Problem

In $10,000$ simulated trials, A has mean $+\$1.20$, loss rate $0.42$, worst $-\$20$; B has mean $+\$0.35$, loss rate $0.30$, worst $-\$5$. Compare return and downside, then state the Monte Carlo and decision-criterion limits.

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What this problem is really about

Read a simulation comparison in separate columns: average return, frequency of loss, severity of loss, and reliability of the estimates. One strategy can lead on return while another leads on downside, so no overall ranking follows without a tradeoff rule. A large run helps, but missing Monte Carlo errors or replications still limits claims about precision.

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B has higher mean despite $.35<$1.20 and lower downside; declare B the overall winner without a criterion or Monte Carlo uncertainty.

A has higher mean and also lower downside, incorrectly reversing its .42 loss rate and -$20 worst result; declare A the overall winner with exact estimates.

A has higher mean while B has lower downside, but claim 10000 trials make the difference exact and select A without a stated criterion.

A has higher mean return, while B has lower downside. The run is large but Monte Carlo uncertainty is unreported, so no overall winner follows without a criterion.

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In \(10,000\) simulated trials, A has mean \(+\$1.20\), loss rate \(0.42\), worst \(-\$20\); B has mean \(+\$0.35\), loss rate \(0.30\), worst \(-\$5\). Compare return and downside, then state the Monte Carlo and decision-criterion limits.

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