Does anyone know why left skewed is bad and creates a higher probability of negative returns than positive returns?
Hi, because there is a higher probability of large negative returns. A risk manager is more concerned about this. Regards Bart
Its because the tail extends out to the left thicker than it does to the right. Since the distribution extends infinitely out in both directions, it is actually much thicker out the left than it is the right. Most of the data to the right of the mean are concentrated close to the mean, with a very low probability of points far out from the rights, while the left side of the mean has far less data points clustered immediately to teh left of the mean, and a lot more points to the far left of the mean. Therefore, high probability of large negative returns (from the mean).
The distributions are loss distributions. Look at the picture of one.
On the y-axis you have probabilities of loss, and on the x-axis you have beginning from ‘Zero’ till a certain point/mean -" Expected Losses/ Mean Loss" and beyond that point/mean, i.e. further towards the right side of that point/mean, “Unexpected losses.”
A left-skewed distribution has a smaller and longer left tail till the mean and while moving to the right side of the mean, the belly of the curve becomes bigger, i.e. the area under the curve is bigger. This denotes that the probability of a loss is bigger beyond the mean and still worse, it is an unexpected loss.
Hope it helped!!