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FRM Part II · FRM Exam Part II · Advances in Artificial Intelligence: Implications for Capital Markets Activities

A quant tests a classifier that flags manipulative trading. In a test set of 1,000 orders, 50 are truly manipulative. The model flags 40 orders, of which 30 are truly manipulative. What are the model's precision and recall?

Precision is 75% and recall is 60%. Of 40 flagged orders, 30 were truly manipulative, giving 30/40 precision. Of 50 actual manipulative orders, the model caught 30, giving 30/50 recall. Using the wrong denominators would swap or distort these figures.

  1. APrecision 75%, recall 60%Correct
  2. BPrecision 60%, recall 75%
  3. CPrecision 75%, recall 3%
  4. DPrecision 97%, recall 60%

Explanation

True positives = 30. Precision = TP / flagged = 30/40 = 75%. Recall = TP / actual positives = 30/50 = 60%. Swapping the denominators gives the 60%/75% distractor; 97% would be accuracy-like thinking (not even exact), and 3% divides by 1,000.

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