The First Shall Be Last and The Last Shall Be First

A common theme in my writing recently has been not being married to any one specific set of trading rules. It’s very easy to get excited about an amazing recent performance (such as the Brute Force VRP strategy in October), but over the long-term, I’m sure that a holistic approach that considers many different concepts will win the day.

This year has been a perfect illustration of that. Every month I produce a graph like the one below showing the year-to-date performance of all of the simple strategies that we’ve blogged about.

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Read about test assumptions, or get help following these strategies.

That’s a lot of information to digest, so in the next graph I’ve stripped out just the best performing strategy YTD in blue (Brute Force VRP), and the worst performing in grey (DFTB’s StDev).

At near-term peaks at points #1 and #2, DFTB’s StDev was the best performing strategy of all of those we track, while the Brute Force VRP strategy was either the absolute worst, or somewhere very close.

Fast-forward to point #3 where we find ourselves today, and all of that has been flipped on its head. DFTB’s StDev is now at the bottom of the barrel, and the Brute Force VRP strategy is the tippity-top performer.

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Here’s the rub though, there really is no way to know in advance which of these concepts is going to outperform next because in all trading, but especially when trading instruments as volatile as VIX products, there’s an element of randomness and the luck of the draw.

That means that the best way to ensure future success is to employ a bit of balance, to use a more holistic approach that draws from many different concepts.

The epic shift in the graph above has played out time and time again historically. That’s why you consistently find me staying very Zen about both a strategy that has performed very well recently and one that has performed poorly. Because the best strategy for the future, given what we know today, probably lies somewhere in between the two.

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

Good Trading,
Volatility Made Simple

VIX Trading Strategies: (Usually) Just Variations on a Theme

We’ve tested 16 simple and effective VIX trading strategies on this blog that, based on all of my readings both academic and in the blogosphere, are broadly representative of how most traders (of the quantitative, swing-trading variety) are trading VIX products.

Even though those strategies are keying off of completely different metrics, ranging from the shape of the futures term-structure to moving average crossovers, most are at their core, really variations on a theme: momentum/trend-following.

Nearly all of the strategies tend to trade long volatility when the VIX is rising, and short when the VIX is flat or falling (as opposed to mean-reversion strategies like this one which are actively betting against the prevailing trend).

That means that all of those strategies are going to agree more often than not. There’s nothing inherently wrong with that. It’s tough to argue with a long XIV/short VXX position when (for example) equities are in an uptrend, VIX futures are strongly contangoed, and a juicy VRP all exist concurrently.

But that also means that judging one strategy versus another is really about understanding the narrow periods of time when these different approaches don’t agree. This also makes designing strategies more difficult as the sample size of truly relevant data is much smaller than it would at first seem.

The table below illustrates how frequently our representative sample of simple VIX trading strategies agreed with one another. Fifteen trading strategies (1) are listed (see legend below table). Find where a given pair of strategies intersect on the table to find out how often their respective positions agreed.

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Key: (1) First vs Second Month Futures, (2) VIX vs Front Month Futures, (3) VIX vs 1-Month Constant Maturity, (4) VIX vs VXV Indices, (5) V&M’s VIX:VXV Ratio, (6) DFTB’s StDev Strategy, (7) DFTB’s Spread Strategy, (8) DDN’s Momentum Rotation, (9) DDN’s VRP Strategy, (10) 10/100-Day MA Crossover, (11) TWP’s Quadratic Fit, (12) NAS’s VIX Futures Momentum, (13) S&P 500 50/200-Day Crossovers, (14) Brute Force Optimized VRP, (15) LI’s Bollinger Band Strategy

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Strategies agreed with one another on average 79% of the time. The two individual strategies that disagreed with one another the most often, still agreed 65% of the time.

Again, these strategies are meant to be broadly representative of how most traders are trading VIX products. The key takeaway is that even though these strategies are keying off of completely different metrics, most are really variations of momentum/trend-following, and as such, will agree with one another more often than not. One of the keys to designing VIX trading strategies is better understanding the narrow periods of time when strategies disagree.

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When the strategies that we cover on our blog 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 TM RSI(2) strategy was excluded from this analysis as it trades far too infrequently to make for an apples-to-apples comparison.
  2. I took some mathematical liberties when deciding whether two strategies “agreed”. If strategy X was 100% long VIX and strategy Y was 100% short VIX, I counted that as full disagreement. But if strategy X was in cash, and strategy Y was 100% long or short VIX, I counted that as only a half disagreement. I did this to compensate for the fact that some strategies are long/short and some short vol-only.

Strategy Performance by Market Regime

Designing VIX trading strategies like ours is made more complicated by the extremely bipolar nature of VIX products.

When things are good, they’re consistently good because of the existence of a consistent volatility risk premium, but when they turn sour, things can get out of hand quickly because of the “spiky” nature of volatility.

To illustrate, the graph below shows XIV (inverse VIX) from 03/2004, with losses exceeding -40% shaded red/black.

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The four losses shown are -40%, -92%, -53%, and -74% respectively. Ouch.

All four of those losses represent major shifts in the market regime, and all are going to have a major impact (for better or for worse) on the backtested performance of a strategy, but those shifts tended to occur within very short periods of time.

That means that, when designing VIX trading strategies, it’s very easy to be fooled in to thinking a strategy is better than it actually is because it happened to be positioned correctly going in to one of these very brief, but very significant events.

I put little value in knowing a strategy did well during one of these bearish regimes (because it might just be good luck), but I do put value in knowing a strategy consistently did poorly during one of these regimes (because it might not just be bad luck).

To illustrate, of all of the 14 simple strategies we’ve tested previously on this blog, the two that have performed the worse during the bearish regimes are the First vs Second Month strategy (blue in the graph below) and the S&P 500 50/200-day Crossover strategy (grey). I’m assuming we traded the VIX ETPs XIV and VXX (see test assumptions).

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Regardless of each strategy’s overall performance, their consistent inability to correctly play these bearish regimes correctly is a black eye and a reason I think not to trade either as a standalone strategy.

On the flip side, (as noted above) I don’t put much value in knowing a strategy did well during the bearish regimes because it might just be a product of luck, but for the sake of completeness, the two strategies that performed the best during the bearish regimes are DDN’s Momentum Rotation (blue) and TM’s RSI(2) strategies (grey).

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In summary, it’s important to look at major market regimes when assessing VIX trading strategies. Good performance during bearish regimes isn’t necessarily a good thing, but consistently poor performance is probably a bad thing.

Good Trading,
Volatility Made Simple


Wonk notes:

In the analysis above, I ignored the period in late-2008 that is shaded black in our first graph. Because that massive crash in XIV (i.e. spike in volatility) came at the tail end of a long bearish period, many of the strategies we’ve talked about did well timing it. But the way in which the late-2008 crash unfolded was a unique event, and though there will be future crashes similar in magnitude, they will likely be dissimilar enough to make drawing any conclusions from the late-2008 crash futile.

Data prior to the launch of XIV and VXX has been simulated. We’re able to do this accurately using a combination of the indices and the futures data on which these ETPs are based. Read more about simulating data for VIX ETPs.

The Bread-and-Butter of VIX (Swing-Trading) Strategies

Our strategy has held its current position (long XIV or ZIV) for 50 trading days so far, gaining 44% trading XIV or 19% trading ZIV.

In this post I look at how often our strategy has held a position for such a long time, but note that the conclusions reached here would be applicable to most of the simple strategies we’ve discussed previously on this blog.

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The graph above shows the cumulative number of trading days we would have spent in a given position from 07/2004 to the present. Our current position (50 days) is only the 17th longest.

At first glance, it looks as if most of our trades are of this longer variety, but that would be incorrect. The table below shows the number of positions we would have taken historically based on length. Note how the vast majority of trades (67%) would have lasted less than 1 week.

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Note too how longer positions tend to be more often profitable (see right-most column).

Our strategy and most of the simple strategies we’ve talked about on this blog are, in a roundabout way, akin to momentum strategies. They tend to take a position when the market is already moving in a favorable direction (as opposed to mean-reversion strategies, which take a contrarian position).

That means that positions that survive unchanged for longer tend to be more profitable (otherwise the strategy would likely have already made a change). These lengthier positions, like the one we’re in currently, are really the bread-and-butter of how most VIX (swing-trading) strategies generate return.

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

Good Trading,
Volatility Made Simple


Wonk note: data prior to the launch of XIV and VXX has been simulated. We’re able to do this accurately using a combination of the indices and the futures data on which these ETPs are based. Read more about simulating data for VIX ETPs.

Chasing the Hot Hand is Usually a Bad Idea

Each month I show the month and YTD results of all of the simple VIX trading strategies we’ve talked about on this blog (which are of course separate and unrelated to our own strategy).

Just to be clear, the point of showing these results is not to imply that readers should choose the best performer in recent history. To the contrary, that would usually be a bad idea.

To illustrate, below in grey are the results of all of the simple strategies we’ve blogged about previously, trading XIV and VXX since 2005 (1). The bold line in red assumes that at the end of each month we selected the best performing strategy of the previous 6-months and traded just that strategy for the next month.

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Read about test assumptions.

In terms of risk-adjusted performance (Sharpe and UPI), the red line performed worse than nearly all of the individual strategies.

Because of how volatile VIX ETPs like XIV and VXX are, one day’s difference here or there can have an enormous impact on returns in the short-term. That means choosing strategies based on which one has the hot hand at the moment is usually a bad idea.

I think it’s much more effective in the long run to select strategies based on a more comprehensive understanding of the individual factors that drive VIX ETP returns (see examples here and here).

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

Good Trading,
Volatility Made Simple


(1) TM’s RSI(2) strategy was not included in this analysis because of how infrequently the strategy trades.