Derivatives Foundation interview preparation

Questions

100

Traced to a firm

29

Firms

19

Updated

September 2026

Asked at

All firmsMSMorgan Stanley4Nomura4Akuna Capital2Amundi2HSBC2PIMCO2Bank of America1Barclays1Citadel1DRW1Goldman Sachs1Jane Street1Millennium Management1Mizuho1Old Mission Capital1RCRBC Capital Markets1Scotiabank1UBS1Wells Fargo Securities1

Topic

All topicsForwards and futures10Options basics8Option pricing7The Greeks10Volatility7Option strategies9Swaps and rates7Credit derivatives4Market structure and clearing6Indian derivatives8Trading and markets9Brainteasers6Fit9

Level

AnyCoreIntermediateHard

Type

AnyTechnicalCaseMarket viewBrainteaserFit

1. 067What did post-2008 regulation actually change about the derivatives market?Market structure and clearingHardsuperdayRisk managementClearing and risk

   Say this

   Four things: standardised OTC derivatives must be centrally cleared, uncleared ones must exchange two-way margin, everything must be reported to a trade repository, and dealer capital charges for derivatives rose sharply. The combined effect was to make bespoke and long-dated derivatives much more expensive and to shrink dealer balance sheets.

   Then walk it

   1. The clearing mandate under Dodd-Frank in the US and EMIR in Europe: interest rate swaps in major currencies and index CDS have to go to a CCP. That converted the most systemic part of the OTC market into a margined, netted, reported system.
   2. Execution moved too. Swap Execution Facilities in the US and the trading obligation in Europe pushed the standardised flow onto platforms with pre-trade transparency, which compressed dealer spreads on vanilla products considerably.
   3. Uncleared margin rules put two-way initial margin on the rest, phased in from 2016. Reporting to trade repositories gave regulators — for the first time — a picture of who held what.
   4. Capital is the underrated piece. The leverage ratio, the credit valuation adjustment capital charge, and SA-CCR for counterparty exposure all raised the balance sheet cost of a derivative. That is why dealers price CVA, FVA and capital into a quote now, and why a long-dated uncollateralised swap with a corporate can be startlingly expensive.
   5. Volcker and the ring-fencing rules changed who provides liquidity. Dealers stopped warehousing risk in size, and a meaningful share of market making in derivatives migrated to non-bank firms — which is one reason prop shops and electronic market makers matter more now than in 2007.
   6. The honest assessment: the reforms genuinely reduced the risk of a bilateral credit cascade, which was the 2008 failure mode. They introduced a new one — synchronised margin-driven liquidity demand — which showed up in March 2020, in the 2022 UK LDI crisis and in European energy. Regulators fixed the problem they had and created the problem they now study, which is roughly what you should expect from any reform of this scale.

   Where candidates lose it

   Listing acronyms. The strong answer groups the changes into four buckets, names the capital piece — which most candidates omit — and closes by saying which risk was reduced and which was created. Naming LDI 2022 or March 2020 as the new failure mode is what shows judgement.

   Expect next

   • Which reform had the biggest effect on dealer pricing?
   • Why did market making migrate to non-bank firms?
   • What is the new systemic risk the reforms created?
2. 071Walk me through SEBI's margin framework and position limits for derivatives.Indian derivativesHardtechnicalIndian derivatives desksClearing and risk

   Say this

   Margin has two main layers: SPAN, which is the portfolio risk margin computed by the clearing corporation across scenarios, and exposure margin on top of it. Since 2020, margins are collected upfront and monitored at random intraday snapshots rather than end of day. Position limits are set separately for clients, trading members and foreign investors, in notional or open-interest terms.

   Then walk it

   1. SPAN margin: the clearing corporation revalues your whole portfolio under a grid of price and volatility scenarios and charges the worst case. It gives credit for genuine offsets, which is why a hedged spread costs far less margin than two outright positions.
   2. Exposure margin sits on top as an additional buffer, and short option positions attract specific additional requirements. Close to expiry, extra margins apply to in-the-money and near-the-money short positions because of settlement risk.
   3. The 2020 peak margin reform is the structural change worth knowing. Brokers must collect the full upfront margin, and compliance is checked against four random intraday snapshots each day, with penalties for shortfalls. That killed the intraday leverage brokers used to extend, which had been 20 to 50 times.
   4. Physical settlement in single stock derivatives compounds it: in the expiry week, margins on in-the-money single stock options escalate sharply, because delivery obligations arise. Retail traders regularly get caught by this.
   5. Position limits: client-level limits on index options in notional terms, market-wide position limits on single stocks expressed as a share of free float with a 95 percent trigger that bans new positions, and separate FPI category limits. Index option limits were tightened in 2025 with delta-adjusted rather than notional measurement, which was a direct response to the concentration issues the year before.
   6. Where the framework is genuinely good and where it strains: the upfront margin regime materially reduced client default risk and broker failures, which was the point. The strain is procyclicality and cost — margins rise into volatility, spreads widen, and hedging gets more expensive precisely when it is most needed. And measuring index option limits in notional rather than delta terms was an obvious gap until it was fixed.

   Where candidates lose it

   Naming SPAN and stopping. An Indian desk expects the 2020 peak-margin reform and the intraday snapshot mechanic, because it changed the whole broking business model. And the delta-adjusted position limit change is recent enough that knowing it marks you as current.

   Expect next

   • What did peak margin reporting do to the broking industry?
   • Why did SEBI move to delta-adjusted position limits?
   • How does SPAN give credit for a hedged position?
3. 072SEBI data shows most individual derivatives traders lose money. Should retail access be restricted?Indian derivativesHardsuperdayIndian derivatives desksIndian broking

   Say this

   I would restrict the product design and the leverage rather than the access. The data is stark — SEBI's studies found roughly nine in ten individual traders losing money, with aggregate losses in the tens of thousands of crores — but an outright ban pushes the same demand into dabba trading and offshore apps, where there is no margin, no clearing and no recourse.

   Then walk it

   1. What the data actually says: across SEBI's 2023 and 2024 studies, the large majority of individual F&O traders lost money, losses were concentrated in short-dated index options, and a sizeable share of participants were young and new to markets. The average loss per loss-making trader was several times the median Indian household's annual savings capacity.
   2. The structural causes are identifiable rather than mysterious: weekly expiries create a near-daily lottery, tiny premiums make the minimum bet trivially small, mobile apps gamified the interface, and finfluencer marketing sold option selling as income.
   3. What SEBI has done and what I think is right: fewer weekly expiries, larger contract sizes, upfront margin collection, higher near-expiry margins, mandatory risk disclosures, and action against unregistered advisers. These raise the ticket size and remove the leverage without banning the instrument.
   4. What I would add: a suitability step for first-time derivatives users, a hard cap on intraday leverage for new accounts, and removing the ability to build a position out of many tiny lottery tickets. And I would look hard at broker incentives, since brokerage revenue is proportional to churn.
   5. The counter-argument to take seriously: adults are entitled to take risk with their own money, retail participation adds liquidity that institutional hedgers benefit from, and the same loss statistics are true of day trading equities. Singling out options is partly a choice about which losses we find visible.
   6. Where I land, and I would say it plainly: the case for intervention here is not paternalism about risk, it is that the product design was engineered for frequency rather than for hedging. Fix the design and the leverage, keep the access, and be honest that the market will lose real revenue when you do — which is why exchanges and brokers lobbied against every one of these changes.

   Where candidates lose it

   Taking a side without engaging the counter-argument, or reciting the loss statistics without a policy view. Interviewers on Indian desks ask this to see if you can hold a commercial position and an ethical one at once. Name the displacement risk — dabba trading and offshore apps — because that is the strongest argument against a ban.

   Expect next

   • Would a ban just move the activity offshore?
   • What is the strongest argument against restricting access?
   • Whose revenue falls if you are right?
4. 075How does a foreign investor hedge Indian equity exposure, and why does so much of it happen offshore?Indian derivativesHardsuperdayIndian derivatives desksEquity derivatives

   Say this

   Three routes: onshore index futures and options through an FPI registration, offshore instruments like SGX or GIFT Nifty and participatory notes, and total return swaps with a bank that holds the onshore position. The choice is driven less by pricing than by registration burden, tax treatment and position limits — which is why a large share of the risk transfer historically sat offshore.

   Then walk it

   1. Onshore: register as an FPI, get a custodian, and trade Nifty futures and options directly. You get the tightest pricing and deepest liquidity, and you accept Indian tax, reporting and category-level position limits.
   2. Offshore listed: the Nifty contract that traded on SGX migrated to NSE IX at GIFT City in 2023 as GIFT Nifty. It settles in dollars, trades nearly 21 hours, and lets an offshore investor take Nifty risk without an FPI registration or rupee exposure.
   3. Synthetic: a total return swap or participatory note written by a bank that holds the onshore hedge. The client gets the economics in dollars with no Indian registration. The cost is a financing spread and full counterparty risk to the issuer.
   4. The drivers of the offshore preference are structural: registration takes time, the securities transaction tax and capital gains treatment change the after-tax return, and the currency leg has to be hedged separately in a market with its own constraints. P-notes were largely a regulatory-arbitrage product and SEBI has steadily squeezed them.
   5. GIFT City is the deliberate policy answer — bring the offshore activity onshore into a tax-neutral IFSC with dollar settlement. The migration of the SGX Nifty contract was the flagship success, and rupee derivatives and offshore banking units are the next phase.
   6. The risk to flag, and it is the one that actually catches people: currency and equity are correlated for a foreign investor in India. The rupee weakens when foreign flows leave, which is when equities are falling, so an unhedged currency leg doubles the drawdown. Hedging the equity with GIFT Nifty in dollars looks clean but embeds the rupee move into the contract's value rather than removing it — you have to be explicit about which risk each leg is carrying.

   Where candidates lose it

   Listing the routes without the reason. The interviewer wants the drivers — registration, tax, limits — and the GIFT Nifty migration as the policy response. And the equity-currency correlation for a foreign investor is the analytical point most candidates miss entirely.

   Expect next

   • What happened to the SGX Nifty contract, and why did it matter?
   • Why has SEBI discouraged participatory notes?
   • How correlated are Indian equity drawdowns and rupee depreciation?
5. 079Why is crypto lagging gold even though both are supposed to be hedges?Trading and marketsHardsuperdayNomuraGlobal Markets · New York · 2026

   Say this

   Because they are not hedging the same thing. Gold is a hedge against monetary debasement and geopolitical risk, with central banks as a price-insensitive structural buyer. Bitcoin behaves empirically like a high-beta risk asset — it correlates with the Nasdaq and with liquidity conditions, not with fear. The 'digital gold' framing is a narrative, and the correlation data has never really supported it.

   Then walk it

   1. Look at the behaviour in stress. In March 2020, in the 2022 rate shock, and in most risk-off episodes, bitcoin fell with equities and often fell harder. Gold's drawdowns in the same episodes were smaller and shorter. That is not a hedge, that is a levered risk asset.
   2. The buyer base explains most of it. Central bank gold buying has been running at record levels since 2022, accelerated by the freezing of Russian reserves, which gave every non-aligned reserve manager a reason to hold an asset no one can sanction. That flow is price-insensitive and persistent.
   3. Crypto's marginal buyer is discretionary risk capital, plus ETF flows that are themselves procyclical. When liquidity tightens, that buyer disappears — which is precisely when a hedge is supposed to work.
   4. There is a real overlap in the thesis: both are non-sovereign stores of value with no yield. But gold has four thousand years of institutional acceptance, a central bank bid, and jewellery demand as a floor. Bitcoin has a fixed supply schedule and a much shorter track record, and its volatility is five to eight times gold's, which makes it unusable as a reserve asset regardless of the thesis.
   5. The honest possibility that it changes: as the holder base institutionalises, correlation could fall and behaviour could converge towards gold. There is some evidence of that in the post-ETF period. I would want several full cycles before believing it.
   6. So the way I would frame it for a client: gold is a hedge you hold and forget, crypto is a risk position with an option on monetary regime change. Sizing them the same way is the error, and calling them both hedges is how that error gets made.

   Where candidates lose it

   Accepting the premise that both are hedges and looking for a reason one is underperforming. Reject the premise: the correlation data says bitcoin is a risk asset. And name the central bank gold bid post-2022, because that is the specific flow story behind the divergence.

   Expect next

   • Could crypto's correlation profile change as the holder base institutionalises?
   • Why has central bank gold demand been so strong since 2022?
   • How would you size the two differently in a portfolio?

   Reported by candidates at Nomura (Global Markets, New York, 2026). Source: Wall Street Oasis.

6. 080How does AI affect equities and rates?Trading and marketsHardsuperdayNomuraGlobal Markets · New York · 2026

   Say this

   In equities it has concentrated the index and shifted the story from software margins to capital expenditure, which changes the quality of the earnings. In rates the channel is more interesting and less discussed: a genuine productivity shock raises the neutral real rate, and the capital spending itself is a large new demand for financing. So AI is arguably a steeper-curve, higher-real-yield story as much as an equity story.

   Then walk it

   1. Equities first, and the honest structural fact: index concentration is at multi-decade highs, with a handful of names driving most of the return. That makes the index itself a different instrument than it was — higher single-name risk inside a supposedly diversified product, which shows up as index volatility being low while dispersion is high.
   2. The earnings-quality shift matters for valuation. The hyperscalers moved from asset-light software economics to spending a large share of cash flow on data centres and chips. Depreciation follows with a lag, so reported margins face a headwind two to three years after the spending, and the return on that capital is the open question.
   3. The derivatives expression of that: correlation is low and dispersion high, so index volatility understates single-name risk. Being long single-name volatility and short index volatility — long dispersion — is the natural way to express scepticism without taking a directional view.
   4. Rates channel one: if AI genuinely raises productivity growth, the neutral real rate rises, which means the whole curve settles higher than pre-2020 assumptions and long-duration assets are structurally repriced.
   5. Rates channel two, which is nearer term: the capital expenditure is enormous and increasingly debt-financed, including a fast-growing data-centre securitisation and private credit market. That is a new, large supply of credit issuance, and it concentrates exposure to a single technology thesis inside the credit market.
   6. Where I would be honest: nobody knows if the productivity effect is real, and previous technology capital cycles — railways, fibre in 1999 — delivered the technology and destroyed the capital. So I would hold the equity view loosely, and note that the trade with the clearest logic is the dispersion trade, because it profits from the concentration being mispriced regardless of which way the thesis resolves.

   Where candidates lose it

   Giving a generic technology-optimism answer. On a Global Markets desk the differentiator is the rates channel — neutral rate plus financing supply — and the derivatives expression, which is the dispersion trade. And having the humility to name the fibre 1999 comparison keeps it from sounding promotional.

   Expect next

   • What is a dispersion trade and how would you put it on?
   • Why would AI raise the neutral rate?
   • What does the 1999 telecom build-out tell you about this one?

   Reported by candidates at Nomura (Global Markets, New York, 2026). Source: Wall Street Oasis.

7. 082Pitch me a ten-year trade.Trading and marketsHardsuperdayBank of AmericaSales and Trading · London · 2025

   Say this

   A ten-year horizon means the trade has to rest on a structural change, not a cycle, and it has to be expressible in an instrument that survives ten years. So: name the structural driver, name the instrument, state the carry, and be explicit about what could make the structure wrong rather than just the timing.

   Then walk it

   1. Pick a driver that is demographic, fiscal, technological or regulatory — something that does not mean-revert inside the horizon. Ageing populations and their effect on savings and fiscal deficits, the electrification of energy demand, the fiscal cost of defence rearmament in Europe, or the structural build-out of power capacity for computing.
   2. Then the instrument, and be realistic. Nothing liquid trades for ten years in options, so a long-horizon view is usually expressed in a forward-starting swap, a curve steepener rolled forward, physical exposure, or equity in the beneficiaries. If your idea needs a ten-year option, say that the structure would have to be a bespoke OTC trade and price accordingly.
   3. State the carry explicitly. A view that costs 3 percent a year to hold needs the structural move to be very large, and most long-horizon trades fail on carry rather than on being wrong. The best structural trades are ones where you are paid to wait.
   4. Give a worked example rather than a theme: 'I would be a receiver of the very long end in a country with a shrinking workforce and a pension system that has to buy duration, funded by paying the belly, because the demographic flow is a known buyer for a decade.' Name the flow, not the feeling.
   5. Then the falsifier at the structural level. Not 'if it goes against me', but 'if the demographic assumption is offset by immigration policy, or if the fiscal response changes the supply of duration, the trade is wrong in kind rather than in timing'.
   6. And the risk management: a ten-year view held in a mark-to-market book still has to survive drawdowns, so I would size it as a carry position with periodic reassessment, not as a conviction trade I refuse to cut. Being right in 2035 is no use if the position is closed in 2027.

   Where candidates lose it

   Pitching a cyclical view with a ten-year label on it — 'I think rates go down'. The question is testing whether you can separate structural from cyclical and whether you know what instruments actually exist at that horizon. Naming the carry and the instrument constraint is what makes it sound like a desk answer.

   Expect next

   • What instrument actually exists at that maturity?
   • What does the trade cost you to hold each year?
   • What would tell you the structure, not just the timing, was wrong?

   Reported by candidates at Bank of America (Sales and Trading, London, 2025). Source: Wall Street Oasis.

8. 088Compute the probability and then bet on whether you draw another black stone.BrainteasersHardtechnicalCitadelQuantitative Trading · New York · 2025

   Say this

   Two parts, and the second is the real test. Compute the conditional probability by Bayes, updating on what has already been drawn, then price a bet at odds that give you an edge and size it so a wrong answer does not end you. Most candidates get the arithmetic and then bet like the arithmetic is certain.

   Then walk it

   1. Set up the inference properly. If the composition of the bag is unknown, drawing a black stone is evidence about the composition, so you update over the possible bags rather than treating the draw as independent.
   2. The classic version: two urns, or a bag with an unknown mix, and a black draw raises the posterior weight on black-heavy compositions. With no replacement, conditioning on the draws already made is essential — a common error is to compute the unconditional probability and hand it over.
   3. Worked case to show the mechanism: three stones, one known black, one known white, one unknown with equal odds. You draw black. Posterior probability the unknown is black rises to two thirds, so the next draw being black is now more likely than the prior suggested. That is the Bayes step they are checking.
   4. Then the betting step, which is where the interview is decided. If my computed probability is 0.6, I want odds better than 3 to 2 to have an edge. I would quote a market rather than accept theirs — say I am a buyer at 55 and a seller at 65 — because that is the trading answer rather than the maths answer.
   5. Then sizing. Kelly says stake a fraction equal to the edge over the odds, and in an interview I would bet a small multiple less than Kelly, because my probability estimate is itself uncertain and Kelly assumes it is not.
   6. And I would say the honest caveat: my probability depends on my prior over the bag's composition, and if I have the prior wrong my edge is imaginary. So I would take the bet at odds that leave room for my model being wrong, which means demanding better than fair odds rather than exactly fair ones.

   Where candidates lose it

   Computing the probability and then accepting whatever odds are offered. Citadel is watching whether you distinguish your estimate from your confidence in it, quote a two-way market, and size below Kelly because the input is uncertain. The maths is the easy half.

   Expect next

   • What is your prior over the bag's composition, and how much does the answer depend on it?
   • What odds do you need to take the bet?
   • How much would you stake, and why not more?

   Reported by candidates at Citadel (Quantitative Trading, New York, 2025). Source: Wall Street Oasis.

9. 089There are n cars on a circular track and between them just enough petrol for one car to complete a lap. Show that there is a car that can complete the lap by collecting petrol from the others as it goes.BrainteasersHardsuperdayMillennium ManagementInvestments · London · 2024

   Say this

   Yes, such a car always exists. The cleanest proof: imagine a phantom car with enough fuel to complete the lap anyway, start it anywhere, and track its fuel level as it picks up each deposit. The point at which its fuel is at its minimum is a valid starting car — from there the cumulative balance never goes negative.

   Then walk it

   1. Set it up as a sequence of partial sums. Going around the circle, each car contributes a gain of its petrol and each gap costs fuel. Total gains minus total costs is exactly zero, because there is precisely one lap's worth.
   2. The argument: define the running balance starting from an arbitrary car. It ends at zero. Take the position where the running balance is at its global minimum, and start there instead. Relative to that point, every partial sum is non-negative, because you subtracted the most negative value from all of them.
   3. So the starting car is the one immediately after the minimum of the cumulative balance. That is a constructive answer, not just an existence proof, which is what makes it satisfying.
   4. There is an induction proof too: with n cars, there must exist some car that has enough petrol to reach the next one — otherwise the total would be insufficient. Merge those two into a single car and you have the same problem with n minus 1. Induct down to one car, which trivially works.
   5. One line for n equals 2 to show the mechanism: if car A has 0.7 laps of fuel and B has 0.3, and the gap from A to B is 0.4, then A cannot reach B directly if it only had 0.3 — the partial-sum argument tells you which one to pick without checking cases.
   6. Why this gets asked at a fund rather than in a maths class: it is the same structure as a cash flow or margin problem. You know the total is sufficient and you need to know whether the path ever goes negative. That is exactly a funding liquidity question, and the answer is always about the minimum of the cumulative balance, not the total.

   Where candidates lose it

   Trying small cases and asserting a pattern. The interviewer wants the partial-sum or induction argument. And the move that impresses is connecting it to cash flow timing — total sufficiency does not imply path feasibility, which is the whole of liquidity risk.

   Expect next

   • Give me the induction version of the proof.
   • Is the starting car unique?
   • What financial problem has exactly this structure?

   Reported by candidates at Millennium Management (Investments, London, 2024). Source: Wall Street Oasis.

10. 100What do you think makes a good derivatives trader, and which part of it would you be worst at?FitHardsuperdayProp trading firmsMarket making

    Say this

    Three things: being able to hold two probabilities at once — your view and your confidence in it — being ruthless about size, and being genuinely comfortable being wrong in public. The maths is table stakes. The part I would be worst at is cutting a position I still believe in, and I would rather say that than pretend the weakness is something cosmetic.

    Then walk it

    1. First trait: calibration, not conviction. A good trader can say 'I think this is 60-40 and here is what would move it to 40-60'. The failure mode is a strong view with no sense of how strong it should be, which is how positions get oversized.
    2. Second: discipline about size. Almost every blow-up is a sizing failure rather than an analysis failure, and the traders who last size to survive being wrong rather than to maximise being right.
    3. Third: an unusual relationship with error. In this job you are publicly wrong several times a week, and the people who do well treat a loss as information rather than as an identity problem. That is a temperament, and it is more scarce than quantitative ability.
    4. Fourth, specific to derivatives: comfort with multidimensional risk. You can be right on direction and lose on volatility, right on volatility and lose on timing. That means being able to say precisely which of your views the position actually expresses.
    5. Then the weakness, stated as something real with a mitigation. 'I am slow to cut a position I still believe in, so I now write my exit level and my falsifier down before I enter, and I have a rule that I do not average down.' A named weakness with a named control is credible. A fake weakness is not.
    6. And I would say what I do not yet know, because a junior claiming to have this figured out is the least convincing possible answer. I have not run risk through a genuine dislocation, and the honest thing is that nobody knows how they behave in one until it happens.

    Where candidates lose it

    Naming traits that describe you conveniently, then giving a fake weakness like 'I care too much' or 'I work too hard'. The second half of the question is the whole test. Name a real weakness, name the control you put on it, and admit what you have not been tested on yet.

    Expect next

    • What is the control you use for that, and does it work?
    • Have you ever had to hold risk through something that scared you?
    • What would make you leave this job in three years?

Firm tags come from public, anonymous candidate reports on Wall Street Oasis: strong signal, not sworn testimony. Firms are named as the places a question was reported, not as partners of Fin Maverick. Answers are written for this page to show how to think out loud; they are not scripts to recite.