Here's the beauty of an oil and gas trust: given forecasts of production, sales prices, and expenses, its distributions may be forecast far into the future. The total of these distributions, discounted to the present day, provides an estimate of what the trust is really worth. That estimate, together with the market price, can help an investor know when to buy and when to sell.
Of course, the key to a useful estimate is the selection of an appropriate discount rate. The same factors used to forecast distributions also influence the risk in that forecast. From an investment perspective, the greater the risk, the greater the discount rate that should be used. So how should we set discount rates for trusts?
This article presents a simple risk model that suggests possible discount rates for each of the trusts that I follow.
Risk comes from many sources
For oil and gas trusts, there are many sources of risk. Some risks are inherent in the general nature of trusts. For example, future government regulation, energy costs, weather, and unforeseen production issues may affect all trusts, including those that have been consistent payers for many years, like Permian Basin Royalty Trust (NYSE:PBT).
There are myriad ways to account for these risks, some better than others. I prefer a simple approach:
- Start with a base risk that applies to all trusts.
- Identify and categorize sources of trust-specific risk, such as: production, time, expense, operator, and other.
- Evaluate and assign a score, or risk premium, to each trust for each category.
- The sum of a trust's risk premiums determines its level of risk and suggested discount rate.
Fig. 1: A "simple" model to evaluate trust risk
Of course, there are still plenty of ways to assess risk even with this simple model. Comments and discussion are encouraged.
Base risk refers to the risk that is inherent in all trusts and sets a premium for generic trust income above what an investor might require from a low-risk alternative, such as U.S. T-bills. For me, base risk also includes those risks that I do not consider directly in my analysis, such as changes in oil and gas price futures.
For my analysis, I set the premium for base risk equal to 4% for all trusts.
When it comes to forecasting a trust's distributions, no element is more challenging than production. The performances of young wells and vaguely-described "capital improvement" programs are often difficult to predict. Take ECA Marcellus Trust I (NYSE:ECT), for example. It was clear to most investors in 2013 that production was going to decline, as the last of the wells had been completed. However, it was more difficult to predict the magnitude of that decline. Even after production declines set in and appeared to stabilize, they accelerated last quarter. Young wells increase risk.
Fig. 2: Production from young wells can be difficult to forecast. Source: ECT SEC filings and author's analysis.
The same reasoning also applies to trusts with stable or increasing production, such as Pacific Coast Oil Trust (NYSE:ROYT). As my model assumes that new wells will be added, increasing production, there is substantial production risk.
At the same time, perpetual trusts that might see future CapEx, such as ROYT, offer a desirable upside potential. Terminal trusts like ECT and VOC Energy Trust (NYSE:VOC) are unlikely to ever see new wells or work overs and don't have such potential. Thus, production risk should be greatest for those trusts with high production uncertainty and no upside potential and least for those trusts with stable production trends and the possibility of future investment.
For trust-specific production risks, I add +2% if production forecasts are subject to substantial uncertainty and +1% if the trust is unlikely to ever see additional wells or work overs.
Time and reserve risks
Generally speaking, forecast uncertainty increases with time. So a trust with front-loaded payouts, such as MV Oil Trust (NYSE:MVO), may be less risky than one with similar valuation but payouts far in the future, such as San Juan Basin Royalty Trust (NYSE:SJT).
To make it simple, I consider time by looking at distributions for residual payments (for reserves) and that will occur 20+ years in the future. The chart below compares trusts by the relative weight of their NPV-10 that is due to these "long-term" distributions.
Fig. 3: A comparison of trusts by weighting of long-term payouts. Source: SEC filings and author's analysis
For the model, I add 2% to the required discount rate if long-term distributions account for more than 10% of the current NPV-10 (and 1% if more than 5%).
As I follow trust prices in the market, expenses seem to be that forgotten factor. Perhaps they aren't sexy, but investors should pay keen attention. Expenses, just like any other input, change over time. If expenses are comparatively small, such as those for SandRidge Permian Trust (NYSE:PER), a moderate 10% increase might not change the distribution by very much. However, for trusts with significant expense ratios like Hugoton Basin Trust (NYSE:HGT), a 10% increase takes a big bite out of the distribution.
Fig. 4: A comparison of operator expense ratios. Source: SEC filings and author's analysis.
For the risk model, I add +1% to the desired discount rate if more than 30% of trailing 36-month revenues were paid in expenses.
Although trusts have no business or engineering functions of their own, each depends on one or more companies to manage the business of its wells. Some of these companies, like Burlington Resources (a subsidiary of ConocoPhillips (NYSE:COP)), have been serving trusts for years, while others like SandRidge Energy (NYSE:SD) are new to the trust game. I haven't done the research to justify it, but all other things equal, I would rather have a trust operated by an established name than one with a new name.
For my analysis, I add +1% if the trust is less than 10 years old.
Lawsuits and other unexplained events that reduce the distribution are like smoke. They may be worth a gamble, but they also increase the investment risk.
I add +1% to HGT for its ongoing legal issues.
A Ranking of Trust Risks
So how do the trusts stack up using this simple analysis?
Fig. 5: Total risk premiums by trust and risk category. Source: author's analysis.
Considering the overall set of rates, the minimum (NYSE:NDRO) is 5%, while the maximum (ECT and ROYT) is 9%, and most of the trusts are centered in the middle at 7% and 8%. These bounds roughly reflect common premiums for the upper range of trusts in the market.
Examining individual trusts, we see that those with highly uncertain (ECT, SDT, and SDR) production receive higher suggested discount rates. But so do trusts with more stable production (PBT and ROYT) that are also undertaking large capital expansions.
In comparing the risk premiums to my 2013-Q4 value rankings, a couple of other interesting points jump out at me:
- On the whole, the risk premiums applied to trusts by the market appear to be too low. However, these values are skewed by trusts such as MVO, SDR, and SDT, which are currently selling for more than their non-discounted sums of future distributions.
- The market appears to be ignoring the possible risk of older trusts, like PBT and SJT, possibly because it is ignoring their high costs.
- Alternatively, risks for VOC (and PER, as based on a more recent evaluation), appear to be less than those ascribed by the market.
That said, I view this analysis as a first cut. Personally, I'm not sure that I would be comfortable with any trust that returns only 4 or 5% when other stocks in my portfolio (BP, OHI, and ARLP) all return more than 5% in annual dividends and have business growth potential, which trusts decidedly do not. Similarly, I've glossed over many issues, like price spreads and the value of having a trust that is diversified in both geography and production types without considering them directly. On the other hand, I also wonder if I'm double-penalizing some trusts, such as PBT, that have high costs because of their capital expansion.
Of course, the "simple" analysis above is just one way to look at it. If you dis/agree with any of the above, please fire away with a comment or email.
If you've read this far, then I should admit to you that I don't think about risk exactly as discussed in the model above. Deeper consideration of risk involves thinking about not just whether a source of risk is a major factor, but trying to measure that risk. Simple metrics, like standard deviations and coefficients of variation, can be used to evaluate the uncertainty of individual inputs. Correlations tell us how these inputs relate. And even deeper analyses can be undertaken to turn production, prices, and expenses into quantified, stochastic functions, which contain interconnected probabilities that change over time. I leave that type of full-blown sophistication to the major investment houses, but, at the same time, I draw on these deeper ideas when I fudge the results of simpler risk techniques, such as the table above, when I use them for my own purposes.
Disclosure: I am long PER. 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.