Try 10 focused CISI Risk questions on Market Risk, with answers and explanations, then continue with Securities Prep.
| Field | Detail |
|---|---|
| Exam route | CISI Risk |
| Issuer | CISI |
| Topic area | Market Risk |
| Blueprint weight | 15% |
| Page purpose | Focused sample questions before returning to mixed practice |
Use this page to isolate Market Risk for CISI Risk. Work through the 10 questions first, then review the explanations and return to mixed practice in Securities Prep.
| Pass | What to do | What to record |
|---|---|---|
| First attempt | Answer without checking the explanation first. | The fact, rule, calculation, or judgment point that controlled your answer. |
| Review | Read the explanation even when you were correct. | Why the best answer is stronger than the closest distractor. |
| Repair | Repeat only missed or uncertain items after a short break. | The pattern behind misses, not the answer letter. |
| Transfer | Return to mixed practice once the topic feels stable. | Whether the same skill holds up when the topic is no longer obvious. |
Blueprint context: 15% of the practice outline. A focused topic score can overstate readiness if you recognize the pattern too quickly, so use it as repair work before timed mixed sets.
These questions are original Securities Prep practice items aligned to this topic area. They are designed for self-assessment and are not official exam questions.
Topic: Market Risk
An investment bank’s emerging-market bond desk assumes normally distributed daily returns. Its one-day 99% confidence interval for daily P&L is -£3m to +£3m. The desk is concentrated in three sovereign issuers, and after a geopolitical shock it records six daily losses below -£3m in 20 trading days. Which response is the single best one for the market risk team?
Best answer: A
What this tests: Market Risk
Explanation: Six breaches of a normal-based 99% P&L interval in only 20 trading days is a strong warning that returns may not be normally distributed. In a concentrated, shock-driven market, fat tails are more plausible, so the team should revisit the distributional assumption rather than just tweak the existing model.
This tests distribution analysis in market risk. A normal distribution has relatively thin tails, so extreme gains or losses are expected to be rare. Here, the desk has concentration risk and a geopolitical shock, then experiences six losses outside a normal-based 99% confidence interval in only 20 trading days. That pattern suggests the actual P&L distribution may be fat-tailed, meaning extreme losses are more likely than the normal model implies. The best response is to test a more appropriate distribution and recalibrate the tail estimate. Using more history or a higher confidence level may change the number reported, but neither fixes the core problem if the underlying distributional assumption is wrong. Confidence intervals are only as reliable as the model assumptions behind them.
Repeated losses outside a normal-based 99% interval suggest the P&L distribution has fatter tails than assumed, so tail estimates should be recalibrated.
Topic: Market Risk
A bank measures 1-day 95% VaR for the same portfolio in three ways.
If the portfolio value is £20 million and daily volatility is 1.5%, which option is correct?
Best answer: C
What this tests: Market Risk
Explanation: The method using volatility and a 95% z-score is parametric VaR, so the estimate is £20 million × 1.5% × 1.65 = £495,000. Replaying the last 250 actual market moves is historical simulation, while generating 10,000 model-based scenarios is Monte Carlo.
The core distinction is how each VaR approach produces the loss distribution. Parametric VaR assumes a statistical distribution and uses summary inputs such as volatility and a confidence-factor z-score. Here, the one-day 95% VaR is:
\[ \begin{aligned} \text{VaR} &= £20{,}000{,}000 \times 0.015 \times 1.65 \\ &= £495{,}000 \end{aligned} \]Historical simulation does not assume a distribution; it replays actual past market moves, so the analyst using the last 250 observed days is using that method. Monte Carlo VaR creates many hypothetical scenarios from a model of risk-factor behaviour, so the analyst generating 10,000 scenarios is using Monte Carlo. An answer showing £300,000 confuses one standard deviation of daily movement with a 95% VaR estimate.
X is parametric because it uses volatility and a z-score, giving £20,000,000 × 1.5% × 1.65 = £495,000, while Y uses past observations and Z uses simulated scenarios.
Topic: Market Risk
A UK fund reporting in GBP buys 2,000 shares in a US-listed oil producer at USD 40 each, financed partly by a USD 50,000 floating-rate loan.
After one month:
Which statement is most accurate?
Best answer: C
What this tests: Market Risk
Explanation: This is a foreign, commodity-linked equity position funded with floating-rate debt, so several market risks sit in one trade. The net position moves from USD 30,000 to USD 38,000, which translates from about £24,000 to £31,667, giving a gain of roughly £7,667 before interest.
A single position can carry several market-risk drivers at the same time. Here, the oil producer shares create equity risk, the producer’s sensitivity to oil prices adds commodity risk, the USD asset and USD loan translated into GBP create currency risk, and the floating-rate loan adds interest-rate risk.
So the simplified gain is about £7,667 before any loan interest. The key point is that one funded foreign equity holding can be exposed to multiple market-risk factors at once.
Net USD exposure rises from USD 30,000 to USD 38,000, which is about £24,000 to £31,667, and the position combines all four market risks.
Topic: Market Risk
A bank’s market risk team reviews daily returns for a trading portfolio.
Exhibit:
0.0%1.5%95% of days should fall within ±1.96 standard deviations of the mean1,000 trading days, 40 days had returns below -3.0%Which interpretation is most appropriate?
Best answer: B
What this tests: Market Risk
Explanation: A normal distribution with mean 0% and standard deviation 1.5% gives a 95% range of about -2.94% to +2.94%. In 1,000 days, only about 25 observations would be expected below the lower boundary, but 40 occurred. That points to more extreme losses than normal, consistent with a fat-tailed loss distribution.
This is a distribution analysis question: compare observed tail losses with what a normal distribution would predict. The lower edge of the 95% interval is approximately 0% - (1.96 × 1.5%) = -2.94%, so a return below -3.0% is just beyond that boundary. In a normal distribution, about 2.5% of observations should fall below the lower 95% boundary, so over 1,000 days you would expect about 25 such days. The portfolio had 40, which is materially higher.
-2.94%2540So the evidence suggests a fatter-than-normal loss tail, meaning a normal-based market risk measure could understate extreme-loss frequency.
40 breaches as normal mixes up the full 5% outside a two-sided 95% interval with the 2.5% expected in the lower tail only.Because -3.0% is roughly the lower 95% boundary, a normal distribution would imply about 25 such days, not 40, indicating a fatter loss tail.
Topic: Market Risk
Which statement best describes basis risk in a hedged position?
Best answer: A
What this tests: Market Risk
Explanation: Basis risk is the risk that a hedge is directionally right but still imperfect because the hedging instrument does not track the exposure exactly. The residual market risk comes from changes in the price difference or sensitivity between the two positions.
The core concept is imperfect offset. A firm may choose a hedge that generally moves in the same direction as the exposure, but if the prices do not change by the same amount, or their spread changes over time, the hedge leaves residual market risk. That residual mismatch is basis risk, and it commonly appears in cross-hedging, index hedging, or futures hedging where the hedge instrument is similar to, but not identical with, the underlying exposure.
Basis risk typically arises because:
So the key idea is not whether the hedge is directionally sensible, but whether it offsets the exposure closely enough in practice. Counterparty, funding, and liquidity issues are different risk types.
Basis risk arises when the relationship between the hedged item and the hedge instrument changes, leaving an imperfect offset.
Topic: Market Risk
A UK fund has the following position. Assume the hedge is exact and ignore credit risk.
Exhibit:
Which market-risk type best describes the fund’s main remaining exposure?
Best answer: B
What this tests: Market Risk
Explanation: The fund is long USD 5,000,000 through the ETF and short USD 5,000,000 through the forward, so its net currency exposure is zero. With the FX exposure hedged away, the Treasury ETF is mainly sensitive to changes in market interest rates.
The key is to identify the remaining price driver after netting the hedge. The ETF creates a USD exposure, but the forward sells the same USD amount, so the currency position is offset. Because the instrument is a US Treasury ETF, its value mainly moves with changes in US yields: rising yields typically reduce bond prices, and falling yields typically increase them.
So the main remaining market risk is interest rate risk, not foreign exchange risk.
The USD forward offsets the ETF’s currency amount, leaving the Treasury holding mainly exposed to movements in market yields.
Topic: Market Risk
A risk manager wants a measure showing how strongly a portfolio is expected to move when its market benchmark moves. Which measure is most relevant?
Best answer: A
What this tests: Market Risk
Explanation: Beta is the measure of an asset’s or portfolio’s sensitivity to movements in a market benchmark. It indicates the expected relative size and direction of the portfolio’s move when the market moves.
Beta measures systematic market exposure: how much a portfolio tends to change when the relevant market index changes. A beta above 1 suggests the portfolio usually moves more than the market, while a beta below 1 suggests lower sensitivity. In practice, beta is commonly estimated using regression of portfolio returns against benchmark returns, so it is a core tool in market-risk measurement and control.
This differs from other common measures. Alpha is the return not explained by market exposure, correlation shows the strength and direction of linear co-movement, and volatility measures standalone dispersion of returns. The key distinction is that beta focuses on sensitivity to the benchmark, not just variability or association.
Beta measures the sensitivity of a portfolio’s returns to movements in the benchmark or market factor.
Topic: Market Risk
An FX market maker is comparing manual hedging with an electronic auto-hedging system. Assume estimated market loss equals position size multiplied by the adverse price move.
| Measure | Manual hedging | Electronic hedging |
|---|---|---|
| Average unhedged position | £8,000,000 | £2,000,000 |
| Adverse FX move for comparison | 0.50% | 0.50% |
| One stressed rapid hedge order | — | £30,000,000 |
| Estimated price impact of stressed order | — | 0.20% |
Which statement is most accurate?
Best answer: D
What this tests: Market Risk
Explanation: Electronic trading reduces ordinary directional market risk here because the average unhedged FX position falls from £8,000,000 to £2,000,000, cutting loss on a 0.50% move from £40,000 to £10,000. But it can also amplify market loss in stressed conditions if a large hedge order hits a thin market and incurs £60,000 of price impact.
The core concept is that electronic trading can shrink one market-risk exposure while increasing another. Faster auto-hedging reduces inventory or directional exposure because the firm carries a smaller unhedged position for less time. Here, the comparison loss falls from £8,000,000 × 0.50% = £40,000 to £2,000,000 × 0.50% = £10,000, so routine directional risk is reduced by £30,000.
In stressed conditions, however, rapid electronic execution can create a larger price-impact loss if market depth is weak. The stressed hedge order is £30,000,000 and the estimated impact is 0.20%, so the potential loss is £60,000. The key takeaway is that electronic trading can reduce day-to-day directional exposure but amplify execution-related market loss when speed and size meet poor liquidity.
The routine loss drops from £40,000 to £10,000, while a £30,000,000 stressed order at 0.20% implies a £60,000 price-impact loss.
Topic: Market Risk
A bank uses a market-risk metric that starts with potential price moves and then adds the likely cost of unwinding a position quickly when market depth is limited and execution cannot be immediate without moving the price. Which tool best matches this description?
Best answer: C
What this tests: Market Risk
Explanation: Liquidity-adjusted Value at Risk is designed to reflect that actual losses can be higher when positions must be exited in thin markets. Limited depth and weak immediacy increase bid-offer costs, price impact, and liquidation time, so a simple frictionless market-risk measure may understate exit losses.
The core concept is market liquidity risk within market risk. Liquidity-adjusted Value at Risk takes a standard potential-loss estimate and adds the effect of trading frictions such as limited market depth, wider bid-offer spreads, and longer liquidation horizons. These matter because a firm may be unable to sell quickly at the last quoted price; trying to exit size in a thin market can push the price further against the seller and increase the realised loss.
Other market-risk tools may measure tail loss, impose controls, or validate models, but they do not specifically capture the cost of forced unwinding in illiquid conditions.
It extends a standard loss estimate by incorporating liquidation costs caused by poor market depth, wider spreads, and slower execution.
Topic: Market Risk
A firm implements a control that automatically passes trade details from order entry through confirmation and settlement, reducing manual re-keying and failed trades. The control is intended to address execution failure rather than losses from market-price movements. Which control best matches this description?
Best answer: B
What this tests: Market Risk
Explanation: Straight-through processing automates the trade lifecycle from order entry to settlement. That primarily reduces operational and execution failures such as mis-booking, delayed confirmation, or failed settlement, not losses caused by adverse asset-price movements.
The key distinction is between market risk and execution failure. Market risk arises when the value of a position changes because prices, rates, spreads or foreign exchange move. Execution failure arises when the intended trade is not captured, confirmed or settled correctly.
A control that removes manual hand-offs and re-keying across the trading process is therefore designed to reduce failed or inaccurate execution. Straight-through processing does this by automating trade capture and downstream processing. By contrast, tools such as Value at Risk, diversification and stop-loss limits are used to measure or constrain exposure to price changes during or after position-taking.
The closest distractors are market-risk tools, but they do not primarily fix booking or settlement failures.
Straight-through processing reduces mis-booking and settlement errors across the trade lifecycle, so it targets execution failure rather than asset-price risk.
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