Financial Risk Manager Part 1
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During a statistical test to determine if the mean return on an asset is different from zero, an FRM Part 1 candidate obtains a p-value of 1.4%. With a significance level of 1%, she would:
Explanation:
Explanation
In statistical hypothesis testing:
- P-value (1.4%): The probability of observing a result as extreme as, or more extreme than, the observed result if the null hypothesis were true
- Significance level (1%): The threshold set by the researcher for rejecting the null hypothesis
Decision Rule:
- If p-value ≤ significance level → Reject null hypothesis
- If p-value > significance level → Fail to reject null hypothesis
Since 1.4% > 1%, the candidate would fail to reject the null hypothesis.
Why Other Options Are Incorrect:
A. Reject the null hypothesis - Incorrect because p-value (1.4%) > significance level (1%)
C. Conclude that the mean return is different from zero - Incorrect because failing to reject the null hypothesis means we don't have sufficient evidence to conclude the mean is different from zero
D. Conclude that the mean return is negative - Incorrect because the test only determines if the mean is different from zero, not the direction of the difference
Key Takeaway:
A p-value greater than the significance level indicates insufficient evidence to reject the null hypothesis, meaning we cannot conclude the mean return is statistically different from zero.