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Cautionary Stress Testing: Global Telecom Industry To FY 2018

|About: China Mobile Limited (CHL), T, VIV

Stress tests are run on global telecom firms CHL, T and VIV (SIC 4813), with a combined market cap of about $450 billion.

Firm-level stress testing may offer further insights into the prospects for dividends, recession, policy and financial institution default exposure.

Scenario estimates suggest higher criticality in cash flow (CHL) and revenues (VIV); also see any qualifications and the Dividend Coverage Roundup report.

Tabular results of the estimated critical zones for each scenario are shown below, with brief interpretations provided alongside the charts further below.

Note: NFCF/revenues may also be abbreviated NFCF (net free cash flow).

Results in Charts

CHART 1 NFCF/Revenues <0%. In this scenario, the firm no longer has adequate NFCF to cover its financing obligations (i.e. dividends and debt service) --a potential marker for insolvency. The estimates suggest greatest vulnerability for CHL and moderately high levels for T and VIV.

CHART 2 NFCF/Revs < -0.25%. This assumed shock is a drop in annual net free cash flow below 25%. CHL remains at approximately double the level of criticality.

CHART 3 Rev Growth <0%. In this scenario, the company’s annual revenues fall below zero growth. VIV and T’s estimates suggest elevated vulnerability to a revenue shock.

CHART 4 Rev Growth <-25%. In this more severe revenue shock scenario, VIV remains more vulnerable than the other firms.

Qualifications. A question arises as to the possibility of incompatible results across reports (this Cautionary Stress Testing vs. the Dividend Coverage Roundup). As noted elsewhere, the analyses are based on fitted curves; the continuous scale parameters (estimates of dispersion) may help explain discrepancies. For example, in this stress testing, CHL (NFCF/Revs) and VIV (Revenue growth) are the standouts in terms of criticality: For the NFCF/Revs variable, this scale parameter estimate is 0.05, 0.024, and 0.025, for CHL, T and VIV, respectively; for revenue growth, the estimates are 0.026, 0.017 and 0.032 for the firms, respectively.

Stress Testing: Additional Comments

Applicability. Firm-level stress testing may aid in assessing vulnerabilities within financial institutions (loans), capital markets and investment portfolios (securities). Moreover, criticality levels may offer insights as to 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.

Methodology and other details are consolidated in a separate post titled Cautionary Stress Testing: Background Notes, referenced in the Author’s page. For a complementary analysis on the companies, see the companion Dividend Coverage Roundup report for the same fiscal year, if made available. Clarifications & Qualifications: The criticality level is assigned based on the critical zone estimates and refers to the extent to which a given scenario could in theory become a reality. However, the results of stress testing should not be equated with predictions or forecasting; at best they can be viewed as imprecise indicators of the vulnerability of firms to shocks. A default assumption of fat tails for the theoretical models 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 model shortcomings, at the very least it is hoped that they 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.