Green Investors Were Crushed. Now It’s Time to Make Money.
The lessons have been hard, and are a reminder of the basic facts of investing
4 min
Invest according to your political views, and you’re unlikely to make money. Companies that appeal to left-wingers or to right-wingers might be good or bad investments, but the fact of being, on current politics, clean and union-friendly for the left or oily and gun-friendly for the right is neither here nor there. What matters is their ability to make money and how highly they are valued.
This has been rammed home for environmentally-minded investors in the past year, as a coordinated selloff in anything with green credentials crushed the idea of making money while doing good.
It turns out that the real world is tougher than advocates of ESG—environmental, social and governance—investing claimed. The lessons have been hard, but should remind investors in the sector of some of the basic facts of investing. The fall in prices has improved the outlook for the stocks.
This year has been almost universally bad for clean investments. The two worst performers still in the S&P 500 are solar companies Enphase Energy and SolarEdge Technologies, down 60% and 70%, respectively. Hydrogen stocks have fallen sharply, led by Plug Power, which warned it might not survive. Wind-farm developers have been doing so badly they have pulled out of some contracts, with Denmark’s Ørsted off 48% in dollar terms and Florida-based NextEra Energy off 29%.
Electric cars have disappointed too, hitting startups and suppliers and pushing the price of lithium ores, used to produce the battery metal, down by three-quarters or more, although market-leader Tesla’s stock has been an exception.
Just as there was a coordinated green selloff, there has been a coordinated partial rebound in the past month or so.
This provides the first lesson: debt. The clean-energy sector is dependent on vast amounts of borrowing, so high interest rates really hurt. Roman Boner, who runs a clean-energy fund at Dutch fund manager Robeco, points out that major projects are typically financed with 80% debt, so rises in financing costs have a big impact on competitiveness.
Investors who bought into green stocks probably didn’t think they were making a leveraged bet on Treasurys, but that is what they ended up with. It isn’t only about corporate financing costs, either. High borrowing costs hit consumer demand for rooftop solar and for electric cars, both of which are often leased, since leasing costs depend on the cost of debt.
At a very high level, this is about long-term thinking. Low rates encourage investors to think long term, because they make future profits almost as valuable as current profits, and encourage borrowing to try to secure those future profits.
High rates encourage short-term thinking, by making profits today far more valuable than future profits—why bet on the future when you can earn 5% from Treasury bills? Short-term we get fossil-fuel profits, while long-term we get either clean energy or global warming; recently investors have been encouraged by rising rates to think short term.
The second lesson: government. Ronald Reagan overstated it when he said: “The nine most terrifying words in the English language are: ‘I’m from the government, and I’m here to help.’” But investors who rely on state subsidies to ensure profits leave themselves at the mercy of both fickle politicians and the bureaucrats Reagan was concerned about. This year’s selloff has been worsened by the bureaucrats and their failure to provide the details of many of the subsidies promised in last year’s badly named Inflation Reduction Act.
“We’re still hoping to get them by year end,” says Ed Lees, co-head of the environmental strategies group at BNP Paribas Asset Management. The next problem might be the politicians, at least if Donald Trump wins the presidency and torches the IRA. Lees thinks this will be hard, because so many IRA-subsidised projects are heading for Republican states. But Trump certainly has no sympathy for environmental causes.
The third lesson is the one most relevant to buying today: valuation. Buying stocks when they are trendy and wildly overpriced is a recipe for disaster. Perhaps the most extreme example of late is the L&G Hydrogen Economy ETF, launched in London at the height of clean-energy excitement in February 2021. It plummeted from day one, never regained its launch price, and is down 55% since then.
“We’ve seen a very harsh reality check,” said Sonja Laud, chief investment officer of L&G Investment Management.
The question is whether the hype has left. Laud worries that one year of high rates won’t have crushed all the excesses built up in 12 years of near-zero rates. But clearly valuations are much lower than they were, and she is hopeful there are opportunities to be found now.
“The huge green premium you had previously is no longer there,” says Velislava Dimitrova, who runs sustainable funds at Fidelity International. Clean-energy stocks are “much more interesting than they used to be—I don’t believe that renewables are dead.”
In the bond market, investors are no longer paying much if any “greenium,” or extra price for green bonds. In stocks, it is harder to judge: The S&P Global Clean Energy index trades at a discount to the global market on some measures, but not others, making it difficult to conclude that the sector as a whole is a wonderful bargain.
Still, it is good news for buyers that the hype has evaporated. Investors who care about profits more than purpose can finally consider clean-energy stocks again.
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Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
4 minA sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.
The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.
The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.
The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.
This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.
The debt behind the AI build-out
Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.
Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.
JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.
The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.
That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.
A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.
When interest rates rise, those assumptions become less forgiving.
Inflation changes the calculation
September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.
The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.
CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.
Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.
Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.
The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.
China adds another source of pressure
Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.
Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.
The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.
That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.
A reset rather than the end of the boom
The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.
What has changed is the market’s willingness to overlook the price and financing structure of that growth.
The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.
More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.
For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.
Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.
The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.
Fact box
Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026
Philadelphia Semiconductor Index: Down approximately 11.4 per cent
Micron Technology: Down approximately 14.6 per cent
Samsung Electronics: Down approximately 18 per cent
SK Hynix: Down approximately 24 per cent
US September inflation: 3.7 per cent annually
Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion
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