Wondering if NICE stock could be a hidden gem or just another falling knife? You’re in the right place to get an honest, in-depth take on whether it’s time to buy or wait.
The stock has seen a dramatic ride lately, climbing 3.4% in the last week but still sitting 22.8% lower over the past month and down a hefty 45.6% year-to-date.
Recent market headlines have focused on sector-wide volatility and shifts in investor sentiment, with NICE specifically highlighted for its approach to new technology partnerships and industry collaborations. This extra context is key, as news-driven swings are impacting short-term moves and shaping longer-term expectations.
With a valuation score of 4 out of 6, there is a lot more to unpack below the surface. Let’s dig into how different valuation methods assess NICE, and stick around to the end for a perspective that might change how you think about value altogether.
Find out why NICE’s -48.1% return over the last year is lagging behind its peers.
A Discounted Cash Flow (DCF) model estimates a company’s intrinsic value by projecting its future cash flows and discounting them back to today’s value. This approach helps investors gauge what a business is truly worth compared to its share price in the market.
For NICE, its current Free Cash Flow stands at $684.36 Million. Analyst forecasts suggest steady growth, with projected Free Cash Flow reaching $963.8 Million by 2029. While analysts provide estimates for the next five years, Simply Wall St extends these projections further out and offers a longer-term perspective on future performance.
Using these cash flow projections, the DCF model calculates a fair value of $688.13 per share. This suggests the stock is trading at a 50.7% discount compared to its estimated intrinsic value, indicating it may be undervalued at current prices.
Result: UNDERVALUED
Our Discounted Cash Flow (DCF) analysis suggests NICE is undervalued by 50.7%. Track this in your watchlist or portfolio, or discover 920 more undervalued stocks based on cash flows.
NICE Discounted Cash Flow as at Nov 2025
Head to the Valuation section of our Company Report for more details on how we arrive at this Fair Value for NICE.
For profitable companies like NICE, the Price-to-Earnings (PE) ratio is a key valuation tool. It shows how much investors are willing to pay today for each dollar of last year’s earnings. This metric is especially useful because it captures both a company’s ability to generate profits and the market’s expectations around its future growth and risks.
Growth expectations and risk play a significant role in what constitutes a “normal” or “fair” PE. Higher growth companies often warrant higher multiples, while increased risk leads investors to be less willing to pay a premium. Therefore, looking only at the surface-level PE can be misleading if these factors are not taken into account.
NICE currently trades at a PE ratio of 11.5x. For context, the average Software industry PE is 27.6x, and the average for NICE’s direct peers is a much higher 46.0x. At first glance, NICE appears significantly cheaper than others in its space.
However, simply comparing with industry or peer averages does not provide the full picture. This is where the Simply Wall St “Fair Ratio” comes in. The Fair Ratio is a proprietary measure that considers a company’s own earnings growth, industry dynamics, profit margin, total market cap, and its unique risks. This more tailored approach helps move beyond the limitations of traditional benchmarking and offers a clearer sense of whether the stock’s valuation is justified.
For NICE, the Fair Ratio is calculated at 10.7x, which is very close to its current PE of 11.5x. This indicates the market price is generally in line with the company’s underlying fundamentals at present.
Result: ABOUT RIGHT
TASE:NICE PE Ratio as at Nov 2025
PE ratios tell one story, but what if the real opportunity lies elsewhere? Discover 1443 companies where insiders are betting big on explosive growth.
Earlier, we mentioned that there is an even better way to understand valuation, so let’s introduce you to Narratives. A Narrative is your chance to put a story behind the numbers by combining what you know about a company’s strategy, risks, or catalysts, along with your assumptions for future revenue, earnings, and margins. Narratives connect your view of the company’s direction to a set of financial forecasts, which then generate your own fair value for the stock.
The beauty of Narratives is their accessibility. On Simply Wall St’s Community page, millions of investors use Narratives to create, refine, and share their perspectives on companies like NICE. This tool empowers you to outline your story, back it up with the factors you believe matter most, and see how your assumptions compare to both analyst estimates and the market price.
Narratives help you decide how your Fair Value relates to the current Price, and they dynamically update as new news or earnings are released, so your outlook stays relevant and actionable. For instance, one Narrative for NICE assumes rapid AI-driven revenue growth and gives a fair value over ₪750 per share, while a more cautious view highlights margin pressures and assigns a much lower value.
Do you think there’s more to the story for NICE? Head over to our Community to see what others are saying!
TASE:NICE Community Fair Values as at Nov 2025
This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned.
Companies discussed in this article include NICE.TA.
Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email editorial-team@simplywallst.com
Curious whether Rio Tinto Group is a bargain or just another big name in the market? You are not alone, and now is a great time to get the facts on its real value.
The stock has climbed 13.8% year-to-date and delivered a 16.6% return over the last 12 months. Recent weeks saw a small dip, showing both resilience and sensitivity to market shifts.
This movement has been driven by renewed optimism in global commodities, especially as ongoing infrastructure projects and demand from emerging economies continue to put upward pressure on iron ore prices. A recent surge in environmental investments has also caught investor attention, further influencing Rio Tinto’s position in the materials sector.
According to our valuation checks, Rio Tinto Group scores 5 out of 6 for being undervalued. We will examine this result in more detail by breaking down the numbers with different valuation methods, and later, share an even smarter way to make sense of it all.
Find out why Rio Tinto Group’s 16.6% return over the last year is lagging behind its peers.
A Discounted Cash Flow (DCF) model estimates a company’s true value by projecting its future cash flows and discounting them back to the present. This approach aims to reveal whether the market price is aligned with the business’s earning power over time.
For Rio Tinto Group, recent financials show a last twelve months Free Cash Flow of $7.08 billion. Analysts anticipate strong ongoing growth, with free cash flow projected to rise to $15.26 billion by 2028. Over the coming decade, Simply Wall St extrapolates these trends and projects free cash flow to approach nearly $35.5 billion by 2035. All these projections are provided in the company’s reporting currency, U.S. dollars.
The DCF model values Rio Tinto’s shares at an intrinsic fair value of $189.55, which is 71.4% higher than the current share price. According to this projection, the company appears significantly undervalued compared to where its cash flows are expected to be over time.
Result: UNDERVALUED
Our Discounted Cash Flow (DCF) analysis suggests Rio Tinto Group is undervalued by 71.4%. Track this in your watchlist or portfolio, or discover 920 more undervalued stocks based on cash flows.
RIO Discounted Cash Flow as at Nov 2025
Head to the Valuation section of our Company Report for more details on how we arrive at this Fair Value for Rio Tinto Group.
For profitable companies like Rio Tinto Group, the Price-to-Earnings (PE) ratio is a widely used valuation metric because it connects a stock’s current price directly to its earnings power. A lower PE can suggest a bargain, while a higher one might point to high growth expectations or perceived safety. What counts as a “normal” or “fair” PE ratio depends on how much the market expects the company to grow and how much risk is involved. Faster growth or lower risk can justify a higher ratio.
Rio Tinto currently trades at a PE ratio of 11.4x. For context, the global Metals and Mining industry averages about 16.3x, while Rio Tinto’s peer group is even higher at 39.0x. This means Rio Tinto is priced well below both its sector and direct competitors based solely on its trailing earnings.
Simply Wall St’s “Fair Ratio” analyzes what a reasonable PE would be for Rio Tinto by considering its growth outlook, risk profile, profit margins, market cap, and industry dynamics. This proprietary metric is more powerful than a simple peer or sector comparison because it accounts for company-specific strengths and weaknesses, not just where it sits among competitors.
With a Fair Ratio of 23.6x, Rio Tinto’s actual PE is less than half of what Simply Wall St’s model suggests is justified for the business at this time. This large gap points to the stock being undervalued relative to its potential, even after adjusting for unique factors that make Rio Tinto stand out or pose more risk compared to the average miner.
Result: UNDERVALUED
LSE:RIO PE Ratio as at Nov 2025
PE ratios tell one story, but what if the real opportunity lies elsewhere? Discover 1443 companies where insiders are betting big on explosive growth.
Earlier we mentioned that there’s an even better way to understand valuation, so let’s introduce you to Narratives. A Narrative is a simple, interactive story that connects your views on a company’s future, such as revenue, earnings, margins, and risk, to a concrete financial forecast and a resulting fair value. Instead of relying solely on formulas or analyst targets, Narratives allow you to express your own perspective on what will drive Rio Tinto Group’s future, whether that’s mining expansion in battery metals or challenges from cost inflation.
This approach makes investing more human and accessible, transforming numbers into living stories. It is available on Simply Wall St’s Community page, where millions of investors share and update their Narratives in real time. By comparing fair values shaped by these stories to the current market price, you get clear, up-to-date information on whether to buy, hold, or sell. Narratives automatically adapt as new information, such as earnings or market news, comes in so your analysis stays relevant.
For example, some investors may see Rio Tinto Group’s aggressive growth in copper and lithium as reason for a high fair value. Others focus on commodity risk and project execution to arrive at a more conservative price, letting you explore both optimistic and cautious scenarios, all grounded in actual financial assumptions.
Do you think there’s more to the story for Rio Tinto Group? Head over to our Community to see what others are saying!
LSE:RIO Community Fair Values as at Nov 2025
This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned.
Companies discussed in this article include RIO.L.
Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email editorial-team@simplywallst.com
New Gold (TSX:NGD) has been getting some attention as investors look for value in the gold mining sector. The company saw its share price move higher this week, which has sparked curiosity about what might be driving renewed interest.
See our latest analysis for New Gold.
New Gold’s latest rally is not just a short-term blip. The 4.2% share price gain in a single day capped off a notable year-to-date surge of over 200%, with total shareholder return up 193% in the past year and momentum clearly building. Recent strength points to growing optimism about the company’s fundamentals and its role in today’s gold market.
If this sort of momentum has you wondering where else to look, it might be the right moment to explore fast growing stocks with high insider ownership.
With such rapid gains, the big question now is whether New Gold’s shares are trading below their true value, or if the strong performance means any future upside is already reflected in the price. Is there still a buying opportunity, or has the market fully priced in the company’s growth prospects?
With New Gold’s fair value estimate set at $15.12, over 24% above its last close of $11.42, there is renewed debate among investors about how much further this rally could go, or whether the upside is already priced in. The most popular narrative driving this figure draws heavily on ambitious projections for revenue and earnings, as well as anticipated benefits from operational changes.
Ramp-up of higher-grade ore production at both Rainy River (open pit and underground) and New Afton (C-Zone block cave), supported by strong operational execution and milestones achieved, is expected to drive increased gold and copper output at lower unit costs, directly improving revenue and net margins over the next 2 to 3 years.
Read the complete narrative.
Curious what makes analysts so bullish? The linchpin of this narrative rests on some bold growth projections and striking assumptions about margins. Want to know which financial leaps underpin this eye-catching fair value? Click through and discover the detailed forecasts behind the price target.
Result: Fair Value of $15.12 (UNDERVALUED)
Have a read of the narrative in full and understand what’s behind the forecasts.
However, factors such as high operating costs or unforeseen setbacks during mine expansions could quickly dampen New Gold’s momentum and challenge the bullish outlook.
Find out about the key risks to this New Gold narrative.
If you have your own view on New Gold’s story or want to dig into the numbers firsthand, you can easily craft a personal take in just a few minutes. Do it your way.
A good starting point is our analysis highlighting 3 key rewards investors are optimistic about regarding New Gold.
Don’t let opportunities pass you by. Use the Simply Wall Street Screener to uncover standout stocks that match your investment goals and could give your portfolio an edge.
This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned.
Companies discussed in this article include NGD.TO.
Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email editorial-team@simplywallst.com
Berkshire Hathaway’s portfolio owns at least three leading tech stocks that are benefiting from AI.
All three of these juggernauts have excellent prospects beyond their AI-related work.
10 stocks we like better than Apple ›
Warren Buffett, often regarded as the greatest investor of all time, has historically been cautious about investing in technology companies. However, whether it was his doing or due to the influence of some of its investing lieutenants, Berkshire Hathaway‘s (NYSE: BRK.A)(NYSE: BRK.B) portfolio holds several tech stocks, or at least tech-adjacent ones. Some of them are notable players in the growing field of artificial intelligence (AI) as well, and could deliver excellent returns over the long run as they capitalize on this massive opportunity. Three stocks in the conglomerate’s portfolio, in particular, Apple(NASDAQ: AAPL), Amazon(NASDAQ: AMZN), and Alphabet(NASDAQ: GOOG)(NASDAQ: GOOGL), appear to be excellent AI stocks to buy.
Image source: Getty Images.
Despite Berkshire Hathaway selling Apple shares on multiple occasions in recent years, the iPhone maker remains the conglomerate’s largest holding. And although Apple is perceived as lagging behind some of its similarly sized tech peers in AI, the company is making slow but steady progress in that department. Apple added even more AI features to its latest iPhone, the 17, which is seeing strong demand. Management believes AI features are part of the reason.
The iPhone 17 and the previous 16 are hitting supply constraints, preventing Apple from meeting the high demand for these models. Over the next couple of years, the company should see a strong renewal cycle, which will help boost sales.
Meanwhile, Apple is significantly increasing its AI-related investments. Apple is likely still in the early stages of its AI strategy and will capitalize on its large installed base to further strengthen its ecosystem by adding a slew of AI features across its devices. And as it does, the company’s hardware business, particularly the iPhone, should continue to be a decent growth driver. Furthermore, Apple’s services segment will also continue to make progress.
This long-term, high-margin opportunity will help boost profits as Apple’s more than 1 billion subscriptions continue to grow. All these factors make Apple’s prospects attractive and an excellent AI stock to buy and hold on to for a while.
Amazon has become a leading provider of AI services. Through its market-leading Amazon Web Services (AWS), the tech giant offers such products as SageMaker, a service that helps companies build and train machine learning models. Perhaps Amazon’s best-known AI offering is Bedrock, through which it provides access to a library of generative AI models, including some of the market leaders. Amazon is also utilizing in-house AI to enhance efficiency and productivity.
The army of industrial robots in Amazon’s warehouses now uses AI assistance to optimize travel routes. This aligns with Amazon’s ruthless focus on customer service, as it helps expedite shipments to customers even faster. These initiatives are expected to continue positively impacting the company’s financial results.
Amazon’s cloud computing business is performing very well and has recently achieved sales growth of the kind it had not seen in years. Meanwhile, Amazon’s robot-related efforts should help cut costs and increase margins within its e-commerce business. The best part is that these are long-term opportunities for the company, and it boasts a strong economic moat thanks to switching costs within its AWS division and strong network effects for its e-commerce business. All these factors make it a top AI stock to buy and hold.
Alphabet is a newcomer inside Berkshire Hathaway’s portfolio, with the conglomerate initiating a position for the first time during the third quarter. The online search leader is also establishing itself as a leader in AI, although at first, many thought the rise of chatbots would disrupt its search empire; however, it has adapted thanks to AI. Alphabet’s AI overviews and AI mode are achieving strong success. Alphabet also offers access to a variety of AI services through the cloud, which are helping that segment — already the company’s fastest growing — expand even faster.
Meanwhile, the company recently launched its newest AI model, Gemini 3, which it says is its best one yet. It’s clear that Alphabet is benefiting from AI, and not seeing its business decline because of it, as some predicted. And there is more to come, as the company continues to innovate. It adds to the long list of growth drivers it boasts, which also include its streaming ambitions through YouTube and a large and growing number of Google subscriptions. Berkshire Hathaway was right to initiate a position in this excellent AI stock.
Before you buy stock in Apple, consider this:
The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now… and Apple wasn’t one of them. The 10 stocks that made the cut could produce monster returns in the coming years.
Consider when Netflix made this list on December 17, 2004… if you invested $1,000 at the time of our recommendation, you’d have $572,405!* Or when Nvidia made this list on April 15, 2005… if you invested $1,000 at the time of our recommendation, you’d have $1,104,969!*
Now, it’s worth noting Stock Advisor’s total average return is 1,002% — a market-crushing outperformance compared to 193% for the S&P 500. Don’t miss the latest top 10 list, available with Stock Advisor, and join an investing community built by individual investors for individual investors.
See the 10 stocks »
*Stock Advisor returns as of November 24, 2025
Prosper Junior Bakiny has positions in Alphabet, Amazon, and Berkshire Hathaway. The Motley Fool has positions in and recommends Alphabet, Amazon, Apple, and Berkshire Hathaway. The Motley Fool has a disclosure policy.
25% of Warren Buffett’s Portfolio Is Invested in These 3 Unstoppable AI Stocks was originally published by The Motley Fool
The $1 trillion pay package for CEO Elon Musk that Teslashareholders approved on Nov. 6—the world’s first—was labeled by the board as an exemplar of pay for performance. And at first glance, the program appears to fit that description in a big way: The hurdles it establishes for Musk to receive any compensation at all, let alone achieve the maximum 13-digit payout, appear the ultimate in stretch goals. Skeptical observers might wonder: “How could anyone be motivated by targets this seemingly unachievable?”
On the other hand, Tesla loyalists and the three-quarters of Wall Street analysts issuing either a “buy” or “hold” on the EV maker praise the arrangement’s similarity to one from 2018 that spurred Musk to work wonders—at least in boosting the share price. Now, they’re positing: “Elon’s already done it once. Now he’ll be super-motivated to stay in the job and conjure a second miracle. And if that happens, stockholders will pocket another king’s ransom.” Musk concurs.
A close examination of the new plan, however, reveals that it harbors a “betwixt and between” problem. The lower-hanging fruit are too easy to harvest, and the harder goals that would mark substantial and genuine progress in profitability too difficult to attain. Probable outcome: Musk gets nothing resembling the $1 trillion, but still pockets one of the biggest payoffs in corporate America—as shareholders suffer along the way.
The reason the epic scheme risks backfiring: It contains two loopholes that enable Musk to fare handsomely by doing something he’s great at, hyping the stock via making big promises, then delivering just enough on the basic business end to clinch a rich reward.
How Musk’s new pay package is structured
The package consists of 12 tiered grants of restricted stock. Unlocking each “performance milestone” requires reaching both a valuation and an operational goal. It’s the safety deposit model: You need two keys to open the box. The market cap triggers start at $2 trillion and ascend by increments of $500 billion to the summit of $8.5 trillion, a number that’s 70% bigger than the $5 trillion that Nvidia recently notched to reign as the world’s most valuable company. The second group of keys are the “operational milestones.” Four cover sales for key products: separate, cumulative targets for deliveries of vehicles and “bots,” chiefly humanoid robots, as well as for robotaxis in commercial operation and subscriptions for full self-driving software. The other eight are Ebitda tiers that start at $50 billion, and max at $400 billion.
Put simply, anytime Musk hits a new valuation goal, and also captures any one of the dozen operational targets in any order, he receives 35.312 million shares in Tesla restricted stock, adding roughly 1% to his current stake of almost 16%.
The stunner that grabbed headlines, of course, is the $1 trillion in stock—424 million shares—Musk would receive for taking the market cap to $8.5 trillion, and also clinching all 12 of the operational objectives. Musk’s got 10 years to make the numbers that trigger the grants. The “earned share” tranches have two vesting periods: early 2033 for those achieved in the first five years, and late 2035, or at the end of the decade-long program, for the ones reached in years 6 through 10. On the Q3 earnings call, Musk repeatedly insisted that he needs to reach an ownership percentage in “the mid-20s” to ensure “enough voting controls to give a strong influence.” He effectively praised the board for handing him the opportunity to get there, and apparently thinks he stands a great chance at sweeping the board. That coup would get Musk where he wants to go by raising his stake to about 28%.
The higher goals in Musk’s pay package look like a stretch too far
In reality, Musk faces low odds of garnering any of the higher targets. Let’s start with the operational side. Hitting almost all but one of them would require moonshots. For example, the robotaxi target requires achieving an active fleet of 1 million. Today, Tesla offers only an extremely limited pilot plan in Austin, and Waymo, the industry’s largest player, has only 2,000 of the vehicles on the road. And the easiest Ebitda level stands at a towering $50 billion. Ringing the bell would likely require multiplying its current Ebitda run rate around fivefold. Yet Tesla’s now going in the wrong direction by booking puny and declining profits. Reversing that downward trend to reach even the minimum profitability mandated in the operational milestones can only happen if its unproven products prove wildly successful in highly competitive, and capital-intensive sectors.
Now to the valuation milestones. Tesla’s stock already appears vastly overpriced. Its current multiple, based on “core” earnings from its auto and battery businesses of just $3.6 billion in the past four quarters, excluding such items as sales of regulatory credits, towers at 375. Hitting the second highest valuation mark of $2.5 trillion alone would require an 85% jump in its stock price. Huge progress that’s not happening is already baked into the valuation, making the chances of huge, sustained gains from here remote, though a Musk-orchestrated, ephemeral surge can always happen.
Musk’s best shot: Ringing the bell on the two easiest goals
Though Musk probably can’t scale the mountain, he may be able to mount the foothills.
He stands a decent chance of scoring both the lowest valuation number of $2 trillion, and the least challenging operational tier—selling a cumulative total of 20 million vehicles, starting from the time of the grant. On the first item, the surge in Tesla stock since the board unveiled the program in early September has already pushed the price from $334 to $408, lifting its valuation from $1.12 trillion to $1.35 trillion—and the package gives Musk credit for that increase. So if Musk can boost the shares another 48% to $2 trillion, he’ll check the initial box for market cap. The rules require that the shares average $2 trillion or above for six months, and separately for the last 30 days, to hit the target.
It could easily happen. Musk has proved a master at sending the shares skyward by promising great things in robotaxis, full self-driving (FSD), and robots, even though he hasn’t yet significantly commercialized any of them. More promises could breed more excitement that could breed another speculative frenzy in Tesla shares centered on great expectations.
The operational part that’s reachable, especially over a longer period, is the goal of selling 20 million vehicles. This provision invites close scrutiny. According to the plan’s requirements contained in an SEC filing dated Sept. 5, this target doesn’t start from zero at the time the package takes effect. It’s a cumulative total over the entire history of Tesla. Here’s the wording: “20 Million Tesla Vehicles Delivered: Expanding Tesla’s vehicle fleet from 8 million EVs, which it has currently, to 20 million will further grow its adjusted Ebitda, allowing Tesla to reinvest in its other up-and-coming product lines.” Hence, since Tesla has already sold 8 million cars, it only has to deliver 12 million for Musk to capture that operational hurdle.
It’s an incredibly weak requirement, and one of the two wrinkles that aids Musk and skewers shareholders. In the past four quarters, Tesla has delivered 1.9 million cars, and Musk is pledging to expand the lineup to encompass a new affordable EV, and sell self-driving cars to customers. If it averages 2 million cars a year, Tesla would achieve the 12 million figure by the end of year six. Hence, Musk would clinch an operational target by achieving only a minimal annual increase in Tesla’s vehicle sales.
Here’s the second softball pitched by the board. If Musk manages to get the market cap to $2 trillion or above, and keep it there for six months, he’s turned that key definitively. No going back. No matter what happens to the share price after that, he’s got that bogey in his pocket. As Tesla’s SEC filing detailing the plan states, “Once a Market Capitalization Milestone or any particular Operational Milestone is achieved, it is forever deemed achieved for purposes of the eligibility of the Tranches to become Earned Shares.”
So let’s say Musk is able to notch the $2 trillion target in six years. Then the shares bounce around, going above and below that level, so that by the end of the 10-year grant period in late 2035—by which time he’s added the 20 million vehicles prize—its cap is $1.95 trillion, or $585 a share. In other words, Musk could talk up the shares, then see them pretty much go sideways for years, and they could even head below the price that unlocked the award.
Fortunately for shareholders, the stock grants come with a feature similar to equity options that somewhat reduces Musk’s payday, especially in a case like the one above where the plan flops. Musk only gets the gain over the stock price at the time of the grant—in other words, just the appreciation. He’d receive the first tranche of shares at a “net” of $251 per share, that’s the $585 at the end of the 10-year vesting period minus the effective “strike” price of $334 (the price when the program was conceived in September). Hence, he’d pocket $8.86 billion in one stroke (the equivalent of 35.3 million shares x $251).
That would be all of his compensation for 10 years of running Tesla. To be sure, he’d wait a long time for the money, and it isn’t anywhere near the trillion he apparently believes is feasible. But it’s still big, averaging almost $90 million a year. By comparison, in their respective fiscal years, Sundar Pichai earned $10.7 million, Mark Zuckerberg $27.2 million, Jensen Huang $34 million, Jamie Dimon $39 million, Andy Jassy $40 million, Tim Cook $75 million, and Satya Nadella $79 million.
What about the shareholders? Taking the shares from $334 to $585 in 10 years represents paltry gains of just 5.9% annually. That’s a lousy deal for Tesla’s shareholders. They’re suffering at the same time Musk is en route to getting a windfall of nearly $900 million.
Say Tesla’s shares do even worse and end the 10-year grant period at a market cap of $1.8 trillion, $200 billion below the goal of $2 trillion that Musk achieved at one point but couldn’t increase or even hold on to. Shareholders would get returns barely beating inflation, and Musk would still get a payout of $727 million.
To complicate matters, it’s likely that failing to collect on any of the other, extremely challenging tranches will prove a downer for Musk. In our scenario, he’d only increase his stake in Tesla by 1% when his goal is a rise of over 10 points. Musk would have a strong incentive to stay the full 10 years for the haul waiting at the end. But an unhappy Musk might mean a less-than-fully-motivated Musk. This package could hammer shareholders while they witness the decline of the idol it’s designed to empower.
Adaire Fox-Martin understands the needs of Big Tech. Prior to becoming CEO of Equinix (No. 446 on the Fortune 500) last year, she held senior roles at Google, SAP and Oracle. Now, the Irish-born former teacher is driving the expansion of the world’s largest global data center network, with more than 273 data centers in 36 countries. Fox-Martin recently spoke with Fortune about what she learned in her first year in the job and where she wants to go from here.
This interview has been edited and condensed for clarity.
We last met when you were starting out in the role.
It’s been an incredible year of learning and realizing that this job doesn’t come with an instruction manual. You bring the experiences that you’ve had in the past to the decisions that you make for the company for the future. We’ve laid out the strategy and optimized it into 10 simple words. The first of those is “build bolder.” which is how we’re designing and constructing the infrastructure that underpins the digital economy.
The second part of our ten-word strategy is “solve smarter.” This is about how we abstract the complexity of networking and architecture, which is our secret sauce, and render that for our customers, making Equinix the Easy button. The third piece is to “serve better.” Most participants in the data center industry have five or six customers; we have more than 10,000 enterprise customers. So those are the three pillars.
What are the other four words?
Underpinning that, we have “run simpler,” which sounds easy to say and is very hard to do. You’re taking complexity out of your business, looking at systems and processes. And the last piece is our people piece, which is to “grow together,” growing our business with our customers, linking our employee success to our customer success.
Is that a big change?
Equinix has been a company in this segment for 27 years, so we’re one of the long-term players in this industry. And in the next five years, we’re planning to bring on as much capacity as we did in the last 27 years. That’s a big capital investment for us.
Where do you sit in the data-center ecosystem?
I think there’s a general trend to think of data centers as a homogeneous mass of a singular thing. But there are four distinct categories of data centers, and each one has its own nuance and characteristics. We exist in one of those categories. There’s the hyperscale category, the ones built by cloud-service providers, where you see massive investment. The second category is wholesale, where you’re usually building a facility to lease back to one tenant, maybe two, usually supporting (AI) training. The third is enterprise, where big companies like banks want to have their own center structure. And the fourth category is colocation, which is where Equinix sits.
And what are the advantages of that?
Think of us a little like an airport authority. It manages the runaways and the facilities of the airport and gives you the ability to rent ticketing and other kind of facilities in there. Then it manages the process of passenger engagement, so an airline comes in, like KLM, drops a passenger, and then magic happens in the background to move that passenger and their luggage to United to go on to California. We’re a little bit like the airport authority of the internet: a data package comes into Equinix and then moves on to where its next destination is. The difference between us and an airport authority is that the airport lines will compete whereas a lot of our customers colocate so they can collaborate.
What do you do in terms of AI workloads?
We do both training and inference. A pharmaceutical company would do their training privately at Equinix because in the pharma world much of their research and drug discovery processes have to go through private models for regulatory reasons or intellectual property protection. Training is like teaching the model and then inference really putting what the model has learned to work.
What about the energy needs?
The different types of data centers have different characteristics when it comes to energy, who they’re starving, or how they’re supporting local economies and communities.
We’re smack bang in the middle of what I would describe as an energy super cycle. Data centers are one component of it, but so is the electrification of everything. You have the speed of an AI meeting the pace of utilities, and it’s a headfirst collision. We don’t think it’s an insurmountable challenge but it’s going to require collaboration, innovation and time.
How do you seeing it playing out?
Between now and 2028, it’s fair to say there is a power crunch. Anything that we’re delivering until 2028, we understand where our power will come from. From 2028 to 2032, you’ll see an innovation click into the power landscape, in the form of data centers and data center operators looking at how they can self-generate, how they can generate on site, how they can innovate with the grid, and give power back to the grid, how they can be flexible on and off the grid. You’ll see different aspects of innovation, including nuclear, looking at small modular reactors and how they can be utilized.
From 2032 on, the utilities have introduced some changes. In the past, you would go to a utility and say, ‘I want this much here in this time, just-in-time power provision.’ For someone like us, which doesn’t have the same power draw as a hyperscale data center, that was usually good enough. But utilities are looking at their power framework in the form of cluster studies, taking a group of requirements together in a cluster at the same time. You define the load that you’re going to ramp up to and it will likely take the form of take or pay. If you said you’re going to use this much, you will pay for it, whether you use it or not.
It’s important that large energy users, like data centers, pay a premium for what they’re utilizing so that we don’t impact small ratepayers, small energy users, so there’s a lot happening around collaboration. We’ve got a 27-year history of that kind of collaboration with the utilities and so we’re very involved in a number of those processes.
Talk about the challenge of building these centers.
One is supply chain, the things that are needed to construct a data center, some of which have been subject to tariffs. In the short term, that’s not an issue but longer term, that may become something that we have to navigate our way through. And then there’s the workforce, the plumbers and mechanical engineers and welders who are maintaining our environments that keep the internet up. A lot of trade skills, construction skills and technical skills are necessary to create the data center.
Are the centers you’re building for these workloads any larger than the ones that you built in the past?
We do support our hyperscaler partners with the provision of data centers, through a vehicle called xScale, which is a joint venture. We have partners who fund our joint ventures, so we do participate in what I described as the wholesale economy by building what’s called a build-to-suit data center industry for a hyperscaler. So a Google would come to us and say, ‘do you guys have power and land in location X? And would you build for us?’ So we do that through a joint venture off our balance sheet because the capital-intensive nature of that is high. We own 25% of our America JV and we own 20% of our EMEA and our APAC JV. We have 15 centers that are already operational around the globe.
What do you think is underappreciated about your business model?
I think the connectivity of Equinix is underappreciated. We have 270 data centers around the world, so we’re the world’s largest independent data center operator that’s still a public company. People see the physical manifestations of those centers, but the secret sauce is the connections that sit in every single one of those data centers. They take three forms. First is the ability to interconnect a company to another company. We have the trading hubs: 72% of the world’s trading platforms operate on Equinix. You have a trading hub and all their partners located closely to them that need to be literally connected so there’s no latency between the transactions. We have 492,000 deep interconnections between the companies that operate in our centers, between value chains.
The second piece of connectivity is to do with the clouds. They are an exceptionally important part of the technology landscape. Many customers store their data in clouds and most customers store their data in more than one cloud. They spread the love. We have a 35% market share in native cloud on ramps from our data centers. So you can pop into the cloud, get your data and bring it back.
And then the third piece is physically where we’re located. We’re not in the middle of the country. We are in cities, where human beings are with their devices. So many people refer to us as the metro edge, the city edge, the edge where people actually are. So we can connect the cloud, via the metro edge where humans are, to the far edge where devices might be utilized.
Do you think people appreciate the role that data centers play in their lives?
In many countries, we are designated as critical infrastructure, in certain states, too, but not at the federal level. When I think about moving home: water, gas, electricity, internet becomes that fourth utility. And 95% of internet traffic runs through the Equinix environment. If you were on a Zoom call this morning, if you did a stream from any of the major providers, ordered an Uber, purchased a train ticket, you were on a platform accessing Equinix at some point.
“95% of internet traffic runs through the Equinix environment.”Adaire Fox-Martin, CEO, Equinix
What are you seeing in terms of customer trends?
Many of our customers are moving from the proof-of-concept phase of AI into the real-world-application phase of AI. There’s a lot to grapple with in that. It isn’t just about taking a business process and putting AI over the top of it. There are a whole series of considerations around governance and the management of data that haven’t really played into the business picture yet that are very real, especially for industries that are highly regulated.
That’s why some have not even adopted that much AI.
Right. Even if they are frontrunners, now it’s kind of like coming back and saying, ‘oh, how do we make sure that we’re audible, traceable, accountable, all of the things that are good governance for business. If we’re going to deploy a technology that can automate so many things and take my human out of the loop, how do I report, manage, and maintain the governance framework of those processes in my business?
We’re seeing a lot of pushback in local communities where these mega hyperscale data centers are being built. How are you staking your claim to say we’re not that, but this is still critical infrastructure we need?
You look at it through the lens of what are the good things that a data center can do for a local community. We engage very strongly with local communities when we are beginning a construction. You do bring jobs to the area, particularly in the construction face, less so when you’re in the operation face because there isn’t a preponderance of humans across a data center. Second, you’re obviously going to pay tax in that location and that has knock-on benefit. Thirdly, we employ and source locally. I’m very excited about our apprenticeship scheme, where young women and men who maybe didn’t have a formal education path can become data-center technicians or critical facility engineers. And when there’s a build of a data center, there’s often an upgrade of the infrastructure around it, like whether that’s the power capabilities, the roads and so on.
Are people asking more questions about water, energy?
For sure. And we recognize that these are extremely important parts of the life system of our planet. We were the first data center operator to begin reporting on our water usage. When you bring in power, you want to maximize the use of that energy in the deployment of workloads for customers and not just empowering the data center itself. We measure our power and how effective we are in using power. The best way to save energy to use less of it. That’s absolutely an industry standard now.
And water?
Water was never at the same level of investigation or scrutiny as power was. Now, there’s a measure of water-usage effectiveness and we were one of the first to report on that. It’s not as standardized as power and so we’re working in the industry to try and standardize that a little bit more.
In the longer term, data centers will more than likely be cooled by liquid cooling, as opposed to air or evaporative cooling. And liquid cooling, in terms of water use, is a closed-use-loop system. You’re reusing the same water over and over again to cool the chips. The technology itself will become a determinant of sustainability.
All the big tech companies are working to make these models smaller and more efficient. Eventually, they’re going to want to have many little data centers that are colocated. Do you think you’ll benefit from that?
We believe the inference target addressable market, combined with the network, is about $250 billion outside of what the clouds are doing. By 2029, the inference opportunity will be twice the size of training. And that’s why we’re setting ourselves up for this opportunity.
You can think about training as a centralized AI emotion whereas inference is very much a distributed emotion. It will initiate on a device or maybe through voice, or glass, 0r whatever the device is. And it will probably have an agent conduct its orchestra, in terms of instructing other agents to get data from more than one location. That’s why we’ve been very selective about where we built.
You came to this job from Google almost a year and a half ago. Where are you now versus what you were thinking when you came in?
I would say on a journey, not at the destination but heading in the right direction. I’m confident that we have such a unique combination of characteristics—the metro locations, the connectivity, the secret sauce—that we’re ready for prime time. I’m working through the dynamics of some of the negative feelings around data centers. The challenge around energy has been very real in Europe, in particular. There are countries that have just issued a moratorium on data-center builds, like Ireland, my home country, until they can kind of take a breath and understand whether they can do. These problems are absolutely addressable. They’re absolutely surmountable. It’s a time-based issue that’s going to require collaboration and innovation to solve.
What about the regulatory environment? That’s been in flux.
There is a lot of noise on a variety of topics. I’m just working to control the controllable, and carry on the path that we believe for us is the right path. For example, Equinix has some goals around our sustainability narrative. By 2030, we set a goal for ourselves that we would be neutral as it relates to the use of carbon. We’re still on that track. And we’ve set a science-based goal for 2040 to be net zero and we will continue to innovate and work to do that.
It’s not just that we believe there is an opportunity for technology and innovation to exist with good environmental stewardship. Our customers are continuing to ask us for reports on how their usage at Equinix is impacting things that we may be measure.
There’s a lot of what about AI. What will it do? But there’s a where about AI. And we’re like the where of AI. There are physical cables, even under the ocean, and cable trays and billions of wires. If you’re in California, you get to see the history of data centers. The internet will literally be above your head. We have three decades of data center history, from our very first one to our latest one. I never thought I would come into a company where we have 56 active construction projects all around the world.
SANTIAGO, Nov 28 (Reuters) – Copper output in Chile, the world’s largest producer of the metal, fell 7% year-on-year in October to 458,405 metric tons, statistics agency INE said on Friday.
Manufacturing production in the Andean nation was slightly down 0.4% in the month on a yearly basis, the agency also said.
Sign up here.
Reporting by Fabian Andres Cambero y Aida Pelaez-Fernández
Editing by Tomasz Janowski
Our Standards: The Thomson Reuters Trust Principles., opens new tab
Norouzi, M. et al. Risk-averse and flexi-intelligent scheduling of microgrids based on hybrid Boltzmann machines and cascade neural network forecasting. Appl. Energy348, 121573 (2023).
Google Scholar
Abed, A. M. et al. Power generation by utilization of different renewable energy sources in five Middle Eastern countries: Present status, opportunities and challenges. Sustain. Energy Technol. Assess.73, 104101 (2025).
Google Scholar
Pirouzi, S., Latify, M. A. & Yousefi, G. R. Investigation on reactive power support capability of PEVs in distribution network operation, in 23rd Iranian Conference on Electrical Engineering, pp. 1591–1596 (2015).
Yao, M., Moradi, Z., Pirouzi, S., Marzband, M. & Baziar, A. Stochastic economic operation of coupling unit of flexi-renewable virtual power plant and electric spring in the smart distribution network. IEEE Access11, 75979–75992 (2023).
Google Scholar
Roustaee, M. & Kazemi, A. Multi-objective energy management strategy of unbalanced multi-microgrids considering technical and economic situations. Sustain. Energy Technol. Assess.47, 101448 (2021).
Google Scholar
Zare Ghaleh Seyyedi, A. et al. Bi-level sitting and sizing of flexi-renewable virtual power plants in the active distribution networks. Int. J. Electric. Power Energy Syst.137, 107800 (2022).
Google Scholar
Roustaee, M. & Kazemi, A. Multi-objective stochastic operation of multi-microgrids constrained to system reliability and clean energy based on energy management system. Electric. Power Syst. Res.194, 106970 (2021).
Google Scholar
Wu, J. et al. Integrated energy systems. Appl. Energy167, 155–157 (2016).
Google Scholar
Hua, H., Wu, X., Chen, X., Kong, H., Sun, Y., Yang, Q. & Naidoo, P. Carbon reduction oriented regional integrated energy system optimization via cloud-edge cooperative framework. CSEE J. Power Energy Syst. (2025).
Xiao, D. et al. Risk-factor-oriented stochastic dominance approach for industrial integrated energy system operation leveraging physical and financial flexible resources. Appl. Energy377, 124347 (2025).
Google Scholar
Ren, X. Y., Wang, Z. H., Li, M. C. & Li, L. L. Optimization and performance analysis of integrated energy systems considering hybrid electro-thermal energy storage. Energy314, 134172 (2025).
Google Scholar
Ji, Z. et al. Optimal scheduling of park-level integrated energy system considering multiple uncertainties: A comprehensive risk strategy-information gap decision theory method. Appl. Energy377, 124700 (2025).
Google Scholar
Liu, Z. F. et al. Two-layer energy dispatching and collaborative optimization of regional integrated energy system considering stakeholders game and flexible load management. Appl. Energy379, 124918 (2025).
Google Scholar
Wang, Y., Li, Y., Zhang, Y., Xu, M. & Li, D. Optimized operation of integrated energy systems accounting for synergistic electricity and heat demand response under heat load flexibility. Appl. Therm. Eng.243, 122640 (2024).
Google Scholar
Jia, J. et al. Multi-objective optimization study of regional integrated energy systems coupled with renewable energy, energy storage, and inter-station energy sharing. Renew. Energy225, 120328 (2024).
Google Scholar
Yang, Z. et al. A multi-stage stochastic dispatching method for electricity-hydrogen integrated energy systems driven by model and data. Appl. Energy371, 123668 (2024).
Google Scholar
Naghibi, A. F., Akbari, E., Shahmoradi, S., Pirouzi, S. & Shahbazi, A. Stochastic economic sizing and placement of renewable integrated energy system with combined hydrogen and power technology in the active distribution network. Sci. Rep.14(1), 28354 (2024).
Google Scholar
Zhang, J., Wu, H., Akbari, E., Bagherzadeh, L. & Pirouzi, S. Eco-power management system with operation and voltage security objectives of distribution system operator considering networked virtual power plants with electric vehicles parking lot and price-based demand response. Comput. Electr. Eng.121, 109895 (2025).
Google Scholar
Naughton, J., Wang, H., Cantoni, M. & Mancarella, P. Co-optimizing virtual power plant services under uncertainty: A robust scheduling and receding horizon dispatch approach. IEEE Trans. Power Syst.36(5), 3960–3972 (2021).
Google Scholar
Yi, Z., Xu, Y., Zhou, J., Wu, W. & Sun, H. Bi-level programming for optimal operation of an active distribution network with multiple virtual power plants. IEEE Trans. Sustain. Energy11(4), 2855–2869 (2020).
Google Scholar
Lee, J. & Won, D. Optimal operation strategy of virtual power plant considering real-time dispatch uncertainty of distributed energy resource aggregation. IEEE Access9, 56965–56983 (2021).
Google Scholar
Abrisham Foroushan Asl, S. et al. A new two-layer model for energy management in the smart distribution network containing flexi-renewable virtual power plant. Electric Power Syst. Res.194, 107085 (2021).
Google Scholar
Jin, K. et al. Robust power management capabilities of integrated energy systems in the smart distribution network including linear and non-linear loads. Sci. Rep.15(1), 6615 (2025).
Google Scholar
Sui, Q. et al. Scheduling of mobile rail generators capable of uninterrupted power supply for load rescue. IEEE Trans. Power Syst.12(2), 1–12 (2025).
Google Scholar
Li, Z., Hu, C., Zhu, Y., Weng, H., Tan, H. & Mohamed, M. A. An additional stability control strategy of traditional reclosing based on emergency power support. Electric. Eng. 1–12 (2025).
Sui, Q., Wei, F., Wu, C., Lin, X. & Li, Z. Day-ahead energy management for pelagic island microgrid groups considering non-integer-hour energy transmission. IEEE Transa. Smart Grid11(6), 5249–5259 (2020).
Google Scholar
Lu, Z., Tan, H. & Mohamed, M. A. Nonlinear, robust, interval state estimation for distribution systems based on fixed-point expansion considering uncertainties. J. Process Control150, 103427 (2025).
Google Scholar
Pirouzi, S. et al. Two alternative robust optimization models for flexible power management of electric vehicles in distribution networks. Energy141, 635–651 (2017).
Google Scholar
Jiang, W. et al. Optimal economic scheduling of microgrids considering renewable energy sources based on energy hub model using demand response and improved water wave optimization algorithm. J. Energy Storage55, 105311 (2022).
Google Scholar
Dehghani, M. et al. Blockchain-based securing of data exchange in a power transmission system considering congestion management and social welfare. Sustainability13(1), 90 (2020).
Google Scholar
Chen, L. et al. Optimal modeling of combined cooling, heating, and power systems using developed African Vulture Optimization: a case study in watersport complex. Energy Sourc. A: Recovery Utiliz. Environ. Effects44(2), 4296–4317 (2022).
Google Scholar
Yuan, Z. et al. Probabilistic decomposition-based security constrained transmission expansion planning incorporating distributed series reactor. IET Generat. Transmiss. Distribut.14(17), 3478–3487 (2020).
Google Scholar
Yu, D. & Ghadimi, N. Reliability constraint stochastic UC by considering the correlation of random variables with Copula theory. IET Renew. Power Gener.13(14), 2587–2593 (2019).
Google Scholar
Eslami, M. et al. A new formulation to reduce the number of variables and constraints to expedite SCUC in bulky power systems. Proc. Natl. Acad. Sci. India Sect. A: Phys. Sci.89, 311–321 (2019).
Google Scholar
Nejad, H. C. et al. Reliability based optimal allocation of distributed generations in transmission systems under demand response program. Electric Power Syst. Res.176, 105952 (2019).
Google Scholar
Wang, K. et al. A coordinated reconfiguration strategy for multi-stage resilience enhancement in integrated power distribution and heating networks. IEEE Trans. Smart Grid14(4), 2709–2722 (2023).
Google Scholar
Duffey, C. K. & Stratford, R. Update of harmonic standard IEEE-519: IEEE recommended practices and requirements for harmonic control in electric power systems. IEEE Trans. Ind. Appl.25(6), 1025–1034 (1989).
Google Scholar
Abedinia, O. et al. Optimal offering and bidding strategies of renewable energy based large consumer using a novel hybrid robust-stochastic approach. J. Clean. Product.215, 878–889 (2019).
Google Scholar
Leng, H. et al. A new wind power prediction method based on ridgelet transforms, hybrid feature selection and closed-loop forecasting. Adv. Eng. Inform.36, 20–30 (2018).
Google Scholar
Zhang, C. et al. A novel optimal power flow method considering interval uncertainties under high renewable penetration based on security limits definition. IEEE Trans. Sustain. Energy12, 1–12 (2025).
Google Scholar
Meng, Q., He, Y., Hussain, S., Lu, J. & Guerrero, J. M. Optimized energy storage configuration for enhanced flexibility in renewable-integrated power systems. J. Energy Storage132, 117735 (2025).
Google Scholar
Bo, G. et al. Optimum structure of a combined wind/photovoltaic/fuel cell-based on amended Dragon Fly optimization algorithm: a case study. Energy Sour. A: Recov. Util. Environ. Effects44(3), 7109–7131 (2022).
Google Scholar
Ma, K., Yang, J. & Liu, P. Relaying-assisted communications for demand response in smart grid: Cost modeling, game strategies, and algorithms. IEEE J. Sel. Areas Commun.38(1), 48–60 (2020).
Google Scholar
Yang, H. et al. Receding horizon optimization of power demand response for production-oriented users with real-time operating status-awareness. IEEE Trans. Consum. Electron.1, 1–12 (2025).
Google Scholar
Zemin, D., Yueming, L., Zhicheng, Y., Youhong, Y. & Yongbao, L. Coordinated control strategy of engine-grid-load-storage for shipboard micro gas turbine DC power generation system: A review. J. Energy Storage134, 118205 (2025).
Google Scholar
Feng, J., Yao, Y. & Liu, Z. Developing an optimal building strategy for electric vehicle charging stations: Automaker role. Environ. Dev. Sustain.27(5), 12091–12151 (2025).
Google Scholar
Yang, M. et al. Extraction and application of intrinsic predictable component in day-ahead power prediction for wind farm cluster. Energy328, 136530 (2025).
Google Scholar
Gao, W. et al. Transient frequency-voltage support strategy for VSC-MTDC integrated offshore wind farms based on perturbation observer and funnel control. IEEE Trans. Sustain. Energy16(3), 1931–1943 (2025).
Google Scholar
Xu, X. et al. Security assessment of cascading failures in cyber-physical power systems with wind power penetration. IEEE Trans. Power Syst.1, 1–13 (2025).
Google Scholar
Li, G., Luo, Z. & Liao, C. Power capacity optimization and long-term planning for a multi-energy complementary base towards carbon neutrality. Energy334, 137644 (2025).
Google Scholar
Bertsimas, D., Litvinov, E., Sun, X. A., Zhao, J. & Zheng, T. Adaptive robust optimization for the security constrained unit commitment problem. IEEE Trans. Power Syst.28(1), 52–63 (2013).
Google Scholar
Generalized Algebraic Modelling Systems (GAMS). [Online]. Available: http://www.gams.com (2017).
Zeinalzadeh, A., Mohammadi, Y. & Moradi, M. H. Optimal multi objective placement and sizing of multiple DGs and shunt capacitor banks simultaneously considering load uncertainty via MOPSO approach. Int. J. Electric. Power Energy Syst.67, 336–349 (2015).
Google Scholar
Akbari, E. et al. High voltage direct current system-based generation and transmission expansion planning considering reactive power management of AC and DC stations. Sci. Rep.15(1), 15537 (2025).
Google Scholar
Navesi, R. B. et al. Reliable operation of reconfigurable smart distribution network with real-time pricing-based demand response. Electric Power Syst. Res.241, 111341 (2025).
Google Scholar
Wang, R. et al. Stochastic economic sizing of hydrogen storage-based renewable off-grid system with smart charge of electric vehicles according to combined hydrogen and power model. J. Energy Storage108, 115171 (2025).
Google Scholar
Emdadi, K. & Pirouzi, S. Benders decomposition-based power network expansion planning according to eco-sizing of high-voltage direct-current system, power transmission cables and renewable/non-renewable generation units. IET Renew. Power Gener.19(1), e70025 (2025).
Google Scholar
Oboudi, M. H. et al. Reliability-constrained transmission expansion planning based on simultaneous forecasting method of loads and renewable generations. Electr. Eng.107(1), 1141–1161 (2025).
Google Scholar
Zadehbagheri, M. et al. Resiliency-constrained placement and sizing of virtual power plants in the distribution network considering extreme weather events. Electrical Engineering, 1–17 (2024).
Pirouzi, S., Zadehbagheri, M., & Behzadpoor, S. Optimal placement of distributed generation and distributed automation in the distribution grid based on operation, reliability, and economic objective of distribution system operator. Electrical Engineering, 1–14 (2024).
Mohammadzadeh, M. et al. Application of mixture of experts in machine learning-based controlling of DC-DC power electronics converter. IEEE Access10, 117157–117169 (2022).
Google Scholar
Aghaei, J. et al. Flexibility planning of distributed battery energy storage systems in smart distribution networks. Iran. J. Sci. Technol. Trans. Electr. Eng.44(3), 1105–1121 (2020).
Google Scholar
Norouzi, M. et al. Enhancing distribution network indices using electric spring under renewable generation permission. In 2019 International Conference on Smart Energy Systems and Technologies (SEST) (pp. 1–6). IEEE (2019).
Texas Instruments (TXN) has shown some interesting movement in recent trading sessions, with the stock registering a steady gain of 2% over the past week. Investors are paying close attention to the company’s performance as it navigates ongoing sector shifts and broader market volatility.
See our latest analysis for Texas Instruments.
Texas Instruments’ 1-day share price return of 1.77% and a 7-day rally of 5.56% come as the stock bounces off a tough year, with overall total shareholder return still down 13.6% over the past twelve months. While recent momentum suggests optimism may be building around its ability to manage sector headwinds, longer-term performance has been more muted compared to industry leaders.
If the semiconductor rebound has you thinking bigger, now is a perfect time to broaden your search and discover fast growing stocks with high insider ownership
With shares still below analyst price targets and modest annual growth figures, the question for investors is clear: is Texas Instruments currently trading at a discount, or are expectations for a rebound already fully reflected in the price?
Texas Instruments’ narrative-driven fair value estimate stands at $189.56, putting it about 11% above the last close price of $168.27. This divergence points to moderate analyst optimism about the path forward for the company, with a focus on future earnings recovery and margin expansion.
Strategic investment in U.S.-based 300mm wafer fabs and a diversified global manufacturing footprint uniquely position TI to benefit from evolving supply chain localization and customer preferences for geopolitically resilient suppliers. This advantage is likely to help win incremental business, strengthen preferred supplier status, and improve long-term gross margins and pricing power.
Read the complete narrative.
Curious which bold growth levers and projected profit surges sit beneath this bullish narrative? The secret sauce lies in aggressive margin targets, share reductions, and an industry-beating rebound analysts are daring to bake in. Unlock the full story to see how these forecasts stack up and what could challenge them.
Result: Fair Value of $189.56 (UNDERVALUED)
Have a read of the narrative in full and understand what’s behind the forecasts.
However, renewed margin pressure from underutilized fabs or unexpected supply chain disruptions could quickly dampen optimism and challenge the current fair value case.
Find out about the key risks to this Texas Instruments narrative.
While the narrative-driven fair value sees Texas Instruments as undervalued, our DCF model presents a more conservative take. In this approach, the current share price of $168.27 is above the estimated fair value of $150.90, which implies potential downside risk. Which scenario will play out as sector trends shift?
Look into how the SWS DCF model arrives at its fair value.
TXN Discounted Cash Flow as at Nov 2025
Simply Wall St performs a discounted cash flow (DCF) on every stock in the world every day (check out Texas Instruments for example). We show the entire calculation in full. You can track the result in your watchlist or portfolio and be alerted when this changes, or use our stock screener to discover 920 undervalued stocks based on their cash flows. If you save a screener we even alert you when new companies match – so you never miss a potential opportunity.
If you have a different perspective or want to dive into the numbers on your own terms, building your personalized view is quick and straightforward. Do it your way
A great starting point for your Texas Instruments research is our analysis highlighting 3 key rewards and 2 important warning signs that could impact your investment decision.
Stay ahead of the curve by using the Simply Wall Street Screener to uncover stocks that match your strategy before the crowd catches on. Maximize your edge now.
This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned.
Companies discussed in this article include TXN.
Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email editorial-team@simplywallst.com
When examining the flow of wealth in the coming decades, privately wealthy individuals rest in a very healthy position. Their assets have increased in value, their portfolios have performed well, and many are looking to the generations above them for a significant windfall of cash set to come from inheritance.
Governments, with their eye-watering debt burdens and expensive borrowing costs, are eyeing that wealth—and they want in.
Policymakers have leveraged private wealth in the past to pay their way, UBS chief economist Paul Donovan recently told media at a roundtable discussing the economic outlook for 2026—but the question is whether they will use a carrot or a stick to drum up revenue from individuals.
As such, some may prove more popular than others. Donovan said last week: “Governments have long mobilized private wealth to support public finances. There are several approaches. One is to influence market behavior—encouraging individuals to buy government bonds through incentives like tax-free premium bonds, which channel savings directly into state financing. Prudential regulation can also steer pension funds toward domestic government debt, as seen in the UK after 1945, when a debt-to-GDP ratio of 240% was successfully reduced over decades.”
It is this debt-to-GDP ratio that has economists so concerned, rather than the volume of debt itself. After all, the ratio is a useful indicator of whether an economy is growing fast enough to generate the revenues necessary to repay its debts—or the interest payments on its debts—to lenders. If the customers buying a government’s debt feel the ratio is unbalanced, they may demand higher interest to offset the risk and so push the government’s budget even further.
To increase the supply of debt buyers—with individuals motivated by a tax-free incentive, for example—allows governments to borrow more without facing higher market interest.
However, there are other, less popular ways to raise revenue to pay off the debt. “More contentious options exist,” added Donovan, “Such as taxing wealth through capital gains or inheritance levies. In practice, the initial focus tends to be on financial repression—using tax incentives or regulation to direct money into government bonds—before moving toward wealth taxation.”
A timely wealth transfer
Inheritance levies will be of significant interest in the era of the Great Wealth Transfer, with $80 trillion due to change hands over the next 20 years, according to UBS. Some studies put that figure even higher, saying as much as $124 trillion will be passed down from older generations to their younger counterparts.
Donovan has previously warned that politicians will likely be wondering how this shift could help revive their own fortunes. The chief economist said in a video last month: “It seems unrealistic to suppose that governments will just sit idly by as this wealth moves around. We would expect governments to attempt to mobilize that wealth to help fund their debt, but in doing so, that denies private sector investment access to some of those funds.”
With global public debt now surpassing $100 trillion, politicians and the public alike are growing increasingly concerned about the issue. While economists have described President Trump’s methods as “peculiar,” there is no doubt that his tariff regime has brought billions to Uncle Sam’s bottom line.
The White House has also suggested selling “gold cards” to wealthy would-be immigrants, with Trump saying it would be “nice” to offset some of the debt with the proceeds. That being said, this idea was tabled in February with more details promised to emerge within the fortnight—no such small print has been confirmed.
The U.K.’s Chancellor, Rachel Reeves, has adopted a different approach—potentially more in line with the policies Donovan has suggested. In a pre-budget speech a few weeks ago, Reeves made it clear that individuals will be called on to play their part in the wider fiscal trajectory.
“If we are to build the future of Britain together, we will all have to contribute to that effort,” she said. “Each of us must do our bit for the security of our country and the brightness of its future. There is a reward for getting these decisions right, to build more resilient public finances—with the headroom to withstand global turbulence.”