This segment delves into the topic of standard deviation in ways besides the usual options related concepts and way beyond a normal distribution pattern. Knowledge increases confidence and increased confidence leads to better decisions.
Jacob Perlman begins by mentioning the standard deviation (SD) of a normal distribution pattern. That's the bell curve with which most of us are familiar. Standard deviation for an underlying goes well beyond that and Jacob explains it and reviews the math (which is all on slides).
The discussion then progresses to options and SD's role regarding options. He further explains that options pricing models (eg. Black-Scholes) are descriptions for the movements of underlyings that allow for the mean payoff from an option to be computed. These can be used to compute standard deviations for the value of an underlying, but it’s rare that there will be a closed form solution. What we can do is use (options) Greeks. They come from a pricing model and can give a good approximation to the risk for an option. Jacob then explains the math and displays the calculation on a slide.
Jacob then introduces the concept of the standard deviation of a portfolio. Given a collection of various assets, even if the standard deviation for each can be computed, it can be hard to judge your total risk. Jacob explains this concept and mentions how last week’s segment on correlation has information that applies here, in particular how strong negative correlation between long and short options on the same underlying can lower the SD of your portfolio
Watch this segment of “The Skinny on Options Math” with Tom Sosnoff, Tony Battista and tastytrade's Math Genius, Jacob Perlman for an in depth discussion of standard deviation that goes beyond the usual.