This post is very long so, for the full in-depth post you can click here. You can also get diagrams there.
The VIX is a volatility index that shows what the market expects 30-day volatility to be. It is calculated through the implied volatility on S&P 500 Index options. The VIX typically has a negative correlation to the overall stock markets, i.e. when the S&P 500 increases, VIX decreases.
How can it be used? As this is a product that is “forward looking” we can try to gauge where it will be in the short-term.
How does the VIX move?
Looking at data from 2004 to make assumptions.
Present fear of future uncertainty is over-stated. What do I mean by this? People’s fear of what the future might hold is always exaggerated. Do you remember the time you were going to go on your first date and you were petrified you would find a way to ruin it? Well it most likely didn’t end up that bad and you probably went on many more; unless you were scarred for life. This fact applies to us all around the world and in particular, the financial markets.
Granted, there are exceptions to this for example extremely low volatility environments.
If you were to look at the VIX price on a chart you will see that there is a current (spot) price and a “future” price. The “future price” is inclining and this is partly because the further out we go the more uncertainty there is. As we start getting closer to that future date the price gets closer to the spot price as the fear starts to subside. Imagine point 6 moving to point 5, point 5 moves to point 4 and so on.
Data from 2004 – 2017
We obtained data from 2004 through to 2017 and looked at some of the important data that included VIX open, close, high and low for each day.
The first set of data we looked at was the average percentage increase/decrease each day. This was done by taking the close of each day, subtracting the open, dividing it by the open and then multiplying by 100.
For example;
(C – O) / O * 100
15 – 13 / 13 * 100 = 15.38% increase
* Using all of the data points since 2004, the average change each day was -0.42%.
We then looked at the distribution of VIX highs each day to see the highest points. We discovered;
. Very few highs occurred under 10
. The majority were between 10 and 20
. From 20 – 80+ we saw a significant decrease in the number of occurrences.
Furthermore the probabilities of the price being x are listed below.
10+ Occurs 99.99855%
20+ Occurs 34.94%
30+ Occurs 9.54%
40+ Occurs 4.67%
50+ Occurs 2.03%
60+ Occurs 1.04%
70+ Occurs 0.46%
80+ Occurs 0.18%
How Can The Above Data Be Used In Decision Making?
As we know that on average the VIX declines in value by -0.42% we can factor that into our decision making. Let’s use an example to illustrate this; John is looking for a security he can put $250,000 into and has two options 1. VIX options (a volatility product) or 2. the S&P 500.
VIX options on average lose -0.42% a day and the S&P 500 gains 0.04% a day. Straight away the S&P 500 looks a lot more attractive than the VIX. Although the daily gains in the VIX tend to be a lot bigger, the overall decay will eat away at your profits. So how can traders and investors make money from VIX? By trading VIX options when the prices reach a point considered overvalued.
As we also know that the average price of VIX from 2004 – 2017 is around 18.75 and assume that the VIX price is mean reverting we can determine prices significantly under 18.75 are undervalued and prices significantly over 18.75 are overvalued. This then begs the question, how do you determine what is significantly overvalued and what is not. POST CONTINUED IN IDEA UPDATES
The VIX is a volatility index that shows what the market expects 30-day volatility to be. It is calculated through the implied volatility on S&P 500 Index options. The VIX typically has a negative correlation to the overall stock markets, i.e. when the S&P 500 increases, VIX decreases.
How can it be used? As this is a product that is “forward looking” we can try to gauge where it will be in the short-term.
How does the VIX move?
Looking at data from 2004 to make assumptions.
Present fear of future uncertainty is over-stated. What do I mean by this? People’s fear of what the future might hold is always exaggerated. Do you remember the time you were going to go on your first date and you were petrified you would find a way to ruin it? Well it most likely didn’t end up that bad and you probably went on many more; unless you were scarred for life. This fact applies to us all around the world and in particular, the financial markets.
Granted, there are exceptions to this for example extremely low volatility environments.
If you were to look at the VIX price on a chart you will see that there is a current (spot) price and a “future” price. The “future price” is inclining and this is partly because the further out we go the more uncertainty there is. As we start getting closer to that future date the price gets closer to the spot price as the fear starts to subside. Imagine point 6 moving to point 5, point 5 moves to point 4 and so on.
Data from 2004 – 2017
We obtained data from 2004 through to 2017 and looked at some of the important data that included VIX open, close, high and low for each day.
The first set of data we looked at was the average percentage increase/decrease each day. This was done by taking the close of each day, subtracting the open, dividing it by the open and then multiplying by 100.
For example;
(C – O) / O * 100
15 – 13 / 13 * 100 = 15.38% increase
* Using all of the data points since 2004, the average change each day was -0.42%.
We then looked at the distribution of VIX highs each day to see the highest points. We discovered;
. Very few highs occurred under 10
. The majority were between 10 and 20
. From 20 – 80+ we saw a significant decrease in the number of occurrences.
Furthermore the probabilities of the price being x are listed below.
10+ Occurs 99.99855%
20+ Occurs 34.94%
30+ Occurs 9.54%
40+ Occurs 4.67%
50+ Occurs 2.03%
60+ Occurs 1.04%
70+ Occurs 0.46%
80+ Occurs 0.18%
How Can The Above Data Be Used In Decision Making?
As we know that on average the VIX declines in value by -0.42% we can factor that into our decision making. Let’s use an example to illustrate this; John is looking for a security he can put $250,000 into and has two options 1. VIX options (a volatility product) or 2. the S&P 500.
VIX options on average lose -0.42% a day and the S&P 500 gains 0.04% a day. Straight away the S&P 500 looks a lot more attractive than the VIX. Although the daily gains in the VIX tend to be a lot bigger, the overall decay will eat away at your profits. So how can traders and investors make money from VIX? By trading VIX options when the prices reach a point considered overvalued.
As we also know that the average price of VIX from 2004 – 2017 is around 18.75 and assume that the VIX price is mean reverting we can determine prices significantly under 18.75 are undervalued and prices significantly over 18.75 are overvalued. This then begs the question, how do you determine what is significantly overvalued and what is not. POST CONTINUED IN IDEA UPDATES
In order to see what is overvalued we can look at standard deviations. Standard deviations show how certain data points differ from the mean of those data points. In this case a 1 standard deviation would contain roughly 68% of the data points. 2 standard deviations would contain 95% and 3 standard deviations would contain 99.7%. So from this we know that if prices go into the 2 or 3 standard deviation bracket, we could see the next data points move back into that 1 standard deviation bracket. Please keep in mind though, VIX when it starts to increase in value does so at a phenomenal speed.
Finally, the data on daily VIX highs and daily VIX closes. The reason I have looked at this data is because we know the VIX loses an average of -0.43% a day. As we know it declines each day, it makes sense for us to identify the best opportunities to sell volatility. To do this I have taken a stance that it is better to sell into strength and buy into weakness, or better known as buy low and sell high. In order to find the best time to “sell high” I calculated what each high was on the daily VIX and then what it actually closed at that same day.
The average high to close was -4.465%, this means price got up to a certain level and then declined to close lower. To visualize this I have created a distribution graph. (You will have to go to the site to see the diagram).
So from this data you can make the assumption that selling volatility (VIX) is better when trading significantly over 18.75. To aid the selling of volatility you can also consider how much the VIX index is up on that day. If it has significantly increased in value, it would make sense to sell now.