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There are investment gurus who define "value investing" as finding and buying an unloved stock on the basis of its yield and price-to-earnings ratio. They write that a stock with a low price-to-earnings ratio would have less to fall in a market downturn because it already is relatively cheap. They argue that using such a strategy results in a portfolio with a better yield and a better total return via share price appreciation. They also argue that you are buying a safety cushion when you buy higher yielding and low valuation stocks. It is a "buy one (a cheap price), get three free (yield, potential price appreciation and safety). That sounds great. That is what they are calling "value investing."

In this article, I will present stats, from the midstream MLP (energy Master Limited Partnership) sector, that indicate this - in the large majority of cases - is too good to be true. This is an out of consensus opinion. I would call the above stated strategy "cheapest price" investing. A cheap stock at a cheap price is only a fair value. A great stock at a moderate price is a value - but the occasions when you can find such values are few and far between.

This is a continuation of my prior articles on asset quality on
MLPs, Health Care REITs and Regional Banks. In those articles, I presented data that has led me to believe that there are identifiable attributes that make one stock a more valuable than another based on the increased level of safety that comes from the assets they own. The failure to assess individual RRRs (required rates of return) for each stock, by an assessment of asset quality, will result in a failure to differentiate the relatively good from the fair - and the fair from the relatively bad. The same is true when it comes to assessing CAGR (distribution Compound Annual Growth Rate) projections.

Too many MLP investors see the world in "yield plus CAGR" terms without making as assessment of risk. That "yield plus CAGR" perception is an upgrade from seeing the world without a CAGR perception. In the world of the blind, the one-eyed man is king. And on becoming a relative king, most CAGR-aware investors are content. But a one eyed man lacks depth perception. Lacking depth perception, such a king could lead his men into battle in disadvantageous places and be defeated. Lacking value perception, we can lead our portfolio into disadvantageous investments and suffer suboptimal results. Using such a simple metaphor, it is easy to argue for an increased perception of value. It is my task in this article to provide evidence that the metaphor fits.

Let's start with the posting of year-to-date data from 2013 - and full-year returns from 2012 and 2011. That is followed by the current price-to-earning ratios - based on DCF (Distributable Cash Flow) data.

MLP Midstream 09-20-13

Yields are based on the Q3-13 distribution. Under the 'year to date' header, the change in the distribution is actually the change since Q3-12 - or the change over the last year. 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.


CurrentDistrib/Q3 DistDist/dcfDist/dcfYear-to-Date Percent Change
PriceQuarterYield20132014PricePr+DistEPSTargetDCFDist*cagr

Atlas PipelinesAPL38.420.62006.4584.6478.4821.7027.59-1.128.93-4.8710.71-1.09
BuckeyeBPL66.101.06256.4397.2587.2745.5652.580.6125.330.922.41127.78
BoardwalkBWP29.950.53257.11102.90100.9520.2826.70-14.975.09-8.410.00-4.76
ChesapeakACMP46.800.48504.1570.5563.4039.5343.87-21.8234.6615.5515.486.67
CrestwoodCMLP24.900.51008.19105.1597.6115.6522.76-61.904.57-11.822.00-26.67
DCP PartnersDPM48.820.71005.8297.5982.5616.9322.041.8211.72-9.635.973.17
El PasoEPB41.190.63006.1292.9990.0011.4116.53-2.339.96-1.8114.55-21.43
EnbridgeEEP29.720.54357.31115.6496.196.5212.37-33.08-2.37-15.320.00-10.00
EnterpriseEPD61.370.68004.4370.6567.4922.5426.625.5815.272.947.0911.67
Energy TransETP51.340.89386.9686.1476.0619.5925.8422.9615.105.870.0016.67
Eagle RockEROC6.500.220013.54111.3997.78-24.86-17.23-84.85-11.06-26.170.00-83.33
ExterranEXLP27.310.52257.6573.3374.9134.7342.4669.2318.6010.473.98-15.00
GenesisGEL50.210.51004.0675.5664.3540.5744.85-5.9245.1310.6610.8721.43
HollyHEP33.430.48505.8097.0088.581.646.07-24.677.97-9.096.5915.38
Kinder MorganKMP80.031.32006.6097.7891.830.305.261.593.99-4.427.3222.22
MagellanMMP56.040.53253.8080.6872.9529.7533.4512.2231.896.8813.003.53
Mark WestMWE70.290.84004.7896.5569.5737.8042.74-35.4330.47-19.075.00-3.37
TargaNGLS50.140.71505.7099.3182.6634.1439.87-30.0815.61-15.7911.28-5.00
NuStarNS37.971.095011.54125.50106.57-10.62-2.88-51.64-10.24-14.880.00-25.00
OneOKOKS52.800.72005.4598.2987.27-2.201.80-14.29-11.91-9.299.09-20.73
Plains All-AmPAA53.620.58754.3872.0972.3118.5222.4212.2223.149.0310.3341.67
RegencyRGP28.280.46506.5898.9486.9230.4436.88-45.4512.18-6.931.09-12.50
SpectraSEP42.560.50884.7896.9173.2136.2841.17-5.9933.94-1.414.9171.43
SuncoSXL65.550.60003.6656.0755.3031.8135.4313.2426.4926.2527.6630.88
TCPipelinesTCP48.840.81006.6389.2686.1721.0127.03-7.326.020.283.85-11.76
TransmontaigneTLP41.400.65006.2874.2972.229.0314.17-21.7621.83-1.411.5620.69
WesternWES58.700.56003.8288.8974.9223.2426.77-11.0525.07-13.1016.673.33
WilliamsWPZ52.990.86256.51108.4993.758.9014.22-40.73-7.14-16.758.83-16.92
Cross-TexXTEX19.630.33006.7293.6285.7134.9141.720.0023.11-35.020.000.00

Pipeline Average 6.2591.6481.9619.8325.28-12.9314.2510.83
Shipping
NaviosNMM14.260.442512.41101.14121.2316.1226.93-16.84-5.606.060.000.00
MartinMMLP44.670.78006.9897.2089.4043.8251.3512.8029.10-6.142.306.45
TeeKayTGP43.340.67506.2393.4396.0914.7220.08-6.765.63-6.170.00-60.00

Shipping Average 8.5193.00 24.8932.76-3.609.71

MidStream Average 6.4792.1683.8720.3125.98-12.0513.83

MLP Midstream Stats for 2012

EPD's DCF jump from the sale of units in ETE is weeded out from the consensus data. Yields are based on the Q4-12 distribution. Under the 'year to date' header, the change in the distribution is actually the change since Q4-11 - or the change over the last year.


12-31-11CurrentDistrib/Q4 DistDist/dcfDist/dcfYear-to-Date Percent Change
PricePriceQuarterYield20122013PricePr+DistEPSTargetDCFDist*cagr

APL37.1531.570.57007.2291.9474.03-15.02-8.88-38.24-4.01-12.985.560.00
BPL63.9845.411.03759.14110.3795.84-29.02-22.54-22.35-19.08-13.961.22-65.38
BWP27.6724.900.53258.5598.1694.25-10.01-2.31-4.20-3.92-1.360.955.00
ACMP29.0033.540.43505.1979.0973.1115.6621.66-12.5025.8411.6815.850.00
CMLP31.7421.530.51009.4898.5592.73-32.17-25.74-58.50-13.17-13.756.25-47.06
CPNO34.2031.630.57507.27106.4883.33-7.51-0.79-68.89-2.28-28.000.0034.15
DPM47.4741.750.68006.51101.4984.47-12.05-6.3219.633.51-7.596.2531.25
EPB34.6236.970.58006.2889.2384.066.7913.49-7.933.00-3.7018.37-12.50
EEP33.1927.900.54357.79110.9297.93-15.94-9.39-33.13-1.63-17.302.07-11.76
EPD46.3850.080.65005.1975.3669.527.9813.5815.9320.659.526.1211.11
ETP45.8542.930.89388.3396.6291.20-6.371.4368.40-1.11-7.500.000.00
EROC11.658.650.220010.1788.0082.24-25.75-18.20-82.76-21.51-13.0410.00-29.41
EXLP20.1520.270.507510.0182.5278.680.6010.672.99-5.32-6.824.10-11.11
GEL28.0435.720.47255.2983.2677.4627.3934.13-10.6423.760.8910.53-12.50
HEP53.7865.780.92505.6287.8984.0922.3129.19-8.8120.874.735.718.33
KMP84.9579.791.26006.3296.3789.20-6.07-0.14-4.3316.133.988.6212.50
MMP68.8886.380.97004.4987.0078.7025.4131.049.7038.992.5321.2521.43
MWE55.0651.010.81006.3585.7175.35-7.36-1.47-31.41-3.29-20.4210.961.14
NGLS37.2837.380.66257.0983.6077.490.277.38-29.6913.730.6313.7311.11
NS56.6642.481.095010.31139.94106.83-25.03-17.30-69.47-17.43-33.400.00-20.00
OKS57.7453.990.68505.0883.0384.83-6.49-1.7513.1620.0611.1115.132.50
PAA73.4590.481.08504.8070.0072.5823.1929.0946.3538.7234.209.0533.33
RGP24.8621.680.46008.4998.9291.09-12.79-5.39-47.46-7.21-6.531.1017.07
SEP31.9631.230.49006.2894.2392.02-2.283.85-6.182.59-6.734.26-16.00
SXL39.4049.730.51754.1655.9561.0626.2231.4755.1458.3542.8625.219.68
TCP47.4340.360.78007.7380.8386.19-14.91-8.33-14.85-8.17-5.391.30-20.93
TLP33.6037.970.64006.7470.9172.1113.0120.6321.8622.065.873.233.57
WES41.2747.630.50004.2074.9168.9715.4120.26-21.8926.456.3719.050.00
WPZ59.9948.660.80756.6495.0084.55-18.89-13.50-44.95-1.46-22.738.03-7.14
XTEX16.2214.550.33009.0780.0060.83-10.30-2.160.00-7.53-2.946.45-25.00

Pipeline Average 6.9989.8882.16-2.464.12-12.177.2511.95
Shipping
NMM14.7412.280.442514.4193.65107.27-16.69-4.68-9.63-21.6311.180.57-66.67
MMLP34.4431.060.77009.9295.3690.06-9.81-0.87-10.76-1.93-17.180.980.00
TGP33.1737.780.67507.1590.0087.6613.9022.043.037.610.007.1411.11

Shipping Average 10.4993.00 -4.205.50-5.79-5.32

MidStream Average 7.3190.1683.33-2.624.25-11.596.11

MLP Midstream Stats for 2011

There is more than one way to calculate a yield. Several sites use the sum of the last four distributions divided by the current price. I don't. I use the distribution from the most recent quarter in which all MLPs have announced a distribution. Yields below are calculated using the formula of four times the calendar Q4-11 distribution divided by the price for the day of the update.


12-31-10CurrentDistrib/Q4 DistDist/dcfDist/epsYear-to-Date Percent Change
PricePriceQuarterYieldRatioRatioPricePr+DistEPSTargetDCFDistcagr

APL24.6737.150.54005.8175.79127.0650.5959.34840.9860.2725.9554.2984.00
BPL66.8363.981.02506.4193.82117.48-4.261.87-1.775.04-8.635.1315.56
BWP31.1327.670.52757.6395.91147.55-11.11-4.34-16.35-8.45-12.282.43-50.00
CHKM28.7729.000.37555.1876.2498.820.806.02-4.267.037.8811.26na
CMLP27.1931.740.48006.0580.00130.6116.7323.80-15.8612.8722.2914.2921.43
CPNO33.7534.200.57506.7376.67255.561.338.15-81.8218.46-6.200.0017.14
DPM37.4047.470.64005.3988.28157.0626.9333.7745.2623.85-4.174.9220.00
EPB33.4534.620.49005.6672.5986.343.509.36-1.851.304.3519.51-15.79
EEP62.3866.381.06506.4289.68133.126.4113.24-13.588.97-4.193.6536.00
EPD41.6146.380.61255.2877.78108.4111.4617.3512.908.3620.215.15-12.90
ETP51.8245.850.89387.8089.38143.00-11.52-4.62-41.73-9.15-4.760.00-16.67
EROC8.8211.650.20006.8769.57137.9332.0941.1620.6944.490.98700.0070.00
EXLP26.8620.150.48759.6873.86291.04-24.98-17.72-81.487.492.034.28-13.46
GEL26.4028.040.42756.1076.00121.286.2112.69-10.669.13-8.6810.320.00
HEP50.9153.780.87506.5187.06118.645.6412.511.6211.17-2.474.7911.63
KMP70.2684.951.16005.4692.25200.8720.9127.510.007.420.644.5011.11
MMP56.5068.880.80004.6573.5688.6421.9127.5820.1313.917.637.3840.00
MWE43.3155.060.73005.3061.47105.4227.1333.8765.4146.2624.2914.06158.82
NGLS33.9637.280.58256.2573.97121.359.7816.6419.8630.8613.158.3746.94
NS69.4856.661.09507.7393.19136.45-18.45-12.15-10.98-7.25-7.481.86-7.41
OKS79.50115.481.19004.1280.0089.4745.2651.2546.8033.3610.675.31128.57
PAA62.7973.450.99505.4286.1593.6516.9823.3261.618.1630.864.684.65
RGP27.2624.860.45507.3291.46308.47-8.80-2.13-33.82-0.39-7.042.25-2.38
SEP32.8531.960.47005.8884.30105.62-2.713.01-9.78-11.38-5.096.82-30.56
SXL83.59118.201.24004.2063.8468.0441.4047.3440.7925.1833.005.98-6.06
TCLP52.0047.430.77006.4975.49101.65-8.79-2.8710.074.50-0.522.6730.30
TLP36.4133.600.62007.3872.73115.35-7.72-0.91-9.52-9.291.543.33-15.15
WES30.3041.270.42004.0766.9383.5836.2041.754.3746.4111.6313.513.45
WPZ46.6559.990.74754.9867.9579.5228.6035.0116.1921.2814.088.7329.63
XTEX14.4016.220.31007.6472.942480.0012.6421.250.0025.5816.6724.0060.00

Pipeline Average 6.1585.14 10.8017.4329.1114.5210.65
Shipping
NMM19.4514.740.440011.94103.53130.37-24.22-15.172.19-0.85-9.374.76na
MMLP39.3734.440.76258.8678.21193.04-12.52-4.78-10.9567.65-8.861.673.33
TGP37.9933.170.63007.6084.00127.27-12.69-6.05-25.821.08-4.445.00-4.26

Shipping Average 9.4683.98 -16.48-8.67-11.5322.63

MidStream Average 6.4585.03 8.3215.0625.4115.25

MLP Price/DCF Stats by Category 09-20

DCF / UnitDCF GrowthPrice/DCF Ratios
Co.2008200920102011201220132014201511-1212-1313-1414-152012201320142015
Large Capped MLPs
BPL3.504.054.133.623.764.374.875.133.87%16.22%11.44%5.34%17.5815.1313.5712.88
BWP2.051.672.161.952.172.072.112.1811.28%-4.61%1.93%3.32%13.8014.4714.1913.74
EPB1.411.692.272.452.602.712.802.976.12%4.23%3.32%6.07%15.8415.2014.7113.87
EEP2.292.132.272.201.961.882.262.47-10.91%-4.08%20.21%9.29%15.1615.8113.1512.03
EPD2.682.603.173.553.453.854.034.37-2.82%11.59%4.68%8.44%17.7915.9415.2314.04
ETP4.323.553.403.503.704.154.704.575.71%12.16%13.25%-2.77%13.8812.3710.9211.23
KMP4.174.154.404.705.235.405.756.0811.28%3.25%6.48%5.74%15.3014.8213.9213.16
MMP1.781.511.832.032.232.642.923.319.85%18.39%10.61%13.36%25.1321.2319.1916.93
NS5.864.894.454.603.133.494.114.64-31.96%11.50%17.77%12.90%12.1310.889.248.18
OKS2.982.312.323.303.302.933.303.870.00%-11.21%12.63%17.27%16.0018.0216.0013.64
PAA2.012.052.052.633.103.263.253.1017.87%5.16%-0.31%-4.62%17.3016.4516.5017.30
WPZ3.652.983.744.253.403.183.683.97-20.00%-6.47%15.72%7.88%15.5916.6614.4013.35

Average 0.03%4.68%9.81%6.85%16.2915.5814.2513.36

DCF / UnitDCF GrowthPrice/DCF Ratios
Co.2008200920102011201220132014201511-1212-1313-1414-152012201320142015
Small Capped MLPs
GEL2.211.942.162.002.272.703.173.8013.50%18.94%17.41%19.87%22.1218.6015.8413.21
HEP1.651.721.751.832.102.002.192.3314.75%-4.76%9.50%6.39%15.9216.7115.2614.35
SEP1.622.092.002.052.082.102.782.401.46%0.96%32.38%-13.67%20.4620.2715.3117.73
SXL1.942.131.942.903.704.284.343.9027.59%15.68%1.40%-10.14%17.7215.3215.1016.81
TCP4.184.003.904.003.863.633.763.86-3.50%-5.96%3.58%2.66%12.6513.4512.9912.65
TLP3.153.243.443.303.613.503.603.539.39%-3.05%2.86%-1.94%11.4711.8311.5011.73

Average 10.53%3.64%11.19%0.45%16.7216.0314.3314.41

DCF / UnitDCF GrowthPrice/DCF Ratios
Co.2008200920102011201220132014201511-1212-1313-1414-152012201320142015
G&P MLPs
APL3.850.901.672.302.482.933.163.637.83%18.15%7.85%14.87%15.4913.1112.1610.58
ACMP0.000.001.541.802.202.753.063.1222.22%25.00%11.27%1.96%21.2717.0215.2915.00
CMLP1.662.071.972.002.071.942.093.003.50%-6.28%7.73%43.54%12.0312.8411.918.30
DPM2.422.692.482.772.682.913.444.03-3.25%8.58%18.21%17.15%18.2216.7814.1912.11
EROC2.341.621.051.001.000.790.900.960.00%-21.00%13.92%6.67%6.508.237.226.77
EXLP3.142.192.262.502.462.852.792.41-1.60%15.85%-2.11%-13.62%11.109.589.7911.33
MWE3.362.943.484.303.783.484.836.07-12.09%-7.94%38.79%25.67%18.6020.2014.5511.58
NGLS3.142.552.653.303.172.883.463.87-3.94%-9.15%20.14%11.85%15.8217.4114.4912.96
RGP2.541.591.821.901.861.882.142.00-2.11%1.08%13.83%-6.54%15.2015.0413.2114.14
WES1.401.582.212.402.672.522.993.2211.25%-5.62%18.65%7.69%21.9923.2919.6318.23
XTEX2.521.371.642.001.651.411.541.86-17.50%-14.55%9.22%20.78%11.9013.9212.7510.55

Average 0.39%0.38%14.32%11.82%15.2815.2213.2011.96

DCF / UnitDCF GrowthPrice/DCF Ratios
Co.2008200920102011201220132014201511-1212-1313-1414-152012201320142015
Marine Transport MLPs
NMM1.601.701.902.101.891.751.461.50-10.00%-7.41%-16.57%2.74%7.548.159.779.51
MMLP3.663.313.073.053.233.213.494.185.90%-0.62%8.72%19.77%13.8313.9212.8010.69
TGP2.402.422.512.503.002.892.813.4420.00%-3.67%-2.77%22.42%14.4515.0015.4212.60

Average 5.30%-3.90%-3.54%14.98%11.9412.3512.6610.93

We know from the bond market that risk is a component in the pricing of investments. Treasuries yield less than AAA rated bonds of the same duration due to their lower risk. AAA rated bonds yield less than BBB rated bonds - as so on. We inherently know that. Many investors forget this when it comes to equities. Even an informed investor is rarely provided the data to size the importance of the risk attribute when it comes to equity valuation.

I will start my parsing of the data with a presentation showing the evidence that a "required rate of return" is at least partially priced into MLPs.

The relationship between credit ratings and yields:

The following midstream companies had their S&P corporate credit ratings equal to BBB+ or BBB: BWP, EEP, EPD, KMP, MMP, OKS, PAA, SEP, TCP and WPZ. Their current average yield is 5.70%. Their average CAGR is 5.63%. The average yield + CAGR is 11.33%.
The following companies had corporate credit ratings of BBB-: BPL, DPM, EPB, ETP, SXL and WES. Their current average yield is 5.47%. Their average CAGR is 6.30%. The average yield + CAGR is 11.77%.
The following companies had corporate credit ratings of BB+, BB or BB-: ACMP, GEL, HEP, MWE, NGLS, NS and RGP. Their current average yield is 6.09%. Their average CAGR is 6.57%. The average yield + CAGR is 12.66%.
The following companies had corporate credit ratings of B, B+, B- or were note rated: APL, CMLP, EROC, EXLP, TLP, XTEX, NMM, MMLP and TGP. Their current average yield is 8.27%. Their average CAGR is 3.57%. The average yield + CAGR is 11.84%.

The data from the last grouping is evidence that if an investor is provided enough yield, many will forget about CAGR awareness. There are also many investors who lack CAGR awareness - or they lack sufficient faith in those projections to use them in an investment decision.

We would logically expect that MLPs with higher CAGR projections would sell at higher Price/DCF (Distributable Cash Flow) ratios - and they do.

Price/DCF ratios and CAGRs 2013:
The following companies had CAGRs under 4.5%: BPL, BWP, CMLP, EEP, ETP, EROC, EXLP, NS, RGP, TCP, TLP, NMM, MMLP and TGP. Their mean distribution Price/DCF ratio was 12.67.
The following companies had CAGRs over 4.5%: APL, ACMP, DPM, EPB, EPD, GEL, HEP, KMP, MMP, MWE, NGLS, OKS, PAA, SEP, SXL, WES, WPZ and XTEX. Their mean Price/DCF ratio was 17.91.

On the other hand, we might not logically expect that MLPs with lower RRR projections would sell at higher Price/DCF ratios - they do, too.

Price/DCF ratios and RRRs 2013:
The following companies had RRRs under 11%: BPL, BWP, EPB, EEP, EPD, ETP, KMP, MMP, OKS, PAA, SEP, SXL, TCP and TLP. Their mean distribution Price/DCF ratio was 16.43.
The following companies had RRRs at or over 11%: APL, ACMP, CMLP, DPM, EROC, EXLP, GEL, HEP, MWE, NGLS, NS, RGP, WES, WPZ, XTEX, NMM, MMLP and TGP. Their mean Price/DCF ratio was 14.98.

Risk matters in two ways:

1. I have the impression that investors believe that a dollar's growth in DCF will result in the same or better share price appreciation for those stocks with lower price to earning multiples. The opposite is true. The companies with more secure flows of income have higher price to DCF metrics. The data immediately above parsed the data by individual RRR assessment. Just in case there are some who might have problems with my RRR assignments, I will next parse the data by sub-sectors of different risk.

Investment grade large cap midstream MLPs sell at an average 2013 price/DCF ratio of 15.20. In other words, a dollar's growth in DCF adds an average $15.20 to the share price. Using 2015 DCF projections - the price/DCF ratio for this grouping of stocks is 13.04. A dollar's growth in projected 2015 DCF adds an average $13.04 to the share price.

The mostly non-investment grade smaller cap Gathering and Processing MLPs sell at an average 2013 price/DCF ratio of 14.96. A dollar's growth in FFO adds an average $14.96 to the share price. Using 2015 DCF projections - the price/DCF ratio for this grouping of stocks is 11.78. A dollar's growth in projected 2015 DCF adds an average $11.78 to the share price.

Summation - Risk matters because it shows up in how much price appreciation is gained from a dollar's growth in unit pricing. Risk is a factor in current valuations.

2. The argument that a low price-to-earnings ratio stock would have less to fall in a market downturn is wrong because downturns strongly tend to be the result of an earnings downturn. Stocks with lower price-to-earning ratios merit those lower ratios due to having higher earnings volatility. That volatility results in them having a high required rate of return. Having a higher rate of return results in those lower price-to-earning ratios and higher yields. When earnings fall, low Price/DCF stocks strongly tend to have earnings that fall more.

Intra-year DCF Estimate Increases and Year to Date Returns:
For 2013
The following companies had 2013 DCF estimate increases since the beginning of 2013: BPL, ACMP, EPD, ETP, EXLP, GEL, MMP, PAA, SXL and TCP. Their mean price gain for the year is 30.36%. Their mean total return for the year is 35.46% - and 8 of the 10 beat the sector median yearly price gain [of 19.69%]. Their average accuracy rating is 1.69.
The following companies had 2012 DCF estimate decreases since the beginning of the year: APL, BWP, CMLP, DPM, EPB, EEP, EROC, HEP, KMP, MWE, NGLS, NS, OKS, RGP, SEP, TLP, WES, WPZ and XTEX. Their mean price gain for the year is 14.29%. Their mean total return for the year is 19.92% - and 8 of the 19 beat the sector median yearly price gain. Their average accuracy rating is 2.69.

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 median 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 median yearly price gain. Their average historical DCF projection accuracy rating is 2.50.

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 median yearly 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 median yearly price gain. Their average historical DCF projection accuracy rating is 2.75.

In 2011, APL, EROC and XTEX - three of the MLPs with very low historical DCF projection accuracy - had positive changes in their DCF projection. Good things sometimes happen to low projection accuracy stocks. And bad things sometimes happen to high projection accuracy stocks. BPL and SEP both had falling DCF projections. Their inclusion in the falling DCF projection grouping raised the average historical DCF projection accuracy rating for that group.

Summation - Risk highly correlates to DCF projection disappointments. Because it shows up in the "disappointments," risk matters when it comes to total returns - even in the short term.

In the data below, I provided a second test done using accuracy ratings alone compared to total returns.

For 2013
The following companies had DCF historical DCF accuracy ratings of less than 2.0: ACMP, EPB, EPD, HEP, KMP, MMP, NGLS, OKS, PAA, SXL, TCP, TLP and WES. Their mean price gain for the year is 18.52%. Their mean total return for the year is 23.02% - and 7 of the 13 beat the sector median yearly price gain [of 19.69%]. Their mean CAGR projections were 6.88%.
The following companies had DCF historical DCF accuracy ratings of at least 2.0 - but lower than 3.0: BPL, DPM, EEP, EXLP, GEL and SEP. Their mean price gain for the year is 30.10%. Their mean total return for the year is 35.91% - and 4 of the 6 beat the sector median yearly price gain. Their mean CAGR projections were 5.40%.
The following companies had DCF historical DCF accuracy ratings that were equal or greater than 3: APL, BWP, CMLP, ETP, EROC, MWE, NS, RGP, WPZ and XTEX. Their mean price gain for the year is 15.38%. Their mean total return for the year is 21.83% - and 5 of the 10 beat the sector median yearly price gain. Their mean CAGR projections were 4.46%.
The second grouping out performed the other groupings so far in 2013. This is the only yearly test where there was not a correlation in the total returns and the accuracy groups. That is one reason to believe 2013 may be atypical. Here is a second reason: Four of the six in the middle group - Buckeye (NYSE:BPL), Exterran (NASDAQ:EXLP), Genesis (NYSE:GEL) and Spectra (NYSE:SEP) - have had around 40% share price appreciation. Throw in Access (NYSE:ACMP), and you have a list of the top five midstream MLPs in share price appreciation so far this year. There is one other factor at work in this data. Many of the high CAGR members of the first group entered 2013 with very low yields - and that has been a factor in that groups lack of out performance in 2013.

For 2012
The following companies had DCF historical DCF accuracy ratings of less than 2.0: EPB, EEP, EPD, HEP, KMP, MMP, OKS, PAA, SXL, TCP, TLP, WES and WPZ. Their mean price gain for the year is 6.00%. Their mean total return for the year is 11.82% - and 8 of the 13 beat the sector median yearly price gain [of -2.62%]. Their mean CAGR projections were 5.92%.
The following companies had DCF historical DCF accuracy ratings of at least 2.0 - but lower than 3.0: BPL, ACMP, MWE, NGLS, NS and SEP. Their mean price gain for the year is -7.96%. Their mean total return for the year is -1.50% - and 3 of the 6 beat the sector median yearly price gain [of -2.62%]. Their mean CAGR projections were 5.65%.
The following companies had DCF historical DCF accuracy ratings that were equal or greater than 3: APL, BWP, CMLP, CPNO, DPM, ETP, EROC, EXLP, GEL and RGP. Their mean price gain for the year is -9.37%. Their mean total return for the year is -2.20% - and 2 of the 10 beat the sector median yearly price gain. Their mean CAGR projections were 5.24%.

For 2011
The following companies had DCF historical DCF accuracy ratings of less than 2.0: BPL, EPB, EEP, HEP, KMP, MMP, PAA, SXL, TCLP, WES and WPZ. Their mean price gain for the year is 15.32%. Their mean total return for the year is 21.51% - and 6 of the 11 beat the sector median yearly price gain [of 8.32%]. Their mean CAGR projections were 5.76%.
The following companies had DCF historical DCF accuracy ratings of at least 2.0 - but lower than 3.0: CHKM, EPD, OKS, SEP and TLP. Their mean price gain for the year is 9.42%. Their mean total return for the year is 15.34% - and 2 of the 5 beat the sector median yearly price gain [of 8.32%]. Their mean CAGR projections were 6.04%.
The following companies had DCF historical DCF accuracy ratings that were equal or greater than 3: APL, BWP, CMLP, CPNO, DPM, ETP, EROC, EXLP, GEL, MWE, NGLS, NS and RGP. Their mean price gain for the year is 7.38%. Their mean total return for the year is 14.50% - and 6 of the 13 beat the sector median yearly price gain. Their mean CAGR projections were 5.78%.

Summation - Risk as measured by DCF projection accuracy shows up as an influence in total returns. And it currently shows up in a counter-intuitive way in this sector. It is not "high risk = high return". Lower risk has tended to result in better total returns. This counter-intuitive and atypical outcome is probably due to several lower risk MLPs having very high CAGR projections and CAGR inertia or trends. This "lower risk = better rewards" is the real "buy one, get one free" kind of value investing I want to do. Because risk or accuracy is an influence in total returns, risk or an RRR assessment needs to be a part of our total return projections.

Because risk matters, it needs to be a factor in our calculations of current valuations. It is in the real world. We need to stop seeing valuations as "yield plus CAGR" - and start to seeing valuation as "yield plus CAGR - RRR."

Below is my valuation spreadsheet that contains my "yield plus CAGR - RRR" numbers. This spreadsheet comes with a train load of warnings. Let me provide a partial list. Yield is the only real number in the spreadsheet. Every other number is a projection, valuation assessment or judgment. Projections inherently contain errors - and the specific projections will vary by source. The same is true of all judgments. I have provided my current numbers. These numbers are always in flux. I do minor adjustments in my CAGR and RRR numbers on a monthly basis. The concept that valuation should be a "yield plus CAGR - RRR" calculation is still an out of consensus opinion. I am not aware of a single, full time, professional group of analysts doing this kind of data presentation. That would imply that either every single brokerage is currently doing a noticeably sub-optimal data presentation - or that I am doing something that is "way out there in left field." The data:

Yield + CAGR Total Return Expectations


CompanyQ3-13ConsensusTotalBondsDCFMyTotal RtnConsensusPr ImplDistrib
YieldCAGRReturnRatingsAccrRRRs- RRRRatingsCAGR/ DCF
Large Cap Midstream
BuckeyeBPL6.43%4.10%10.53%BBB-2.3010.400.132.53.9797.25
BoardwalkBWP7.11%2.00%9.11%BBB3.2010.70-1.592.93.59102.90
El PasoEPB6.12%5.50%11.62%BBB-1.2010.301.322.94.1892.99
EnbridgeEEP7.31%2.70%10.01%BBB2.4010.50-0.492.53.19115.64
EnterpriseEPD4.43%6.70%11.13%BBB+1.209.701.431.75.2770.65
Energy TransETP6.96%3.50%10.46%BBB-3.0010.70-0.242.53.7486.14
Kinder MorganKMP6.60%5.50%12.10%BBB1.0010.002.102.73.4097.78
MagellanMMP3.80%8.80%12.60%BBB1.0010.002.602.56.2080.68
NuStarNS11.54%1.50%13.04%BB+4.0012.001.043.30.46125.50
OneOKOKS5.45%6.50%11.95%BBB1.5010.501.453.05.0598.29
Plains All-AmPAA4.38%8.50%12.88%BBB1.0010.002.881.95.6272.09
WilliamsWPZ6.51%5.40%11.91%BBB3.0011.000.912.34.49108.49

Average 6.39%5.06%11.45% 2.56

CompanyQ3-13ConsensusTotalBondsDCFMyTotal RtnConsensusPr ImplDistrib
YieldCAGRReturnRatingsAccrRRRs- RRRRatingsCAGR/ DCF
Small Cap Midstream
GenesisGEL4.06%8.50%12.56%BB-2.7011.800.761.87.7475.56
HollyHEP5.80%6.00%11.80%BB1.3011.200.603.35.4097.00
SpectraSEP4.78%7.20%11.98%BBB2.2010.501.482.95.7296.91
SuncoSXL3.66%8.90%12.56%BBB-1.0010.002.562.76.3456.07
TCPipelinesTCP6.63%3.00%9.63%BBB1.0010.00-0.373.23.3789.26
TransmontaigneTLP6.28%3.50%9.78%NR1.2010.00-0.221.73.7274.29

Average 5.20%6.18%11.39% 2.60

CompanyQ3-13ConsensusTotalBondsDCFMyTotal RtnConsensusPr ImplDistrib
YieldCAGRReturnRatingsAccrRRRs- RRRRatingsCAGR/ DCF
Gathering & Processing
Atlas PipelinesAPL6.45%9.10%15.55%B+5.0013.502.051.47.0584.64
ChesapeakACMP4.15%9.60%13.75%BB-1.5012.001.751.77.8570.55
CrestwoodCMLP8.19%3.30%11.49%B-3.7012.50-1.012.14.31105.15
DCP PartnersDPM5.82%6.50%12.32%BBB-2.7011.800.522.15.9897.59
Eagle RockEROC13.54%1.00%14.54%B5.0013.501.042.6-0.04111.39
ExterranEXLP7.65%3.40%11.05%B-2.2011.50-0.452.53.8573.33
Mark WestMWE4.78%8.60%13.38%BB3.2012.500.881.77.7296.55
TargaNGLS5.70%7.60%13.30%BB1.7012.201.101.96.5099.31
RegencyRGP6.58%4.20%10.78%BB-3.2012.00-1.222.65.4298.94
WesternWES3.82%9.30%13.12%BBB-1.7011.501.621.97.6888.89
Cross-TexXTEX6.72%6.00%12.72%B+4.0013.50-0.782.36.7893.62

Average 6.67%6.24%12.91% 2.07

You might perceive that there is some extraneous data in this spreadsheet. Let's pause so I can explain the inclusion of some extra data. The price implied CAGR, which is the Required Rate of Return minus the yield, is included so that I can verify that my RRRs are generating a believable price implied CAGR. I want to occasionally find price implied CAGRs that are not in agreement with my CAGRs. If the two metrics were in agreement all the time, it would be evidence that all MLPs are correctly valued. High CAGRs almost always come with a discount. So I expect a disagreement of the two metrics in those instances. I want a Goldilocks kind of result in this data. I want enough agreement to confirm that my projections and assessments are correct. At the same time, I want enough disagreement to confirm that this data presentation assists in finding the under valuations - and thus the opportunities - in this sector.

The analyst ratings for the equities are presented after the Total Return minus Required Rate of Return numbers. It is my perception that analyst ratings are reasonably accurate indicators of valuation. Total Return - RRR is my assessment of valuation. I would hope and expect that is a strong correlation between those two valuation indicators. But I also want a Goldilocks kind of result in this data.

Just prior to the listing of my RRRs are my historical DCF Accuracy Ratings and the S&P credit ratings. While I produce a specific spreadsheet that fully justifies my RRR, I like having some of the metric justification for my RRR assessments presented in this data. I want my RRR assignments to result in a logical price implied CAGR calculation. I want my RRR assignments to match up with the quality metrics like the accuracy and S&P ratings. There are times when those two desires are in conflict.

The distribution/DCF ratios are included last in this spreadsheet. A high CAGR projection needs to be justified by strong distribution coverage. Inadequate distribution coverage is also a factor in making an upwards adjustment to the RRR assignment. So the inclusion of this metric helps justify both of the CAGR and RRR numbers.

What the data tells me to buy
I start with an allocation goal, a yield goal and a CAGR goal. I do not start with the goal of maximizing my Total Return minus Required Rate of Return.

My first priority is to have a lower risk portfolio. For that to happen, I need most of my portfolio income to come from the lower RRR stocks. This is my allocation goal.

The calculation of one's total portfolio CAGR is not an 'average' calculation. It is a 'weighted average' calculation. It is not so much weighted by the amount of each component's investment dollars. It is weighted by the amount of each component's income that it produces. My 25% allocation to MLPs is already producing just 50% of my portfolio income. If I want a high CAGR portfolio, then that has to start with having a high CAGR MLP component. As I age, I want to increase the zero CAGR bond allocation in my portfolio. I need a very healthy CAGR number to be prepped for that morphing.

My yield goal within a specific sector will, at times, change with the wind. Early this year I sold high yielding Business Development Companies Triangle Capital Corporation (NYSE:TCAP) and Medley Capital Corporation (NYSE:MCC) when the data indicated that their CAGR projections were falling. This is an example of "headwinds" we all face in our goal to have the optimal portfolio. I had a goal of selling low total return projection Crestwood (NYSE:CMLP) in 2013. When my portfolio lost those two BDC components, my need for yield rose and my goal of selling the sub-optimal and over-valued CMLP has been delayed.

I would strongly suggest that others keep these kinds of goals in their mind when selecting which MLPs to purchase next. That said, here is what the current valuation data is telling me are the top 10 MLPs to buy now. The first four are relatively safe large-cap and investment grade midstream MLPs. The next two are high growth and high fixed fee component gathering and processing MLPs. The last is a mid-cap midstream MLP that has a forecast of strong DCF growth due to upcoming drop downs from its general partner. The last three are the very high growth and IDR or incentive distribution rights owning general partners. The yield plus CAGR numbers for these three are fantastic. It is a pleasant coincidence that the 10 suggestion would make a well rounded, strong growth and low risk portfolio. The number following the ticker is the Total Return - RRR metric.

Plains All American Pipeline (NYSE:PAA) 2.88; Magellan Midstream Partners (NYSE:MMP) 2.60; Sunoco Logistics Partners (NYSE:SXL) 2.56; Kinder Morgan Energy Partners (NYSE:KMP) 2.10; Access Midstream Partners 1.75; Western Gas Partners (NYSE:WES) 1.62; Spectra Energy Partners 1.48; Targa Resources (NYSE:TRGP) 11.21; Atlas Energy (NYSE:ATLS) 8.91; and Williams Companies (NYSE:WMB) 7.00.

I should note that Enterprise Products Partners (NYSE:EPD), MarkWest Energy Partners (NYSE:MWE), Tesoro Logistics (NYSE:TLLP) and Crosstex Energy (XTXI) are frequently members of the top-10 lists. They are not currently selling at relatively attractive yields. But the relative attractiveness of the yields is a constantly changing event. I normally have one or two E&P (Exploration and Production) MLPs on the list like Linn Energy (NASDAQ:LINE) and Vanguard Natural Resources (NASDAQ:VNR). The recent investigation of accounting practices of LINE by the SEC has me bumping the RRRs for the whole E&P sector. As a result, none of the stocks is selling at attractive valuations. Due to their distribution growth inertia and 2014 distribution to DCF ratios, Atlas Resource Partners (NYSE:ARP) and Memorial Production Partners LP (NASDAQ:MEMP) would be the most attractive options in that volatile and relatively risky sub-sector.

Some people would call the method of valuation that was done to derive a list like the one above as doing a risk adjusted return calculation. I understand why they would call it that - but I am not comfortable with that phrasing. It implies something sub-optimal to me. It sounds like you a giving up some return in order to get less risk. The stats are indicating to me that doing such a valuation calculation is giving up nothing. If I am doing anything, I am maximizing total returns by having RRR awareness. If it were called "return maximization via RRR awareness," then I would like the term.

Let's summarize
We inherently know that intra-year earning estimate changes influence yearly total returns. These stats confirm that. We inherently know that the ownership of lower risk assets produce more predictable earning projections. These stats confirm that. In advance of the event, we can gather the data that will predict which stocks are most vulnerable to those unpleasant events. These stats confirm that. For those reasons alone, it is logical to include a significant weighting to a risk assessment metric in our valuation assessments. We cannot make a valuation judgment without a risk assessment. Moderate differences in risk assessments can significantly alter our perception of a stock valuation. The best safety cushion in a market downturn is not a low price to earnings multiple or a high yield. The best cushion comes from the ownership of stocks with higher quality assets. And these are the stocks that tend to have the higher price-to-earning metrics. In this sector, the consensus opinion on where one finds the safety cushion is wrong.

Source: Redefining Value Investing For MLPs