Weekend Reads

The news has been all about the scandals in Washington this week, as if the normal level of blaming and bickering just wasn’t enough. Meanwhile, stocks melted lower in the second half of the week… it’s not much, but it’s apparently what counts for a sell-off in this year of seemingly unflagging market gains. Next week will be a holiday-shortened week, so enjoy the long weekend – here’s what we’ll be reading as we head home:

  • Grain markets still feeling the effects of last summer’s drought (Futures Magazine)
  • Paul Tudor Jones thinks motherhood, divorce incompatible with being a good trader (Washington Post)
  • Fun fact: the first movie ever broadcast on TV was still in theaters at the time (Paleofuture)
  • Has Microsoft beat Apple to the TV market? (Slate)
  • Cockroaches have evolved to avoid the sweeteners used to disguise insecticide (Christian Science Monitor)

Black Gold, Texas Tea, and Brent Bubbly?

Brent Crude needs a nickname…  While Black Gold and Texas Tea are common nicknames in the US for oil, we don’t know the equivalent for Brent Crude.  But Brent is becoming more and more of a player with the glut in the US (because of new sources coming online) driving WTI prices down, pushing the spread between the two from the typical range of $3 or $4 all the way out to more than $25.

As a result, the Brent contract has come to be seen as a better representation of global oil prices, and that has driven greater trading volume to the Brent futures contract (which is traded at ICE) instead of the WTI contract (which is traded at the CME).  All the more reason for a nickname. We’ve been wondering how that would play out in the competition between the two futures exchanges, but it looks like the bigger spread may not last long enough to matter – in the last few weeks, it’s taken a sharp turn back toward normal:

You see, the problem with trying to arbitrage this price difference was the lack of infrastructure – the US was set up to be a net oil importer, and moving huge quantities of oil out of the middle of the country was too expensive to make it worthwhile. But the CME Group’s online magazine sounds hopeful that this is beginning to change. Via Open Markets:

James Burkhard, vice president and head of oil market research of IHS CERA, said the spread will narrow once infrastructure is built, but that takes time. And there already have been changes, such as switching the flow in the Seaway pipeline from Cushing, Okla., to the Gulf to facilitate exports, but more is needed…

Once infrastructure is in place, Burkhard said eventually the price spread between WTI and Brent will likely start to reflect the cost of shipping oil from Cushing to the U.S. Gulf. “So you’re looking at a $3, $4 spread long-term rather than $20,” he added.

The reversal of the Seaway Pipeline to move oil south to the Gulf happened last year, and just a few months ago its capacity was more than doubled from 150,000 barrels/day to 400,000 barrels/day. Coincidentally, that’s right around the time the spread started narrowing. We saw a similar narrowing of the spread in late 2011, but this time around we’re seeing the effects of the structural shifts that are taking place to help balance the US and international oil markets.  It’s beginning to look like the larger-than-normal Brent/WTI spread may already be nearing an end.

Fun fact via Wikipedia:  The name “Brent” comes from the naming policy of Shell UK Exploration and Production, operating on behalf of ExxonMobil and Royal Dutch Shell, which originally named all of its fields after birds (in this case the Brent Goose).

That’s Not a Sell-Off, THIS is a Sell-Off

Only a couple of days after we reposted a chart from Stocktwits comparing the Nikkei rally to the Dow’s climb over the last year, and suddenly things have turned very sour for the Japanese market:

Chart courtesy Finviz.com. Disclaimer: past performance is not necessarily indicative of future results.

Meanwhile, the Dow’s drop in the early hours this morning proved to be little more than a head fake, as the market came all the way back only a few hours later:

Chart courtesy Finviz.com. Disclaimer: past performance is not necessarily indicative of future results.

And don’t let the scale of those two charts fool you – the drop from yesterday’s high in the Dow to today’s low was less than a 2% drop, while the Nikkei decline from yesterday’s highs to today was more than 8%.

It’s just one day’s hiccup in a long, huge climb for both markets, but it looks like at least one piece of evidence that the Japanese surge may be starting to get a little frothy.

Gensler’s MF Global Getaway

As MF Global continues unwinding at the speed of bureaucracy, new pieces of information have been few and far between. But this week, the Inspector General of the CFTC released a report examining the CFTC’s oversight and regulation of MF Global (you can read the full report here).

It’s definitely not groundbreaking, but the part of the report getting the most attention is CFTC Chairman Gary Gensler’s decision to recuse himself from the investigation – particularly whether or not that was in line with the CFTC’s policies. As it turns out, he was advised that it would not be consistent with established policy for him to do so, but that didn’t seem to be the answer he wanted. The Wall Street Journal writes:

“[W]e are concerned with the Chairman’s determination to withdraw from participation” in the investigation, the inspector general’s report concludes, noting that Mr. Gensler’s decision to seek advice on his involvement with MF Global only after the firm became “a public sensation” was “not the most desirable course.”

In other words, Gensler didn’t “realize” that his past ties to Corzine might be a problem until after it became clear that MF Global was going to be a high-profile disaster. It was at that point that he decided it might be a good idea to keep his name far, far away.

Well, it’s good knowing that when the chips are down and the disaster strikes, the head of one of our top regulators has the courage and conviction to step forward and say, “Not It.”

That’s not a Rally… THIS is a Rally

We were reminded of the old “That’s not a knife” line from Crocodile Dundee when taking a look at the Nikkei vs Dow chart put up on StockTwits today. While the move in the Dow has been impressive, those in Japan are likely saying something along the lines of “that’s not a rally” as the move in the Nikkei (black line) is approaching ludicrous speed (another 80s movie reference):

Via Stocktwits. Disclaimer: past performance is not necessarily indicative of future results.

How will US vs Japan,  Abenomics vs QE Infinity, end?  Stay tuned.

What All Volatility Calculations Are Missing

Volatility is one of the main ways we describe risk in the managed futures world, and it’s reflected in the calculation of several other measures of a CTA risk/return profile (like Sharpe Ratio). But last November, Newedge released a paper arguing that the typical method of calculating volatility is flawed because it leaves out an important factor: autocorrelation. Recently, Futures and Options World summarized Newedge’s findings in a more layman-friendly write-up, so we thought it would be worth revisiting the topic for those who wanted the plain English version. (Or you can read the original Newedge research here).

Typically, volatility is calculated by multiplying the standard deviation of a CTA’s returns by the square root of the time series. In other words, if you’re looking at a monthly time series, you would multiply the standard deviation by the square root of 12 (the number of months in a year) whereas if you had a weekly time series you would multiply it by 52 (weeks in a year) and for a daily time series you would use 252 (roughly the number of trading days in a year). This gives you the volatility in percentage terms.

Newedge’s research argues that the drawdowns CTAs experience don’t always match what we would expect based on their volatility, and they point to autocorrelation as the missing piece of data. You see, the typical volatility formula assumes that one period’s returns are independent of any others – that whether a CTA made or lost money in one month will have no bearing on whether or not it makes or loses money in the next month. But when a CTA exhibits autocorrelation that assumption no longer holds true. Positive autocorrelation means that whatever happened last is more likely to happen again (winners win and losers lose) while negative autocorrelation means that whatever happened last is less likely to happen again (reversion to the mean).

And according to Newedge’s work, trend following CTAs tend to exhibit negative autocorrelation. (Just more reason to listen to our advice about the benefits of allocation during a drawdown, although of course past performance is not necessarily indicative of future results). So for most trend following CTAs, Newedge’s work would suggest that we are consistently overestimating their effective volatility (and underestimating it for managers who exhibit positive autocorrelation).

We won’t be switching over all of our volatility calculations to incorporate autocorrelation just yet, but it’s definitely something to keep an eye on.

Managed Futures and the “Smirk” Curve

When AQR’s “100 Years of Trend Following” study came out, one of our favorite parts of the piece was the great use of data visualizations, including their look at the “smile curve” that takes shape when plotting managed futures returns vs stock returns. The idea is pretty simple – managed futures returns are higher when stocks are either doing very poorly, or very well. Charting that relationship creates a smile shape, with managed futures returns at their lowest when stock market returns are around zero – in other words, during choppy, sideways markets.

Now, a new paper from 1741 Asset Management has created a similar set of charts using monthly data, and they’ve added in bonds and commodities for good measure. Using the shorter time frame flattens the curves somewhat, leading to more of a “smirk” curve, but it also helps show more nuance to the data than AQR’s charts could display:

Managed Futures = Barclay BTop50, Bonds = Citigroup WGBI All Maturities USD,
Commodities = MSCI TR Gross World, Stocks = S&P GSCI Official Close Index TR.
Disclaimer: past performance is not necessarily indicative of future results.

There are a few things that jump out at us looking at this. First of all, the tilt of the curve between bonds and equities is nearly a mirror image. Managed futures has historically prospered far more during boom months for bonds, while sporting relatively lower average returns when bonds are falling. For equities, the relationship is reversed, with managed futures loving down months in stocks significantly more than positive months.

This effect is explained by the skew in the magnitude of returns for bonds vs equities. The equity returns on the upside are far more clustered between 0% and 10% than on the downside, which has months well past the -15% mark. The reverse holds true for bonds, where the scattering of outlier moves is on the upside.

The commodity chart is the most intriguing. There is the huge outlier move of -30% returns in commodities (when managed futures stepped up), but there is a flattening of the curve on the far right of the chart for the outlier up moves. And indeed the whole CTA vs commodities curve is rather flat when compared to the other two. Are we perhaps seeing the effect of their use of the BTOP50 index, which tracks the largest CTAs in the industry (currently the 20 largest)? As we’ve seen in the past, those big CTAs have tended to move away from commodity markets – perhaps explaining why big commodity moves to the upside really don’t move the needle that much. We wouldn’t be surprised to find that smaller CTAs would participate in a large commodity market down move in the other asset classes as there would be flight to safety, and it is less likely that a commodity outlier is caused by global economic factors (and more likely caused by drought, oil embargo, etc.).

At the end of the day – the biggest takeaway is the placement of these curves above their 0% line (on average they are positive no matter the environments), and their ability to point up at the corners (so called fat tail performance).

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