In France, Investors Get the Centrist Limbo They Wanted

When it comes to France’s turbulent politics , the current impasse is probably the best investors could have hoped for.

The second round of French legislative elections delivered a widely expected hung parliament, but not its predicted makeup: Rather than coming in first, Marine Le Pen ’s far-right and anti-immigrant National Rally finished third. In a shock twist , the leftist New Popular Front alliance emerged victorious, with the party of President Emmanuel Macron and its allies in second place.

This is because leftists and centrists ended up coordinating. In many local races, candidates dropped out to avoid dividing the vote against the far right. Still, no party has an outright majority, which plunges the country into political gridlock. This was, counterintuitively, the preferred outcome for financial markets.

The CAC 40 initially tumbled when the elections were called in June, driven by fears of a potential National Rally government challenging the European Union with fiscally expansive plans. Then the French stock benchmark perked up, as the first-round results suggested that the far-right wouldn’t get a majority.

Yet markets remained volatile because the rise of the New Popular Front raised even greater concerns. The policies of this coalition, in which leftist firebrand Jean-Luc Mélenchon is a key leader, also include more public spending, on top of widespread tax increases. Indeed, the CAC 40 closed down 0.6% Monday, probably reflecting investors’ concerns about these parties potentially managing to form a new government. Mélenchon has stated that there will be no deals with the centrists.

These worries seem overblown. Yes, there are doubts about how France will handle its budget deficit, which amounted to 5.5% of gross domestic product in 2023 and has forced the EU to launch an “excessive deficit procedure” against the country. Macron may need to accept the reversal of reforms such as a higher retirement age.

Still, a fiscal crisis isn’t in the cards, because the European Central Bank is ultimately in control of France’s bond market.

As for economic growth, it is unclear how much impact Macron’s policies have had in the first place, particularly given resistance from unions and swaths of the public, which resulted in the famous “yellow vest” protests in 2018 and 2020.

What matters for sectors battered in the stock market, including banks, energy firms and infrastructure operators, is that the risk of widespread tax increases, nationalisations and a prolonged standoff with Brussels seems smaller now than a few weeks ago. Whatever Mélenchon says, the left will either have to compromise or else form a minority government that might scare investors but wouldn’t be able to pass laws.

So there isn’t much justification for the lower valuation of lenders such as Société Générale and especially BNP Paribas —one of Europe’s most interesting banks that now trades at 0.65 times tangible book value. The same is likely true for firms such as energy utility Engie and infrastructure-concessions leader Vinci , which have lost 8% of their market value since the end of May.

These elections are more a symptom of Macron’s weakness than its cause. After a chaotic month, French politics is back where it has been for years, with a rising far right forcing the left to back a centrist platform that can achieve little because few people actually like it. Macron himself became president on an anti-Le Pen ticket, but in seven years has failed to rally broad support for his pro-business vision.

This could eventually make Le Pen’s victory inevitable, as she claimed after initial results came in. For now, though, it is more or less what markets ordered.

A 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