Dividend Coverage Roundup: Oil & Gas Production To FY 2018

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Contributor Since 2009

Specialized business audits employing theoretical models that permit coverage analysis and ranking without the need for data on dividends or debt service. Author of the Cautionary Stress Testing, Dividend Coverage Roundup and Natural Rates Review reports.  Research also covers economic system dynamics, interest rate theory and science.  Please refer to the Disclaimer below. Recent books: Dividend Coverage Analytics, Debt Management Analytics (2021), Yield Distortion Dynamics (2020), Financial Distortion Dynamics (2018), Economic Distortion Dynamics (2017). Professional background in commercial banking, securities industry and education; Ph.D, M.Sc.. Polyglot with lifelong pursuits in art, science and music, aspiring to merge analytical work with visuals. Based in East Asia. Writings are for informational purposes only and are not to be viewed as investment advice or recommendations.

The framework for Cautionary Stress Testing, Dividends is detailed in the books Dividend Coverage Analytics (2021) or Debt Management Analytics (2021). Introductory notes are here: https://seekingalpha.com/instablog/471740-raoul-kennedy/5470359-cautionary-stress-testing-dividends-background-notes. For a brief summary here see the Cautionary Tails Framework Notes below.   

Natural Interest Rates: For a brief overview of historical foundations, see the Natural Rates Review intro at https://seekingalpha.com/instablog/471740-raoul-kennedy/5300975-natural-rates-review-intro.

For visual representations of analyses: (1) Videos on YouTube under author name and series "Cautionary Global Analysis." (2) Artwork including stylized 3D sketches of underlying theoretical models for analyses, refer to Collections (Financial Visualizations, Sketching Economics) at raoul-kennedy.pixels.com.  

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CAUTIONARY TAILS FRAMEWORK SUMMARY NOTES. The following notes apply to Dividend Coverage Roundup and Cautionary Stress Testing reports, in particular. Financing obligations (abbreviated FO) combine debt service and dividends because they are paid from the same source: cash flow, defined as net free cash flow NFCF.  Audits include estimation with five principal metrics:
Metric 1. Coverage capacity defined as proportion of outcomes in which company cash flow exceeds its financing obligations (range 0 to 1, where higher values suggest greater capacity, with qualifications); Metric 2. Negative cash flow estimates are proportions of total possible outcomes ranging from zero to one; for example, a value of zero suggests negative cash flow is a theoretical impossibility (i.e. no possible outcomes). Metric 3. Centrality, an estimate of the point which corresponds to bilateral distributional density. Metrics 4 and 5. An alternative coverage metric compares the estimated maximum FO that corresponds to maximum acceptable exposure MAE levels (0.05, 0.10; FO coverage assumed to not be achievable in an "accepted" range of 5%-10% of possible outcomes). Negative estimates suggest inadequate coverage given these specifications.

Qualifications. Estimates are not to be used in isolation and are not forecasts; multiple resources should be consulted for decision-making; estimates are at best rough indicators of what may be possible based on models employed. Data may be based on interim unaudited financial information; results are preliminary as the data and default assumptions are subject to modification to reflect updated information. Results: Imminent default is not necessarily inferred by poor performance, nor do superior results imply absence of default.

Cautionary Approach. Divergent models may be used to describe the same financial process. A default assumption of fat tails is generally made over higher-ranking distributions which may be thinner-tailed; however, estimates derived from thinner tails may also be incorporated in accordance with a principle of erring on the side of caution.
Applicability of Analysis. Firm-level stress testing may aid in assessing exposure within financial institutions, capital markets and investment portfolios, and aggregate results may shed light on the prospects for economic recession and policy countermeasures. Shocks experienced by individual firms may exert impacts on capital markets, financial institution credit portfolios and economic output.

Dividend Coverage Capacity Ranking System.  The tiers are 1, 2, and 3 with rankings from 1.0 to 3.99 (rounded); an estimate of 1.0 suggests the strongest possible performance; estimates of 4.0 and greater fall below the criteria for the top three. To figure within the top 3 tiers, the initial estimates should meet minimum criteria for each of the five individual metrics as follows: Coverage, greater than or equal to 0.50 (range from zero to 1); Negative cash flow exposure, equal to or less than 0.077 (range from zero to 1); Centrality, greater than or equal to 0.098 (i.e. 9.8% of revenues); potential coverage maximum acceptable exposures (MAE 0.05 and 0.10) greater than or equal to 0.05 (i.e. 5% of revenues). The initial estimates (“unfiltered”) are subject to a filtering process which may result in some modifications to the initial rankings. For an example of tiers and ranking: https://seekingalpha.com/instablog/471740-raoul-kennedy/5509407-dividend-coverage-roundup-capacity-tier-finalists-interim-2020;  for a video summary: https://youtu.be/6RyEk-ZZhS8


  • This report examines the capacity of oil and gas producers to cover dividends and debt service to FY 2018.
  • The firms reviewed are CNQ, PTR, and SSL (SIC 1311) with a combined market cap of about $140B.
  • Apart from SSL, net free cash flow and revenue growth range between breakeven to positive; also see qualifications.
  • Sustained coverage of financing obligations may rely on some form of monetary easing due to debt loads.

Tabular Results and Interpretation

The table below shows the results for Canadian Natural Resources (CNQ) and PetroChina (PTR) to FYE 12/31/18 and Sasol (SSL) to FYE 6/30/18, followed by a quick interpretation of each category of analysis:

Dividend Coverage: The coverage variable is NFCF (net free cash flow as a percentage of annual company revenues). Positive (negative) values suggest enough (inadequate) cushion to cover dividends. A figure of zero suggests breakeven coverage.

Deviations (NFCF, Revenue Growth*; latest FY vs. prior): Negative values suggest a recent (1-year) worsening because the latest fiscal year’s value has moved below the prior period central tendency. * Zero or near-zero values suggest that the latest values are in line with historical.

Shifting Centrality (NFCF, Revenue Growth; 3-year): Here the baseline for a shift=1, not zero. Smaller values suggest secular deterioration. This category identifies any shift of each company’s own “core” performance* over the latest 3 years.

Coverage 2 (Dividends+Debt Service DDS): Positive (negative) values suggest an adequate (inadequate) cushion to cover DDS. The coverage variable NFCF is compared to the sum of dividends and debt service* (abbreviated DDS or d+ and may also be termed financing obligations).

(*) Notes: Revenue growth is year on year (YoY) percentage change. Debt service is the sum of principal and interest payments (which in some cases may be estimated), The basis for this analysis is spatial, where the central tendency or “core” may also be referred to as “spatial centrality” or simply centrality.

For any qualifications to the analysis, see the notes further below; refer to the separate post titled Dividend Coverage Roundup: Background Notes referenced in the Author’s page for methodological and other details.

Comparative Overview in Charts

The following charts display the data from the table above. Note that spatial centrality is also shown either by a zero (for Charts 1, 2, 3 and 6), or the figure 1 (for Charts 4 and 5).

Chart 1. Dividend Coverage. Dividend coverage may not be comparable across firms as dividends may vary significantly; for some firms the amounts can be negligible. For a more comprehensive estimate of financing obligations (dividends and debt service together), see Chart 6 and qualifications below.

Chart 2 and 3. Deviations (from Prior FY Centrality).

NFCF. Apart from SSL, the most recent fiscal year, net free cash flow NFCF exceeds the firms’ own prior centrality.

REVG. As of the most recent fiscal year, revenue growth for CNQ and PTR exceeds their historical prior centrality while SSL dipped slightly below breakeven.

Charts 4 and 5. Shifting Centrality (3-year)

NFCF. To the most recent fiscal year, net free cash flow either remains above or in line with its own historical centrality for CNQ and PTR, while SSL’s net free cash flow has shifted downwards over the 3-year period.

REVG. CNQ and PTR have slightly exceeded or maintained their core of revenue growth, while SSL has shifted downwards to a greater extent over the period to its most recent fiscal year end.

Chart 6. Dividends + Debt Service

A more comprehensive analysis of coverage requires examination of debt service, detailed in this section. Debt Service is the sum of principal and interest on debt obligations. Adding debt service onto dividends may result in significantly different conclusions about dividend coverage capacity since both compete for limited company funds, with debt service typically being contractual. The chart below shows the relative performance of the firms when coverage is estimated for dividends and debt service combined; the centrality is represented by zero. All firms appear to fall considerably short in coverage capacity; see note and qualifications below for further details.

Note: CNQ’s current portion of long-term debt as of FY 2018 was significantly lower than for its scheduled future maturities beyond FY 2018: In particular, debt maturities of 1476 for FY 2018 rise to 5996 for FY 2019.To ignore this large discrepancy in the subsequent fiscal year arguably understates the extent of the company’s debt obligations. Therefore, an intermediate estimate averaging the two fiscal years’ debt maturity figures (FY 2018 and FY 2019) was used instead for a more representative debt service figure.


  1. Chart 1. Dividend coverage may not be comparable across firms: For example, the ratio of dividends to revenues for CNQ, PTR and SSL as of FY 2018 was approximately 7%, 1.8% and nearly zero, respectively.
  2. The basis for comparison between firms is less uniform due to the 6-month lag between the fiscal year ends of SSL and the other two firms. Also note that the financial information for SSL is for FY 2018, not FY 2019 (see next comment regarding the delay).
  3. SSL’s financial statements are typically released in August. For fiscal year ending 6/30/19, there has been a delay as stated in the company’s SEC Form 6-K Report of Foreign Private Issuer. According to the report, the financial statements for FY 2019 are expected to be released by the end of October 2019.
  4. See the Note with Chart 6 regarding CNQ’s current portion estimate.
  5. Due to the author’s incomplete dataset for CNQ, there was a single missing observation for FY 2007 revenue growth. Therefore, an estimate was generated from the average of all subsequent fiscal years to FY 2018.

Methodology and other details are consolidated in a separate post titled Dividend Coverage Roundup: Background Notes, referenced in the Author’s page. For more recent analyses, a default assumption of fat tails is generally made in favor of higher-ranking distributions for reasons detailed in the methodology.

Financial Visualizations. For selected 3D stylized and other sketches of underlying theoretical models of selected companies, see the author’s page for links; given the qualifications and shortcomings, at the very least it is hoped that such models might be appreciated for their aesthetic value.

The author may also hold positions in securities of companies, including through ETFs, that are covered herein. The discussion and any visuals may contain significant errors, are subject to revisions and are provided 'as is' solely for informational purposes, not for trading or investment advice. This preliminary analysis is exploratory; no claims are made as to the validity of data, assumptions, theoretical models and methodologies; results may be based on prior data that do not reflect the most current market events.

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