Godot Finance’s Mojito 3.0 Strategy

This is a test of Mojito 3.0, a strategy from Godot Finance for trading VIX ETPs like XIV and VXX. The always entertaining John Orford briefly discussed a previous version. This latest iteration is similar to a number of other strategies that we’ve covered on this blog, in that it compares a shorter-term measure of implied volatility to a longer-term measure, going long or short the VIX when the difference between the two is sufficiently large.

I’ve made some changes to the Godot’s original test for reasons I explain in a bit. Strategy results from 07/2004 trading XIV (inverse VIX) and VXX (long VIX) follow in blue, versus buying and holding XIV in grey. Read about test assumptions, or get help following this strategy.

20150813.01

Strategy rules:

  • Near the close, calculate the 5-day median value of the “IVTS”, or implied volatility term-structure, where IVTS = VIX spot / 45-day constant maturity price of VIX futures (1).
  • Go long XIV at the close when the 5-day median value will be < 0.91, long VXX when the 5-day median will be > 1.10, or else to cash. Hold until a change in position.
  • Read about test assumptions, or get help following this strategy.

* * *

Note that we’ve made important changes to Godot’s original test:

  • We’ve extended the test back to mid-2004, and updated it up to the present, adding an additional 8+ years of data. We’re able to do this accurately using simulated data.
  • In order to make an apples-to-apples comparison with other strategies we’ve tested on this blog, we’ve (a) opted to go long XIV as opposed to short VXX when the strategy calls for a short VIX position, and (b) increased position sizes to 100% (from 60%). Note that a short VXX position would have led to slightly different results, but not dramatically so. A good strategy will still be a good strategy (and vice-versa) with either approach.

20150813.02

As mentioned in the opening paragraph, Mojito 3.0 is similar to a number of strategies we’ve tested on this blog, in that trades are based on comparing a shorter-term measure of implied vol relative to a longer-term measure.

These types of strategies have worked historically because of the tendency to overestimate future volatility that exists across the VIX complex when the VIX complex is in its “normal” contangoed state (2): the VIX spot tends to overestimate future realized vol, VIX futures to overestimate the spot, more distant months to overestimate more than nearer months, etc.

These strategies are each using different metrics to judge whether the VIX complex is in that contangoed state, or more specifically, a contangoed state that is likely to mean that VIX futures are overestimating the eventual spot.

Other examples of this type of strategy include: comparing first vs second month futures, VIX vs front month futures, VIX vs 1-month CM, VIX vs VXV, V&M’s VIX:VXV ratio, QT’s VXV:VXMT ratio, Evolution Capital’s strategy, and many more.

Is this strategy better or worse than those other variations?

That’s impossible to say. I think the broader concept has merit for sure, and it’s a broad concept that we use in our own trading, but I also think that over the long-term, taking a more holistic view that considers many of the key data points across the VIX complex together (rather than two particular data points alone) is probably the more robust solution.

20150813.03

A big thank you to Godot Finance for the thoughts and the opportunity to add our two cents here.

When the strategies that we cover on our blog (including this one) signal new trades, we include an alert on the daily report sent to subscribers. This is completely unrelated to our own strategy’s signal; it just serves to add a little color to the daily report and allows subscribers to see what other quantitative strategies are saying about the market.

Click to see Volatility Made Simple’s own elegant solution to the VIX ETP puzzle.

Good Trading,
Volatility Made Simple


Wonk notes:

  1. The “45-day constant maturity price of VIX futures” is calculated based on a weighted average of 1st and 2nd month futures when the number of calendar days to expiration for the second month is greater than 45 days, otherwise it is based on a weighted average of 2nd and 3rd month futures.
  2. I’m using the term “contangoed” loosely here to mean a more distant measure of implied volatility is priced higher than a nearer measure, rather than the stricter definition of futures vs the spot.

Trading the Odds’ Optimized VRP Strategy

This is a test of another “Volatility Risk Premium” (VRP) strategy from the always excellent Trading the Odds (1). The strategy is similar to the Brute Force VRP, DDN’s VRP, and original TTO’s VRP strategies that we’ve shared previously in that it compares implied and historical volatility to predict changes in VIX ETPs like XIV and VXX.

See footnote re: the difference between my results and those produced by TTO (2).

Below are the results of TTO’s strategy in blue trading XIV and VXX from 07/2004 to present, versus buying & holding XIV in grey. Read about test assumptions, or get help following this strategy.

20150325.01

Strategy rules:

  • At the close, calculate the following: the 5-day exponential moving average of [30-day constant maturity price of VIX futures – (2-day historical volatility of SPY * 100)].
  • Go long XIV at the close when the result of the above formula is greater than 1, otherwise go long VXX. Hold until a change in position.

Note the differences between this strategy and other “VRP” strategies we’ve tested: (1) this strategy uses the 30-day constant maturity price of VIX futures (as opposed to the VIX) as a measure of implied volatility, and (2) it smooths the signal with a more responsive exponential (as opposed to simple) moving average.

20150325.02

While this strategy would have performed better historically than any of the other VRP variations we’ve tested, I remain more or less equally confident in its ability to perform in the future out-of-sample.

Call it the cynic in me, born out of years of deploying strategies here in the real world, but I am much more interested in concepts than specific parameter selection – the concept here being comparing implied and historical volatility.

You’ll find that the fortunes of these concepts tend to rise or fall together. This month is a good example, with this entire class of strategies struggling as a result of the dichotomy discussed here.

Why does this concept work? Because historically, when implied vol as fallen too far below historical vol, it has often meant implied vol is underestimating future realized vol, which over time will put pressure on the VIX and VIX futures to rise, and ETPs like XIV and ZIV to fall.

One final note…

20150325.03

In the results above, I’ve compared the strategy as originally tested to trading XIV-only (and moving to cash instead of VXX). Notice the significant decline in performance, especially in terms of risk-adjusted performance (Sharpe and UPI). Note too how the strategy would have spent a mere 11% of all days long VXX (and most of those days were bunched together in brief periods such as 2007/08).

When such a small percentage of the total sample contributes such a large percentage of performance, it exponentially increases the risk of overfitting (which leads to failure to perform out-of-sample).

That’s true not just for this strategy, that’s true for all of these long/short volatility strategies (including ours) that are heavily biased towards the inverse VIX play, but rely on major VIX pops to boost historical returns. Whether these strategies will be able to so deftly capitalize on those major VIX pops in the future is suspect.

* * *

A big thank you to Trading the Odds for the thoughts and allowing us to add our two cents here.

When the strategies that we cover on our blog (including this one) signal new trades, we include an alert on the daily report sent to subscribers. This is completely unrelated to our own strategy’s signal; it just serves to add a little color to the daily report and allows subscribers to see what other quantitative strategies are saying about the market.

Click to see Volatility Made Simple’s own elegant solution to the VIX ETP puzzle.

Good Trading,
Volatility Made Simple


Wonk notes:

  • These type of strategies, comparing implied and historical volatility, have become known as “volatility risk premium” or VRP strategies. In truth, there are multiple VRPs in the VIX complex (VIX spot vs realized volatility, VIX futures vs realized VIX, etc.), so admittedly, the term is probably not the most accurate. In any case, we stick with that convention here.
  • The results of our tests are worse than those presented by TTO. The biggest reason is that TTO uses the S&P 500 cash index (GSPC), while I use the non-dividend adjusted S&P 500 ETF SPY, to calculate historical volatility. I can find no empirically-sound reason why using one index in place of the other should lead to such starkly different results, so I chalk most of the performance difference up to overfitting. That isn’t intended as a gotcha, as all backtests are inherently overfit to some degree. And it isn’t to say that GSPC or SPY is better or worse than the other. It’s only to say that if I were to use GSPC here, the sole purpose would be to produce a better looking backtest, so I’m sticking with the convention that I’ve used historically on this blog.

QuantStrat TradeR’s VXV:VXMT Strategy

This is a test of a strategy from Ilya Kipnis of QuantStrat TradeR for trading VIX ETPs like XIV and VXX. Ilya provides a framework for testing the robustness of a given set of trading parameters. I encourage you to read Ilya’s piece, but that isn’t the subject of this post. Here I test the strategy that resulted from Ilya’s analysis (with a twist).

Strategy results from 08/2008 trading XIV (inverse VIX) and VXX (long VIX) follow in blue, versus buying and holding XIV in grey. Read about test assumptions, or get help following this strategy.

20150115.01

Ilya’s post found 3 different parameter values that looked promising. Here I’ve combined them into one single strategy. Strategy rules follow (read about test assumptions):

  • After the close, calculate the ratio: VXV (3-month VIX) divided by VXMT (mid-term VIX).
  • Calculate the 60-day, 125-day, and 150-day average of that ratio. These are for the three separate strategies that we will combine into one.
  • For each strategy, when both the current VXV/VXMT ratio is below the average and the average is below 1, that strategy is short vol (XIV). When both the ratio is above the average and the average is above 1, that strategy is long vol (VXX).
  • Average the signal from all three strategies. For example, 2 short vol and 1 cash signal would average out to a 2/3 position short vol.
  • Execute that signal at the following day’s close using a market-on-close order. In other words, this strategy has a 1-day lag. We’ve touched briefly on 1-day lags previously. Hold until a change in position.

20150115.02

Because VXMT data is only available from 2008, we can’t test this strategy back to mid-2004 as readers are accustomed to. The strategy looks promising though despite the limited data, at the very least because some thought went into parameter selection.

Note from the equity curve above (and drawdown curve below) that the strength of the strategy has been in managing losses, and the strategy has tended to lag buy & hold when XIV has been particularly strong.

The strategy spends about 65% of all days with some position on. I should note that of those days, the vast majority (92%) are short the VIX, meaning an important mechanism for the success of this strategy is moving to cash when the ratio is above or below the average (as opposed to switching between long and short VIX).

I look forward to seeing how this strategy performs out-of-sample. Like most of the strategies we test on our blog, we’ll continue tracking this one for the benefit of subscribers.

20150115.03

When the strategies that we cover on our blog (including this one) signal new trades, we include an alert on the daily report sent to subscribers. This is completely unrelated to our own strategy’s signal; it just serves to add a little color to the daily report and allows subscribers to see what other quantitative strategies are saying about the market.

Click to see Volatility Made Simple’s own elegant solution to the VIX ETP puzzle.

Good Trading,
Volatility Made Simple

VRP and Other Measures of Implied Volatility from Trading the Odds

This is a follow up to the posts here and here from the always excellent Trading the Odds. We’ve covered TTO’s work previously when we looked at their variation of a “VRP” strategy, comparing implied vs historical volatility to trade VIX ETPs like XIV and VXX.

In these new posts, TTO looked at other measures of implied volatility beyond just the VIX index. We put these other measures to the test here. Strategy results from 07/2004 trading XIV (inverse VIX) and VXX (long VIX) follow. Read about test assumptions, or get help following this strategy.

20150114.01

There are four equity curves in blue in the graph above, versus buying and holding XIV in grey. I’ve intentionally painted them all the same color (more on why in a moment). But first, the strategy rules as tested:

  • At the close, calculate the following: the 5-day average of [implied volatility – (2-day historical volatility of SPY * 100)].
  • Each of the equity curves above uses a different measure for “implied volatility”: the VIX index, the 30-day constant maturity price of VIX futures, or VXMT (mid-term VIX) (1). I’ve also added the VXV index for good measure.
  • Go long XIV at the close when the result of the above formula is greater than zero (i.e. a premium exists between implied and historical volatility), otherwise go long VXX. Hold until a change in position.

Note that our results differ significantly from TTO’s. See footnote for a discussion of why.

20150114.02

I painted all four equity curves blue to drive home the point that, regardless of any perceived difference, these strategies have performed so similarly that any advantage of one over the others is likely the result of random chance. I would be about equally confident in any of these strategies moving forward.

All four variations were in agreement on about 96% of days. That’s because there’s very little information contained in any one of these measures that’s not also contained in the others.

30-day futures will tend to price higher than the VIX index, VXV higher than futures, and VXMT higher than VXV, simply because they’re measuring implied volatility further out (which adds to uncertainty, which tends to increase required risk premium).

Contrary to my first thought though, that doesn’t mean that longer-dated implied volatility spends significantly more time short the VIX (ex. long XIV). I’m assuming that’s because these type of strategies tend to only take a long vol position when volatility spikes, which is also when the premium between longer and shorter-dated implied vol is compressing, meaning that when it actually counts, using shorter-dated implied vol (like the VIX) doesn’t result in significantly different results than longer-dated vol (like VXMT).

In short, one of these four variations will outperform in the future just by happenstance, but I don’t think history offers a useful enough guide as to which variation that will be. I’d be about equally confident in any of these variations in the future.

A big thank you to Trading the Odds for the thoughts and allowing us to add our two cents here.

* * *

When the strategies that we cover on our blog (including this one) signal new trades, we include an alert on the daily report sent to subscribers. This is completely unrelated to our own strategy’s signal; it just serves to add a little color to the daily report and allows subscribers to see what other quantitative strategies are saying about the market.

Click to see Volatility Made Simple’s own elegant solution to the VIX ETP puzzle.

Good Trading,
Volatility Made Simple


Wonk notes:

  1. For all dates prior to 2008, the VIX index was used in place of the VXMT index.
  2. The results of our tests are significantly worse than those presented by TTO. The biggest reason is that TTO uses the S&P 500 cash index (GSPC), while I use the non-dividend adjusted S&P 500 ETF SPY, to calculate historical volatility. I can find no empirically-sound reason why using one index in place of the other should lead to such starkly different results, so I chalk most of the performance difference up to overfitting. That isn’t intended as a gotcha, as all backtests are inherently overfit to some degree. And it isn’t to say that GSPC or SPY is better or worse than the other. It’s only to say that if I were to use GSPC here, the sole purpose would be to produce a better looking backtest, so I’m sticking with the convention that I’ve used historically on this blog.

Macro Investor’s VIX Trading Strategy

By reader request, this is a test of a strategy from Macro Investor for trading VIX ETPs like XIV and VXX. This strategy, like many you’ll find on this blog and elsewhere, uses the shape of the VIX futures term-structure, going short the VIX when futures are more contangoed and long when more backwardated.

Strategy results from 07/2004 trading XIV (inverse VIX) and VXX (long VIX) follow. Read about test assumptions, or get help following this strategy.

20141209.01

The strategy rules I’ve tested are a bit different than the ones presented by Macro Investor in order to stay more in line with how we generally test things here at VMS. Strategy rules:

  • At the close, calculate R, where R = [average of (VX1 / VIX, VX2 / VX1) – 1]. VX1 and VX 2 represent first and second month VIX futures, and VIX the VIX spot.
  • At the close, calculate the average value for R from inception up to that moment in time.
  • Go long XIV at the close if R > (average historical R * -1), otherwise go long VXX. Hold until a change in position.

Differences between my test and Macro Investor’s:

  • MI’s test traded UVXY (2x leveraged VIX) in place of VXX. This strategy has only spent about 6% of all days long VIX. That greatly increases the risk of overfitting those particular days. We would compound that impact of overfitting by assuming that we traded a leveraged product. Bear in mind that VIX ETPs are already insanely volatile. It would be bad stewardship on my part to even share such a backtest.
  • After applying the strategy to VIX ETPs, MI went on to then apply the strategy to ETP options. I have not done so here as options are beyond the scope of what we usually discuss at VMS, but note that my comments below would apply to options trading as well.

20141209.02

20141209.03

I think the basic concept behind the strategy, going short the VIX when futures are closer to contangoed and long when closer to backwardation, is a sound one and we’ve tested a number of similar strategies previously, such as the VIX vs Front Month and First vs Second Month strategies.

On paper, Macro Investor’s strategy has performed better than most, with an exceptionally smooth equity curve after the 2007/08 crash, but I think there’s an extra helping of overfitting with this strategy as a result of the introduction of the “average historical R”.

The average R value is based on all data from inception up to date. Note that the strategy doesn’t “peek” into the future as the average R value is recalculated each day in our test using only the data available to us at that moment in time.

But let’s pretend that we did have perfect foresight and could use the most up-to-date average R value (4.8%) for our entire test. In other words, from day 1 until the most recent trading day, average R always equals ~4.8%.

With this perfect foresight, this strategy should to some degree improve if the average R is actually honing in on some optimal value, but in fact it does just the opposite. It goes from a sexy Sharpe/UPI of 1.3/2.7 to a less impressive 1.0/1.9.

That tells me that the way in which the “average R” has changed over time (which is an entirely arbitrary result of the date on which the test started, and shouldn’t in and of itself be predictive), is overfit to this particular moment in history and unlikely to provide value out-of-sample.

Again though, beyond my criticism re: the average R and use of a leveraged long VIX ETP, I think the basic concept behind the strategy does have value.

* * *

A big thank you to Macro Investor for posting this strategy.

When the strategies that we cover on our blog (including this one) signal new trades, we include an alert on the daily report sent to subscribers. This is completely unrelated to our own strategy’s signal; it just serves to add a little color to the daily report and allows subscribers to see what other quantitative strategies are saying about the market.

Click to see Volatility Made Simple’s own elegant solution to the VIX ETP puzzle.

Good Trading,
Volatility Made Simple