February was a great month for Wall Street. These were our 5 best-performing stocks

Traders work on the floor at the New York Stock Exchange (NYSE) in New York City, U.S., February 23, 2024. 

Brendan McDermid | Reuters

February was a strong month for stocks and the Club’s portfolio.

The advance came as investors parsed through fourth-quarter earnings results and fresh economic data, searching for clues about when the Federal Reserve will finally cut interest rates. The Nasdaq Composite led the march higher in February, gaining 6.1% and finishing the month at its first record close since November 2021. Meanwhile, the Dow Jones Industrial Average and S&P 500 both hit a series of all-time highs throughout the month, climbing 2.2% and 5.2%, respectively.

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Fed officials expressed caution about lowering rates too quickly at last meeting, minutes show

WASHINGTON – Federal Reserve officials indicated at their last meeting that they were in no hurry to cut interest rates and expressed both optimism and caution on inflation, according to minutes from the session released Wednesday.

The discussion came as policymakers not only decided to leave their key overnight borrowing rate unchanged but also altered the post-meeting statement to indicate that no cuts would be coming until the rate-setting Federal Open Market Committee held “greater confidence” that inflation was receding.

“Most participants noted the risks of moving too quickly to ease the stance of policy and emphasized the importance of carefully assessing incoming data in judging whether inflation is moving down sustainably to 2 percent,” the minutes stated.

The meeting summary did indicate a general sense of optimism that the Fed’s policy moves had succeeded in lowering the rate of inflation, which in mid-2022 hit its highest level in more than 40 years.

However, officials noted that they wanted to see more before starting to ease policy, while saying that rate hikes are likely over.

“In discussing the policy outlook, participants judged that the policy rate was likely at its peak for this tightening cycle,” the minutes stated. But, “Participants generally noted that they did not expect it would be appropriate to reduce the target range for the federal funds rate until they had gained greater confidence that inflation was moving sustainably toward 2 percent.”

Before the meeting, a string of reports showed that inflation, while still elevated, was moving back toward the Fed’s 2% target. While the minutes assessed the “solid progress” being made, the committee viewed some of that progress as “idiosyncratic” and possibly due to factors that won’t last.

Consequently, members said they will “carefully assess” incoming data to judge where inflation is heading over the longer term. Officials noted both upside and downside risks and worried about lowering rates too quickly.

Questions over how quickly to move

“Participants highlighted the uncertainty associated with how long a restrictive monetary policy stance would need to be maintained,” the summary said.

Officials “remained concerned that elevated inflation continued to harm households, especially those with limited means to absorb higher prices,” the minutes said. “While the inflation data had indicated significant disinflation in the second half of last year, participants observed that they would be carefully assessing incoming data in judging whether inflation was moving down sustainably toward 2 percent.”

The minutes reflected an internal debate over how quickly the Fed will want to move considering the uncertainty about the outlook.

Since the Jan. 30-31 meeting, the cautionary approach has borne out as separate readings on consumer and producer prices showed inflation running hotter than expected and still well ahead of the Fed’s 2% 12-month target.

Multiple officials in recent weeks have indicated a patient approach toward loosening monetary policy. A stable economy, which grew at a 2.5% annualized pace in 2023, has encouraged FOMC members that the succession of 11 interest rate hikes implemented in 2022 and 2023 have not substantially hampered growth.

To the contrary, the U.S. labor market has continued to expand at a brisk pace, adding 353,000 nonfarm payroll positions in January. First-quarter economic data thus far is pointing to GDP growth of 2.9%, according to the Atlanta Fed.

Along with the discussion on rates, members also brought up the bond holdings on the Fed’s balance sheet. Since June 2022, the central bank has allowed more than $1.3 trillion in Treasurys and mortgage-backed securities to roll off rather than reinvesting proceeds as usual.

‘Ample level of reserves’

The minutes indicated that a more in-depth discussion will take place at the March meeting. Policymakers also indicated at the January meeting that they are likely to take a go-slow approach on a process nicknamed “quantitative tightening.” The pertinent question is how high reserve holdings will need to be to satisfy banks’ needs. The Fed characterizes the current level as “ample.”

“Some participants remarked that, given the uncertainty surrounding estimates of the ample level of reserves, slowing the pace of runoff could help smooth the transition to that level of reserves or could allow the Committee to continue balance sheet runoff for longer,” the minutes said. “In addition, a few participants noted that the process of balance sheet runoff could continue for some time even after the Committee begins to reduce the target range for the federal funds rate.”

Fed officials consider current policy to be restrictive, so the big question going forward will be how much it will need to be relaxed both to support growth and control inflation.

There is some concern that growth continues to be too fast.

The consumer price index rose 3.1% on a 12-month basis in January – 3.9% when excluding food and energy, the latter of which posted a big decline during the month. So-called sticky CPI, which weighs toward housing and other prices that don’t fluctuate as much, rose 4.6%, according to the Atlanta Fed. Producer prices increased 0.3% on a monthly basis, well above Wall Street expectations.

In an interview on CBS’ “60 Minutes” that aired just a few days after the FOMC meeting, Chair Jerome Powell said, “With the economy strong like that, we feel like we can approach the question of when to begin to reduce interest rates carefully.” He added that he is looking for “more evidence that inflation is moving sustainably down to 2%.”

Markets have since had to recalibrate their expectations for rate cuts.

Where traders in the fed funds futures market had been pricing in a near lock for a March cut, that has been pushed out to June. The expected level of cuts for the full year had been reduced to four from six. FOMC officials in December projected three.

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2 out of 5 industrial stocks are at record highs. Here’s our post-earnings outlook on all of them

Eaton Corporation signage at the NYSE

Source: NYSE

Earnings season was not perfect for our industrial-focused portfolio companies, but we’re feeling pretty good about their prospects for the rest of the year.

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These oil companies could be the next takeover targets in Permian Basin after Diamondback deal

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Bitcoin, AI and Magnificent 7: The emerging ETF trends as industry gathers for big conference

Over two thousand attendees are descending on the Fontainebleau Hotel in Miami Beach for the annual Exchange ETF conference. To entice participants, the organizers rented out the entire LIV Nightclub Miami at the hotel for a Super Bowl party Sunday night.

While much of the conference is an excuse to party among the ETF industry reps and the Registered Investment Advisors  (RIAs) that are the main attendees, the industry needs a lot of advice.

The Good news: still lots of money coming in, but the industry is maturing

The ETF juggernaut continues to rake in money, now with north of $8 trillion in assets under management.  Indexing/passive investing, the main impetus behind ETFs 30 years ago, continues to bring in new adherents as smarter investors, including the younger ones that have begun investing since the pandemic, come to understand the difficulty of outperforming the market.

The bad news is much of the easy money has already been made as the industry is now reaching middle aged. Just about every type of index fund that can be thought of is already in existence. 

To grow, the ETF industry has to expand the offerings of active management and devise new ways to entice investors.  

Actively managed strategies did well in 2023, accounting for about a quarter of all inflows.  Covered call strategies like the JPMorgan Equity Premium Income ETF (JEPI), which offered protection during a downturn, raked in money.  But with the broad markets hitting new highs, it’s not clear if investors will continue to pour money into covered call strategies that, by definition, underperform in rising markets.

Fortunately, the industry has proven very skilled at capturing whatever investing zeitgeist is in the air.  That can range from the silly (pot ETFs when there was no real pot industry) to ideas that have had some real staying power.

Six or seven years ago, it was thematic tech ETFs like cybersecurity or electric vehicles that pulled in investors. 

The big topics in 2024:  Bitcoin, AI, Magnificent 7 alternatives

In 2024, the industry is betting that the new crop of bitcoin ETFs will pull in billions.  Bitcoin for grandma?  We’ll see.

Besides bitcoin, the big topics here in Miami Beach are 1) A.I/ and what it’s going to do for financial advisors and investors, and 2) how to get clients to think about equity allocation beyond the Magnificent 7.

Notably absent is China investing.

Bitcoin for grandma?  Financial advisors are divided on whether to jump in

Ten spot bitcoin ETFs have successfully launched.  The heads of three of those, Matt Hougan, chief investment officer at Bitwise, Steve Kurz, global head of asset management at Galaxy and David LaValle, global head of ETFs at Grayscale, will lead a panel offering advice to financial advisors, who seem divided on how to proceed.

Ric Edelman, the founder of Edelman Financial Engines, the #1 RIA in the country and currently the head of the Digital Assets Council of Financial Professionals (DACFP), will also be present. 

Edelman has long been a bitcoin bull. He recently estimates bitcoin’s price will reach $150,000 within two years (about three times its current price), and has estimated that Independent RIAs, who collectively manage $8 trillion, could invest 2.5% of their assets under management in crypto in the next two to three years, which would translate into over $154 billion.

Inflows into bitcoin ETFs to date have been modest, but bitcoin ETFs are being viewed by some advisors as the first true bridge between traditional finance and the crypto community. 

But many advisors are torn about recommending them, not just because of the large number of competing products, but because of the legal minefields that still exist around bitcoin, specifically around SEC Chair Gary Gensler’s warning that any financial advisor recommending bitcoin would have to be mindful of “suitability” requirements for clients.

For many, those suitability requirements, along with the high volatility, continuing charges of manipulation, and the doubt about bitcoin as a true asset class will be enough to keep them away. 

The bitcoin ecosystem is in going into overdrive to convince the RIA community otherwise.

 Artificial intelligence: What can it do for the investing community?

Thematic tech investing (cybersecurity, robotics, cloud computing, electric vehicles, social media, etc.) has waxed and waned in the last decade, but there is no doubt Artificial Intelligence ETFs (IRBT, ROBT, BOTZ)  has recaptured some interest.  The problem is defining what an AI investment looks like and which companies are exposed to AI.

But the impact is already being felt by the financial advisory community.

Jason Pereira, senior partner & financial Planner, Woodgate Financial, is speaking on how financial advisors are using artificial intelligence.  There are amazing AI tools that financial advisors can now use.  Pereira describes how it is now possible to generate financial podcasts with just snippets of your own voice.  Just plug in a text, and it can generate a whole podcast without ever saying the actual words.  How to generate text?  In theory, you could go to Chat GPT and say, for example, “Write 500 words about current issues in 401(k)s,” and rewrite it slightly for a specific audience.

In a world where a million people can now generate a podcast on financial advice, how do you maintain value?  Much of the lower skilled tasks (data analysis) will quickly become commodified, but Pereira believes a very big difference will quickly emerge between volume and quality.

Equity Allocation Beyond the Magnificent Seven

Financial advisors are beset by clients urging them to throw money at the Magnificent 7.  Roundhill’s new Magnificent 7 ETF (MAGS) has pulled in big money in the last few months, now north of $100 million in assets under management.

Since the end of last year, there have been enormous inflows into technology ETFs (Apple, Microsoft, NVIDIA), and modest inflows into communications (Meta and Alphabet) and consumer discretionary (Amazon).  Most everything else has languished, with particular outflows in energy, health care, and materials. 

Advisors are eager for advice on how to talk to clients about the concentration risks involved in investing solely in big-cap tech and how to allocate for the long haul. 

Alex Zweber, managing director investment strategy at Parametric and Eric Veiel, head of global investments and CIO at T. Rowe Price are leading a panel on alternative approaches that have had some success recently, including ETFs that invest in option overlays, but also on quality and momentum investing in general, which overlaps but is broader than simply investing in the Magnificent 7.

Stop talking about numbers and returns and start offering “human-centric” advice

Talk to any financial advisor for more than a few minutes, and they will likely tell you how difficult it is dealing with some clients who are convinced they should put all their money into NVIDIA, or Bolivian tin mines, or who have investing ADHD and want to throw all their money in one investment one day, then pull it out the next.

Brian Portnoy and Neil Bage, co-founders of Shaping Wealth, are leading one of the early panels on how financial advisors can move away from an emphasis on numbers and more toward engaging with their clients on a more personal and emotional level.

Sounds touchy-feely, but competition for clients has become intense, and there is a new field emerging on how to provide financial advice that is less centered on numbers (assets under management, fees, quarterly statements), and more centered on developing the investor’s understanding of behavioral finance and emotional intelligence. 

Under this style of investment advice, often called “human-centric” or “human-first” advice, more time may be spent discussing behavioral biases that lead to investing mistakes than on stock market minutiae. This may help the clients develop behaviors that, for example, are better suited to longer term investing (less trading, less market timing).  

Advocates of this approach believe this is a much better way to engage and keep clients for the long term.

What’s missing? China

For years, a panel on international investing, and specifically emerging markets/China investing, was a staple at ETF conferences.

Not anymore.  Notably absent is any discussion of international investing, but particularly China, where political risk is now perceived to be so high that investors are fleeing China and China ETFs. 

Indeed, investing “ex-China” is a bit of a thing.

The iShares Emerging Markets ex-China ETF (EMXC) launched with little fanfare in 2017 and had almost no assets under management for several years.  That changed in late 2022, when China ETFs began a long slow descent, and inflows exploded into EMXC from investors who still wanted emerging market exposure, just not to China.

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Oil prices could spike 20%, possibly double if Middle East conflict disrupts Strait of Hormuz

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These Middle East flashpoints could trigger regional conflict that impacts oil prices

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2024 energy outlook: What investors can expect from crude prices, and how to play it

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GPT and other AI models can’t analyze an SEC filing, researchers find

Patronus AI co-founders Anand Kannappan and Rebecca Qian

Patronus AI

Large language models, similar to the one at the heart of ChatGPT, frequently fail to answer questions derived from Securities and Exchange Commission filings, researchers from a startup called Patronus AI found.

Even the best-performing artificial intelligence model configuration they tested, OpenAI’s GPT-4-Turbo, when armed with the ability to read nearly an entire filing alongside the question, only got 79% of answers right on Patronus AI’s new test, the company’s founders told CNBC.

Oftentimes, the so-called large language models would refuse to answer, or would “hallucinate” figures and facts that weren’t in the SEC filings.

“That type of performance rate is just absolutely unacceptable,” Patronus AI co-founder Anand Kannappan said. “It has to be much much higher for it to really work in an automated and production-ready way.”

The findings highlight some of the challenges facing AI models as big companies, especially in regulated industries like finance, seek to incorporate cutting-edge technology into their operations, whether for customer service or research.

The ability to extract important numbers quickly and perform analysis on financial narratives has been seen as one of the most promising applications for chatbots since ChatGPT was released late last year. SEC filings are filled with important data, and if a bot could accurately summarize them or quickly answer questions about what’s in them, it could give the user a leg up in the competitive financial industry.

In the past year, Bloomberg LP developed its own AI model for financial data, business school professors researched whether ChatGPT can parse financial headlines, and JPMorgan is working on an AI-powered automated investing tool, CNBC previously reported. Generative AI could boost the banking industry by trillions of dollars per year, a recent McKinsey forecast said.

But GPT’s entry into the industry hasn’t been smooth. When Microsoft first launched its Bing Chat using OpenAI’s GPT, one of its primary examples was using the chatbot to quickly summarize an earnings press release. Observers quickly realized that the numbers in Microsoft’s example were off, and some numbers were entirely made up.

‘Vibe checks’

Part of the challenge when incorporating LLMs into actual products, say the Patronus AI co-founders, is that LLMs are nondeterministic — they’re not guaranteed to produce the same output every time for the same input. That means that companies will need to do more rigorous testing to make sure they’re operating correctly, not going off-topic, and providing reliable results.

The founders met at Facebook parent company Meta, where they worked on AI problems related to understanding how models come up with their answers and making them more “responsible.” They founded Patronus AI, which has received seed funding from Lightspeed Venture Partners, to automate LLM testing with software, so companies can feel comfortable that their AI bots won’t surprise customers or workers with off-topic or wrong answers.

“Right now evaluation is largely manual. It feels like just testing by inspection,” Patronus AI co-founder Rebecca Qian said. “One company told us it was ‘vibe checks.'”

Patronus AI worked to write a set of more than 10,000 questions and answers drawn from SEC filings from major publicly traded companies, which it calls FinanceBench. The dataset includes the correct answers, and also where exactly in any given filing to find them. Not all of the answers can be pulled directly from the text, and some questions require light math or reasoning.

Qian and Kannappan say it’s a test that gives a “minimum performance standard” for language AI in the financial sector.

Here’s some examples of questions in the dataset, provided by Patronus AI:

  • Has CVS Health paid dividends to common shareholders in Q2 of FY2022?
  • Did AMD report customer concentration in FY22?
  • What is Coca Cola’s FY2021 COGS % margin? Calculate what was asked by utilizing the line items clearly shown in the income statement.

How the AI models did on the test

Patronus AI tested four language models: OpenAI’s GPT-4 and GPT-4-Turbo, Anthropic’s Claude 2 and Meta’s Llama 2, using a subset of 150 of the questions it had produced.

It also tested different configurations and prompts, such as one setting where the OpenAI models were given the exact relevant source text in the question, which it called “Oracle” mode. In other tests, the models were told where the underlying SEC documents would be stored, or given “long context,” which meant including nearly an entire SEC filing alongside the question in the prompt.

GPT-4-Turbo failed at the startup’s “closed book” test, where it wasn’t given access to any SEC source document. It failed to answer 88% of the 150 questions it was asked, and only produced a correct answer 14 times.

It was able to improve significantly when given access to the underlying filings. In “Oracle” mode, where it was pointed to the exact text for the answer, GPT-4-Turbo answered the question correctly 85% of the time, but still produced an incorrect answer 15% of the time.

But that’s an unrealistic test because it requires human input to find the exact pertinent place in the filing — the exact task that many hope that language models can address.

Llama 2, an open-source AI model developed by Meta, had some of the worst “hallucinations,” producing wrong answers as much as 70% of the time, and correct answers only 19% of the time, when given access to an array of underlying documents.

Anthropic’s Claude 2 performed well when given “long context,” where nearly the entire relevant SEC filing was included along with the question. It could answer 75% of the questions it was posed, gave the wrong answer for 21%, and failed to answer only 3%. GPT-4-Turbo also did well with long context, answering 79% of the questions correctly, and giving the wrong answer for 17% of them.

After running the tests, the co-founders were surprised about how poorly the models did — even when they were pointed to where the answers were.

“One surprising thing was just how often models refused to answer,” said Qian. “The refusal rate is really high, even when the answer is within the context and a human would be able to answer it.”

Even when the models performed well, though, they just weren’t good enough, Patronus AI found.

“There just is no margin for error that’s acceptable, because, especially in regulated industries, even if the model gets the answer wrong 1 out of 20 times, that’s still not high enough accuracy,” Qian said.

But the Patronus AI co-founders believe there’s huge potential for language models like GPT to help people in the finance industry — whether that’s analysts, or investors — if AI continues to improve.

“We definitely think that the results can be pretty promising,” said Kannappan. “Models will continue to get better over time. We’re very hopeful that in the long term, a lot of this can be automated. But today, you will definitely need to have at least a human in the loop to help support and guide whatever workflow you have.”

An OpenAI representative pointed to the company’s usage guidelines, which prohibit offering tailored financial advice using an OpenAI model without a qualified person reviewing the information, and require anyone using an OpenAI model in the financial industry to provide a disclaimer informing them that AI is being used and its limitations. OpenAI’s usage policies also say that OpenAI’s models are not fine-tuned to provide financial advice.

Meta did not immediately return a request for comment, and Anthropic didn’t immediately have a comment.

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Friday’s S&P 500 and Nasdaq-100 rebalance may reflect concerns over concentration risk

It’s arguably the biggest stock story of 2023: a small number of giant technology companies now make up a very large part of big indexes like the S&P 500 and the Nasdaq-100. 

Five companies (Apple, Microsoft, Amazon, Nvidia and Alphabet) make up about 25% of the S&P 500. Six companies (Apple, Microsoft, Amazon, Nvidia, Alphabet and Broadcom) make up about 40% of the Nasdaq-100. 

The S&P 500 and the Nasdaq are rebalancing their respective indexes this Friday. While this is a routine event, some of the changes may reflect the concerns over concentration risk. 

A ton of money is pegged to a few indexes 

Now that the CPI and the Fed meeting are out of the way, these rebalances are the last major “liquidity events” of the year, corresponding with another notable trading event: triple witching, or the quarterly expiration of stock options, index options and index futures. 

This is an opportunity for the trading community to move large blocks of stock for the last gasps of tax loss harvesting or to position for the new year. Trading volume will typically drop 30%-40% in the final two weeks of the year after triple witching, with only the final trading day showing significant volume.

All of this might appear of only academic interest, but the big move to passive index investing in the past 20 years has made these events more important to investors. 

When these indexes are adjusted, either because of additions or deletions, or because share counts change, or because the weightings are changed to reduce the influence of the largest companies, it means a lot of money moves in and out of mutual funds and ETFs that are directly or indirectly tied to the indexes. 

Standard & Poor’s estimates that nearly $13 trillion is directly or indirectly indexed to the S&P 500. The three largest ETFs (SPDR S&P 500 ETF Trust, iShares Core S&P 500 ETF, and Vanguard S&P 500 ETF) are all directly indexed to the S&P 500 and collectively have nearly $1.2 trillion in assets under management. 

Linked to the Nasdaq-100 — the 100 largest nonfinancial companies listed on Nasdaq — the Invesco QQQ Trust (QQQ) is the fifth-largest ETF, with roughly $220 billion in assets under management. 

S&P 500: Apple and others will be for sale. Uber going in 

For the S&P 500, Standard & Poor’s will adjust the weighting of each stock to account for changes in share count. Share counts typically change because many companies have large buyback programs that reduce share count. 

This quarter, Apple, Alphabet, Comcast, Exxon Mobil, Visa and Marathon Petroleum will all see their share counts reduced, so funds indexed to the S&P will have to reduce their weighting. 

S&P 500: Companies with share count reduction

(% of share count reduction)

  • Apple        0.5%
  • Alphabet   1.3%
  • Comcast    2.4%
  • Exxon Mobil  1.0%
  • Visa                0.8%
  • Marathon Petroleum  2.6%

Source: S&P Global

Other companies (Nasdaq, EQT, and Amazon among them) will see their share counts increased, so funds indexed to the S&P 500 will have to increase their weighting. 

In addition, three companies are being added to the S&P 500: Uber, Jabil, and Builders FirstSource.  I wrote about the effect that being added to the S&P was having on Uber‘s stock price last week.  

Three other companies are being deleted and will go from the S&P 500 to the S&P SmallCap 600 index: Sealed Air, Alaska Air and SolarEdge Technologies

Nasdaq-100 changes: DoorDash, MongoDB, Splunk are in 

The Nasdaq-100 is rebalanced four times a year; however, the annual reconstitution, where stocks are added or deleted, happens only in December. 

Last Friday, Nasdaq announced that six companies would be added to the Nasdaq-100: CDW Corporation (CDW), Coca-Cola Europacific Partners (CCEP), DoorDash (DASH), MongoDB (MDB), Roper Technologies (ROP), and Splunk (SPLK). 

Six others will be deleted: Align Technology (ALGN), eBay (EBAY), Enphase Energy (ENPH), JD.com (JD), Lucid Group (LCID), and Zoom Video Communications (ZM).

Concentration risk: The rules

Under federal law, a diversified investment fund (mutual funds, exchange-traded funds), even if it just mimics an index like the S&P 500, has to satisfy certain diversification requirements. This includes requirements that: 1) no single issuer can account for more than 25% of the total assets of the portfolio, and 2) securities that represent more than 5% of the total assets cannot exceed 50% of the total portfolio. 

Most of the major indexes have similar requirements in their rules. 

For example, there are 11 S&P sector indexes that are the underlying indexes for widely traded ETFs such as the Technology Select SPDR ETF (XLK). The rules for these sector indexes are similar to the rules on diversification requirements for investment funds discussed above. For example, the S&P sector indexes say that a single stock cannot exceed 24% of the float-adjusted market capitalization of that sector index and that the sum of the companies with weights greater than 4.8% cannot exceed 50% of the total index weight. 

At the end of last week, three companies had weights greater than 4.8% in the Technology Select Sector (Microsoft at 23.5%, Apple at 22.8%, and Broadcom at 4.9%) and their combined market weight was 51.2%, so if those same prices hold at the close on Friday, there should be a small reduction in Apple and Microsoft in that index. 

S&P will announce if there are changes in the sector indexes after the close on Friday. 

The Nasdaq-100 also uses a “modified” market-capitalization weighting scheme, which can constrain the size of the weighting for any given stock to address overconcentration risk. This rebalancing may reduce the weighting in some of the largest stocks, including Apple, Microsoft, Amazon, Nvidia and Alphabet. 

The move up in these large tech stocks was so rapid in the first half of the year that Nasdaq took the unusual step of initiating a special rebalance in the Nasdaq-100 in July to address the overconcentration of the biggest names. As a result, Microsoft, Apple, Nvidia, Amazon and Tesla all saw their weightings reduced. 

Market concentration is nothing new

Whether the rules around market concentration should be tightened is open for debate, but the issue has been around for decades.

For example, Phil Mackintosh and Robert Jankiewicz from Nasdaq recently noted that the weight of the five largest companies in the S&P 500 was also around 25% back in the 1970s.

Disclosure: Comcast is the corporate parent of NBCUniversal and CNBC.

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