Skew | Normal Distribution | Positive | Negative 


What is Skewness?

Skewness is a measure of the symmetry/asymmetry of the frequency distribution of a random variable (like price). Skew is also the correlation between Implied Volatility and Direction.

Most retail traders assume that because probability appears as a graph in your trading platform as an equally shaped cone that the distribution is "Normal". Not so.  

How do you check that the underlying has a Positive, Negative or Dual Skew?

Open up the options chain. Then, compare from the lower strike price to the higher strike price what the readings on the Implied Volatility for Calls and Puts are.  Here's the relationship:

❑  Positive Skew: As strike prices increase, Implied Volatility of both Calls & Puts rises higher.
❑  Negative Skew: As strike prices increase, Implied Volatility of both Calls & Puts falls lower.
❑  Dual Skew: Presence of Positive and Negative skews as strike prices increase/ decrease.

Why must you be aware of what the Skew does to the pricing of Calls and Puts?


You always want to be in position to

❑  Sell the strike with the Higher IV and buy the strike with the Lower IV and not the reverse.  Be on the correct side of where the Skew makes IV rise to or fall from.

❑  Buy Calls or Puts when they are not in demand, to profit as their prices rise.

❑  Sell Calls or Puts when they are in demand, to profit as their prices fall.


An easy way to remember “Positive” and “Negative” Skews is to look at the tail of the graph along the horizontal axis or X-axis. 
❑  If the tail is longer towards zero and more negative, it is a Negative Skew. 
❑  If the tail is longer away from zero and more positive, it is a Positive Skew. 
See below right pagelets for how changes in Skew affects the Density of Probabilities, thereby impacting Call prices vis-à-vis Put prices. 
Recall the 3 Measures of Central Tendency

❑  Mode is the most frequently occurring number (happens the most often) by a random variable – such as price – within a given Standard Deviation.


❑  Mean (arithmetic mean) is the sum of all price observations within the Standard Deviation, divided by the count of all price observations within the Standard Deviation.
❑  Median, assumes an even amount of price observations within the Standard Deviation.  It is computed using the mean of the two numbers in the middle of a given Standard Deviation. The median is the mid-point that separates 50% of the higher half of a Standard Deviation as price rises, from 50% of the lower half of the Standard Deviation as price falls.