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Evolution of Growth Investing in Europe

February 09, 2022

How is the growth equity landscape evolving in Europe? The heads of our Growth Equity team shared their views at a recent Alternative Investment Forum.       

November 22, 2021

The US Department of Labor recently announced a proposed rule that would make it easier for retirement plan fiduciaries to consider climate change and other ESG factors when selecting investments. These proposed “rules of the road” are designed to guide Employee Retirement Income Security Act (ERISA) fiduciaries who are considering ESG incorporation within their investment process.

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Top Research Reports for Apple, Goldman Sachs, & Applied Materials

May 25, 2021 — 03:27 pm EDT

Written by Sheraz Mian for Zacks  ->

Tuesday, May 25, 2021  

The Zacks Research Daily presents the best research output of our analyst team. Today's Research Daily features new research reports on 16 major stocks, including Apple Inc. (AAPL), Goldman Sachs (GS), and Applied Materials (AMAT). These research reports have been hand-picked from the roughly 70 reports published by our analyst team today.  

You can see all of today’s research reports here >>>  

Apple shares have lagged the market this year, with the stock down -4.4% this year vs. the +12.4% gain for the S&P 500 index. Driving this underperformance is the sentiment shift away from the large-cap Tech stocks and rotation into cyclical and 'value'-oriented stocks. That said,  Apple’s second-quarter fiscal 2021 results did reflect continued momentum in the Services segment, driven by a robust performance of App Store, Cloud Services, Music, advertising and AppleCare.

Moreover, iPad, Mac and Wearables contributed strongly to the quarterly results. Further, iPhone sales increased due to strong demand for iPhone 12 devices. China and Japan iPhone sales increased significantly.  

The Zacks analyst believes that Apple’s near-term prospects are bright, driven by new iPhones that support 5G, revamped iPad and Mac line-up of devices, health-focused Apple Watch and robust growth in the Services business. However, increasing scrutiny and legal woes over App Store is a headwind.  

(You can read the full research report on Apple here >>> )  

Shares of Goldman Sachs have gained +55.7% in the last six months against the Zacks Financial - Investment Bank industry’s gain of +45.4%. In fact, the company has an impressive earnings surprise history, having outpaced the Zacks Consensus Estimate in each the trailing four quarters.  

The Zacks analyst believes that the company’s first-quarter 2021 results benefited from robust capital markets performance and reserve release. Goldman’s solid position in announced and completed M&As across the world will keep strengthening the business. Also, business diversification, including digital platforms, helps sustain growth. Efforts to expand consumer lending business are encouraging. Steady capital deployment activities remain a tailwind.  

With a strong liquidity position, it remains less exposed to credit risk in case of any economic downturn. However, legal issues, high dependence on overseas revenues and volatile client-activity might impede top-line growth.  

(You can read the full research report on Goldman Sachs here >>> )  

Shares of Applied Materials have outperformed the Zacks Semiconductor Equipment - Wafer Fabrication industry in the last one-year period (+144.0% vs. +119.0%). The Zacks analyst believes that Applied Materials is driven by strong momentum across Semiconductor Systems and Applied Global Services. Further, solid demand for silicon in several applications across various markets remains a tailwind. Additionally, growing momentum among long-term service agreements is contributing well.  

Furthermore, increased customer spending in foundry and logic on the back of rising need for specialty nodes in automotive, power, 5G rollout, IoT, communications and image sensor markets, is a major positive. Also, strong momentum in conductor etches is benefiting the company’s position in DRAM and NAND. However, market uncertainties continue to persist. Further, mounting expenses are concerns. Also, rising competition poses risk to the company’s market position.  

(You can read the full research report on Applied Materials here >>> )  

Other noteworthy reports we are featuring today include Snap Inc. (SNAP), Exelon Corporation (EXC) and The Travelers Companies, Inc. (TRV).  

Bitcoin, Like the Internet Itself, Could Change Everything  

Blockchain and cryptocurrency has sparked one of the most exciting discussion topics of a generation. Some call it the “Internet of Money” and predict it could change the way money works forever. If true, it could do to banks what Netflix did to Blockbuster and Amazon did to Sears. Experts agree we’re still in the early stages of this technology, and as it grows, it will create several investing opportunities.

Zacks’ has just revealed 3 companies that can help investors capitalize on the explosive profit potential of Bitcoin and the other cryptocurrencies with significantly less volatility than buying them directly.  

See 3 crypto-related stocks now >>  

Sheraz Mian  

Director of Research  

Note: Sheraz Mian heads the Zacks Equity Research department and is a well-regarded expert of aggregate earnings. He is frequently quoted in the print and electronic media and publishes the weekly Earnings Trends and Earnings Preview reports. If you want an email notification each time Sheraz publishes a new article, please click here>>>

Today's Must Read

Robust Portfolio, Services Strength to Benefit Apple (AAPL)

Digital Lending Platform Aids Goldman (GS), High Costs Ail

Applied Materials (AMAT) Rides on Foundry & Logic Spending

Featured Reports

Regulated Investments & Cost Mangement Aid Exelon (EXC)

Per the Zacks analyst Exelon's cost management initiatives will have positive impact on margins and its planned $27B investments through 2024 will strengthen its operation.

Onto Innovation (ONTO) Rides on 5G Momentum Amid Competition

Per the Zacks analyst, Onto Innovation is well positioned to benefit from market strength in memory and radio frequency communications for 5G handsets along with the acceptance of new products.

Auto, Homeowners Business Aid Travelers (TRV), Cat Loss Ails

Per the Zacks analyst, consistent progress and strong market of the auto and homeowners business have driven revenues.

Strength in Glaukos' (GKOS) iStent Product Line Aids Q1 Sales

The Zacks analyst is upbeat about Glaukos' commercial rollout of the iStent inject W. New agreement with Santen Pharmaceutical for PRESERFLO MicroShunt buoys optimism.

Gibraltar (ROCK) Rides on Segmental Performance, Cost Hurt

Per the Zacks analyst' robust performance of Residential, Renewable and Infrastructure segments are likely to boost Gibraltar's margins.

Solid User Growth & Premium Content Demand Aids Snap (SNAP)

Per the Zacks analyst, Snap benefits from an improving user growth driven by strong adoption of Augmented Reality (AR) Lenses and demand for premium Discover content and Shows.

Backlog Boosts Huntington Ingalls (HII), Import Tariff Woes

Per the Zacks analyst, solid backlog count for Huntington Ingalls boosts its revenue growth prospects. Yet expansion of tariffs steel and aluminum import might push up its expenses.

New Upgrades

Electrification & Cost Cuts to Drive American Axle (AXL)

Collaborations with Inovance and REE Automotive are likely to boost American Axle's electrification revenues. Cost cut efforts is also aiding the firm's near-term profits, per the Zacks analyst.

Capri Holdings' (CPRI) Digital Endeavors to Aid Top Line

Per the Zacks analyst, deployment of resources to upgrade distribution infrastructure and e-commerce platform, and expand product offerings bode well for Capri Holdings' sales.

Rising Loans Aid First Republic (FRC), Capital Level Solid

Per Zacks analyst, rising loan and deposit balances along with improving net interest income are likely to aid First Republic's financials. Also, strong capital position remains a favorable factor.

New Downgrades

Biohaven's (BHVN) Reliance on Nurtec Burden Amid Competition

Per the Zacks analyst, Biohaven is solely dependent on successful commercialization of Nurtec for its near-term growth. However, it faces stiff competition from several large pharma companies.

Golar LNG (GLNG) Plagued By Low LNG Demand & Weak Liquidity

The Zacks analyst is concerned about Golar LNG's soft LNG demand, which continues to be hurt by coronavirus-led woes. The company's weak liquidity position is also worrisome.

Phillips 66 (PSXP) to be Hurt by Lower Throughput Volume

Phillips 66 Partners' declining profits due to lower pipeline throughput volumes of crude oil concerns the Zacks analyst. Moreover, its levered balance sheet is troublesome.

The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.

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Unveiling Tilray Brands (TLRY) Q3 Outlook: Wall Street Estimates for Key Metrics

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Earnings Growth & Price Strength Make Micron (MU) a Stock to Watch

Wondering how to pick strong, market-beating stocks for your investment portfolio? Look no further than the Zacks Focus List.

Why AMD Stock Is Down Over 20% From Its Peak

Advanced Micro Devices believes its AI chip, the MI300x, will be its biggest growth opportunity.

• Goldman Sachs-stock
• News for Goldman Sachs

Goldman Sachs Group (GS) Gets a Buy from Evercore ISI

Evercore ISI analyst Glenn Schorr maintained a Buy rating on Goldman Sachs Group ( GS – Research Report ) yesterday and set a price target of $435.00. The company’s shares closed yesterday at $406.25.

Schorr covers the Financial sector, focusing on stocks such as Bank of New York Mellon Corporation, BlackRock, and Citigroup. According to TipRanks , Schorr has an average return of 7.5% and a 61.73% success rate on recommended stocks.

In addition to Evercore ISI, Goldman Sachs Group also received a Buy from Seaport Global’s James Mitchell in a report issued yesterday. However, on March 26, RBC Capital maintained a Hold rating on Goldman Sachs Group (NYSE: GS).

The company has a one-year high of $419.20 and a one-year low of $284.98. Currently, Goldman Sachs Group has an average volume of 2.33M.

Based on the recent corporate insider activity of 22 insiders, corporate insider sentiment is negative on the stock. This means that over the past quarter there has been an increase of insiders selling their shares of GS in relation to earlier this year.

TipRanks has tracked 36,000 company insiders and found that a few of them are better than others when it comes to timing their transactions. See which 3 stocks are most likely to make moves following their insider activities.

Goldman Sachs Group (GS) Company Description:

Founded in 1869, Goldman Sachs Group, Inc. is a leading global investment banking, securities, and investment management firm. The company provides a range of financial services to clients including corporations, financial institutions, governments and individuals. The company operates through four segments: Investment Banking, Global Markets, Asset Management, and Consumer & Wealth Management.

Read More on GS:

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• Reddit (NYSE:RDDT) Prices IPO at $34 Per Share
• Analysts and Technical Indicators Agree: These 3 Stocks Are “Strong Buys” – 03/21/2024 

Goldman Sachs News MORE

Related stocks.

Legal and finance jobs are among the most at risk from AI, while construction and trade jobs face minimal influence, studies suggest

• Generative AI could lead to the widespread automation of jobs, new research found.
• But blue-collar roles in manufacturing and construction face minimal influence, data indicates.
• Here's why some industries will likely be more affected than others by the technology.

Rapid advances in artificial intelligence are stoking employee concerns about the automation of jobs.

Generative AI , a type of AI capable of generating text and other content in response to user prompts, has exploded in popularity in recent months following the launch of OpenAI's ChatGPT. Some companies have already tapped the chatbot to take on content-producing roles.

A recent report from Goldman Sachs found the tech could significantly disrupt the labor market, with it affecting about 300 million full-time jobs or 18% of work. Another recent study , from OpenAI with the University of Pennsylvania, found OpenAI's AI chatbot ChatGPT could affect around 80% of jobs in the US. White-collar roles could be among the worst hit, the study also found. 

While the studies predicted advances in AI tech could also improve labor productivity and create jobs, they said some industries would likely be more affected than others.

Legal services 

The legal industry has been cited in multiple studies as one of the industries most exposed to automation. 

A  study released in March by researchers at Princeton University, the University of Pennsylvania, and New York University, estimated that legal was the industry most likely influenced by AI tech like ChatGPT. The researchers used a benchmark that matched specific work tasks with AI capabilities to calculate the results. 

Manav Raj, one of the authors of the study and an assistant professor of management at the Wharton School of the University of Pennsylvania, told Insider this was because the industry was made up of a relatively small number of occupations already exposed to automation, such as legal assistants. 

The report from Goldman Sachs, which relies on an analysis of data on occupational tasks in the US and Europe, also highlighted legal workers as especially at risk from the new tech.

University education and research 

Education was one of  the first areas to witness some of the effects of ChatGPT, and institutions, especially those in higher education, are scrambling to deal with the consequences of the technology.

The study led by Princeton University, which was authored by Raj, Ed Felten, and Robert Seamans, identified postsecondary teachers as some of the workers highly exposed to large language models.

Professors across a variety of subjects made up eight of the top 10 affected occupations, while junior colleges were ranked the 17th most likely sector to be influenced. Raj said this was because AI chatbots tended to be very good at research tasks such as identifying patterns and writing reports.

Related stories

The research from Goldman Sachs, which was written by Joseph Briggs and Devesh Kodnani, estimated almost 30% of work tasks in education instruction and library services in the US and Europe could be automated.

Administration 

Administrative roles have particularly high exposure to automation, Goldman researchers found. They estimated that about 46% of work tasks in the sector could be automated.

Wharton's Raj said that sectors like administration, where there's a "relatively high prevalence of white-collar roles, tended to be more exposed" to advanced AI technology. But the effect of AI on the labor market will be "multifaceted," Raj said, in some cases complementing human work.

Finance 

Banks are already incorporating AI tech into their day-to-day business operations.

More than half of banks say they've used the tech for revenue generation, according to the Cambridge Centre for Alternative Finance and the World Economic Forum. Financial quantitative analysts were also identified in a study led by OpenAI and the University of Pennsylvania as one of the occupations highly exposed to advanced AI technology. 

AI chatbots like ChatGPT have excelled at writing code. The new programs can analyze numbers and produce code, often at a faster rate than humans can. 

The study led by Princeton University ranked software publishers as the 11th most likely sector to be affected by tech like ChatGPT, something Raj put down to the chatbot's impressive coding abilities. The Goldman researchers estimated that about 29% of computing and mathematical tasks in the US and Europe could be automated.

Construction

Sectors with a high number of blue-collar roles, such as construction, scored relatively low on Goldman Sachs' report. In the US and Europe, the researchers estimated less than 10% of work tasks in the sector were exposed to automation.

Construction and related workers were also ranked some of the least influenced occupations on the list compiled by researchers at Princeton University, the University of Pennsylvania, and New York University. 

Trade workers

Trade workers are also projected to be relatively untouched by the tech. 

Trade work requires practical, hands-on experience and specialized training, and many of the tasks involve manual labor.

Craft and related trade workers had the lowest share of industry employment exposed to automation in Europe, Goldman Sachs found. The researchers estimated that only 4% of the industry was exposed to automation by AI in the region.

Axel Springer, Business Insider's parent company, has a global deal to allow OpenAI to train its models on its media brands' reporting.

Watch: What is ChatGPT, and should we be afraid of AI chatbots?

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Rating Report

Goldman Sachs México, Casa de Bolsa, S.A. de C.V.

Mexico   Tue 02 Apr, 2024 - 9:48 AM ET

Las calificaciones de Goldman Sachs México, Casa de Bolsa, S. A. de C. V. (GSMX) están impulsadas por la opinión de Fitch Ratings sobre la propabilidad de que la casa de bolsa reciba soporte extraordinario, si es necesario, de su accionista en última instancia, The Goldman Sachs Group, Inc. (GS, el accionista).

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• US Economics Analyst

Data Quality Is Still a Problem: Seasonal Distortions and Falling Response Rates (Walker)

Data quality is still a problem: seasonal distortions and falling response rates, the us economic and financial outlook.

The market’s sensitivity to individual data releases has increased sharply over the last couple of years, as those releases will ultimately decide Fed policy. However, two data quality issues have made assessing the implications of data releases for the outlook in real time more difficult.

First, distortions to seasonal adjustment factors caused by level shifts and much larger than usual swings in data early in the pandemic can bias our perception of the state of the economy. These distortions are most apparent in continuing jobless claims—which have predictably risen over the last couple of months because of seasonal adjustment issues—and Census retail sales—which will likely underperform “true” consumption activity during the holiday season—but likely affect a broader set of economic indicators.

We assess whether revisions to pre-pandemic seasonal factors for 22 indicators have introduced new seasonal distortions. Our analysis suggests that, on average, residual seasonality boosts seasonally-adjusted economic indicators by 0.2 standard deviations between March and May—the period when economic activity declined most sharply in 2020—and weighs them down during the rest of the year. On average, the effects are modestly smaller than when we conducted the same analysis last year and should continue to fade in future years.

Second, falling response rates to government statistical surveys can increase the uncertainty around the reported state of the economy. For example, the response rate to the Job Openings and Labor Turnover Survey (JOLTS) has plummeted almost 30pp since the start of the pandemic to just over 30%. The resulting smaller sample size has likely boosted its median monthly standard error—a measure of the expected discrepancy between a sample estimate and the true value of a population—by more than 90% relative to 2002-2013 (equivalent to a 90% confidence interval of roughly 700k).

Lower response rates have also likely contributed to larger-than-usual data revisions, as incremental responses can have a greater influence on updated estimates. For example, JOLTS job openings have been revised by an average of 180k in the second print over the last couple of years, double what was typical four years ago and more than triple what was typical six years ago.

Understanding these data quality problems introduced by the pandemic has been vital to interpreting the economic data over the last few years. In particular, it has enabled investors to see through several misleading signals sent by fluctuations in the jobless claims and official job openings data. We have addressed these challenges by calculating our own seasonal adjustment factors when necessary and supplementing official data plagued by low response rates with alternative data based on much larger sample sizes.

The market’s focus on and sensitivity to individual data releases has increased sharply over the last couple of years, as those releases will ultimately determine Fed policy. Unfortunately, the increased scrutiny comes at a time when data quality issues have made assessing the implications of data releases for the outlook in real time more difficult. In this week’s Analyst , we discuss two data quality issues. First, we explore the extent to which seasonal distortions could be biasing our perception of the state of the economy. Second, we assess the impact of falling response rates to government statistical surveys, which can increase the uncertainty around a reported state of the economy.

Residual Seasonality: Seasonal Echoes of the Pandemic

Almost all US economic data are presented in a seasonally adjusted format. At its most basic level, seasonal adjustment involves comparing unadjusted values in a given month with the average value in other months; months that typically see weaker activity (e.g. housing starts in the winter) are adjusted up, while months that typically see strong activity (e.g. starts in the summer) are adjusted down—with the overall impact roughly netting out over the full year.

While seasonal adjustment allows economists to look through typical seasonal patterns and extract the underlying signal from economic indicators, as we wrote last year, the large swings in economic data during the pandemic have introduced distortions to several series, for two main reasons.

First, if a series is adjusted “multiplicatively”—that is, if seasonal swings are assumed to happen in proportion to the series’ level—a rapid level shift in that series will result in a proportional swing in the seasonal factors. But if the magnitude of seasonal changes remains similar to what it was before the shift, the seasonal factors will over-correct the series’ typical fluctuations, leading it to look higher in months when it is typically lower and vice-versa.

We find that this issue continues to distort seasonally-adjusted nominal retail sales ex. autos, which are multiplicatively seasonally adjusted. Retail sales ex. autos have increased to 35% above Feb. 2020 levels as consumer spending has seen a persistent shift away from services and towards goods. The series’ multiplicative seasonal factors have not meaningfully changed since 2019, meaning that the amplitude of the implied additive seasonal factors has grown substantially as a result of the higher year-round level of spending. For example, the December seasonal hurdle increased by $6bn year-over-year in 2021 and by $2bn in 2022.

It seems unlikely that the typical seasonal increases in spending around the holidays should rise proportionately with the increased year-round level of spending: the fact that consumers buy 35% more goods today does not necessarily imply that they will also buy 35% more at Christmas relative to how much they bought during the rest of the year. If, instead, consumers increased their demand for goods year-round but the typical dollar-increase that happens in the holidays remained unchanged (e.g. a consumer decides to buy a computer to work from home but does not buy more computers for her relatives at Christmas), the “true” seasonal swing would thereby be additive to the level of retail sales, and using a multiplicative seasonal factor would distort the series.

Even almost four years since the start of the pandemic, it is still hard to gauge which of these descriptions—additive or multiplicative—applies to retail sales. The increase in retail sales driven by higher prices—~13pp of the 35% increase—probably should be multiplicatively adjusted while it's less obvious for the remaining 22pp. But if the seasonal “truth” lies somewhere in between, a purely multiplicative approach would result in a meaningful deceleration in retail sales following the strength in the fall, other things equal. And indeed, as shown in Exhibit 1, seasonally-adjusted retail sales declined sharply last November and December, when the seasonal hurdle became sharply more punitive, before reversing the decline in January and February, when the seasonal hurdle swung back in the other direction. Seasonal fluctuations are often very large relative to seasonally-adjusted changes, and as a result, estimates of seasonally-adjusted changes can be very sensitive to any imperfections in the seasonal adjustment factors.

Exhibit 1 : Retail Sales Growth Disappointed Last Holiday Season, as Spending Did Not Grow Proportionally with the Elevated Level of Retail Sales

Source: Department of Commerce, Goldman Sachs Global Investment Research

A second issue that can distort seasonal factors is the large swings in many economic indicators at the height of the pandemic. While the pandemic was the shortest recession on record, it was also the deepest in post-war history, with most economic indicators hitting their lows by the start of 2020Q2. Unless special measures are taken, seasonal adjustment programs react to this plunge in activity by generating more of a “boost” for data in surrounding years during those early spring months; adjustment factors for the months of the rapid plunge (those surrounding March 2020) will “help” more and those in other months will become more negative. However, if the underlying seasonal patterns have not actually changed, seasonally-adjusted data will then look stronger in the early part of the year and weaker thereafter.

The left panel of Exhibit 2 shows seasonally-adjusted continuing jobless claims that were reported as of the end of 2019. The right panel shows the seasonally-adjusted series as of today. After the BLS recalculated the old seasonal factors with pandemic era data, a distinct seasonal pattern emerged in the 2018 and 2019 seasonally-adjusted series. In those years, the revised continuing claims series shows a steeper decline from March through September followed by a rebound in September through March.

Exhibit 2 : Seasonal Patterns Emerged Across Seasonally-Adjusted Continuing Claims Following the Recalculation of Seasonal Factors With Pandemic Era Data

Source: Department of Labor, Goldman Sachs Global Investment Research

These revisions could in principle simply be the result of properly evolving seasonal factors. “True” seasonal patterns often change over time; when they do, seasonal factors should change with them. For example, there has been a gradual shift in not-seasonally-adjusted retail sales from December to October and November over many years as consumers started holiday shopping earlier. The evolution in the seasonal factors for retail sales has taken that shift into account, as it ought to, and the resulting change in seasonal adjustment was therefore not the result of residual seasonality.

However, naturally-evolving seasonal changes are unlikely to explain the predictable seasonal patterns introduced by the revisions shown in Exhibit 2. As evidence of residual seasonality, Exhibit 3 compares the revisions to pre-pandemic seasonally-adjusted continuing claims [ 1 ] to the latest vintages of seasonally-adjusted continuing claims in 2023. The high degree of correlation shown (0.45 on a w/w basis, 0.80 on a 4w change basis) indicates that the changes to seasonal factors that arose from the pandemic are likely continuing to have undue influence on this year’s seasonally-adjusted data. Exhibit 4 shows that if taken at face value, this exercise suggests that essentially all of the 182k increase in continuing claims over the last couple of months is attributable to residual seasonality.

Exhibit 3 : Revisions to Pre-Pandemic Data Arising From the Recalculation of Seasonal Factors Have Predicted Changes in Seasonally-Adjusted Continuing Claims This Year

Exhibit 4 : Seasonal Distortions Can Alter Our Perception of the State of the Economy: Continuing Claims Have Been Flat Over the Last Couple of Months if Properly Adjusted

We can apply this same analysis—using revisions to pre-pandemic seasonal factors as a measure of residual seasonality—to a broader suite of economic indicators. Exhibit 5 shows the results of this exercise, expressed relative to the standard deviations of each indicator in 2019 (e.g. residual seasonality boosts seasonally-adjusted continuing claims by 0.7 standard deviations on average in January; note that we flip the sign for claims so that lower levels, which are a positive signal about growth, show up as positive residual seasonality) and ordered so that indicators with greater average absolute residual seasonality are at the top of the table.

Jobless claims appear at the top of the list, which is unsurprising for two reasons. First, the increase in claims at the outset of the pandemic was particularly outsized and thus the impact on the estimation of seasonal factors should be similarly outsized. Second, government statisticians sometimes remove obvious outliers from seasonal calculations, leading some series to be less likely to be distorted by pandemic-related residual seasonality. These kinds of adjustments were made earlier this year to jobless claims, meaningfully reducing the seasonal distortions in initial claims —which topped the list last year—but inadvertently amplifying them in continuing claims—which received special adjustments to a similar set of weeks despite evolving differently in 2020 and 2021. Seasonal distortions are also much more apparent in continuing claims than initial claims today because the series’ underlying volatility has fallen to below pre-pandemic levels while initial claims’ remains ~60% above.

Consistent with adjustment factors evolving to “help” more in the months that experienced the most rapid plunges at the start of the pandemic, our analysis suggests that residual seasonality is most supportive of measured activity in March-May (+0.2 standard deviations on average) and more punitive in the rest of the year, particularly in October-December (-0.2 standard deviations on average).

On average, these estimated effects are modestly smaller than when we conducted the same analysis last year and should continue to diminish with time (Exhibit 6). However, at the same time, the underlying data has become less volatile (the avg. standard deviation is 23% above 2019 levels in 2023 vs. 55% in 2022), suggesting that seasonal distortions could explain a greater share of the data’s variation going forward.

Exhibit 5 : On Average, We Estimate That Residual Seasonality Boosts Seasonally-Adjusted Economic Indicators by 0.2 Standard Deviations in March-May and Lowers Them During the Rest of the Year

Source: Goldman Sachs Global Investment Research

Exhibit 6 : Our Estimates of the Impact of Residual Seasonality on Seasonally-Adjusted Economic Indicators Have Declined in Magnitude Relative to Last Year

Falling Response Rates: Would You Answer the Call?

Response rates to government statistical surveys have fallen sharply during the pandemic, accelerating a downward trend seen over the past decade (Exhibit 7). We see two main channels through which a lower response rate can impact economic data. The first is through nonresponse bias (i.e. a declining response rate can bias medium-term trends if the probability of nonresponse is correlated with respondents’ answers). Earlier this year, we showed that nonresponse bias may have been modestly boosting the reported level of job openings, and a few studies from Fed and government economists have suggested that select series have been impacted by nonresponse. [ 2 ] However, we do not have reason to think that the broader set of data has been biased by nonresponse.

Exhibit 7 : The Pandemic Accelerated the Secular Decline in Response Rates to Economic Surveys

Source: Department of Labor, Department of Commerce, Goldman Sachs Global Investment Research

Second, a lower response rate reduces the sample size, which can increase month-to-month volatility (see Appendix) and widen the confidence interval around point estimates. For this point, we focus on the Job Openings and Labor Turnover Survey (JOLTS). The decline in the JOLTS response rate has been particularly severe, falling from roughly 70% a decade ago to just under 60% in 2019 and just over 30% by the end of last year. Exhibit 8 shows that, as a result, the median monthly standard error—a measure of the expected discrepancy between a sample estimate and the true value of a population—for the JOLTS job openings rate has likely increased by over 90% relative to 2002-2013. [ 3 ] An increase of this magnitude translates to a 90% confidence interval of roughly 700k around the latest job openings reading.

Exhibit 8 : A Lower Response Rate Has Likely Pushed the Median Monthly Standard Error for the Job Openings Rate More Than 90% Higher Relative to 2002-2013

A smaller sample size can also lead to larger revisions in previously reported data, as incremental responses have a greater influence on updated estimates. Exhibit 9 shows that JOLTS job openings have been revised by an average of 180k in their second reading over the last couple of years, double what was typical four years ago and more than triple what was typical six years ago.

Exhibit 9 : The Magnitude of Revisions to JOLTS Has Risen Meaningfully Over the Last Few Years

Understanding these data quality problems introduced by the pandemic has been vital to interpreting the economic data over the last few years. In particular, it has enabled investors to see through several misleading signals sent by fluctuations in the jobless claims and official job openings data. We have addressed these challenges by calculating our own seasonal adjustment factors when necessary and supplementing official data with alternative data. The decline in response rates to government surveys has increased the relative value of administrative and alternative data (e.g. jobless claims and web-based measures of job openings) that are immune from declining response rates and often calculated from much larger samples . However, as we have highlighted for many years, those series often have their own issues and are often best thought of as complements and cross-checks to the official government statistics.

Ronnie Walker

Economic data remains more volatile vs. pre-pandemic—even after controlling for changes in growth—potentially in part because of lower response rates to economic surveys.

Investors should consider this report as only a single factor in making their investment decision. For Reg AC certification and other important disclosures, see the Disclosure Appendix , or go to www.gs.com/research/hedge.html .

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We, Jan Hatzius, Alec Phillips, David Mericle, Spencer Hill, CFA, Ronnie Walker, Tim Krupa and Manuel Abecasis, hereby certify that all of the views expressed in this report accurately reflect our personal views, which have not been influenced by considerations of the firm's business or client relationships.

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• Jan Hatzius
• Economics Research
• United States

How to diversify as global stock markets grow more concentrated

Stock market concentration has increased dramatically in recent years at the market, sector, and stock level. However there are ways investors can diversify their portfolios while maintaining exposure to market leaders, according to Goldman Sachs Research.

“Market dominance is not unprecedented and is only a problem if it is not supported by fundamentals,” Peter Oppenheimer, chief global equity strategist and head of Macro Research in Europe for Goldman Sachs Research, writes in the team’s report. “That said, at the stock level in particular, dominant companies rarely stay the best performers over long periods of time.” ( Listen to the Goldman Sachs Exchanges podcast on rising stock market concentration .)

Why is the US stock market so strong?

The US stock market has consistently been the world’s biggest over the past 50 years, but its share has been steadily climbing in the aftermath of the global financial crisis (GFC). It now captures around 45% of the global equity market, compared with about 30% in 2009.

The longer-term rise in the relative size of the US equity market has reflected the strength of the US economy, but its dominance has accelerated dramatically since the GFC, outstripping increases in market capitalization in Asia and Europe. Relative to GDP, the US share of equity market capitalization has risen steadily as well, though part of this reflects the fact that many non-US companies are now in the US stock market.

The stellar earnings growth of US companies over this time further explains their relative outperformance, Oppenheimer writes. Both share prices and earnings per share have consistently declined for non-US companies relative to their US-listed counterparts. In addition, the US stock market has more exposure to faster growing industries than the rest of the world, the reinvestment rate of companies in the US stock market is higher than in most other markets, and it enjoys greater liquidity that helps reduce the risk premium.

“The US economy is bigger and stronger than others and the growing trend towards US listings by foreign-based companies has added to this effect,” Oppenheimer writes.

While the US equity market has become increasingly expensive relative to the rest of the world, the premium being placed on US stocks is justified by superior rates of return, and the US valuation premium isn’t extreme when adjusting for its higher level of profitability and returns on equity, according to Goldman Sachs Research. Furthermore, diversifying outside the US isn’t always straightforward — other markets may be correlated with the US.

That said, “there are many quality growth companies” in other regions, and they should be considered as part of a diverse portfolio, Oppenheimer writes. The report cites Japan as a potentially attractive market among developed markets, and our analysts say there may be opportunities in India (notably growth stocks) and China (value stocks).

Goldman Sachs Research also recommends an overweight allocation to Europe’s consumer-cyclical stocks — companies whose performance is closely linked to the state of the economy and the business cycle — as the region’s activity rebounds (European consumers have high savings and real wage growth).

Tech sector domination could continue

Another source of increasing market concentration is among sectors, as technology, media, and telecom stocks have continued to capture a rising share of the global stock market, particularly in the US but also in other markets such as Asia.

While global technology profits have surged since the GFC, other sectors in aggregate have made “virtually no progress,” Oppenheimer notes. This dynamic was exacerbated by the pandemic, which enforced social distancing and drove demand for technology relative to other parts of the economy.

“While the rise in interest rates over the past couple of years dented the relative earnings growth of the technology sector, its superior growth rate has resumed over the past year,” Oppenheimer writes. Tech firms’ significant cash piles have given them a further advantage from the recent rise in interest rates, as they have reinvested their cash at a very high rate.

The level of tech concentration is not unprecedented among dominant sectors in the past, according to Goldman Sachs Research. The current tech sector is about the same size as the energy sector was at its height in the mid-1950s, for example, and it remains smaller than both transportation (which dominated in the 20th century) and finance and real estate (which drove the stock market in the 19th century).

“Over the past 200 years, the biggest industry represented in the stock market at each point in time has reflected the major driver of economic growth,” Oppenheimer writes.

While our researchers recommend overweight allocations to technology stocks in all regions, they see good opportunities for investors to hedge technology dominance by diversifying tech exposure with selected fast growing, or “growth” stocks, that are cheaper. There may be opportunities in healthcare in all regions except Japan, due to a combination of attractive valuations and high growth prospects, Oppenheimer writes. Likewise European GRANOLAS — 11 of the largest companies in the STOXX 600 — as a group is relatively cheaper than their Magnificent Seven counterparts in the US. These European stocks have similarly strong balance sheets, high profits, and high and stable margins, according to the report.

To diversify further among sectors, investors can increase exposure to “ex tech compounders” — the term the team uses for companies that have market capitalizations above $10 billion and share certain key factors. These include high margins, high profitability, strong balance sheets, low volatility, strong growth prospects, and a decade’s worth of consistent earnings growth behind them.

Finally, quality growth stocks can be complemented with some value stocks — companies that trade at relatively cheap valuations compared to their growth and earnings potential. Some examples of these equities include energy and financials in the US, and consumer cyclicals in Europe, according to Goldman Sachs Research.

Can the Magnificent Seven hold on?

Oppenheimer and his colleagues also take a look at the investment implications of a small handful of companies dominating the stock market. Separate analysis by Goldman Sachs Research finds that the US stock market has often rallied after bouts of high concentration. Oppenheimer and his team find similar patterns of high concentration in other markets, including Europe (the group of GRANOLAS stocks account for nearly one quarter of the value of the 600 biggest companies).

“While high stock market concentration may be a sign of a bubble, it does not necessarily mean there is one,” Oppenheimer writes. High stock concentration isn’t unusual, and many of the dominant companies of late have high profits and strong balance sheets.

Even so, today’s dominant companies are far from assured of having such a high share of market capitalization further down the line. Only 52 companies have appeared every year in the Fortune 500 since 1955, according to Goldman Sachs Research, and it predicts that almost all of today’s top companies will be missing from the list when it’s released 70 years from now.

“Historically, with new entrants emerging, few companies remain unscathed as competition either forces companies to disappear, merge, or be acquired,” the authors write. “From this perspective, a market that becomes dominated by a few stocks becomes increasingly vulnerable to either disruption or anti-trust regulation.”

This article is being provided for educational purposes only. The information contained in this article does not constitute a recommendation from any Goldman Sachs entity to the recipient, and Goldman Sachs is not providing any financial, economic, legal, investment, accounting, or tax advice through this article or to its recipient. Neither Goldman Sachs nor any of its affiliates makes any representation or warranty, express or implied, as to the accuracy or completeness of the statements or any information contained in this article and any liability therefore (including in respect of direct, indirect, or consequential loss or damage) is expressly disclaimed.

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