In the Land Shark auction model, what outcome is estimated by running simulations across many trials?

• A. The count of bidders in each trial.
• B. The distribution of possible winning bid values.
• C. The probability of winning for a given bid.
• D. Whether Land Shark wins the auction and its net return.

Answer: (D)

Monte Carlo simulations in an auction setting are used to estimate the actual payoff outcome Land Shark would experience across many possible worlds. In each trial you simulate the random elements—how other bidders behave, what Land Shark bid, and whether Land Shark wins—and you compute the net return if a win occurs (or zero if it doesn’t). After many trials you obtain the distribution of win/lose outcomes and their associated net returns, which lets you estimate expected profit, risk, and the probability of winning. While you could extract related quantities like the distribution of winning bid values or a bid-specific winning probability, the quantity most directly estimated by running many trials is whether Land Shark wins the auction and what its net return is.