Skewness measures the asymmetry of the return distribution. A negative skewness value, such as -1.5, indicates that the left tail (negative returns) of the distribution is longer or fatter than the right tail (positive returns). This suggests that there is a higher relative probability of observing negative returns compared to what would be expected under a normal distribution, which is symmetric. In this case, the negative skewness implies a higher chance of experiencing extreme negative returns, making option A the correct interpretation.