YIELD SPREAD – the belly of the curve is even flatter, but the big one almost every objective strategist monitors (10s/2s spread) has compressed another 7bps this morning to a fresh YTD low of +146bps wide (-38% YTD)
“And who is the author of all this?”
While it’s getting difficult to pin down who, specifically, nailed the narrative of worldwide #deflation, crashing long-term bond yields, and flattening yield curves as the driver of the all-time high in the SP500… that’s what makes a market!
The aforementioned quote comes from a section in The Theory That Would Not Die titled “Enlightenment and the Anti-Bayesian Reaction” (page 30) where Napoleon realizes that Pierre-Simon Laplace wasn’t as full of it as those who weren’t yet enlightened.
Much unlike the perma bulls, bears, and partisan hacks in our profession, Laplace was a math, stats, and probability guy. In forecasting terms, he didn’t cling to religion or failed academic dogmas. As the facts changed, he did – or at least he had a framework (Bayes Rule) to try.
Back to the Global Macro Grind…
While I can try to explain why the SP500 can drop 103 points in a straight line (in 7 days), then ramp 106 points in 4 days, I don’t think that’s where I add value. There are legions of pundits on the #OldWall that use 1-factor moving averages than can help you with that.
Using my #waterfall metaphor for multi-factor, multi-duration risk management, I’m much more comfortable trying to explain market moves in terms of what is happening beneath the headline US stock market index price.
What’s interesting, but not surprising, is that some of the big Global Macro factors that concerned consensus on December 16th (when the SP500 closed -5.1% lower at 1972) are actually worse today than they were then.
No, I’m not talking about where Russia is trading (-41% YTD). I’m talking about really big US economic risk indicators like:
“So”, now that I am in the holiday cheer spirit, allow me to knock those pins down, one by one:
But #NoWorries, “the market is up”…
Not clear what that means, but if the “market” includes things like global bond markets, international equity markets, commodities, currencies, etc., that CNBC type statement would make a 16th century dude who called the world “flat” look smart.
Asia (ex-Japan, which we’re actually net long for now via the DXJ) continues to trade much more in line with global #GrowthSlowing than the Dow does. Dr. KOSPI (South Korea) was down another -0.3% overnight to -3.5% YTD. Australia (struggling alongside Canada, Brazil, etc. with #deflation expectations) was -1.1%, and both the Hang Seng and Thailand failed @Hedgeye TREND resistances too.
All the while, High Yield and Junk started going down again yesterday. Remember that part of the December 16th #Deflation Dominoes? I do. Down Yen and Euro à Up Dollar à Down Oil, Commodities, etc. (#deflation) à Down High Yield Energy Bonds.
In other words:
After the 2000 and 2008 crashes, who is the author of all this risk management speak?
Don’t blame me. It’s Mr. Macro Market’s message. And, at a bare minimum this morning, I wanted to remind you of it as those who are in the business of being willfully blind into year-end won’t.
Our Global Macro Risk Ranges are now:
UST 10yr Yield 2.05-2.22%
Oil (WTI) 52.05-56.99
Best of luck out there today,
Keith R. McCullough
Chief Executive Officer
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This note was originally published at 8am on December 09, 2014 for Hedgeye subscribers.
“It solved practical questions that were unanswerable by any other means.”
-Sharon Bertsch Mcgrayne
That’s how Sharon Bertsch Mcgrayne summarizes using a Bayesian approach to problem solving in an important book for your risk management library – The Theory That Would Not Die.
“Although Bayes’ Rule drew the attention of the greatest statisticians of the 20th century, some of them vilified both the method and its adherents, crushed it, and declared it dead… In discovering its value for science, many supporters underwent a near-religious conversion yet had to conceal their use of Bayes’ Rule and pretend they employed something else.”
Much like during Bayes’ revolutionary times (18th century), where “mathematics was split along religious and political lines” (pg 4), today we are at the crossroad for the same in economic analysis. If you tell me what someone’s political and/or financial motivation is, I can usually predict their answers. If you’re Bayesian in your approach, your answers are far less certain.
Back to the Global Macro Grind…
We hosted an astute group of RIAs (Registered Investment Advisors) at HedgeyeHQ after the close yesterday where I gave a teach-in on our #process. One of the main examples I like to use is Bayes trying to locate a billiard ball’s location (blindly) on a table…
Each incremental throw gives you more information on where the ball is not. After multiple throws, you can narrow the probability of the ball’s location to a probable range. I call this the Risk Range. And I have no business telling the table where the ball has to be.
What happens if there are multiple competitors at the table, all racing to figure out where the ball is at the same time? That’s what makes a market. Whether you like my competitive style or not, I fully intend on coming out of the room with the ball (read Diary of a Hedge Fund Manager for details!).
If you want to beat your competitors in this game, not only do you need to play your game (read: #process), but you need to understand where the other players at the table are positioned and why. One really simple way to look at this from a consensus hedge fund positioning perspective is through CFTC Non-Commercial net LONG/SHORT futures/options.
I cite the rate of change in this Bayesian information as frequently as I can, but whether I do in a timely fashion or not doesn’t mean that the information ceases to exist. Yesterday’s rip (higher) in the Long Bond (TLT +1.2%) and drop in the SP500 (SPY -0.73%) can be (partly, but importantly) explained by the Consensus Macro’s net positioning as of Friday’s close:
In other words, into the “everything is awesome” jobs cheerleading report:
“So”, no matter what you think consensus is… that’s what it was - and the next Bayesian probabilities to weigh have everything to do with why consensus is positioned that way. Isolating why on both GROWTH and INFLATION, here are a few A/B tests (toss the ball):
A) On GROWTH, they must think US growth, employment, wages etc. are fixing to achieve some sort of “escape velocity”…
B) Or they realize that even if they are wrong on growth… that the Fed, BOJ, and ECB bails them out anyway
While its perverse, that B) scenario is credible. It’s the levered-long heads you win, tails you win bet – throw the ball anywhere on the table (other than the Russell 2000 and Energy stocks) and you win, right? How about we roll the queue ball on INFLATION?
A) As #deflation expectations accelerate, consensus must think the Fed is going to raise rates into that? …
B) Or that consumption growth is going to be so strong that the Fed will dismiss #deflation as a risk and hike anyway
The problem with what we call the #Quad1 scenario: A) US growth accelerating B) on inflation decelerating is that it’s a theory, not yet a reported reality. And that’s the thing about theories – they are for people who are smarter than me that don’t need to keep taking more reps with the uncertainty ball. They just need a survey confirming their pre-determined belief.
What if McDonalds (MCD) reporting a down -4.6% year-over-year same store sales number for November has something to do with the non-Wall Street economy that still has no wage growth? What if the recent Retail Sales, real personal consumption growth, and jobless claims numbers reported by the government are right (they’ve been slowing)?
Well, that will make Friday’s Consensus Macro position in SPY vs TLT wrong… and it might remind some of us that practical questions are unanswerable by any other means than by embracing the uncertainty of each risk management day.
Our immediate-term Global Macro Risk Ranges are now:
UST 10yr Yield 2.16-2.32%
WTI Oil 61.27-68.02
Best of luck out there today,
Keith R. McCullough
Chief Executive Officer
Takeaway: Elevated Attrition + Peaking Penetration = Declining Users in 2015.
This is a summary of the salient points behind our thesis. As usual, we will be publishing follow-up notes with incremental analysis, and hosting a call to run through the detail. In the interim, let us know if you have any questions or would like to discuss in more detail.
We have previously identified that P has historical retention issues, which we detail in the chart below. Since 1Q11, P has added more than 160M registered accounts, yet only grew active users by 45M, suggesting total churn of at least 115M accounts, or 72% of its gross account gains during this period. The bigger issue is that P has already exhausted much of its TAM, particularly the low-hanging fruit.
Back in August, we ran a survey of 20K US internet users to determine P's actual penetration levels. Our survey results suggested that P has penetrated roughly 55% of US adult internet users. That may sound like a ton of runway, but we estimate that roughly 2/3 of P’s remaining adult TAM is over the age of 45, roughly half is over age 55. Further, we also estimate that P has likely penetrated over 70% of the teenage population. In short, new user growth will prove more challenging from here.
We estimate that P needs to sustain a run-rate of gross new quarterly account adds of 11M-13M to maintain its active user base given our estimate of mid to high-teens quarterly churn rate. Even If that run-rate was possible over the long-run, and P could penetrate every internet user in the US, we estimate that P would exhaust its unpenetrated TAM within 7-10 quarters
In a more likely scenario, we expect gross new account adds to slow given the high concentration of older users within P's unpenetrated TAM, which should lead to y/y declines in user and/or listener hour growth sometime in 2015. See the link below supporting detail and charts on our survey results & TAM analysis.
P: User Penetration Survey (N=20,000)
08/28/14 04:12 PM EDT
Outside of listener hours, advertising revenue per user (ARPU) is driven by increasing ad load and ad rates; we're most concerned about the former. P’s ad load has steadily risen throughout its history. However, we suspect that it’s these increases in ad load that are exacerbating its retention issues, particularly its most recent one in late 2013.
Back in August 2013, P increased its max ad load per listener hour from 4 to 6, but the bigger issue was that P altered its ad feed from 1 every 15 minutes to 2 every 20. Collectively that translates to as much as a 33%-100% increase in ad load depending on how long the user’s session lasts. Further, the altered ad feed conditioned the user to expect back-to-back ads, which we suspect may cause some users to end their session prematurely upon hearing the first ad.
That said, it shouldn’t be a surprise that in 4Q13, P saw its sharpest deceleration in net user growth in its reported history (from 25% to 14% y/y growth). We suspect that surge in ad load in 8/13 led to accelerated churn in the following quarter. Moving forward, we have no reason to expect anything different when/if P increases ad load again: rising ad load will push the user away, especially with a growing wave of options for streaming music online.
The one big positive for P is ad rates, specifically its push into the local advertising market, which the company suggests carries rates as high as 2.5x the national average. However, we do not believe P has the geo-targeting ability to command rates that high (P’s geo-targeting based on the zipcode provided by the user during the registration process). Regardless, consensus estimates already imply a sharp acceleration in ad pricing; even if the sell-side doesn’t realize it (we’re likely alone in our declining user view).
In the table below, we’re running a scenario analysis on 2015 revenues; flexing ad-supported listener hours against Ad RPMs (proxy for ARPU). We have included P’s 2014 YTD performance on both fronts for perspective. We caution not to read too much into its YTD listener hour growth since that is inflated by the removal of P's mobile listening cap from 2013 (see chart below). In 2015, we don't believe listener hour growth will exceed double-digits.
That means that consensus estimates for 2015 are unattainable outside of a considerable acceleration in ARPU. As mentioned above, increasing ad load will come at the expense of listener hours and/or user retention. So the question is whether its local ad push can produce accelerating pricing growth vs. 2014, and if so, by how much…all things considered, we suspect it won’t be enough.
We believe the stock could easily trade in the $13-$16 range (~15%-30% downside) based on 0.5x-1.0x turns of P/S multiple compression on our 2015 estimate of $1.1B. Note that P recently closed at $16.90 last Tuesday
But the better question is how much do you pay for a company that starts losing users before it generates positive FCF? Or what happens to the stock the first time P prints declining users? Our price target range may be too optimistic.
Let us know if you have any questions, or would like to discuss in more detail.
Hesham Shaaban, CFA
The total percentage of successful long and short trading signals since the inception of Real-Time Alerts in August of 2008.