The sample kurtosis here refers to the (non-excess) kurtosis coefficient computed from the fourth central moment divided by the square of the second central moment. In FRM Part 1 contexts (and many exam-style questions), this is typically calculated as:

(Note: This is equivalent to using the sample standard deviation in the denominator after adjusting for the population-style moments with divisor n.)

Step-by-step calculation:

1. Sample standard deviation $s = 5.287\% = 0.05287$.
   Sample variance $s^2 = (0.05287)^2 = 0.0027952369$.

2. Sum of squared deviations:
   $\sum (r_t - \bar{r})^2 = (n-1) \times s^2 = 358 \times 0.0027952369 \approx 1.00069481$.

3. Given: $\sum (r_t - \bar{r})^4 = 0.0026$.

4. Plug into the formula:

   $$\text{Kurtosis} = \frac{359 \times 0.0026 }{ (1.00069481)^2 } \approx \frac{0.9334}{1.00139} \approx 0.932$$

   (Slight differences may appear due to rounding of the given mean and standard deviation, but it rounds to 0.93.)

This value < 3 indicates the distribution is platykurtic (thinner tails than a normal distribution).

Correct answer: A: 0.93