Let me state at the start - this less than accurate claim about MLPs (Master Limited Partnerships) comes from those who write about them - and not the MLPs themselves. But it is a misconception that they could potentially correct, if more of their earnings releases were focused on the components that cause variations in their DCF (Distributable Cash Flow - the key MLP earnings metric). So - of what should you be "skeptical"?
It is hard to do any due diligence on energy pipeline companies without coming across a slew of articles - and comment sections on other articles - that contains a line similar to "Think of pipelines as toll roads whose traffic is oil, natural gas, natural gas liquids." Let me imply motive. These comments were provided to imply that MLPs' earnings would be much less volatile than other commodity sensitive investments. While there is truth in those comments, the comment can lead to a fictitious conclusion. Compared to other sectors, MLP earnings projections are very volatile.
In this article, I will compare earnings volatility for Master Limited Partnership (or MLP) stocks like Enterprise Products Partners (EPD), Kinder Morgan Energy Partners (KMP), Magellan Midstream Partners (MMP) and Plains All American Pipeline (PAA); compare it to the volatility of other sectors that I follow; compare the impact of earnings volatility on the calendar year price changes and total returns for 2013 and 2012 for MLPs; and discuss how this increased amount of volatility should influence your investment behavior.
First, I will show spreadsheets with the 2013 price appreciation and total returns, along with data that tracks the changes in earnings projections during the calendar year. For the purpose of this article, I would ask you to focus on the earnings projection change column in this data presentation.
MLP Midstream 12-31-13
Yields are based on the Q4-13 distribution. Under the 'year to date' header, the change in the distribution is actually the change since Q4-12 - or the change over the last twelve months. The change in the target, EPS, DCF and CAGR is the percentage change in the consensus 2013 projection that has happened since the beginning of the year.
|Current||Distrib/||Q4 Dist||Dist/dcf||Dist/dcf||Year-to-Date Percent Change|
Grocery Portfolio 12-31-13
The Q4-13 div is used for yield calculations. GIS has already declared an increased dividend for Q3-13. HRL has already declared an increased dividend for Q1-14. The second Div/EPS ratio has the 2014 EPS projection as the denominator. HRL purchased Skippy and share prices jumped. FLO make an offer for Hostess and share prices jumped. FLO had a three-for-two split on 6-19-13. "Div 1 yr" measures the change in the dividend since Q4-12. "Div 5 yr" measures the average change in the dividend since Q4-08.
|Company||Price||Price||/Quarter||Yield||EPS13||EPS14||Price||Pr+Div||EPS13||Target||Div 1yr||Div 5yr|
|ArDanMidlnd||ADM||27.39||43.40||0.190||1.75||34 %||23 %||58.45||61.23||-28.30||45.94||8.57||7.14|
|Campbell||CPB||34.89||43.28||0.313||2.89||47 %||50 %||24.05||27.63||3.94||14.23||7.76||5.00|
|Coke||KO||36.25||41.31||0.280||2.71||54 %||50 %||13.96||17.05||-4.57||6.13||9.80||9.47|
|ConAgra||CAG||29.50||33.70||0.250||2.97||46 %||43 %||14.24||17.63||3.85||9.74||0.00||6.32|
|Colgate||CL||52.27||65.21||0.340||2.09||48 %||44 %||24.76||27.36||-4.07||19.77||9.68||14.00|
|Ingredion||INGR||64.43||68.46||0.380||2.22||30 %||26 %||6.25||8.61||-13.80||-4.08||46.15||34.29|
|Clorox||CLX||73.22||92.76||0.710||3.06||66 %||63 %||26.69||30.57||0.00||15.53||10.94||10.87|
|Flowers||FLO||15.35||21.47||0.113||2.10||49 %||43 %||39.87||42.80||18.18||40.50||5.44||13.73|
|General Mills||GIS||40.42||49.91||0.380||3.05||57 %||53 %||23.48||27.24||0.37||17.09||15.15||15.35|
|Hershey||HSY||72.22||97.23||0.485||2.00||52 %||47 %||34.63||37.32||4.79||33.54||15.48||12.55|
|Hormel||HRL||31.21||45.17||0.200||1.77||41 %||35 %||44.73||47.29||1.55||52.47||17.65||23.24|
|Kellogg||K||55.85||61.07||0.460||3.01||49 %||46 %||9.35||12.64||3.58||15.52||4.55||7.06|
|Kimberly-Clark||KMB||84.43||104.46||0.810||3.10||57 %||53 %||23.72||27.56||2.33||18.11||9.46||7.93|
|Lancaster||LANC||69.19||88.15||0.440||2.00||44 %||44 %||27.40||29.95||-1.24||3.14||15.79||10.88|
|McCormick||MKC||63.53||68.92||0.340||1.97||43 %||39 %||8.48||10.62||-6.85||9.03||9.68||8.33|
|Pepsi||PEP||68.43||82.94||0.568||2.74||52 %||48 %||21.20||24.52||-1.59||19.22||5.58||6.71|
|Procter&Gamble||PG||67.89||81.41||0.603||2.96||60 %||56 %||19.91||23.46||2.27||16.07||7.11||10.13|
|JM Smucker||SJM||86.24||103.62||0.580||2.24||43 %||40 %||20.15||22.84||3.07||26.47||11.54||16.25|
|Average||2.48||48 %||45 %||24.52||27.57||-0.92||19.91||6.18||12.18|
Next, I will compile and compare the stats on earnings projection volatility. For the MLPs, 19 of 32 of the non-marine midstream stocks had earnings projection volatility (in their DCF/share) in the double digits (or more than a 10% variance). Fifteen of the 19 were downgrades. For 2012, 13 of 30 had double-digit volatility. Nine of the 13 were downgrades. For the "Grocery List" stocks, 3 of 18 had EPS volatility in the double digits. Two of those three are more involved in providing commodities (Archer Daniels Midland and Ingredion) - and probably do not belong in this sector grouping. FLO acquired portions of Hostess, and had upgrades it its earnings projection. For 2012, 2 of the 19 in the sector (Heinz was a member back then) had earnings projection volatility in the double digits. One of those two was, once again, ADM.
In an effort to minimize the number of spreadsheets, let me summarize the data for some of the other sectors I follow. What follows is the data for 2013.
For the technology and industrial stocks, 4 of the 24 had EPS earnings projection volatility of more than 10%.
For the banks of the South and West, 5 of the 19 had EPS earnings projection volatility of more than 10%.
For the banks of the North and East, 4 of the 18 had EPS earnings projection volatility of more than 10%.
For Health Care REITs (Real Estate Investment Trusts), 2 of the 14 had FFO earnings projection volatility of more than 10%. One of those was a 2013 IPO.
For Multi-Family REITs, 3 of the 12 had FFO earnings projection volatility of more than 10%. Two of those twelve had write-downs (or accelerated costs) related to major acquisitions that impacted the FFO projections.
For Retail REITs, 2 of the 22 had FFO earnings projection volatility of more than 10%. Both of those instances upgrades.
For Office and Industrial REITs, 4 of the 21 had FFO earnings projection volatility of more than 10%. Three of those four were downgrades.
For BDCs (Business Development Companies), 13 of the 29 had EPS earnings projection volatility of more than 10%.
What follows is the data for 2012.
For the technology and industrial stocks, 6 of the 24 had EPS earnings projection volatility of more than 10%.
For the banks of the South and West, 12 of the 19 had EPS earnings projection volatility of more than 10%.
For the banks of the North and East, 11 of the 18 had EPS earnings projection volatility of more than 10%.
For Health Care REITs, 2 of the 8 had FFO earnings projection volatility of more than 10% - both of them upgrades.
For Multi-Family REITs, 1 of the 12 had FFO earnings projection volatility of more than 10%.
For Retail REITs, 2 of the 22 had FFO earnings projection volatility of more than 10% - both of them downgrades.
For Office and Industrial REITs, 4 of the 21 had FFO earnings projection volatility of more than 10%.
For BDCs, 12 of the 29 had EPS earnings projection volatility of more than 10%.
At the end of 2012, banks mostly had median P/Es in the 12s. At the end of 2013, banks had P/E in the 17s. Why? Well, banks borrow at short-term rates and lend at longer-term rates. Short-term rates are flat and long-term rates are rising. So there is an expectation that bank net interest margins will rise. But this numbers guy will tell you that one of the factors in their valuation increase is the decrease in earnings projection volatility.
Why do REITs have lower yields than MLPs while at the same time having lower dividend projection growth? This numbers guy will tell you that the one key factor is their lower earnings projection volatility. While this REIT investor is not totally happy with REIT earnings releases due to the absence of FAD stats in way too many reports, I will testify that even the current and faulty REIT earnings releases have far superior transparency than MLP earnings releases. Transparency is a factor in market valuations.
Projection volatility differs - but does that matter?
Why do BDCs and MLPs offer the highest yields of the above listed alternatives? They are the two sectors with the highest earnings projection volatility. Why do large cap midstream stocks have lower "yield plus distribution CAGRs" than the gathering and processing midstream MLPs? They have lower earnings projection volatility. Why do midstream stocks have lower yields than the exploration and production MLPs? They have lower earnings projection volatility.
I should have already made the point that earnings projection volatility matters by sector; and that the volatility for MLPs is relatively high. But, does volatility matter on a stock by stock basis? I am going to pretend that you can handle mountains of data. So far, this article has only climbed a hill. Let's keep on moving - and look at the next data set.
Intra-year DCF Estimate Increases and Year to Date Returns - 2013: The following companies had 2013 DCF estimate increases since the beginning of 2013: ACMP, EPD, ETP, EXLP, MMP, OILT, PAA and SXL. Their mean price gain for the year is 45.03%. Their mean total return for the year is 51.40% - and 6 of the 8 beat the sector median yearly price gain of 32.47%. Their average historical DCF projection accuracy rating is 1.61.
The following companies had 2013 DCF estimate decreases since the beginning of the year: AMID, APL, BKEP, BPL, BWP, CMLP, DPM, EPB, EEP, EQM, GEL, HEP, KMP, MWE, NGLS, NS, OKS, RGP, SEP, TCP, TLLP, TLP, WES, WPZ and XTEX. Their mean price gain for the year is 28.09%. Their mean total return for the year is 35.55% - and 7 of the 25 beat the sector median yearly price gain. Their average accuracy rating is 2.58.
There are problems in having apples to apples numbers. It is like that every year. There are always exceptions that need to be weeded out to see the true trends. And 2013 was like that. Let me do an instant replay of the same test on the data - this time doing some needed weeding.
The following companies - editing out AMID and XTEX (which had CAGR changing events in transactions involving their General Partners) - had 2013 DCF estimate decreases since the beginning of the year: APL, BKEP, BPL, BWP, CMLP, DPM, EPB, EEP, EQM, GEL, HEP, KMP, MWE, NGLS, NS, OKS, RGP, SEP, TCP, TLLP, TLP, WES and WPZ. Their mean price gain for the year is 22.35%. Their mean total return for the year is 29.49% - and 5 of the 23 beat the sector median yearly price gain. Their average accuracy rating is 2.41.
Data for 2012: The following companies had 2012 DCF estimate increases since the beginning of 2012: ACMP, EPD, GEL, HEP, KMP, MMP, NGLS, OKS, PAA, SXL, TLP and WES. Their mean price gain for the year is 13.69%. Their mean total return for the year is 19.71% - and 10 of the 12 beat the sector average yearly price gain of -2.62%. Their average historical DCF projection accuracy rating is 1.33.
The following companies had 2012 DCF estimate decreases since the beginning of the year: APL, BPL, BWP, CMLP, CPNO, DPM, EPB, EEP, ETP, EROC, EXLP, MWE, NS, RGP, SEP, TCP, WPZ and XTEX. Their mean price gain for the year is -13.22%. Their mean total return for the year is -6.27% - and 3 of the 18 beat the sector average yearly price gain. Their average historical DCF projection accuracy rating is 2.50.
Data for 2011: The following companies had 2011 DCF estimate increases since the beginning of 2011: APL, CHKM, CMLP, EPB, EPD, EROC, EXLP, KMP, MMP, MWE, NGLS, OKS, PAA, SXL, TLP, WES, WPZ and XTEX. Their mean price gain for the year is 19.07%. Their mean total return for the year is 25.77% - and 14 of the 18 beat the sector average price gain of 8.32%. Their average historical DCF projection accuracy rating is 2.39.
The following companies had 2011 DCF estimate decreases since the beginning of the year: BPL, BWP, CPNO, DPM, EEP, ETP, GEL, HEP, NS, RGP, SEP and TCLP. Their mean price gain for the year is -1.59%. Their mean total return for the year is 4.93% - and 1 of the 12 beat the sector average yearly price gain. Their average historical DCF projection accuracy rating is 2.75.
Before I continue on about MLPs, I need to note that the very strong correlation between total returns and earnings projection changes is something that is atypical. I will go back to the data from my grocery list portfolio.
The Importance of EPS Revisions in 2013 - The following companies had growing EPS estimates since the beginning of 2013: CPB, CAG, FLO, GIS, HSY, HRL, K, KMB, PG and SJM. Their mean price gain for the year is 25.41%. Their mean total return for the year is 28.64% - and 3 of the 10 beat the sector average yearly price gain.
The following companies had decreases to the EPS estimates since the beginning of 2013: ADM, KO, CL, INGR, LANC, MKC and PEP. Their mean price gain for the year is 22.93%. Their mean total return for the year is 25.62% - and 3 of the 7 beat the sector median yearly price gain.
For 2012: The following companies had growing EPS estimates since the beginning of 2012: CPB, CAG, INGR, CLX, HNZ (Heinz), HSY and HRL. Their mean price gain for the year is 11.35%. Their mean total return for the year is 14.28% - and 4 of the 7 beat the sector average yearly price gain.
The following companies had decreases to the EPS estimates since the beginning of 2012: ADM, KO, CL, FLO, GIS, K, KMB, LANC, MKC, PEP, PG and SJM. Their mean price gain for the year is 8.45%. Their mean total return for the year is 11.39% - and 6 of the 12 beat the sector average yearly price gain.
For 2011: The following companies had growing EPS estimates since the beginning of 2011: ADM, CPB, CPO (which is now INGR), HSY, HRL, LANC and SJM. Their mean price gain for the year is 12.95%. Their mean total return for the year is 15.41% - and 5 of the 7 beat the sector average yearly price gain. The positive results from HSY alone were enough to skew the superior total returns from this grouping of stocks.
The following companies had decreases to the EPS estimates since the beginning of 2013: KO, CL, CLX, FLO, HNZ, K, KFT (which was deleted from my coverage universe when it divided itself into two separate companies), KMB, MKC, PEP, PG and SLE (Sara Lee). Their mean price gain for the year is 8.13%. Their mean total return for the year is 11.46% - and 3 of the 12 beat the sector average yearly price gain.
Why would there be less price depreciation in this sector (compared to MLPs) in the stocks that had falling earnings projections? (1) When there are downward EPS projection adjustments, they strongly tend to be smaller. (2) When there are downward EPS projections, they are rarely to the degree that the dividend would appear threatened. Put in different words, the dividend coverage ratios are much stronger in the grocery sector. (3) This "grocery list" sector is full of stocks that have long histories of consistently raising their dividend. The only dividend cut in the last decade was from CAG in 2007. And CAG really does not belong in this grouping. On the other hand, distribution cuts have happened with MLPs. APL, ATLS, BBEP, EROC, OXF, XTEX and XTXI have all had cuts. Close to half of MLPs in my coverage universe have had pauses in their distribution growth - or periods of noticeable declines in their growth rate. I would speculate that there is a synergy in those three factors that insulate the grocery stocks from price declines when earnings projections are cut.
I want to flash back to the MLP and their correlation between total returns and DCF estimate changes. The lesson I draw from the numbers - If you are going to have a portfolio that beats the sector average, then you are going to have to own the stocks that had rising DCF projections. In any given year, that is a game of chance. But over the long term, you are best served by owning a high weighting in stocks that have better than average earnings projection accuracy. Those stocks have strongly tended to be large-cap midstream Enterprise Products Partners, Kinder Morgan Energy Partners, Magellan Midstream Partners and Plains All American Pipeline.
The above data set gave reference to my DCF projection accuracy ratings. Let's look at that data:
Changes in DCF estimates by Year: Some MLPs Have Assets That Produce More Predictable DCFs
This is a data set that is worthy of a full article of discussion - but we don't have the time for that today. I am going to keep moving on. Today, I said I would try to answer how this increased amount of earnings volatility should influence your investment behavior when it comes to your MLP portfolio. I am moving on to the one spreadsheet that is the dominant one that should influence your valuation assessments - the "Yield + CAGR Total Return Expectations" spreadsheet.
Yield + CAGR Total Return Expectations 1-17-2014
|Company||Q4-13||Consensus||Total||Bonds||DCF||My||Total Rtn||Consensus||Pr Impl||Distribution|
|Yield||CAGR||Return||Ratings||Accr||RRRs||- RRR||Ratings||CAGR||/14 DCF|
|Large Cap Midstream|
|Company||Q4-13||Consensus||Total||Bonds||DCF||My||Total Rtn||Consensus||Pr Impl||Distrib|
|Yield||CAGR||Return||Ratings||Accr||RRRs||- RRR||Ratings||CAGR||/ DCF|
|Small Cap Midstream|
|Company||Q4-13||Consensus||Total||Bonds||DCF||My||Total Rtn||Consensus||Pr Impl||Distrib|
|Yield||CAGR||Return||Ratings||Accr||RRRs||- RRR||Ratings||CAGR||/ DCF|
|Gathering & Processing|
I am frequently asked on message boards, in comment sections after articles, in comment sections after InstaBlogs and in private messages "Which MLPs do you think will outperform in 2014." I point to the data in the spreadsheet that is immediately above for my best answer. But this article should tell you one big fact: The returns in a given year are all about the variances between the current earnings projections and the end of the year earnings projections. Pinpointing those specific stocks is a crap shoot. But it is also a game where the die is loaded. The historical record tells you which stocks are least likely to have negative surprises.
So what should you be expected to do with this data? I would say you need to invest in a fairly wide assortment of stocks that have the favorable metric attributes. That is the key point in today's lesson - "cast a wide net," but only for those stocks with favorable metric attributes. Given the number of MLPs out there - that should not be a difficult task. If you want a safer than average portfolio, then have higher weighting in those stocks with greater earnings projection accuracy. If you want a portfolio that has higher unit price growth, buy higher distribution CAGR projection stocks. If you want a higher yield, then throw in an E&P MLP or two with a well-covered distribution. If your desire for yield results in a very low weighting of MLP General Partner shares - then you are sub-optimizing your total return. An alternative solution to generating more yield from your total portfolio would be to raise you weighting in MLPs to gain that yield. But I have told you this stuff before.
An ending note: This article was written for those already familiar with MLPs. For those wanting access to materials that are made for beginners, I would direct you to the National Association of Publicly Traded Partnerships. A selection of presentations and primers can be found by clicking here.
To summarize the findings in this article: (1) MLP earnings projections are relatively volatile. The "toll road" analogy will lead one to an impression that is inaccurate. (2) Total returns in a given year are strongly influenced by that volatility. (3) Earnings projection volatility varies by MLP - and by MLP sub-sector. (4) Due to that earnings projection volatility, I strongly believe that data is telling us to cast a wide net in selecting the components in our MLP portfolios. I also believe the data is telling us to have a major weighting in MLPs that have a historical record of superior earnings projection accuracy.