The Quick-Hits

  • AI’s appetite for energy is insatiable, and the grid is struggling to feed it
  • Growth stocks surge further ahead
  • Rate cuts on both sides of the border based on economic growth and labour concerns
  • Guardian Capital LP wins LSEG Lipper Awards for Best Canadian Equity Fund and Best Bond Fund Family Group
  • Quote of the month:
    “If history is any guide, the greatest risks often come not from what is unknown, but from what is assumed to be certain.”
    – Author unknown, widely cited in financial markets

Macro Musings

With a title like ‘Power Struggle,’ the possibilities for this month’s commentary were endless: U.S. vs. China. Russia vs. Ukraine. Democrats vs. Republicans. Even Toronto Blue Jays vs. L.A. Dodgers. Tempting, right? But no. Despite the lingering heartbreak from game 7 and the ‘no kings’ protests making headlines, I’m not talking crowns and thrones—I’m talking about the moans and groans of an increasingly stretched power grid struggling to feed the insatiable appetite for energy by Artificial Intelligence (AI) data centers.

Before we talk power, big headlines in the world of AI this past month included NVIDIA breaking through a $5 trillion market cap – the first company in history to hit the milestone. It seems like not long ago, the $1 trillion milestone was a big deal, but in the era of AI, unprecedented numbers are the norm. Before the release of ChatGPT, NVIDIA was valued at $400 billion. It took them 13 months to go from $3 trillion to $4 trillion and just over three months to go from $4 trillion to $5 trillion. To put that in context, NVIDIA alone is now worth more than the entire stock market of Japan, and worth more than the stock markets of Germany, France and Italy combined! As of October month end, it was the largest holding in the MSCI World Index¹ at 6%.

OpenAI, the other ‘face’ of AI, also made headlines, having completed a major corporate restructuring in late October, splitting into two segments. OpenAI Group is now the ‘for-profit’ arm (a public benefit corporation), while OpenAI Foundation is the new, re-branded version of the original nonprofit entity, which retains control over the for-profit entity, while Microsoft now also owns a 27% stake ($135 billion). Investor enthusiasm has grown after this restructuring was announced, particularly as it opens the door for what seems to be a likely IPO in the near future. Interestingly, the restructuring also further reinforced binding commitments for OpenAI to ensure that the development of artificial general intelligence (AGI) serves the best interests of humanity. For instance, its ‘Stop-and-Assist’ clause states that once OpenAI believes they have achieved AGI, it is required to stop competing and instead join forces with other leading AGI efforts. Will it stay true to its ‘mission’, or will ambiguity around the definition of AGI creep in and delay or avoid this clause; with profit motivations being too strong? We’ll see.

Talk of bubbles now seems to be ubiquitous. Katie Martin of the Financial Times, in a recent column, referred to “the bubble here is a bubble in people talking about bubbles.”

Let’s explore some examples of what was said in and around markets this past month related to AI.

On JPMorgan Chase’s Q3 earnings call, CEO Jamie Dimon said, “You have a lot of assets out there which look like they’re entering bubble territory.”²

A recent IMF report also raised concerns: “Valuation models show risk asset prices well above fundamentals, raising the risk of sharp corrections. Markets appear complacent as the ground shifts.”³

Dario Amodei, CEO of Anthropic, an AI safety and research company, said last month that AI could wipe out half of all entry-level white-collar jobs and spike unemployment 10-20% in the next 1-5 years.

Scott Galloway, Professor of Marketing at NYU Stern School of Business, has mentioned, on a couple of occasions on his Prof G Markets podcast, that implicit in the ‘Mag 10’ valuations is that AI will help these companies cut costs or grow revenue by $1 trillion in the next two years. In his view, we’re likely to see either a massive destruction in valuations, which will affect U.S. and global stocks, (if that revenue bar proves to be set too high), or a massive destruction in employment across industries with the highest concentrations of white-collar workers. ‘Cost-cutting and doing more with less’ is just Latin for ‘layoffs.’

Of course, on the other hand, there are certainly the Tech evangelists touting the potential upside for investors and humanity at large.

Sundar Pichai, CEO of Google/Alphabet, has said, “AI is one of the most profound things we’re working on as humanity. It’s more profound than fire or electricity.”

Meanwhile, Jeff Bezos, CEO of Amazon, has articulated his view that, yes, there is a bubble in AI, but rather than looking at it as a negative, he sees it as a positive bubble. His view is that there is indiscriminate funding of AI startups happening, irrespective of those with viable or weak ideas and, ultimately, if the bubble bursts or things cool off, the weaker businesses will get filtered out. He believes that regardless of the number of eventual losers in the space, society will be better off based on the innovation and advancements made in the run-up to the possible shake-out.

It’s very difficult to fight momentum, and AI has that in spades right now. Furthermore, markets over time tend to go up and to the right, meaning optimists tend to perform better over the long term than pessimists. We know, however, that investors ‘feel’ losses more than they enjoy an equivalent amount of gains, so diversification remains important. That said, ‘being diversified’ does seem to be getting increasingly difficult as companies across regions and sectors become increasingly entangled in the clutches of AI’s tentacles.

Even if you’re in the camp of believing in the transformational potential of AI and that stocks of companies operating in the space are still undervalued based on this future potential, there comes the question of whether we’ll be able to ‘get there’ as quickly as optimists might believe. Or, in other words, could valuations have stretched too far in the near term? Will companies actually be able to generate the cash flow required to justify these valuations in the not-too-distant future? This is up for debate, but one huge challenge to overcome appears to be generating enough energy to power all of the data centers, either up and running, currently under construction, or those that have been announced.

OpenAI, for example, wants to build a chip network that would consume 250 gigawatts (GW) of energy, which is equivalent to 20-25% of America’s current electrical grid capacity. The firm has called on the government to invest more heavily in power generation, encouraging them to commit to building 100GW of new capacity every year⁴, which is the equivalent of building 100 nuclear reactors each year⁵, a seemingly herculean and improbable task. According to an ABC News Fact Check article published in 2024⁶, the average build time for U.S. nuclear reactors since 1970 was about nine years, but these figures do not factor in any time spent on planning or design, both of which can take a minimum of a couple of years each. On top of that, if there are any delays due to regulatory hurdles, lawsuits or supply chain issues, it’s not unfathomable that this process could take between 15-20 years. Hope may be on the horizon, though, in the form of small modular reactors (SMRs), promising faster build times. Companies like NuScale claim they can have the process completed in three years, but skeptics abound, and there are no SMRs that operate at scale yet⁷.

Where does that leave us today? From an immediate standpoint, data centers are accounting for a growing proportion of consumption from the energy grid. Where demand is high and supply is constrained, prices rise. This has been the case for parts of the U.S., and it could be coming to a head. With a general affordability crisis being a hot-button issue in the U.S. (see Zohran Mamdani’s NYC mayoral victory), paying more to keep your lights on because the data center next door is tapping into the grid to ensure AI chatbot’s stay online probably isn’t going to be palatable.

Research from Evergreen Gavekal⁸ shows that the U.S. is hovering at the threshold of the ‘political danger zone’ with regard to increasing energy prices based on the 5-year percentage change of the U.S. Energy Consumer Price Index⁹. Today’s value sits right at the 50% threshold and is no doubt something on the radar of the current U.S. administration.

So, with regards to energy, there’s clearly a demand issue (it’s rising fast) coupled with supply constraints (new power generation currently is not keeping pace with demand). Do we need to solve this from the demand side or the supply side? The answer is yes.

On the demand side, it’s highly unlikely that demand will abate, and efforts to try to curb consumption are almost sure to fail. Instead, in order to ease the demand burden, tech leaders should (or perhaps must) focus their efforts on greater energy efficiency of AI. I’m compelled again to rehash recent remarks from Professor Scott Galloway of NYU, who believes, “the Chinese tech sector is about to ‘Old Navy’ the s**t out of the US economy…and they’ve done it across BYD electric vehicles.” What does his ‘Old Navy’ quip mean? It’s based on the notion that retailer Old Navy’s success was based on being able to provide 80% of the value proposition of The Gap for 50% of the price. Perhaps there’s a political angle to this as well. China realizes the U.S. today is essentially one big bet on AI. Might not the Chinese opt to flood the market with cheap (free?) large language models (LLMs) like they did with DeepSeek? They certainly have the time, money and scientists to do it. And President Xi might be thinking that’s an ideal approach to derail America’s one big bet and sway the pendulum in China’s favour.

With regards to Chinese efficiency, Alibaba’s Cloud unit just announced a new system that cuts their GPU (Graphic Processing Unit) usage by 82%, meaning they’re able to use just 200 GPU chips to perform what would otherwise take 1200 GPU chips¹⁰, with some saying what they’ve done for hardware is akin to what DeepSeek did to software.

And China, while being a Communist nation without capitalist incentives, appears to be ahead in at least a couple of areas – notably in both energy efficiency, but also in pure energy capacity as well.

That takes us to the supply side. China now has more existing energy capacity than the U.S. and Europe combined. Yes, regulation is easier and construction times are, therefore, much quicker, but China also leads in renewable energy. In fact, the renewable energy they produce provides more power than the entire European or U.S. grids overall. So, despite the Trump administration’s ‘Drill, baby, drill’ mentality, the reality that gas or coal-fired power is going to solve the supply constraints is unrealistic. Just as the Administration, despite their best efforts, is benefiting from a resilient (and increasingly AI & Tech-driven) economy, so too could they see an ushering in of renewable energy in a big way, despite their affinity for carbon-emitting sources, particularly as the cost of solar and wind power is a fraction of what it was just years ago.

Rounding out our macro views, President Trump and President Xi of China recently met, and Trump called it a “12 out of 10” meeting. Apparently, they have agreed on a framework for a trade truce. To be clear, again, like many purported ‘deals’ announced under the current Administration, nothing has been signed. It sounds much more like a short-term truce with loose understandings in place, in which China would agree to resume soybean imports from the U.S. (U.S. farmers have NOT been happy of late) and pause export controls on rare earth elements for one year. In exchange, it’s reported that Trump would agree to reduce tariffs on Chinese goods from 57% to 47%.

Equities

Equity markets had another strong month in what is shaping up to be another excellent year for stocks globally. Leading the major indices was the NASDAQ 100 Index, powered by Tech heavyweights. Interestingly, Emerging Markets nearly matched the NASDAQ 100, despite the fact that the main constituent, China, was down almost 4% in October. Results were buoyed by stock strength in South Korea (SK Hynix and Samsung) as well as in Taiwan (TSMC). In both Canada and the U.S., the Tech sector was the best performer, up over 6% in the U.S. and almost 14% in Canada. On the flip side, Materials was the worst performing sector in both countries, namely due to volatility among gold miners.

Overall, the best performing stocks in Canada for the month were: Celestica (+43%), Energy Fuels (+35%) and TransAlta (+30%), while the worst performers included: Allied Properties REIT (-28%), MDA Space (-21%) and OR Royalties (-19%).

In the U.S., the best performers were: Advanced Micro Devices (+58%), Micron Technology (+34%) and Teradyne (+32%), while the worst performers were: Fiserv (-48%), Alexandria Real Estate Equities (-30%) and F5 Inc. (-22%).

Growth stocks were the stylistic favourite in October, up 4.7%, after also being up 4.6% in September. At the other end of the spectrum, as one might expect, were Value and Dividend stocks. Dividend factor stocks have been the worst performers for the year, in relative terms, but still up a very respectable 10% in absolute terms. Gold was up 3.7% in October, but that figure masks the volatile ride investors experienced over the month as the price started at $3,840, rose to its highest closing price ever of $4,336, only to decline 8% from that peak to close the month at $3,982. While gold has seemed to morph into a ‘FOMO’ momentum trade, the underlying drivers of fiscal worries and central bank buying remain in place. With regards to currency, the Canadian dollar declined by 0.9% vs. the U.S. dollar, which closed the month at US$0.7114. As stated previously, the trend for the U.S. dollar this year has been weaker and could continue as such. Much of the developed world has already cut their interest rates considerably and could be much closer to an end to their respective easing cycles—Canada included—while the U.S. has lagged in that regard. The U.S. has kept rates elevated in the face of inflation concerns, but we have now begun to see cuts taking place to combat weaker economic growth and labour market concerns.

Fixed Income

With regards to fixed income, Canadian bonds narrowly edged out their U.S. counterparts from a broad benchmark standpoint, with investors slightly favouring more duration than less. Meanwhile, one of the better performing areas of fixed income, U.S. high yield, took a breather as credit spreads notched higher.

Both the Bank of Canada (BoC) and the U.S. Federal Reserve (Fed) cut rates again by 25 bps in October for the second consecutive month. At the time of writing, the market does not expect the BoC to cut rates again this year, though it does expect one more (25 bps) cut from the Fed.

From a Canadian standpoint, the recent rate cut now puts the target for the overnight rate at 2.25%. Comments from the BoC included mention that monetary policy cannot undo trade war damage and that tariffs are imposing severe effects on steel, aluminum, auto and lumber. As a result, they expect GDP growth to be weak for the remainder of the year. On the inflation front, the BoC sees it easing in the months ahead and expect the Consumer Price Index¹¹ (CPI) to remain near 2%. Interestingly, however, as part of a keynote address at a recent industry conference, previous governor of the BoC, Stephen Poloz, addressed the crowd with a message largely centered around stagflation concerns. The long-and-short of his remarks were that a trade war would increase prices and reduce demand for Canadian goods, leading to inflation and weak economic growth. These remarks, however, were delivered prior to the recent Canadian Federal Budget, which appears strongly geared towards spending on projects that could improve growth in Canada over the long term – likely a very welcome development in Mr. Poloz’s mind, as he was critical of Canada’s recent track record of not doing enough to stimulate economic growth through investment.

From a U.S. standpoint, the recent cut now puts the U.S. Federal funds target at 3.75-4.00%. Their decision was largely based on a weakening labour market. With the government shutdown (now representing the longest in U.S. history as at the time of writing), the Fed relied on private indicators to aid in their decision. ADP, for instance, recently reported that private payrolls declined by 32,000 jobs in September, the largest decline since 2023. In his comments, Fed Chairman, Jerome Powell, made mention of a few important points. First, that a December rate cut ‘is not a foregone conclusion’ based on disagreement amongst the Federal Open Market Committee (FOMC) members on the best path forward. Second, he stressed a more measured, wait and see approach, particularly based on a lack of publicly sourced employment data, ‘What do you do if you’re driving in the fog? You slow down.’ Additionally, the Fed announced that they would be ending quantitative tightening (QT) to prevent liquidity strains in money markets. As a quick refresher, QT refers to the central bank selling its Treasury bond holdings or letting them mature without reinvesting the proceeds. When this happens, U.S. banks end up having less reserves on hand to lend out, in turn leading to higher interest rates for borrowers. In a sense, it’s an indirect driver of interest rates and the Fed does not want to inhibit access to loans, stifle economic growth or exacerbate a weak labour market by making capital harder to come by.

John Pagliacci
Vice President, Investment Programs and National Accounts | Guardian Capital LP
John Pagliacci is Vice President, Investment Programs and National Accounts for Guardian Capital LP. He contributes to strategic planning for the Canadian retail asset management business, including product strategy and development, overall sales enablement initiatives and serving as a brand ambassador.

David Onyett-Jeffries
Vice President, Economics & Multi Asset Solutions | Guardian Capital LP
David Onyett-Jeffries is Vice President, Economics & Multi Asset Solutions, at Guardian Capital LP (GCLP). He provides macroeconomic guidance to GCLP and its affiliates. Additionally, he is a portfolio manager of GCLP’s multi-asset portfolios and funds and works closely with GCLP’s Directed Outcomes team.

 

 

¹ Source: MSCI.com. The MSCI World Index captures mid- and large-cap representation across 23 developed market countries.
² Roic.ai, JPMorgan Chase & Co, Transcripts, Q3 3025 Earnings Call Transcript, November 6, 2025, https://www.roic.ai/quote/JPM:CI/transcripts/2025-year/3-quarter
³ International Monetary Fund, Publications, Global Financial Stability Report, Shifting Ground beneath the Calm– October 2025, October 14, 2025, https://www.imf.org/en/Publications/GFSR/Issues/2025/10/14/global-financial-stability-report-october-2025
⁴ CNBC, Tech, OpenAI says U.S. needs more power to stay ahead of China in AI: ‘Electrons are the new oil’, October 27, 2025, https://www.cnbc.com/2025/10/27/open-ai-power-china.html
⁵ Tom’s Hardware, Tech Industry, Artificial Intelligence, OpenAI calls on U.S. to build 100 gigawatts of additional power-generating capacity per year, increase equivalent to 100 nuclear reactors yearly — says electricity is a ‘strategic asset’ in AI race against China, October 28, 2025,
https://www.tomshardware.com/tech-industry/artificial-intelligence/openai-calls-on-u-s-to-build-100-gigawatts-of-additional-power-generating-capacity-per-year-says-electricity-is-a-strategic-asset-in-ai-race-against-china
⁶ Australian Broadcasting Company, News, Fact Check, Chris Bowen says the average time to construct a nuclear plant in the United States has been 19 years. Is that correct?, March 20, 2024, https://www.abc.net.au/news/2024-03-21/fact-check-chris-bowen-nuclear-power-plant-19-years/103611282
⁷ Mis.asia, Resource, Energy, How Long Does It Take To Build A Nuclear Power Plant, April 6, 2025, https://www.mis-asia.com/resource/energy/how-long-does-it-take-to-build-a-nuclear-power-plant-2.html
⁸ Evergreen Gavekal, Louis-Vincent Gave, The Energy Trade-Off, October 30, 2025, https://evergreengavekal.com/blog/the-energy-trade-off/
⁹ The US energy Consumer Price Index (CPI) is a measure of the average change over time in the prices that urban consumers pay for a ‘market basket’ of energy-related goods and services, including electricity, natural gas, and motor fuels.
¹⁰ https://techstartups.com/2025/10/20/alibabas-aegaeon-cuts-nvidia-gpu-usage-by-82-doing-to-ai-hardware-what-deepseek-did-to-software/
¹¹ Inflation measured by the CPI is defined as the change in the prices of a basket of goods and services that are typically purchased by specific groups of households.

 

 

 

   

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Published: November 12, 2025