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. 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.

2. 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.

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.