As amateur painters train and develop into masters, a good portion of their ability to improve comes with a better understanding of the tools they need to produce masterpieces.
Experimenting with a wide range of paints, brushes, and canvases ultimately helps a master like Vincent van Gogh select the precise instruments for a given project.
For traders, the elevation of our skill level is much the same, in that our experience with a wide range of strategies, across varied market environments, can help us select the most optimal position for a given set of circumstances.
Here at tastytrade, we are constantly trying to tweak our perspective on the financial markets in order to uncover new kernels of research, which we ultimately hope will assist traders in their endeavors.
In that spirit, a recent episode of Market Measures may be worth a few moments of your time. On this installment of the series, the hosts present new internal research focusing on the average moves (up and down) in implied volatility for some of the best-known trading vehicles in the volatility universe.
Listed below are the eight symbols included in the study, as well as the associated implied volatility products for each:
As you can see in the chart above, the study presented on Market Measures explores some of the most important segments of the financial markets - including equity indexes and commodities.
Specifically, the study sought to better understand how implied volatility behaves in those eight symbols, by examining how much implied volatility moves on average in a given month. For traders that are banking on a reversion in the volatility mean, this may help them better frame their expectations.
In order to produce these findings, a backtest on all eight symbols was run with the following parameters:
Utilized 8 different volatility products (listed above)
Subdivided and analyzed rallies and contractions in implied volatility for each
Calculated average monthly % moves in implied volatility for each
Used data from 2011 to present
Given what we know about the relative performance of short premium strategies versus long premium strategies (on average), the results of this analysis were slightly surprising.
As you can see below, the average monthly up move in implied volatility across all eight products was higher than the average monthly down move. This may be attributable to the fact that upswings in volatility tend to be larger in magnitude, due to the power of fear which materializes during selloffs. In contrast, declines in volatility tend to be more gradual.
A graphic presented later on the show illustrates another important point - that the increase and decrease in implied volatility for the products associated with equity indexes was on average higher than commodities.
In this case, that difference is likely attributable to the fact that implied volatility for commodities "lives" at higher levels - meaning it's already inflated relative to actual volatility (i.e. richer premium at "normal" levels).
The main takeaway, however, relates to the first slide, which should help traders gain better context on how much implied volatility could theoretically increase or decrease from the inflated/depressed level at which a trade is initiated.
Of course, these should only serve as rough guidelines, and not concrete expectations - given that the above numbers are averaged out over numerous occurrences.
On the balance of the show, the hosts walk viewers through an even more detailed breakdown of the findings, and we recommend watching the complete episode of Market Measures focusing on the average up and down moves in implied volatility when your schedule allows.
If data such as this intrigues you, a recent installment from the Skinny Series focused on "Negative Drift" is also worth reviewing.
If you have any questions or feedback on any of these topics, please don't hesitate to leave a message in the space below, or reach out directly at email@example.com.
We look forward to hearing from you!
Sage Anderson has an extensive background trading equity derivatives and managing volatility-based portfolios. He has traded hundreds of thousands of contracts across the spectrum of industries in the single-stock universe.
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