How Retail MLP Investors Can Profit By A Focus On Growth

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 |  Includes: ACMP, MMP, SXL, WES
by: Factoids

In this article, I examine the proposition that analyst distribution CAGR (Compound Annual Growth Rate) projection awareness aids the retail investor in their selection of a winning MLP (Master Limited Partnerships) portfolio by looking at recent historical evidence.

Let's quickly address three questions before we get into the specific historical two year test that is the focus of this article. How big is current growth? How has distribution growth influenced stock appreciation? Who is exempt from thinking growth first?

How big is current growth?
Which midstream MLPs come to mind when you think of high distribution CAGR MLPs? The list should include large cap midstream MLPs like Magellan Midstream Partners (NYSE:MMP) -- which recently offered guidance of annual distribution growth targets of 16% for 2013 and 15% for 2014 -- and Sunoco Logistics Partners (NYSE:SXL) that announced a distribution that was a 28% increase over last year's August distribution. The list should include gathering and processing MLPs like Access Midstream Partners (NYSE:ACMP) -- which declared a distribution for August that is 15.5% larger than the payment from last August -- and Western Gas Partners (NYSE:WES) -- which declared a distribution for August that is 17% larger than the payment from last August.

How has distribution growth influenced stock appreciation?
When it comes to MLPs, big distribution growth can happen. Distribution growth strongly tends to result in unit price appreciation. Let me show those stats one more time. For this question, I will let the stats do all the talking.

Price Changes and Total Returns Since the Beginning of 2012, 2011 and 2010

07-26-13 12-31-11 Change 12-31-10 Change 12-31-09 Change Dist Growth
Company Price Price Price Pr+Dist Price Price Pr+Dist Price Price Pr+Dist since Q4-09
Large Capped MLPs
BPL Buckeye 71.94 63.98 12.44 22.17 66.83 7.65 22.97 54.45 32.12 57.95 13.51
BWP Boardwalk 32.44 27.67 17.24 28.78 31.13 4.21 21.19 30.03 8.03 32.39 7.58
EPB El Paso 44.03 34.62 27.18 36.92 33.45 31.63 47.29 25.96 69.61 95.76 77.14
EEP Enbridge 32.80 33.19 -1.18 8.58 31.19 5.16 22.25 26.84 22.21 49.60 9.80
EPD Enterprise 63.23 46.38 36.33 44.66 41.61 51.96 67.02 31.41 101.31 128.53 21.27
ETP Energy Trans 51.41 45.85 12.13 23.82 51.82 -0.79 16.46 44.97 14.32 42.14 0.00
KMP Kinder Morgan 85.73 84.95 0.92 9.68 70.26 22.02 39.13 60.98 40.59 67.38 23.81
MMP Magellan 55.72 34.44 61.79 70.04 28.25 97.24 112.81 21.66 157.25 184.26 42.96
NS NuStar 45.61 56.66 -19.50 -7.91 69.48 -34.36 -18.65 56.09 -18.68 8.38 2.82
OKS OneOK 50.28 57.74 -12.92 -5.97 39.75 26.49 42.44 31.15 61.41 88.92 31.19
PAA Plains All-Am 55.00 36.72 49.78 58.63 31.39 75.22 91.78 26.43 108.10 134.88 25.00
WPZ Williams 52.59 59.99 -12.34 -4.31 46.65 12.73 29.27 30.67 71.47 105.26 33.46

14.32 23.76 24.93 41.16 55.64 82.96

Click to enlarge
07-26-13 12-31-11 Change 12-31-10 Change 12-31-09 Change Dist Growth
Company Price Price Price Pr+Dist Price Price Pr+Dist Price Price Pr+Dist since Q4-09
Small Capped MLPs
GEL Genesis 51.48 28.04 83.59 93.60 26.40 95.00 111.87 18.90 172.38 203.84 41.13
HEP Holly 39.50 26.89 46.89 57.14 25.45 55.21 72.79 19.92 98.29 128.99 20.13
SEP Spectra 45.52 31.96 42.43 51.58 32.85 38.57 53.09 29.57 53.94 75.82 25.32
SXL Sunco 62.00 39.40 57.36 64.85 27.86 122.54 138.92 22.30 178.03 205.23 61.27
TCP TCPipelines 51.08 47.43 7.70 17.52 52.00 -1.77 13.04 36.84 38.65 67.54 6.85
TLP Transmontaigne 43.58 33.60 29.70 41.07 36.41 19.69 36.94 27.53 58.30 89.79 8.47

44.61 54.29 54.87 71.11 99.93 128.54

Click to enlarge
07-26-13 12-31-11 Change 12-31-10 Change 12-31-09 Change Dist Growth
Company Price Price Price Pr+Dist Price Price Pr+Dist Price Price Pr+Dist since Q4-09
G&P MLPs
APL Atlas Pipelines 39.27 37.15 5.71 14.89 24.67 59.18 80.22 9.81 300.31 356.78
ACMP Access 47.80 29.00 64.83 73.68 28.77 66.15 80.02 28.77 66.15 81.20
CMLP Crestwood 26.81 31.74 -15.53 -6.02 27.19 -1.40 16.37 20.97 27.85 58.61 30.77
DPM DCP Partners 52.00 47.47 9.54 18.07 37.40 39.04 56.60 29.57 75.85 106.25 16.67
EROC Eagle Rock 8.10 11.65 -30.47 -19.23 8.82 -8.16 14.48 5.79 39.90 76.12 780.00
EXLP Exterran 30.89 20.15 53.30 68.34 26.86 15.00 33.43 22.22 39.02 69.64 11.89
MWE Mark West 67.77 55.06 23.08 31.82 43.31 56.48 73.93 29.27 131.53 166.11 29.69
NGLS Targa 49.53 37.28 32.86 43.34 33.96 45.85 64.00 24.31 103.74 137.74 34.78
RGP Regency 28.32 24.86 13.92 25.02 27.26 3.89 20.60 20.95 35.18 65.42 3.37
WES Western 62.13 41.27 50.55 57.67 30.30 105.05 120.02 23.80 161.05 185.95 68.75
XTEX Cross-Tex 20.88 16.22 28.73 40.88 14.40 45.00 66.81 8.60 142.79 182.21

21.50 31.68 38.73 56.95 102.12 135.09

Click to enlarge
07-26-13 12-31-11 Change 12-31-10 Change 12-31-09 Change Dist Growth
Company Price Price Price Pr+Dist Price Price Pr+Dist Price Price Pr+Dist since Q4-09
Marine Transport MLPs
NMM Navios 15.22 14.74 3.26 21.23 19.45 -21.75 0.82 14.79 2.91 43.85 9.26
MMLP Martin 46.62 34.44 35.37 48.73 39.37 18.42 37.85 31.48 48.09 81.93 3.33
TGP TeeKay 42.55 33.17 28.28 40.35 37.99 12.00 29.18 26.47 60.75 94.35 18.42

22.30 36.77 2.89 22.62 37.25 73.37

Click to enlarge

Who is exempt from thinking growth first?
When the talking heads talk MLPs, they tend to talk yield first. I believe that the data above suggest a different start to the story. For investors under 75, when it comes to thinking about MLPs, think growth first. Except in cases where you are selling to capture the potential capital gains, it takes several years to fully capture the benefits of those rising distributions. That is why I make an exception for those over 75.

It is my expectation that there are those who question the value of using a consensus analyst CAGR projection for MLP distribution as a tool in stock selection. I have shown my evidence that the projections are volatile. I have suggested that you need multiple projections because you should not trust a single projection. Those two caveats might serve to discourage their use. That was not my intention. I have been doing home-made consensus CAGR projections for several years -- and using those projections as a tool in making my buy, sell and hold decisions. In prior articles on MLP CAGRs (part one and part two), I have suggested that the building of your own CAGR projection should be a major component -- or focus -- of your early due diligence. This article will show that the analyst projections have been an effective tool in weeding out low growth MLPs that have under performed the sector.

Let's go back in time for two years to see what recent history is telling us about projected CAGR use in our decisions. Why two years? Because I am about to show some Yahoo Finance graphs for a two year period. I will show my consensus CAGR projection spreadsheet from two years ago. These projections did contain quite a few errors. Those who say that the only thing that is consistent is "change" are missing something. Projection errors are consistent, too. Let's use those projections to make three "menus." One for stocks which have attractive growth prospects, another with the least attractive growth prospects, and one with average growth. I want to see if sorting by CAGR projections creates menus that improve our dining experience.

Then we will ask a short series of simple questions on this data:

(1) Did the high CAGR choices work to steer you to the best options?
(2) Did the low CAGR choices succeed at steering you away from the worst options?
(3) Did the average CAGR projections also result in close to average unit price appreciation?
(4) Did the Yahoo Finance EPS CAGRs appear to be a much help in setting correct CAGRs or in finding the best investments?
(5) Would a consensus CAGR projection be a better tool in selection than "ratings"?

Setting my consensus CAGRs

The names of the brokerages from which I make my consensus CAGRs are redacted. Brokerages own their projections. These are numbers that do not belong in the public domain if you knew their specific source. My consensus analyst CAGR projections are not arithmetic averages of those projections. They are lightly informed by other inputs. Still, I do not want to set a consensus projection that is higher than the high projection -- or lower than the low projection.

The price implied CAGR uses the dividend discount model as the formula. The price as of 8-31-11, the Q3-11 distribution and my required rate of return are used to calculate that metric. Required rates of return varied with the S&P credit ratings. I was very hesitant to set any CAGR that varied more than 150 basis points from the price implied CAGR. Markets tell us when they are ignoring the analyst projections. We need to be aware of those instances.

The market's history of accuracy in projecting growth is in the same neighborhood as the analysts' history for accuracy. Back in August of 2011, the market was wrong about CHKM/ACMP, GEL, MWE, NGLS, OKS, PAA, SEP, SXL, WES and XTEX. All these MLPs had much higher distribution growth since mid-2011 than was implied in their prices. Back in August of 2011, the market was right about BPL, BWP, EEP, EROC, RGP, TLP, WPZ and NMM. All these MLPs had much lower distribution growth since mid-2011 than was implied in the analyst CAGR projections.

Dividend growth inertia and DCF (distributable cash flow) growth projections are also used to influence my CAGR projections. The market discounts the CAGR projections. The market discounts high projections more than moderate projections. I account for some of this discounting in setting my consensus projections. Because of this, I never set a CAGR above 9% for MLPs. The data:

CAGR assignment spreadsheet 8-31-11


Consensus Broker 2011-13 2008-11 LTM 2011 Est. Price My
Co. CAGR Est. CAGR Est DCF/yr Dist/yr Distrib DCF/Dist implied CAGR Explanation
Jun Mar Dec xxx xxx xxx xxx xxx Growth Growth Growth Ratio CAGR

APL 19.5 10.0 11.0 0.0 12.9 14.3 0.0 5.0 21.82% na na 1.26 6.82 9.0 Great Distrib coverage
BPL 8.6 7.9 3.3 4.9 5.2 4.5 5.8 0.0 10.10% 5.80% 5.19 0.98 3.57 5.1 Low cover/good hist
BWP 3.8 4.5 5.0 1.9 1.9 3.5 3.2 3.2 4.28% 3.90% 2.94 0.98 1.83 2.9 Low renewal cntrcts
CHKM 10.0 9.5 7.3 12.0 10.3 7.6 7.9 10.2 6.83% na na 1.18 7.30 9.5 Drop Down Growth
CMLP 7.9 7.9 7.5 6.6 10.6 0.0 10.1 9.3 8.41% 10.48% 9.52 1.16 5.80 8.2 Good DCF Growth
CPNO 3.3 2.5 2.9 1.2 5.7 3.9 2.9 3.1 16.92% 0.89% 0.00 0.96 5.41 4.3 No recent growth
DEP 4.0 4.0 4.2 0.0 4.2 4.0 3.0 4.1 10.22% 3.17% 2.22 1.49 5.67 4.0 Haynesville growth
DPM 4.0 4.5 8.5 5.3 5.0 4.3 5.9 5.4 0.18% 1.94% 4.10 1.20 4.95 5.2 Re-started dist growth
EPB 8.0 8.6 5.0 13.6 11.4 8.6 13.8 14.4 -0.83% 20.90% 20.00 1.41 6.48 8.7 Great coverage
EEP 2.6 3.0 2.5 4.1 3.7 2.7 2.8 3.7 2.52% 2.53% 3.65 1.05 2.53 3.7 Bad dist growth history
EPD 7.9 7.9 5.9 4.9 6.0 4.5 5.2 5.6 1.53% 5.83% 5.22 1.34 4.96 5.6 Huge Cap-Ex
ETP 9.6 6.3 3.5 2.9 3.3 4.0 3.3 3.1 9.89% 0.00% 0.00 0.96 3.27 3.3 Zero recent dist growth
EROC 10.0 7.0 0.0 27.0 13.1 0.0 99.9 0.0 2.37% -18.09% 650.00 1.47 5.94 9.0 New Acquisition
EXLP 3.0 4.8 8.2 0.0 4.8 0.0 0.0 0.0 5.70% 4.51% 4.32 1.25 4.53 4.5 Zero recent dist growth
GEL 6.5 6.5 6.5 7.8 10.5 0.0 11.2 9.7 4.96% 10.58% 10.67 1.20 5.29 8.2 Good dist/DCF ratio
HEP 5.0 5.0 4.5 4.2 6.2 0.0 5.3 4.6 5.46% 5.37% 4.85 1.02 4.38 4.9 Average Growth
KMP 7.8 7.0 3.8 2.8 4.1 2.3 5.3 4.1 2.65% 5.39% 5.50 1.03 3.34 4.1 Low cover/OK growth
MMP 5.7 4.9 4.5 6.8 7.5 4.8 6.9 7.0 5.81% 4.73% 7.17 1.25 4.76 6.8 Low DCF growth
MWE 6.0 6.8 3.5 11.2 10.3 6.8 8.3 10.2 4.85% 3.70% 9.37 1.51 6.17 8.3 Dist growth soon
NGLS 6.0 5.0 6.0 0.0 8.4 5.3 8.5 7.0 -3.89% 3.74% 8.06 1.43 5.05 7.0 Good Dist/DCF Ratio
NS 4.7 2.4 5.0 2.8 2.1 2.7 3.4 3.0 5.95% 3.72% 2.82 1.05 2.80 2.9 Below average growth
OKS 7.6 7.2 6.9 6.5 7.6 5.6 6.3 5.6 4.58% 3.46% 4.46 1.14 4.72 6.2 Low dist growth
PAA 4.1 3.0 3.8 4.1 4.4 4.7 4.6 4.5 -1.22% 3.57% 4.24 1.22 3.49 4.3 Low DCF growth
RGP 4.3 4.5 2.0 5.3 5.2 4.4 4.3 3.4 8.31% 0.37% 1.12 1.03 4.16 4.5 Good foot-print
SEP 6.0 6.0 6.2 3.0 5.8 4.9 8.9 8.0 6.21% 12.25% 8.14 1.10 3.80 4.9 High DCF growth
SXL 5.0 5.0 4.5 5.9 6.3 4.6 6.2 6.0 1.41% 9.98% 6.58 1.45 5.03 6.0 High DCF growth
TCLP 6.1 5.7 4.5 3.0 3.5 4.5 4.2 4.7 6.99% 3.07% 5.48 1.35 3.64 4.5 No DCF growth
TLP 4.0 4.0 4.0 3.2 5.3 0.0 4.8 0.0 0.93% 2.30% 3.33 1.33 3.39 4.2 Great coverage
WES 9.6 8.5 3.1 13.6 13.1 10.8 13.2 11.9 1.88% 11.67% 15.71 1.52 7.54 9.5 Strong DCF growth
WPZ 6.0 5.0 5.0 0.0 7.3 6.0 7.7 7.0 5.05% 5.73% 8.92 1.32 5.49 6.8 Merger
XTEX 6.0 6.0 6.0 0.0 7.9 8.8 0.0 44.2 -3.32% na na 1.65 5.43 7.5 Great dist coverage
NMM 2.3 0.0 0.0 0.0 2.6 0.0 0.0 0.0 -21.69% 8.57% 4.76 1.88 1.90 2.5 Lo Growth Hist
MMLP 4.1 9.7 4.0 1.2 4.2 0.0 3.1 0.0 6.52% 1.01% 1.67 1.04 3.91 3.0 Low growth history
TGP 9.2 15.4 5.0 3.1 3.8 3.5 4.9 3.3 9.35% 4.85% 5.00 1.00 5.02 4.5 OK history
Click to enlarge

As noted before, there were significant errors in my projections for CMLP, EROC, MMP and PAA. There were moderate errors in several others.

The three menus
Below are the graphs of stock price performance over the past two years sorted by the CAGR projections.

The high CAGR menu

Click to enlarge

The average CAGR projection menu

Click to enlarge

The low CAGR menu

Click to enlarge

Now that you have seen the data, let's get to the task of answering the questions I have posed.

(1) Did the high CAGR choices work to steer you to the best options?
Of the ten MLPs with high CAGR projections, five significantly outperformed the sector. Four of those were up over 60%. Three were close to the sector average and two were well below average. The two that were below average would have failed my risk test. I expect to address the issue of risk assessment in upcoming articles.

Of the 27 MLPs in this experiment, only five had appreciation over 60%. The high CAGR projection sort found four of those five. While the percentage of sector beating MLPs was not significantly superior to using a screen for average CAGRs, the capture of the ultra high performers was significantly better screening for high CAGRs.

(2) Did the low CAGR choices succeed at steering you away from the worst options?
Seven out of seven of the low CAGR MLPs underperformed the sector. I would not expect a 100% correlation in each time period this test could be done. But this test suggests that one should have second and third thoughts about buying any MLP with a low consensus CAGR projection.

(3) Did the average CAGR projections also result in close to average unit price appreciation?
Four of the ten MLPs with average CAGR projections significantly outperformed the sector. Three were close to the sector average and two were well below average. PAA was the best performer in this group. PAA had upgrades to its CAGR projection during this period. PAA was the only one in this group that was up over 60%.

(4) Did the Yahoo Finance EPS CAGRs appear to be a much help in setting correct CAGRs or in finding the best investments?
There is a correlation between EPS growth and DCF growth. DCF growth results in distribution growth. So there is some correlation of the Yahoo EPS CAGR and analyst distribution CAGRs. And there are strong similarities between MLPs with high analyst projections and MLPs with high Yahoo EPS CAGRs.

I would argue that the Yahoo projections lack sufficient accuracy to use as a tool in investment decisions. There are some big failures in the Yahoo consensus projections. A good example is ETP with a 9.6% CAGR. There has been no distribution increases for ETP in this two year period -- while the ETP EPS CAGR was one of the higher projections. Compare the CAGRs for ETP and SXL. The Yahoo consensus forecast was for ETP to grow at twice the rate of SXL. The consensus analyst distribution CAGRs shows SXL to grow at twice the rate of ETP. The analysts were more than right.

Compared KMP to MMP. The Yahoo projection for growth was saying buy KMP. The analyst projections were saying buy MMP. The analysts were right.

Compared MWE to WPZ. The Yahoo projection for growth was saying the two options were equal. The analyst projections were saying buy MWE. The analysts were right.

Compared EPD to GEL. The Yahoo projection for growth was saying buy EPD. The analyst projections were saying buy GEL. The analysts were right.

Compared OKS to BPL. The Yahoo projection for growth was saying buy BPL. The analyst projections were saying buy OKS. The analysts were right.

Even with these errors, the Yahoo projections can be used as a tool to confirm the analyst projections. I want to see high analyst distribution CAGR projections confirmed by high Yahoo Finance EPS CAGR projections. But the Yahoo projections are not catching any analyst projection errors -- with the best example being PAA. And the Yahoo projections contain a lot of erroneous CAGR volatility. Examples of this are APL, BPL, DPM, EPB, ETP, EXLP, KMP, RGP, WESM, MLP and TGP.

There is one factor that bothers me when it comes to the Yahoo Finance MLP EPS CAGRs. We do not know which brokerage firm projections are going into the consensus numbers. You are lost without a good DCF projection (a topic covered in a prior article) -- and there are brokerages that fail to show their DCF projections. I do not think they are intentionally hiding them. I think they fail to do them. I would not want to trust an EPS CAGR projection that comes from a firm that fails to also calculate the DCFs. And I suspect that some of the EPS CAGR projections that go into the Yahoo numbers are from such firms.

I have not found problems with using Yahoo CAGR projections in most other sectors. With the exception of BDCs (Business Development Companies) and MLPs, I strongly depend on Yahoo CAGRs in setting my mid-term dividend growth projections. I do not know what causes the MLP problem. I suspect the problem lies with the some of the MLP analysts that make up the Yahoo consensus.

(5) Would a consensus CAGR projection be a better tool in selection than "ratings?"

Given the relative success of the high CAGR projection MLPs, I can see how some of you low due diligence readers looking for a short cut might be tempted to substitute CAGRs for ratings. Don't do that. Here are three reasons why.

CAGR projections do not contain any adjustments for risk. Risk is a major component in valuations. The good thing about risk -- risk assessments have low volatility. The bad thing about risk -- risk has an ego. The minute you forget about risk, risk will remind you of its importance.

2013 has been a year where I have been reminded that stock appreciation is not all about CAGRs. Appreciation results from CAGRs at a reasonable price. It is my perception that the high CAGR MLPs like MMP, PAA, SXL and WES have been relatively average performers in 2013 because they entered the year with relatively low yields.

A high CAGR portfolio could easily be a portfolio that is light on large cap, midstream, geographically diverse, investment grade MLPs. (The same is true with a high yield MLP portfolio.) It is my belief that a good MLP portfolio is heavy on its allocation to these types of MLPs. Those were the MLPs that suffered the least in the 2008 correction. They are the ones that continued their distribution growth in those hard times. The high CAGR MLPs in this lower risk category are the "must own" MLPs. It is my belief that these should be the first ones you buy when you start a MLP portfolio.

Summation
There are too many MLPs to do adequate due diligence on them all. You need tools to point you towards those stocks that will outperform. While screening for high CAGRs is not a perfect tool, it is one I have used with success. I have bought MLPs with superior growth prospects in buckets to increase the odds of owning one of the MLPs that was projected to do great. I have had more success than failure -- but I have had relative failures.

Disclosure: I am long CMLP, DPM, EPB, EPD, GEL, KMP, MMP, MWE, WES. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.