Click here to download all the VXZ, and 4th up until the 7th VIX futures and their associated contango and backwardation data since 2004. Note that the data was updated on May 22 2017 13:20:56 (California Time).
The calculated VXZ price is modeled based on VIX futures data. This allows to obtain the price of the VXZ since the VIX futures started trading (2004/march) until now. The price model can also be used to forecast future VXZ data based on VIX futures prices.
This is the model used to generate the data:
 For any given day n, calculate R(n) as the return that you would get by holding a combination of 4th, 5th, 6th and 7th VIX futures from day (n-1) to day n.
Note that the VXZ price is calculated quite similarly as the VXX as explained here. In the VXX case 2nd month VIX futures contracts are bought with the proceeds of selling 1st month ones. In the VXZ case, 7th month futures are bought with the proceeds of selling 4th month ones. At all times a basket of 4th, 5th, 6th and 7th vix futures contracts are present, a basket which in average represents a mid term volatility future between the 5th and the 6th month. That amount of futures and their respective values define the price of the VXZ
 Apply VXZ’(n+1) = VXZ’(n) + VXZ’(n) x R(n+1)
Take as initial value the market value adjusted for splits of the VXZ on its first trading day: VXZ’(1)=107.98
 Calculate the daily tracking error, F, by solving:
VXZ(n+1) = VXZ’(n+1) x F
With border conditions:
VXZ’(N)= Market price of the VXZ on the last trading day (N = day of the last close).
The estimated VXZ’ model, based only on  gives slightly different values than the market prices. That difference with respect to the market data is used to calculate the tracking error.
This is how the model and the data looks like. Note that the graph was made with info up to the 22nd August 2014 but the downloadable spreadsheet has updated data :
Looking at the data you can see that in low volatility periods the VXZ goes down. The high volatility periods during 2008/2009, 2010 and 2011 are clearly seen on the VXZ spikes. The VXZ is like a less extreme version of the VXX but at the same time both funds are correlated. The VXZ has much less extreme movements than the VXX. That smaller volatility is maybe why some like to use the VXZ for trading.
The VXZ had a long fall since 2004 up until 2007, it's value more than halved from around 85 to under 40. During the 2008/2009 crisis it basically trippled reaching almost 120. Since then it has fallen a lot in an irregular and risky way, interrupted by significant spikes in the years 2010 and 2011.
If you want to calculate new VXZ values you will have to implement the formulas inspired by what I explained here or by using the model definition above. It is ideal if you can implement how to calculate the data in order to have a better understanding of the VXZ dynamics. The VXZ historical prices are available from yahoo finance. The VIX future prices are available at the CBOE website. You can use them to keep on updating the model since I may not update it regularly. In case you are interested in the more extreme VXX data you may find it here.
You may not have the time or inclination to implement the pricing formulas or you may want future VXZ forecasts based on VIX futures values. I sell for 45 US$, or its equivalent on any currency accepted by paypal, the same spreadsheet with a data model for historical and future forecasted data. It includes:
1) Pricing formulas.
2) Forecast future values based on VIX futures values, with random market noise to see different outcomes.
3) Latest data update, and future updates if you don’t manage to do them.
4) Mid term VIX futures (4th to the 7th), contango and backwardation data up to 2004.
5) Support on forecasting, modelling and updates.
Besides the historical and modelling data it has the advantage that you can understand how the mid term VIX futures determine the VXZ price. You may also use it to make forecasts of how the VXZ could behave since it includes VXZ prices based on VIX futures values, with which you can play with, to estimate what the VXZ price will be depending on different scenarios.
You can make the payment via paypal to my email [email protected] or with the button below. Via the paypal payment button, in addition to allow you to use paypal, you may also chose cards such as visa, master, american express, discover or maestro. You may pay in dollars or the equivalent amount in the supported currency of your choice. Once paid I will be notified by email and I’ll send you the excel spreadsheet with the latest data and the formulas. I’ll gladly give you e-mail support if you need it. You may request an invoice by email if you specify it before or during the payment process.
Here below is the button to buy in US dollars:
And here is the paypal button in Euros for those who prefer to pay in that currency:
Alternatively if you are in Europe you can send a transfer, free among EU members, for the equivalent amount to my European bank account (ask me if you want it).
Note that if you trade both the VXZ and the ZIV I sell both for 75 US dollars, or the equivalent on any currency accepted by paypal. That would be cheaper than buying them separately for 90 US$ (45 each). In case you are interested in short term volatility funds, besides the VXX model mentioned above I have also a model for the XIV for sale, as well as a UVXY, a SVXY and a TVIX model. The more models that you buy the less you pay, for example if you buy all the four mid term volatility models (VXZ+ZIV+VIIZ+TVIZ) you pay 100 US$, less than the 45x4 = 180 US$ that you would pay by buying them separately.
Originally I implemented the VXX pricing model after I shorted the VXX in August 2011 and panicked when I realised I hardly knew how it was priced. Acquiring the knowledge gave me the strength to hold and turn a badly losing trade into a handsome profit. I still trade the VXX up until today. Having done it initially for myself I was surprised to see many people adopting it. Some among them who trade with other volatility funds asked me about their price models or how the funds they traded would have behaved in the past. I thought about it sometimes a bit but never allocated time to develop them because initially I preferred shorting the VXX. I finally did it when someone offered to pay for them and when I decided to start trading them myself.
The models are basically a tool you can use as a platform for your own research and a guide to feel more confident and under control with your trading !
Anyone else interested in sharing modelling or trading ideas feel free to contact.
Hope this data is useful and if you find any interesting patterns by analyzing it please do not doubt to let me know !
PD1 -> How is Contango/Backwardation calculated and why does it affect the VXZ ? That is answered in the VXX blog post where it says PD4, basically the same is applied to VXZ with the difference that in this case contango is a measure of the spread between the 7th and the 4th VIX future. Since when in contango the 7th future is more expensive than the 4th, and since 4th month vix futures are sold to buy the 7 month ones then the amount of contracts tends to be reduced while in contango. That is because under contango selling one 4th month future is not enough to buy a 7 month one. The opposite effect happens while in backwardation, which leads to the increase of the amount of futures which is a tailwind to the VXZ price.
PD2 -> Why does the calculated data change as more data becomes available ?
That’s due to the way that the model is designed to learn from available market data and extrapolate. All the calculated data changes depending on the amount of market data that the model learns from. Not only does the first 2004 calculated value change but all of them do.
I could fix an initial 2004 value arbitrarily choosing it. But that would be probably an error since you can at most estimate it with ever growing and changing available data. That makes that initial value a variable too. At most you can calculate it by learning from the available market values.
Differences in calculated values happen every day. They are normal because the data is calculated all the way back to 2004 by taking into account all the available market data since the VXZ started trading up until the last available market value. The model fixes the 1st and last available VXZ market values and uses all the VIX futures market values in between to calculate the VXZ and project it back to 2004 or into the future (see the VXZ model definition above).
For example from 2009 to 2012 there is one less year of data than from 2009 to 2013. So it's normal that the calculated values, including the first calculated value, on both cases differ.
The changes may look big and concerning but they are actually small if you consider that the annualized percentage change of the VXZ in both cases is almost the same.
You can also graph different series of calculated data taken in different periods and you will notice slight differences. No calculated data series is better than another, that depends on the market data quality. Most probably the more market data that you feed the model the better that the calculated data will be, since in such case the model will use more information to learn from.