CAT 2025 Slot 1 · VARC · Question 4

CAT 2025 Slot 1 previous year question on Strengthen and Weaken Arguments, with the answer and a step-by-step solution.

Strengthen and Weaken ArgumentsVerbal AbilityMultiple choiceMedium

RC passage 1: Complex Systems, Noise and Tail Events — this question belongs to a set. Read the full set with all 4 questions →

The passage below is accompanied by four questions. Based on the passage, choose the best answer for each question.

Understanding the key properties of complex systems can help us clarify and deal with many new and existing global challenges, from pandemics to poverty . . . A recent study in Nature Physics found transitions to orderly states such as schooling in fish (all fish swimming in the same direction), can be caused, paradoxically, by randomness, or 'noise' feeding back on itself. That is, a misalignment among the fish causes further misalignment, eventually inducing a transition to schooling. Most of us wouldn't guess that noise can produce predictable behaviour. The result invites us to consider how technology such as contact-tracing apps, although informing us locally, might negatively impact our collective movement. If each of us changes our behaviour to avoid the infected, we might generate a collective pattern we had aimed to avoid: higher levels of interaction between the infected and susceptible, or high levels of interaction among the asymptomatic.

Complex systems also suffer from a special vulnerability to events that don't follow a normal distribution or 'bell curve'. When events are distributed normally, most outcomes are familiar and don't seem particularly striking. Height is a good example: it's pretty unusual for a man to be over 7 feet tall; most adults are between 5 and 6 feet, and there is no known person over 9 feet tall. But in collective settings where contagion shapes behaviour – a run on the banks, a scramble to buy toilet paper – the probability distributions for possible events are often heavy-tailed. There is a much higher probability of extreme events, such as a stock market crash or a massive surge in infections. These events are still unlikely, but they occur more frequently and are larger than would be expected under normal distributions.

What's more, once a rare but hugely significant 'tail' event takes place, this raises the probability of further tail events. We might call them second-order tail events; they include stock market gyrations after a big fall and earthquake aftershocks. The initial probability of second-order tail events is so tiny it's almost impossible to calculate – but once a first-order tail event occurs, the rules change, and the probability of a second-order tail event increases.

The dynamics of tail events are complicated by the fact that they result from cascades of other unlikely events. When COVID-19 first struck, the stock market suffered stunning losses followed by an equally stunning recovery. Some of these dynamics are potentially attributable to former sports bettors, with no sports to bet on, entering the market as speculators rather than investors. The arrival of these new players might have increased inefficiencies and allowed savvy long-term investors to gain an edge over bettors with different goals. . . .

One reason a first-order tail event can induce further tail events is that it changes the perceived costs of our actions and changes the rules that we play by. This game-change is an example of another key complex systems concept: nonstationarity. A second, canonical example of nonstationarity is adaptation, as illustrated by the arms race involved in the coevolution of hosts and parasites [in which] each has to 'run' faster, just to keep up with the novel solutions the other one presents as they battle it out in evolutionary time.

Which one of the following observations would most strengthen the passage's claim that a first-order tail event raises the probability of further tail events in complex systems?

A
In epidemic networks, initial super-spreading episodes are isolated spikes after which outbreak sizes match the baseline distribution from independent contact models across comparable cities with no rise in the frequency or size of later extreme clusters.
B
After a major equity crash, researchers find dense clusters of large daily moves for several weeks, with extreme days occurring far more often than in normal circumstances for assets with customarily low volatility profiles.
C
River discharge records show water levels fit a normal distribution with thin tails that match laboratory data, regardless of storms or floods.
D
Following large earthquakes, regional seismic activity returns to baseline within hours with no aftershock sequence once data are adjusted for reporting effects, which suggests independence across events rather than any elevation in subsequent tail probabilities.

Pick an option, then check.

Answer & solution

Answer: Option B

The claim to strengthen is the second-order tail event idea: once one extreme event happens, further extreme events become more likely. Evidence that strengthens it must show clustering of extremes after a first extreme.

Option 2 does exactly that – after a major equity crash, large daily moves cluster densely for weeks, and extreme days occur far more often than usual. The phrase 'for assets with customarily low volatility profiles' makes it stronger still, because even calm assets start throwing up extremes.

Option 1 says super-spreading episodes are isolated spikes with no rise in later extremes. That is evidence against the claim.

Option 3 says the distribution is normal with thin tails irrespective of storms. This weakens the whole heavy-tail framework, let alone the second-order claim.

Option 4 says there is no aftershock sequence and that events are independent. Independence is precisely what the claim denies, so this weakens it. Note that the passage itself offers aftershocks as an example of second-order tail events, so an option denying aftershocks cannot strengthen it.

Shortcut: three of the four options here contain a reversal marker – 'isolated', 'returns to baseline', 'normal distribution with thin tails'. Only one option describes clustering, and clustering is the signature of the claim. Pick it without weighing the rest.

Hence, the answer is option 2.

CAT 2025 Slot 1 · VARC · Question 4

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