11 things you should know about the Crude Oil Drop

Christmas came a month early for those short Crude Oil over the past couple of months, specifically last week, and even more specifically – Friday.  Since July, WTI crude has dropped more than 30%, with 10% of that coming the day after Thanksgiving. And just about everyone and their mom (mom’s who have a blog about commodities?) have written something about the Crude Oil move.  Here’s 11 insights into what might make this drop more than just this week’s headline.

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Liquid Alt Analysis: AQR’s Managed Futures Fund (AQMIX)

AQR’s managed futures offering has garnered quite a bit of assets in the Liquid Alt section of managed futures “40 Act” funds (aka mutual funds) over the past two years. Since the inception of AQR’s Managed Futures Strategy I ($AQMIX) in Jan ’10, they’ve gone from $0 to $6.6 Billion in assets as they’ve canvassed the country with wholesalers pitching famous quant Cliff Asness’ products. It doesn’t hurt, either, that Cliff is everywhere…  Connie Mack interviews, Investment News conferences, CNBC appearances, etc.)

One investment advisor we talked to invested in $AQMIX said he invested because he liked the story about Cliff Asness in “The Quants” punching his computer. That’s one way to pick investments… just don’t tell your clients.

Now, whenever we see popular liquid alts like this gaining steam (see 361 Capital’s here), we wonder just how well they stack up against real managed futures managers, you know, the one’s doing separately managed accounts and privately offered funds. High Net Worth Individuals can invest directly in such managers through folks like Attain, while advisors typically need to access through privately offered funds (CPO), as once it’s a fund, it becomes a security, making them licensed to sell it and it able to show up on the client’s statements.  PS – There’s a little group we know doing some good stuff in the privately offered fund space, see here.

But all this leads to the question of how do the Liquid Alts like the gorilla of a fund, AQMIX, stack up against the privately offered stuff.

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Thanksgiving Reads

Decoupling a “Convex” Relationship with Volatility Cycles – (CME Group)

Managed futures outperform in Q3 – (Futures Magazine)

Option Trading is For (Thanksgiving) Turkeys – (Attain’s Alternatives Blog)

Robo advice meets alternative investments – (Investment News)

CFTC knocks CME for lack of enforcement staff – (Crains Chicago)

John Deere’s Gloomy Economic Outlook In 7 Slides – (Business Insider)

Fed vows review of regulatory gaps for bank commodity arms – (Reuters)

Burning Money: Natural Gas Flaring Costs Millions in Lost Revenue — (Before It’s News)

Just for Fun:

25 PEOPLE YOU SEE AT YOUR HOMETOWN BAR THE NIGHT BEFORE THANKSGIVING – (Thrillist)

What Derek Jeter, Pope Francis, Taylor Swift, and FDR have in Common – (Bloomberg)

The 10 Tallest Buildings That Were Never Finished – (Business Insider)

Happy Thanksgiving! 

Turkey Chill

Option Trading is For (Thanksgiving) Turkeys

It’s that time of year. The Christkindlmarket is open on the Daley Plaza, there’s ice skating in Millennium Park, and we’re preparing ourselves for the savoring smells and tastes of Thanksgiving dinner, where no platter of food is more important than that of the turkey. The relative that might disagree is your vegetarian cousin (Tofu turkey for you), and the guy who makes the ultimate sacrifice in the name of giving thanks…. the turkey.

Don’t feel too sorry for the turkey though… it had a great life, and died at the peak of its existence (being fed everyday), but the only issue is it had no idea, the “turkey surprise,” was coming. If fact, there’s a lovely chart of the turkey life, courtesy of Nassim Taleb’s wonderful book The Black Swan. Taleb’s depicts “the good life” of a turkey, including round the clock care, all the food it can muster, developing a life of self-satisfaction, just so us humans can prepare the unfortunate creature for the not so pleasant surprise ending.

The Turkey Surprise

 

Now we’re not trying to lend advice on your eating habits, but can’t help but use this example in the investment realm. While it seems impossible to imagine this chart could be a stock market index tomorrow, next week, or next month – this chart is to remind those caught in stock market dream that anything could happen, at any moment, without notice; especially those selling volatility for a living.

Which brings us back to Mr. Turkey. The turkey sees 1000 days of small gains followed by one day of large losses, and we can’t help but think of that as a lot like the performance profile of option sellers. The reason is option sellers are technically short volatility programs which on the whole make a living by risking a large amount to make a small amount. There’s an old saying about option sellers ‘picking up pennies in front of a freight train’. They can get away with this (in theory), because they have a large winning percentage where the large losses are very rare.

But no matter the math and no matter how good your option selling manager is, or has been to date, there is no denying that they have a greater than zero chance of a large negative surprise akin to the turkey’s 1001st day at some point in the future.  Indeed, just this year (last month to be exact), a spike in volatility in October sent some option sellers to the dinner table, as they didn’t see the turkey’s day of demise coming.

Now, professional option selling managers design their programs not to lose everything on a single day like the turkey; but they are betting against the occurrence of such a day, being set up to realize frequent but small gains in exchange for the risk of infrequent but very large losses (making them perhaps a distant cousin to the turkey).

In the meantime, Happy Thanksgiving to you and yours from the Attain team!

10 of the Worst ETFs Money Can Buy

It’s typically a slow week in the financial world for the few days leading up to our collective feasts on Thanksgiving day, and that gives us a little down time to catch up on matters we typically don’t get to day to day, or even week to week.

One of those things is checking in on ETFs some people thought were a smart idea at the time, and now doesn’t look so good. Without Further ado, the Top 10 worst performing ETFs over the past twelve months:

ETFTicker1 Year %
VelocityShares 3x Inverse Natural Gas ETN$DGAZ-82.10%
C-Tracks Citi Volatility Index TR ETN$CVOL-80.31%
Direxion Daily Jr Gld Mnrs Bull 3X Shrs$JNUG-75.06%
Direxion Daily Jr Gld Mnrs Bear 3X Shrs$JDST-73.52%
VelocityShares Daily 2x VIX ST ETN$TVIX-73.05%
ProShares Trust Ultra VIX Short$UVXY-72.94%
Direxion Daily Semicondct Bear 3X Shares$SOXS-67.15%
Direxion Daily Russia Bull 3X Shares$RUSL-66.00%
Direxion Daily Nat Gas Rltd Bull 2X Shrs$GASL-60.71%
UltraShort DJ-UBS Natural Gas$KOLD-59.91%

(Disclaimer: Past performance is not necessarily indicative of future results)
Table Courtesy: ETF.com

Our Notes:

  1. We’re not surprised to see 3 of the Top 10 worst performing etfs be “tracking” Natural Gas, and again – both a bull fund and inverse fund both among the worst performers (it is truly magical their ability to pull that off). Those ETFs seem to not perform well under…let me see here, ok, under most circumstances.
  2. Gold Miners still suck. (See Here Here and here.) And now they join the dubious distinction club as being one of the plays where you lose no matter whether you thought Gold Miner’s were going up or going down. This one’s even more egregious than the Nat Gas, as they are bull and bear on the same index – yet both down more than -70% in past year.
  3. The Good old VIX. Betting on Volatility is a tricky, tricky game. Betting short on the VIX over the past 5 years probably seemed like a good bet, right up until October when the VIX spiked without notice, and all the sudden you lost half of the investment.

So how did you fare? Hopefully not as bad as some of these… Have an ETF that surprised you? Let us know.

The Success Equation, Untangling Skill and Luck

The Success EquationWe like to read around here – and just recently got done with one that has been on the wishlist (it’s more like a… when the kids are quiet for 10 minutes and there’s not a client dinner or conference in town or presentation for a business deal – as time permits list, but I digress) for quite some time: Michael Mauboussin’s, “The Success Equation: Untangling Skill and Luck in Business, Sports, and Investing.”

The title caught our eye right away, being in the business of untangling luck and skill to a certain extent in helping clients identify and invest in alternative investment managers. The question at the end of the day is whether the impressive track record a client is considering investing in is the result of skill, or whether it is luck. If you’re a chess player – or even tennis, it’s nearly all skill. If you’re a hockey player… it’s way more luck than your agent would care to admit.

 

And what about an investment manager?  How much of that track record is skill versus luck. The manager themselves usually portrays it as skillful, and charges as if it were entirely skill – but even the most successful of managers have to admit there is some skill in there. How much, and what questions should you be asking to determine the role of skill and luck are the parts of Mauboussin’s book we’re most interested in.

Here’s his handy graphic breaking down the major sports, slot machines, roulette, and trading in the stock market on a pure luck to pure skill continuum.

New Picture

Mauboussin tells us that where skill is the dominant factor, history is a useful teacher, but where luck is the dominant force, history is a poor teacher. And that the type of feedback you get is a good tool to measure how much luck there is in your endeavor. On skill side, there is a very close relationship between cause and effect; but feedback on the luck side is often misleading – where good decisions can lead to failure and poor decisions lead to success in the short run (due to luck).  For more on the latter – read anything by Nassim Taleb, who’s made a career pointing out that a lot of the skill you see in the world (the banker, insurance company, option trader, etc) is nothing more than the result of 1 out of a million people destined to be quite lucky.

Essentially – what worked in the past may not work in the future on a heavy luck endeavor (such as investments), which I guess the regulators knew long ago when they made it a requirement to put the ‘past performance is not necessarily indicative of future results’ disclaimer on investment documents.

To measure the effect of luck, he introduces us to the James Stein estimator and the ‘shrinkage factor’ (straight out of Seinfeld), shows us how reversion to the mean is highly dependent on how much luck is involved, and discusses how even when you know how much skill there is – you’re in trouble because skills deteriorate (he quotes a source as saying the peak age for matters of finance is 53, and after that our skills start to deteriorate).

We enjoyed two parts in particular.

One, the discussion of ‘the paradox of skill’, which he explains: as skill improves, performance becomes more consistent, and therefore luck becomes more important. Mathematically, if the variance in skill becomes smaller than the variance in luck – luck becomes the dominant factor. In his own words:

“When everyone in business, sports, and investing copies the best practices of others, luck plays a greater role in how well they do.”

He shows stats supporting this from baseball, where all of the hitters have gotten better, but the rough averages have remained the same. Why? Becasue the pitchers have gotten better too!  But the interesting part of this to us is in the investment realm, and more importantly – the alternative investment realm. The discussion sure gets you thinking about our modern world of global markets, derivatives, and mangers earning billions; and whether the world has become so skilled in analyzing and trading them – that any performance is due mainly to luck, and due for a healthy reversion to the mean?  It makes us think of all the money in systematic trend following, and whether there is a real world experiment in the ‘paradox of skill’ happening there before our very eyes. Are any variations in the performance of trend follower A versus Trend Follower Z due to luck? Are they outperforming due to luck in including Coffee in their list of markets – luck in risking 0.25% per trade and getting an extra Hog trade versus the guy who’s model was risking just 0.20%? And so on.  Are those differences skill, or luck?

We also enjoyed Mauboussin’s discussion of the ‘dumb money effect’, which we know as emotional investing, or getting in at the highs, and out at the lows (see our discussions on it here, here, here). He shows some stats calculating it costs investors 1% in returns each year, and that institutional investors  have foregone $170 Billion in value over a couple decades because of this dumb money effect.

Why do we do it?  We’re hardwired that way, with Mauboussin showing a survey where 2/3rds of respondents admitted they tend to rely more on judgement when analysis becomes more complex, and how we tend to give disproportionate weight to whatever has happened most recently, buying when at all time highs and getting out when at lows, causing some specific losses:

“Individual investors consistently earn results that are 50-75 percent those of market itself due to bad timing.”

And if this dumb money effect is so prevalent among individual investors and institutional alike – should we really expect our managers to be immune from it? It’s not too hard to imagine an investment manager doing their own version of the dumb money effect – changing a model around after a streak of losses, adding more markets on a model which is doing well to expand its exposure, and so forth. This is the danger to perceived skill – where changes meant to help actually result in pushing the inevitable reversion to the mean back further.

You can’t help but feel a little hopeless upon finishing the book – and realizing just how much of investing (and life) is due to luck instead of skill. But the lesson to be learned shouldn’t be to pack it in and put your money under the mattress. The lesson for us is to realize luck’s part, to realize that impressive winning streaks are just that – streaks. That depressing losing streaks are just that – streaks. And that some luck (or lack thereof) means reversions to the mean, so avoid getting in at the tops and out at the bottoms.. avoid the dumb money effect. The lesson for us is that process matters a lot more than outcome in the short run, and that the more you base your investment decisions on the recent past, the more likely you are to be disappointed.

 

Bad Year for Commodities, Whether in ETFs or Futures

Here’s our monthly look at the various commodity ETFs and how they track a simple strategy of buying December futures and rolling them annually. Plus, a comparison to Ag Traders and an overall commodity index.

Some Notes:

  1. Only 4 on the commodity contracts we’re tracking are positive on the year, suggesting that buying and holding a commodity market no matter the exposure, would be enough to make you cringe.
  2. For the first time this year,  buying and holding futures contracts (on average) are outperforming their etf counterparts.
  3. While the Long/Short AG Trader’s Index looks pretty impressive sitting there at +4% or so (compared with -13% for $DBC, the all commodities ETF), it’s been a rough couple of months for the Ag Trader’s as Grain markets have bounced back from yearly lows. If looking for smart commodity exposure, there’s no better time than now to look at the Ag Traders (in our opinion).

(Performance as of 10/31/2014)

Commodity ETF Over/Under Performance 2014

CommodityFuturesETFDifference
Crude Oil$CL_F
-13.14%
$USO
-13.28%
-0.14%
Brent Oil$NBZ_F
-19.49%
$BNO
-22.25%
-2.76%
Natural Gas$NG_F
-11.02%
$UNG
-1.98%
9.03%
Cocoa$CC_F
6.90%
$NIB
5.95%
-0.95%

Coffee$KC_F
56.54%
$JO
63.59%
7.06%
Corn$ZC_F
-16.36%
$CORN
-14.09%
2.26%
Cotton$CT_F
-17.82%
$BAL
-18.95%
-1.12%
Live Cattle$LE_F
25.96%
$CATL
20.20%
-5.76%
Lean Hogs$LH_F
10.72%
$HOGS
1.43%
-9.29%
Sugar$SB_F
-10.26%
$CANE
-6.94%
0.99%
Soybeans$ZS_F
-7.81%
$SOYB
-6.48%
1.33%
Wheat$ZW_F
-16.88%
$WEAT
-19.59%
-2.72%
Average-1.05%-1.23%-0.17%
Average without Coffee-6.29%-7.12%-0.83%
Commodity Index $DBC-12.98%
Long/Short Ag Trader CTAs4.59%

(Disclaimer: Past performance is not necessarily indicative of future results)
(Disclaimer: Sugar uses the October contract, Soybeans the November contract.)
Long/Short Ag Trader CTA = Barclayhedge Ag Traders Index