Tom's Life Bits

There are stats that I calculate that expose more of my thinking than I want to have exposed - so I do not show them often. At year end - and being almost fully invested - I had decided to share those stats. I really hope that most of you do not go to the effort to understand them - and that most of you believe this is a bunch of voo-doo math that will never work in the real world. That is partially a correct impression - because I will show that the stats are only about 70% predictive and 30% in error.

Given that the statistical analysis is NOT the end of my investigations - and not the sole determinant of my investing decisions, I can live that with level of error. The statistical analysis is just the beginning - it highlights what MLPs I want to investigate further.

And the first step in generating predictive numbers is to generate good forward CAGR [compound annual growth rate] numbers. The first spreadsheet shows where I get those numbers - and why the numbers I use differ from the CAGR estimates the one can find at Yahoo! Those numbers are in the next message.

MLP CAGRs - Why Consensus Estimates Are Not Used

The dominant factor in assigning amended CAGRs is the distribution coverage ratio, with forecast DCF growth second and recent distribution growth third. My CAGRs are close to the analyst estimates - with only a few exceptions.

The Whole Enchilada part three Predictive MLP Metrics The spreadsheet [on the next message] presents stats from four different valuations models - mixes them - then produces a forecast for future price movements. Now that I have what I think are reasonable good CAGR estimates - I use them in calculating three of my four valuation models.

  The first is the dividend discount model [DDM]. The formula uses a required return of 15% - and on average the market is demanding just under 9% distribution [and unit price] growth plus a 6% yield [or a tad lower] and the total of those two gets one to a 15% total return. This model is given a small weighting [15%] in the final calculation because, despite its simplicity and logic, it fails to be accurately predictive. But including the DDM with other models tends to aid in the overall predictivity. The DDM produces high valuation for MLPs with high CAGRs.
   The second valuation is the current price plus the assumed gain from the difference between its distribution and its distributable cash flow. MLPs re-investing more of their DCF should have an advantage in getting a higher annual unit price gain. Any forecast of price change needs to come from its psychological anchor - the current price - and this model does that. The yearly DCF minus the distribution is calculated and shown. This model is given a weighting of 20% in the final calculation, and produces lower valuations for MLPs with higher CAGRs.
 The third valuation is based on 2008 EPS - and produces a higher model P/E multiple for MLP with higher CAGRs. It takes the 2008 EPS estimate and multiplies that times the sum of 12 plus the CAGR. And 12 plus a sector average CAGR of 8 gets one to 20 - most MLPs sell at or under an 20 P/E. This metric suggests huge changes in MLP prices and is given a weighting of 25%.
  The last valuation is based on 2008 DCF - and again rewards MLPs with higher CAGRs, which should logically sell at a higher P/DCF. It takes the 2008 DCF estimate and multiplies that times the sum of 6 plus [CAGR divided by 1.2]. The average MLP sells at a P/DCF multilpe of 12.5 [on 12-31-07] - and with the average CAGR approaching 8, 8 divided by 1.2 [6.7] then added to 6 gets one to 12.7. Also, the P/DCF ratios range from 11 to 16 - and MLPs with CAGRs of 12 would merit a 16 P/DCF under this formula while MLPs with CAGR of 5 would merit a 10.17 P/DCF ratio. This valuation metric is the single most predictive estimate - thus its weighting at forty percent is the highest of the four.    The weighting for Current Price + Gain from Dist/DCF advantage - 20%, the weighting for the Dividend Discount Model - 15%, the weighting for P/E at 11 + CAGR - 25% and the weighting for P/DCF at 10 + (CAGR divided by 2) - 40%.

The calculations are show in the next message - 'the whole enchilada part four“. And in part five - I will show the back-testing of how the components of the model worked in predicting price changes in 2007.