ZIV historical data and pricing model since VIX futures are available (2004)

Click here to download all the ZIV, and the 4th up until the 7th VIX futures and their associated contango and backwardation data since 2004. Note that the data was updated on November 19 2014 19:16:20 (California Time).

The calculated ZIV price is modeled based on VIX futures data. This allows to obtain the price of the ZIV since the VIX futures started trading (2004/march) until now. The price model can also be used to forecast future ZIV data based on VIX futures prices.

This is the model used to generate the data:

[1] For any given day n, calculate R(n) as the return that you would get by shorting a combination of 4th, 5th, 6th and 7th VIX futures from day (n-1) to day n.

Note that the ZIV 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 ZIV case, 4th month futures are bought with the proceeds of selling 7th month ones. At all times a basket of shorted 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 basket of futures and their respective values define the price of the ZIV

[2] Apply ZIV’(n+1) = ZIV’(n) + ZIV’(n) x R(n+1)
Take as initial value the market value adjusted for splits of the ZIV on its first trading day: ZIV’(1)=12.3

[3] Calculate the daily tracking error, F, by solving:
ZIV(n+1) = ZIV’(n+1) x F
With border conditions:
ZIV’(N)= Market price of the ZIV on the last trading day (N = day of the last close).
and
ZIV(1)=ZIV’(1)

The estimated ZIV’ model, based only on [2] 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 23rd October 2014 but the downloadable spreadsheet has updated data :

Looking at the data you can see that in low volatility periods the ZIV goes up and in high volatility periods it goes up. The high volatility periods during 2008/2009, 2010 and 2011 are clearly seen on the ZIV lows. The ZIV is like a less extreme version of the XIV and the SVXY. The ZIV has much less extreme movements than the SVXY and XIV. That smaller volatility is maybe why some like to use the ZIV for trading. One important difference is that the ZIV goes up, on low volatility periods, quite less fast that the XIV and the SVXY. Maybe for that reason the ZIV has hardly grown. The ZIV is an inverse version of the VXZ as you can appreciate by comparing the graph above with the VXZ graph available here. You can observe that basically the ZIV, from 2004 until now, went up, then down and back up, while the VXZ on the same periods was going down then up and back down. The ZIV is basically at the same level from where it started while the VXZ has lost a big percentage of its value because the latter goes down at a faster rate than the rate of increase of the ZIV

The ZIV had a long increase, during the extreme low volatility years, since 2004 up until the begining of 2007, more than doubling its value, from over slightly 20 to a bit under 50. When volatility came in 2007 and lasted up until the end of 2011, its value went down from under 50 to 10. Since then it recovered back to under 50.

If you want to calculate new ZIV 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 ZIV dynamics. The ZIV 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 XIV data you may find it here or if you want the also more extreme SVXY data you may find it here.

You may not have the time or inclination to implement the pricing formulas or you may want future ZIV 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 ZIV price. You may also use it to make forecasts of how the ZIV could behave since it includes ZIV prices based on VIX futures values, with which you can play with, to estimate what the ZIV 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:

ZIV and other volatility funds pricing models (sold in US$)

And here is the paypal button in Euros for those who prefer to pay in that currency:

ZIV and other volatility funds pricing models (sold in Euro)

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 ZIV and the VXZ 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.

Best!
jrv

PD1 -> How is Contango/Backwardation calculated and why does it affect the ZIV ? That is answered in the VXX blog post where it says PD4, basically the same is applied to ZIV 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 bought with the proceeds of selling the 7 month ones then the amount of contracts tends to be increased while in contango. That is because under contango selling one 7th month future gives more than enough to buy a 4 month one. The opposite effect happens while in backwardation, which leads to the decrease of the amount of futures which is a headwind to the ZIV 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 ZIV started trading up until the last available market value. The model fixes the 1st and last available ZIV market values and uses all the VIX futures market values in between to calculate the ZIV and project it back to 2004 or into the future (see the ZIV 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 ZIV 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.

Cheers!
jrv

About jrv

I was born in Spain and lived in Belgium, Chile, France, USA, Argentina among other places. Currently I am trying to settle down in a wild place. I am "retired", even though now I dedicate more hours "working" for my investments than I ever worked in the real labor market where I used to work in IT and Banking. I am a family man, I have a lovely wife, several sons and one step daughter. I have humble tastes, I like to stay home and read about companies and investments. I started investing at 25 before the internet bubble exploded. I did not know much about investing and liked technical analysis so my results were pretty bad. Fortunately I did not have much to lose. Some years later in 2006 bored of doing only real state investments and with quite a lot of money saved I opened an account in a cheap and excellent online broker and started again. This time I did not want to commit the same mistake, so I decided to follow a model. I heard that Warren Buffett was the best at making money via stocks so I started by reading a lot about him, all of his shareholders letters and several of the books that he recommended. I learned a lot, started applying his investing principles and reading a lot of 10K's. Digested news from lots of different sources. Basically I started buying very good and cheap companies and holding them for ever if possible and if nothing changed fundamentally. When the housing crisis started I was more than 75% cash. At that time I identified good companies at incredibly cheap prices so I invested most of my savings in stocks. In less than I year I doubled. By the second semester of 2009 I turned my software company into an investment vehicle and dedicated myself full time to it. My wife and I decided to change our lifestyle and moved from Belgium to the beach in a wild country. The goal was to keep fixed costs low in order to be able to live with a minimum 6-8% yearly return but specially to move away from the inhuman life of civilization and to have finally some peace and sunny weather to concentrate better on investing. Now I can think and study about companies 60 hours a week and I am doing great. I can finally do what I want full time and can proudly say that I have never been so happy, specially also with my just born 4th son, my other great kids and my sweet wife who supports me fully while I study most of the day and patiently wait for the opportunity to make a swing ! You can learn a bit more about my portfolio by viewing it at www.kuchita.com/view/sumo.php or you may learn more about me and my family by following the link "Author's site" from the menu above.
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