hits profit in full, and the PIK half turns up as more debt.

How does it move through each statement?

Income statement: interest of Rs 100 crore cuts pre-tax profit by 100. Assuming all of it is deductible, tax falls by Rs 40 crore, so net income falls Rs 60 crore. Cash flow statement: start from net income, down 60, and add back the Rs 50 crore of PIK as a non-cash charge. Cash from operations falls by only Rs 10 crore, because the tax saving on the whole Rs 100 crore nearly covers the Rs 50 crore of cash interest. Balance sheet: cash down 10 on the assets side; debt up 50 and retained earnings down 60 on the other side. Both sides fall by 10.

What should you add after the walk-through?

Two points earn credit. First, the tax assumption: some tax systems limit how much interest a company can deduct, and the rules on PIK can differ, so say you have assumed full deductibility and would confirm the current rule. If the PIK half were not deductible, net income would fall Rs 80 crore and cash Rs 30 crore. Second, PIK compounds: next year's interest is charged on a loan Rs 50 crore larger, which is why lenders price it higher and why it shows up in leveraged buyouts where cash is tight early on.

About Rs 157.5 crore. Start from potential rent of Rs 20 crore and take off 10% vacancy to reach effective gross income of Rs 18 crore. Operating expenses at 30% of that are Rs 5.4 crore, leaving net operating income of Rs 12.6 crore. Divide NOI by the 8% cap rate: Rs 12.6 crore over 0.08 is Rs 157.5 crore, which is 12.5 times NOI.

Why does a cap rate apply to net income and not to rent?

Think of a flat you rent out for Rs 30,000 a month. Some months it sits empty, and the society charges, repairs and property tax come out of your pocket. What you would pay for the flat depends on what is left, not on the rent written in the agreement. A cap rate is the yield a buyer wants on net operating income, the cash the building throws off after vacancy and running costs but before any loan payments. Applying it to gross rent values money the owner never receives.

How do you walk from potential rent to value?

Three steps, in order. Gross potential rent is what the building would earn fully let: Rs 20 crore. Take off vacancy first, because operating expenses here are a share of the income actually collected, not of the potential. 10% vacancy leaves effective gross incomeRent the building actually collects after vacancy and bad debts, before operating expenses. of Rs 18 crore. Expenses at 30% of 18 are Rs 5.4 crore, which leaves NOI of Rs 12.6 crore. Then divide by the cap rate.

What makes the exit cap rate the number to argue about?

Value is very sensitive to the cap rate: one point lower, at 7%, the building is worth Rs 180 crore; one point higher, at 9%, Rs 140 crore. That 1 point swing moves value by about Rs 40 crore on a Rs 157.5 crore building. Analysts usually set the exit cap rate a little above today's rate, because the building will be older when it is sold. Say the limit as well: a single cap rate assumes NOI is stable, so a building with large leases expiring soon needs a cash flow model, not one division.

EBITDA is wrong: it should be Rs 80 crore, not Rs 90 crore. Check every subtotal. Revenue less cost of goods sold is 200, so gross profit is right. Gross profit less opex is 80, not 90. EBITDA less D&A is 70, not the 60 shown. EBITDA is the only number in both failed checks, and setting it to 80 makes every line reconcile, including EBIT at 60.

Where do you start when one number in a page is wrong?

Think of a shop's daily cash sheet where the till, the card machine and the total do not agree. You do not stare at the biggest number; you re-add each subtotal and see which ones break. A P&L is a chain of subtractions, so every subtotal can be tested against the lines above it and the lines below it. Write the three identities out loud: gross profit is revenue less cost of goods sold; EBITDA is gross profit less operating expenses; EBIT is EBITDA less D&A.

Why is EBITDA the culprit and not opex or EBIT?

Two checks fail, and they share exactly one line. The wrong number is the one whose single correction fixes every failed check at once. Suppose opex were wrong instead: setting it to 110 makes EBITDA of 90 look right, but 90 less 20 still is not 60, so a second error would be needed. Suppose EBIT were wrong: 70 would fix the bottom check but leave 200 less 120 against 90. Only EBITDA at 80 repairs both. The puzzle says exactly one number is wrong, so that settles it.

What should you say beyond the answer?

State the assumption that made the puzzle solvable: operating expenses here exclude D&A, so EBITDA is gross profit less opex. If opex included depreciation, the chain would read differently. On the job, this test is the first thing a reviewer runs on any summary table, because subtotal errors usually come from a hard-coded number that did not update when the line above changed. Say where you would look next: the cell that feeds EBITDA, and whether margins quoted elsewhere in the pack used the wrong 90. At 90, the EBITDA margin reads 18% instead of 16%.