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Companies And Sectors Most Impacted By U.S.-Chinese Tariffs

Judge OKs AT&T/Time Warner, Opening A Potential Bidding War For FOX Assets

Technology, Media & Telecom

Kagan MediaTalk - Episode 2: TV’s Summer Soccer Fever

50 Years Of Altman Z-score, And PD Model Fundamentals – Case Study General Motors

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Credit Analysis
Companies And Sectors Most Impacted By U.S.-Chinese Tariffs

Highlights

President Trump’s proposed tariffs impacted the short-term market perceived credit quality of U.S. firms more than Chinese ones

May. 07 2018 — Written by Camilla Yanushevsky, with analysis contributions from Paul Bishop and Jim Elder, Directors of Risk Services, Melissa Doscher, Senior Manager, Risk Services, and Chris Rogers, Panjiva Research Director.

Consumer confidence soared to an 18-year high in February, on the tailwinds of the passage of the most sweeping tax rewrite in over 30 years at the end of 2017. But now, with U.S. President Donald Trump’s ramp up of protectionist rhetoric and heightened concerns of a global trade war, the optimism has begun to diminish. The Conference Board Consumer Confidence Index declined to 127.7 in March, from the high of 130.0 in February, with many pointing to President Trump’s tariffs as playing a major role for the drop off. [i] Companies have already started to examine the potential impact to their supply chains and are reevaluating the way they conduct business. Although the implementation details of the President’s tariffs have yet to be provided, we went ahead and evaluated the levies’ potential market implications.

U.S. tariff announcements have occurred 31 times in the last 35 years, according to an S&P Global Market Intelligence analysis using Kensho, provider of next-generation analytics and data visualization systems, which was recently acquired by S&P Global. On a rolling quarterly basis, following the announcement, the S&P 500 increased, on average, by 2.79%, trading positively more than 78% of the time. Energy stocks tended to be the bottom performing among the S&P 500 sectors, while S&P 500 Information Technology and S&P 500 Consumer Discretionary companies posted slight positive returns for the quarter.

Figure 1: S&P 500 average return and percent of trades positive after U.S. tariff announcement
S&P 500 average return and percent of trades positive after U.S. tariff announcement

Following President Trump’s March 22, 2018 signing of an executive memorandum to impose regulatory tariffs on up to $60 billion in Chinese products belonging to the aerospace, information and communication technology, and machinery industries, among others, we examined and highlighted notable sector, industry, and company-level probability of default (PD) changes as indicated by our PD Market Signal Model, a structural model that calculates the likelihood of a company defaulting on its debt or entering bankruptcy protection over a one- to five-year horizon.[ii]

U.S. Financials, Energy companies among the biggest losers

Following the memorandum signing, the U.S. Financials sector saw the largest escalation in market-perceived credit risk. The sector’s PD increased 29.32% from 0.39% on March 21, 2018 to just under 0.50% on March 29, 2018, nearly crossing into a speculative grade equivalent (bb+) median credit score for the sector. [iii]

While not directly impacted by President Trump’s tariffs, diversified banks and investment banking and brokerage companies are reexamining their business investment and lending decisions due to the levies’ potential negative repercussions on economic growth.

According to an analysis conducted by the Tax Foundation: “$37.5 billion in tariffs would lower GDP and wages 0.1 percent, lower employment by the equivalent of 79,000 fewer full-time jobs in the long run, and make the US tax burden less progressive.” [iv] On such concerns, as well as the possibility of retaliation by other countries, fund managers have already begun to reduce their U.S. holdings and look for opportunities overseas. [v]

President Trump’s proposed tariffs also dealt a significant blow to the U.S. Energy sector, which relies heavily on steel and aluminum for various projects, including pipeline construction and wind and solar power installation. Following the announcement, the U.S. Energy’s PD jumped 25.15%, from 1.56% on March 21, 2018 to 1.95% on March 29, 2018.

President Trump’s proposed tax on steel and aluminum imports will not only raise the costs of these projects and drive up prices for consumers, but in the long run can also reduce the demand for clean energy, while harming the quest for ‘American energy dominance’ in the process.

Figure 2: U.S. 1-week median Market Signal Probability of Default change by GICS sector (%)

U.S. 1-week median Market Signal Probability of Default change by GICS sector (%)

Taking a deeper dive into subsectors, aluminum, a subset of Materials, saw the largest increase in PD of 120.71%. Copper, another subset of Materials, also saw a substantial incline in PD of 120.54%. Both these important industrial metals were singled out on the President’s proposed list of tariff targets. [ii]

Figure 3: U.S. largest increases in 1-week Market Signal Probability of Default by industry (%)

U.S. largest increases in 1-week Market Signal Probability of Default by industry (%)

China’s Consumer Discretionary sector takes a blow

Chinese consumer discretionary companies also are bearing the brunt of the looming trade war, with President Trump’s tariffs targeting a range of consumer goods from China including flat screen televisions, household appliances, and auto parts. Immediately following the announcement, the sector observed the largest market-perceived escalation in credit risk. The sector saw its PD increase 8.09% from 1.82% on March 21, 2018 to 1.96% on March 29, 2018.

President Trump’s tariffs also carry far-reaching implications on China’s property market, which after two stellar years of property sales and developer margins, is seeing a toughening of industry conditions — tighter lending rules, restrictive policies to control price appreciation, and intensifying competition. [vi]

Fears of faster-than-expected rate hikes and inflation growth spiraling from the tariff battle does not bode well for Chinese developers looking for capital overseas. Following the signing of the March 22, 2018 memorandum, China’s real estate sector observed a PD uptick of 6.4%, from 0.93% on March 21, 2018 to 0.99% on March 29, 2018.

Figure 4: China 1-week median Market Signal Probability of Default change by GICS sector (%)

China 1-week median Market Signal Probability of Default change by GICS sector (%)

On a subsector level, China’s property and casualty insurance, a subset of Financials, observed the largest one-week escalation in credit risk with its PD jumping 133.9% from 0.23% to 0.53%. The industry’s PD uptick is likely a ‘spillover’ of the tightening of the credit markets for property developers to the insurers offering project assurance.

Figure 5: China largest increases in 1-week Market Signal Probability of Default by industry (%)

China largest increases in 1-week Market Signal Probability of Default by industry (%)

Tariff headwinds hit both sides

On a company-level, roughly 65% of U.S. and 58% of Chinese publicly traded companies experienced an increase in their one-year PD the week following the announcement. U.S. companies saw a larger escalation in credit risk, with a median PD change of 13%, compared to China’s 3%. Companies with U.S./China cross-border exposure were also more likely to see an increase in credit risk.

Figure 6: 25 largest increases in 1-week Market Signal Probability of Default by U.S. S&P Global Market Intelligence-covered companies with exposure to China (%)

25 largest increases in 1-week Market Signal Probability of Default by U.S. S&P Global Market Intelligence-covered companies with exposure to China (%)

Figure 7: 25 largest increases in 1-week Market Signal Probability of Default by Chinese S&P Global Market Intelligence-covered companies with exposure to the U.S. (%)

25 largest increases in 1 week Market Signal Probability of Default by Chinese S&P Global Market Intelligence

Some U.S. companies uneasy over China tariff threat to supply chains

Considering the complexity of international supply chains, many market participants are on edge that new tariffs might have damaging unintended consequences. According to supply chain market intelligence firm Panjiva Inc., which was recently acquired by S&P Global:

“The targeting [striking] of China’s duties is significantly more focused than those introduced by the U.S., with 106 categories compared to 1333 in America’s section 301 duties. They are also more focused in terms of products, with the top three products accounting for 71.7% of total product coverage. Those include aircraft (HS 8802.40, worth $14.05 billion, or 26.3% of the total, soybeans (HS 1201.90 worth $13.96 billion) and midsize engine cars (8703.23, $10.32 billion).

The inclusion of soybeans is particularly notable given that the promotion of imports were a part of the package of trade enhancements announced when President Trump visited China in November 2017.” [vii]

Figure 8: Focused strike on politically important U.S. products

Focused-strike-on-politically-important-U.S.-products

In summary, our PD Market Signal model shows that President Trump’s proposed tariffs impacted the short-term market perceived credit quality of U.S. firms more than Chinese ones. While the trade penalties have yet to be implemented, we saw steep tariffs and protectionism policies spur declines in global trade in the 1930s, stifle economic growth, and contribute to the depth of the Great Depression. More recently, we saw trade fears trigger volatility in global equities. Likewise, President Trump’s tariffs will likely create similar supply and demand imbalances, while boosting prices for consumers, increasing costs for manufacturers, and potentially exacerbating trade tensions with other countries. Companies, as well as individuals, should be especially alert as the negotiations play out.

This report was updated on May 15, 2018 to add the last two columns, Implied Credit Score and S&P Rating/Outlook, to Figures 6 and 7, as well as to clarify that the companies listed have reported revenue exposure to China on a consolidated basis.

[i] The Conference Board Consumer Confidence Index Declined in March (March 27, 2018). Retrieved April 25, 2018, from https://www.conference-board.org/data/consumerconfidence.cfm

[ii] Notice of Determination and Request for Public Comment Concerning Proposed Determination of Action Pursuant to Section 301: China’s Acts, Policies, and Practices Related to Technology Transfer, Intellectual Property, and Innovation (n.d.). Retrieved April 25, 2018, from https://ustr.gov/sites/default/files/files/Press/Releases/301FRN.pdf

[iii] Mapping Letter Grade Score to Probability of Default Technical Reference Guide. Published November 2017.

[iv] Modeling the Impact of President President Trump’s Proposed Tariffs (April 12, 2018). Retrieved April 25, 2018, from https://taxfoundation.org/modeling-impact-president-President Trumps-proposed-tariffs/

[v] President Trump’s tariffs prompting some U.S. fund managers to look overseas. (March 9, 2018). Retrieved April 25, 2018, from https://www.reuters.com/article/us-usa-stocks-weekahead/President Trumps-tariffs-prompting-some-u-s-fund-managers-to-look-overseas-idUSKCN1GL1KV

[vi] China’s Developers Strengthen Defense for A Funding Crunch (April 22, 2018). Retrieved April 25, 2018, from S&P Global Ratings.

[vii] Four Facts About China’s $53 Billion President Trump Tariff Retaliation (April 5, 2018). Retrieved April 25, 2018, from Panjiva Inc.

Want to learn more about companies and sectors impacted by U.S.-Chinese tariffs?
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Technology, Media & Telecommunication
Judge OKs AT&T/Time Warner, Opening A Potential Bidding War For FOX Assets

Highlights

A federal judge approved the AT&T – Time Warner Merger, setting the stage for a frenzy of media consolidation. First up: a bidding war over 21st Century Fox.

The following post comes from Kagan, a research group within S&P Global Market Intelligence.

To learn more about our TMT (Technology, Media & Telecommunications) products and/or research, please request a demo.

Jun. 14 2018 — A U.S. district judge on June 12 approved AT&T Inc.'s acquisition of Time Warner Inc. with no restrictions, which should open up the media M&A floodgates in a world that is increasingly moving toward digital consumption of content. First up to bat: competitive bidding for most of 21st Century Fox Inc.

Comcast Corp., emboldened by the decision that the merger did not violate antitrust laws, offered on June 13 to purchase most of 21st Century Fox for $79.17 billion in cash, a 19.7% premium to Walt Disney Co.'s stock offer of $66.14 billion, worth $68.36 billion based on the close of Disney's stock June 13.

On a cash flow basis, the deal would be expensive, at 14.1x 2018 cash flow, although this drops to less than 10x when $2 billion in synergies are factored in.

Although the offer from Comcast is attractive, we think a competing offer that allowed shareholders to choose cash or stock may have been more attractive to some shareholders that have a low basis in their shares. Since this deal was widely expected to be announced, Disney has had plenty of time to consider whether it will bid higher, and if so, if it will do so with a mix of stock and cash. Should the board decide Comcast has the better deal, Disney would have five days to come up with a counter offer.

As the table below shows, the regional sports networks are the most expensive piece of the company, valued at an estimated $19.14 billion in the Comcast offer.

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Listen: Kagan MediaTalk - Episode 2: TV’s Summer Soccer Fever

The following post comes from Kagan, a research group within S&P Global Market Intelligence. To learn more about our TMT (Technology, Media & Telecommunications) products and/or research, please request a demo.

In this second episode of Kagan MediaTalk, senior research analysts Justin Nielson and Tony Lenoir discuss the upcoming FIFA World Cup, to be held in Russia June 14-July 15, and what soccer's biggest international stage means for the U.S. TV ecosystem.

In addition to being hosted on Soundcloud this podcast is also available on iTunes, Stitcher, and TuneIn.

No content (including ratings, credit-related analyses and data, valuations, model, software or other application or output therefrom) or any part thereof (Content) may be modified, reverse engineered, reproduced or distributed in any form by any means, or stored in a database or retrieval system, without the prior written permission of Standard & Poor's Financial Services LLC or its affiliates (collectively, S&P).


Credit Analysis
50 Years Of Altman Z-score, And PD Model Fundamentals – Case Study General Motors

Jun. 11 2018 — The year 2018 marks the 50th anniversary of the Altman Z-score, which was designed to gauge credit strength of publicly traded manufacturing corporates. Until this day, the model has been used by financial practitioners to obtain a condensed picture of the financial strength of a company, and serves as a benchmark for credit risk assessment models.

As a part of providing data and tools for a comprehensive analysis of credit risk, S&P Global Market Intelligence has developed a family of PD Model Fundamentals (PDFN). The PDFN is a statistical model that produces probability of default (PD) values over a one- to more than thirty-year horizon for public and private banks and corporations of any size. The model maps the PD values to credit scores1 (i.e. ‘bbb’), based on historical observed default rates (ODRs) extracted from S&P Global Ratings’ database (available on CreditPro® ) PDFN also offers a global coverage of over 250 countries and more than 20 segments, regions, and industries.

PDFN incorporates both financial risk and business risk to generate the overall PD value. This innovative approach captures, in a statistical PD model, important credit risk drivers as identified by S&P Global Ratings’ extensive experience in corporate credit assessments, and provides users with a well-rounded measure of credit risk, where different sources can be easily identified.

We apply the credit assessment metrics to analyze one of the most publicized bankruptcy events in the last decade, the case of General Motors (General Motors Company, formerly General Motors Corporation). In Figure 1 we present the historical evolution of credit risk for General Motors (GM) from January 2005 to May 2018, accompanied by bankruptcy related Key Developments. We compare assessed credit score by PDFN, Altman Z-score, and corresponding S&P Global Ratings Issuer Credit Rating.

At the beginning of 2005, PDFN indicates a credit risk score of ‘bbb-‘, while the S&P Global Ratings Issuer Credit Rating is ‘BBB-‘. The credit risk score indicates that General Motors had adequate capacity to meet its financial commitments. However, adverse economic conditions or changing circumstances are more likely to lead to a weakened capacity of the obligor to meet its financial commitments. Likewise, the Z-score indicates a rather problematic financial situation, placing General Motors in distressed zone category.

In the following months, the credit quality of General Motors rapidly deteriorated. PDFN signals highly increased probability of financial distress already at the beginning of 2007, more than two years in advance. The implied ‘ccc’ credit score suggests high vulnerability to adverse business, financial, or economic conditions with at least a one-in-two likelihood of default. A few months before default, PDFN indicates a credit score of ‘cc’, thus expecting default to be highly likely. Similarly, the S&P Global Ratings Issuer Credit Ratings shows decaying credit quality, albeit the credit rating changes are more sporadic and have larger increments. The Z-score starts to show a significant deterioration of credit quality one year prior to default, but with a notable lag in comparison with PDFN.

After completion of the post-bankruptcy reorganization, creditworthiness of General Motors improved, and PDFN indicates a fairly stable credit risk profile with an implied score of ‘bbb’. In comparison, S&P Global Ratings Issuer Credit Rating initially shows a greater conservatism in light of the reorganization processes. Since then, the credit rating has improved steadily, converging with PDFN estimate. Z-score shows a somewhat steady estimate of credit risk, with a slight deterioration in the recent years.

Figure 1: Historical evolution of credit risk for General Motors (GM)

The shaded area denotes the period of reorganization between the bankruptcy announcement and reemergence of General Motors (GM) as a public company on the New York Stock Exchange (NYSE). Dashed vertical lines denote bankruptcy related Key Development (see corresponding numbers for details). The Z-score scale has been selected to match the credit score level at the beginning of the period.

Source: S&P Global Market Intelligence (as of May 30th, 2018). For illustrative purposes only.

General Motors (GM) – Key Developments:
(1) Nov 8, 2008: GM heads towards bankruptcy
(2) Dec 31, 2008: GM expects to receive $13.40 billion in funding from U.S. Department of The Treasury.
(3) Feb 14, 2009: GM contemplates bankruptcy
(4) Jun 1, 2009: GM filed for bankruptcy
(5) Nov 17, 2010: GM has completed an IPO and starts trading on NYSE

PDFN incorporates both financial and business risk dimensions to generate an overall PD value as well as an assessment of each individual dimension (financial and business risk). It also comes equipped with a useful analytic tool, the contribution analysis, which allows users to identify drivers of risk, in absolute or relative terms, to define potential paths to creditworthiness improvement or deterioration.

Figure 2 presents the current credit risk profile of General Motors as provided by the PDFN based on last twelve months of data. The contribution analysis indicates that overall business risk is strong, but the company’s financial position is aggressive and is currently the main driver of overall PD estimate. A deep dive analysis shows a weak total equity position which in addition to profitability (EBIT/Total Assets) and efficiency (EBIT/Revenues), resulting in limited financial flexibility (Retained Earnings/Total Assets), represent the risk factors with the largest driver for the assigned credit risk score for General Motors.

Figure 2: Credit risk profile of General Motors (GM)

Source: S&P Global Market Intelligence (as of May 30th, 2018). For illustrative purposes only.

This case study exemplifies the value of PD Model Fundamentals, in providing predictive insights into companies’ creditworthiness and dynamic estimates of PD value and mapped credit score. Our model was trained and calibrated on default flags and is able to signal deterioration of credit quality well in advance of the actual bankruptcy event. The combination of both financial risk and business risk enables a comprehensive overview of a company's creditworthiness, while also providing an in-depth review of a company's credit risk profile to identify and distinguish the main sources of risk. S&P Global Market Intelligence leverages leading experience in developing PD models to achieve a high level of accuracy and a robust out-of-sample model performance. The integration of PDFN into the S&P Capital IQ platform allows users to access a global pre-scored database with more than 45,000 public companies and almost 700,000 private companies, obtain PD values for single or multiple companies, and perform a scenario analysis.

1 S&P Global Ratings does not participate in the creation of credit scores generated by S&P Global Market Intelligence. Lowercase nomenclature is used to differentiate S&P Global Market Intelligence PD credit model scores from the uppercase credit ratings issued by S&P Global Ratings.

Companies And Sectors Most Impacted By U.S.-Chinese Tariffs

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