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

Energy

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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.

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Watch: Power Forecast Briefing: Fleet Transformation, Under-Powered Markets, and Green Energy in 2018

Steve Piper shares Power Forecast insights and a recap of recent events in the US power markets in Q4 of 2017. Watch our video for power generation trends and forecasts for utilities in 2018.


Technology, Media & Telecom
Trading Of US Linear TV Advertising Shifting To Programmatic Trading

Oct. 08 2018 — Both buyers and sellers of traditional linear TV advertising, not including connected TV or over-the-top video, are moving toward the adoption of programmatic trading. In 2017, Kagan estimates that $690 million or 0.9% of total linear TV spend was traded programmatically. Within the next five years, that figure is expected to climb to $9.76 billion or nearly 12% of total linear TV advertising revenue. MVPDs are forecast to trade the greatest percentage of their ad inventory programmatically in 2022 with 30% of ad revenue from programmatic trading.

Kagan defines programmatic trading as being automated and data-enhanced, not just one or the other. Trading may be through a private or open marketplace and does not have to be through an auction, which is more common in digital video advertising.

There are several issues holding participants back from programmatic trading. Unlike digital programmatic marketplaces, where there is a seemingly unending supply of ad inventory, linear TV has a finite supply. Demand for TV inventory exceeds the supply, so there is still an attitude of "If it isn't broken, don't fix it." TV ads are also bought well in advance, not immediately.

While many agencies have experimented with the programmatic trading of linear TV, not all are on board. Many of the advertisers and agencies are interacting directly with the supplier platform rather than going through a demand-side platform, or DSP, today. In their experiments, the agency needs to use separate platforms to aggregate inventory and tie it together, which is a lot of work.

The lack of inventory is one factor holding back programmatic trading. The only way it takes off is to make linear TV inventory available in some type of buyer platform that can combine the various supply platforms. It is even more complicated when the buyer wants to bring in connected TV (OTT).

Agencies do like the automation capabilities of programmatic, particularly where the process takes a lot of time. An algorithm may do better in areas such as weighting estimation, the first pass at scheduling and the negotiation process as well as postings and billings. The process of buying inventory is not difficult, but computing where a buyer will be able to find its preferred audience is. Therefore, interest in automating the planning and analysis to find an optimal audience is high.

We forecast a gradual uptake for programmatic trading with continued testing in 2018. Broadcast stations and networks, cable programmers, and MVPDs need to add more inventory to programmatic platforms before agencies begin using it in earnest. It will take time for all parties to feel comfortable transacting in a new way.

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Technology
Every Industry Is Now A Technology Industry

Highlights

And every company is now a technology company.

Sep. 28 2018 — As machine learning (ML), artificial intelligence (AI), and robotics become commonplace and enter the operations of mainstream organizations, leadership teams are finding that failure to harness and leverage AI puts them behind the competition. Repeatable tasks are carried out by bots in a fraction of the time and employees are more focused on adding value, which means companies on the forefront of technology can be more reliable, more user-friendly, and faster to market.

In this highly disruptive environment, one traditional truth of business has withstood, or has perhaps even guided, these technological advances: above all, the customer experience is king. More than ever before, businesses have effective technologies at their fingertips to quickly and effectively address customer pain points, while at the same time dramatically improving their internal operations.

At S&P Global Market Intelligence, we strive to get beyond the buzzwords and truly deliver essential insight. And second to this, we strive to adopt real operational efficiencies into our delivery that are paralleled by the workflow efficiencies we promise to our customers. To that end, we are committed to remaining on the cutting edge of emerging technologies, first through optimization, then automation.

Download a recent analysis of how we’re applying new technology like natural language processing to structure data, robotic process automation to deliver insights faster, and predictive analytics to stay ahead of the market.

You can also view this analysis in Spanish, Portuguese, Mandarin, and Japanese.

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Technology, Media & Telecom
Online Video Bolstering Consumer Home Video Spend, Spearheaded By Subscription Streaming

Highlights

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.

Sep. 20 2018 — Spending on home entertainment is rising toward levels not seen since 2004, when consumers spent $24.37 billion building massive home-video libraries of DVDs and VHS cassettes. Since then, the optical-disc market saw more than a decade of significant declines as consumers shifted to digital entertainment. By 2012, total spending on home entertainment was down to $20.13 billion, with $4.13 billion coming from online video while DVDs and Blu-ray discs accounted for $12.88 billion and multichannel PPV/VOD contributed the remaining $3.13 billion.

Fast forward to 2017 and the mix of consumer spending has changed significantly. Consumers spent a total of $22.62 billion on home entertainment from multichannel, online and disc retail/rental sources. Online spending accounted for $13.00 billion of that total while spending on discs dropped to $6.84 billion and multichannel PPV/VOD shrank to $2.79 billion.

While the data might seem like good news for traditional providers of home entertainment, a key component of the growth in digital spending is the rise of subscription video on demand. The majority of online spending is going to over-the-top services like Netflix, Hulu and Amazon Prime, which increasingly have focused on creating original programming (mainly episodic TV) rather than licensing content from Hollywood studios.

Removing subscription streaming from the consumer spending pool paints a less favorable picture for traditional content providers. In 2012, consumers spent just $1.43 billion on non-subscription online video purchase/rental, and a total of $17.44 billion excluding the SVOD component. By 2017, while consumer spending on online video overall had risen to $13.00 billion, some $10.47 of that came from streaming subscriptions versus $2.53 billion from online video purchase/rental, and total home-entertainment spending was just $12.16 billion excluding SVOD.

Spending on sell-through home video peaked in 2006 when consumers shelled out $16.53 billion for DVDs and VHS cassettes. Since then spending has declined by hundreds of millions (sometimes billions) each year. In 2017, consumers spent $6.50 billion on DVD and Blu-ray sell-through and electronic sell-through. This seems to suggest that people are becoming less and less interested in adding to their home-video libraries and are turning to the more affordable streaming options. The story is similar for the home-video rental segment, which saw consumer spending peak in 2001 at nearly $8.45 billion before dropping to $2.87 billion by the end of 2017.

This has to be a somewhat unsettling trend for the major film studios, and is likely a key factor in shifting their strategy to focus on major franchise films and low-cost genre fare. The former tend to have broad worldwide appeal and can still move enough video units to help offset their high production and distribution costs. The low-cost genre fare, on the other hand, may be more risky and not sell as well internationally, but has a fair chance to break even. If the latter films lose money, the successful franchise films typically cover the losses.

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