Since Implied Volatilities can be used to calculate the market’s expected move of the S&P 500, we wanted to place some probabilities around how often the market actually falls within (or outside) these expectations. Typically, we will look to use the VIX in order to calculate the expected move for the next 30 days and have shown this to be a very accurate measure. We have also found that Implied Volatility is often overstated, and is one of the reasons that we are primarily premium sellers.
We have also previously shown that there are a number of different volatility indices that can be used for different periods of time. These include a 9-day (1 week) index called VXST, a 3-month index called VXV and a 6-month index called VXMT. Since these indices are looking at different time periods, we can use these values for our calculations in order to get a more accurate representation of the expected move for our chosen duration. However, are these indices really more accurate?
Today, Tom Sosnoff and Tony Battista look to see how often the actual move lies within the expected move predicted by the indices for the different time periods. The guys find out that while all of the indices overstated the actual move, the further out in time (VXV and VXMT) the more accurate the estimate was. This means that the longer duration indices overestimated the actual move more often. This is a large part of our trading strategy, so it’s important to know how reliable these calculations are.
It’s also important to know why Implied Volatility generally tends to overstate actual volatility. Implied Volatility is sometimes called a “fear index” because it typically spikes when uncertainty occurs (meaning far more premium is built into the option’s price due to demand). Sellers of options take this risk from buyers (who are seeking safety) and would therefore expect to be compensated. Fear, however, is rarely rational – markets generally make understated price moves. This makes actual price moves less than the market’s expectations. This is another reason why longer-term time spans tend to be more accurate and shorter-term predictions have much more variance (i.e. they tend to be more volatile).
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