Risk & Modelling interview questions

Quant-risk candidates are expected to translate a correlation assumption into a portfolio-risk estimate without confusing volatility with return.

A portfolio is 50% in Asset A with 20% annual volatility and 50% in Asset B with 10% annual volatility. Their correlation is 0.25. Calculate the portfolio's annual volatility and explain what drives the diversification…

Mental math screen. Expect several of these in rapid succession, no calculator.

An investment compounds at 9% annually. (a) Roughly how long to double? (b) What is it worth after 24 years, as a multiple? (c) A fund returns 2.5x over 6 years. What is the approximate annualised return?

Banks and funds use this prompt to assess whether a candidate understands risk beyond normal-distribution statistics.

How would you design a stress test for a multi-asset portfolio? What makes a stress test decision-useful rather than a dramatic set of numbers?

Risk analysts are routinely asked to translate a rate sensitivity into an approximate P&L.

A bond portfolio has a DV01 of $85,000. What does that mean, and what is the approximate P&L if yields rise by 12 basis points? What would you check before relying on the answer?

This is a standard follow-up for market-risk analyst candidates.

Your desk has a one-day 99% VaR of $4 million. Explain precisely what that says, what it does not say, and how you would use it in a daily risk meeting.

Liquidity risk is a core risk-management topic for funds, dealers and asset managers.

A portfolio has attractive daily VaR but owns several thinly traded credit instruments. Why can it still be risky, and how would you measure the liquidity risk?

Market-risk teams use this first-round question to test whether candidates understand the loss tail rather than only a headline metric.

What is expected shortfall, and why might a risk team use it alongside a 99% VaR?

A first-round risk interview checks that you can distinguish the core risk types before discussing models.

What is market risk? Give examples for an equity, bond and FX position, and explain how a risk team makes the definition useful in practice.

Credit-risk teams use this to test whether candidates look beyond default as the only adverse outcome.

Why does a corporate bond investor care about credit migration if the issuer never defaults? Walk through the risk of a BBB bond being downgraded to BB.

This mirrors the morning escalation a market-risk analyst may prepare after a desk breaches an approved risk limit.

At 8:30am, a credit-trading desk's expected shortfall is $18m against a $15m limit, up from $11m yesterday. The trader says no meaningful risk was added. What would you investigate, and what would you recommend before…

Model validation teams ask this to test whether candidates understand governance as well as mathematics.

What is model risk? You inherit a pricing and risk model used to set limits. How would you decide whether it is fit for use?

Foundational maths underpinning every valuation method.

Derive the formula for a growing perpetuity. Then value: (a) $100/year forever at a 10% discount rate, (b) the same cash flow growing at 3%, and (c) $100/year for 10 years at 10%.

A market-risk interview often tests whether you can diagnose a model exception without overreacting to one data point.

A desk's 99% one-day VaR is breached six times over 250 trading days. How do you interpret that result and investigate it?

Risk interviews use this question to distinguish a correlation calculation from an understanding of regime risk.

A portfolio manager says two positions are safe together because their trailing three-year correlation is -0.2. Why might that conclusion fail in a crisis, and how would you challenge it?

Senior quant-risk interviews test whether you can balance a plausible model improvement against control risk and commercial pressure.

A quant team wants to deploy a new equity factor-risk model on Thursday, before a major central-bank decision. It lowers measured risk for a profitable book by 20% because it treats recent sector correlations as more…

Quant research and derivatives interviews test conceptual understanding over derivation.

Why do we model stock prices as geometric Brownian motion rather than arithmetic Brownian motion? What does Itô's lemma tell us, and why is the drift of log returns lower than the drift of prices?

A market-risk interview for a portfolio whose normal-day VaR understates gap and volatility risk.

A portfolio is short index puts and long a smaller number of single-stock puts. Its one-day VaR is stable, but the risk manager is worried about a sharp equity sell-off. What would you test beyond VaR, and why?

Senior risk interviews assess whether a candidate can connect portfolio metrics to governance and escalation.

How would you turn a firm's broad risk appetite statement into useful desk-level limits? What makes a limit framework effective?

Core to risk management interviews at banks and funds.

Define Value at Risk. What are its weaknesses as a risk measure, and what would you use alongside or instead of it?

A derivatives-risk interview uses this to test whether you recognise nonlinear exposures before discussing a VaR number.

A book is delta-neutral at the start of the day. Why can it still lose heavily after a large market move? Explain the role of gamma, volatility and hedging liquidity.