Future Returns: The Banking Crisis Didn’t Scare Off Alternative Investors

Investing for high-net-worth clients can be a bit of a high-wire act because they can have significant amounts of money tied up in complex alternative investments. When the panic started with the collapse of Silicon Valley Bank in March, wealth manager Tom Ruggie was relieved that none of his clients were directly invested.

“We got lucky there,” says Ruggie, a certified financial planner and author who is based in central Florida. “But when it came to Credit Suisse, we had a little bit of a scare.”

Ruggie’s firms—a family office business called Destiny Wealth Partners and a financial planning firm called Ruggie Wealth Management—did some work with the troubled financial institution on debt obligations. It turned out that all of the contracts were completed, but if Credit Suisse had failed, Ruggie and his clients would have lost a lot of money because the notes would not have been paid back.

Investors who have money in private equity, hedge funds, and direct investments in start-ups are used to taking on a lot of risk and have the financial capacity to absorb it. Ruggie points to an EY study that a third of those with assets above US$250,000 hold some alternatives in their portfolios, including 81% of ultra-high net worth clients with more than US$30 million. Scares don’t happen often, but when they do, “it’s an eye-opening event,” Ruggie says.

Still, rather than run to safety when things turn sour, Ruggie’s clients are more likely to go back and do it again. “They are usually willing to take risks when everyone else is running for cover,” he says. “When you have something come up, like the current banking crisis or the situation in 2008, a lot of people psychologically don’t do well with uncertainty. But the savvy investors, they look at it as an opportunity.”

Here’s where Ruggie says high-net-worth investors want to put their money today.

How Much Risk?

Not all high-net-worth investing is deep in alternatives. Ruggie says he divides client money into three pools: short-term money in fixed income, mid-range money in traditional equity investments like mutual funds and exchange-traded funds, and then long-term money in private investments.

To decide the ratio, he says “it’s a statistical correlation of how much money you have to how much you need and for how long. There’s no cookie-cutter answer.”

Some clients don’t put more than 10% of their net worth into non-traditional alternatives. Ruggie’s personal portfolio is pushing 40% alternatives, he says. Much of that is tied up in sports memorabilia—mostly an extensive baseball card collection—and some collectible wines, along with direct investments in companies.

Non-fungible tokens (NFTs) are a bridge too far—“I personally can’t see the advantage of investing in something like that, and never recommend for a client to do so,” Ruggie says.

As for cryptocurrency, Ruggie has dabbled, but just for the experience. “I wanted to learn,” he says. “I did quite well, but when clients came to us for advice, our guidance was that it’s off our path. Our client base is more concerned about long-term performance than the gambling aspect of investing.”

How Much Capital is Required?

Ruggie says direct investments in companies can start as low as US$25,000. These are the opportunities that are the most interesting to his clients right now, especially technology-based start-ups.

Some clients also take a step back and put their money into private-equity that then pools investments and finds companies worth investing in. Those typically require putting in at least US$250,000 and the purchaser has to be qualified, with a net worth of US$5 million net. Ruggie’s clients also invest in hedge funds, real estate, and collectibles.

Of these investments, hedge funds are the most liquid. There’s usually a lock-in period of a year, but then money can typically be withdrawn with 30-days notice.

Private equity has much less flexibility. “I tell people to basically anticipate no liquidity at all,” Ruggie says. “My mindset on private equity is that this is long-term money.”

The same goes for most direct investments in companies, which aside from the potential to sell stakes on the secondary market, there’s no ability to get cash out unless the company goes public and the shares appreciate.

The Potential Gain?

The main reason for investing in alternatives is that the potential upside of these investments is unlimited.That’s what makes it worth the risk. The other reason is that many high-net-worth clients have money to put on the line.

“What is excess? It’s a correlation between what you have and what you need,” says Ruggie. “Everyone’s definition of rich is different.”

In a year like 2022, advisers like Ruggie have had to go to clients with bad news about losses for the year and say, they may have outperformed the market but still lost 10% or whatever the number. But for Ruggie, that’s a temporary situation with paper losses.

The rest of the speech goes something like this: “It’s my belief—backed up by my personal investments—that what we’re doing with alternatives is going to outperform the market with statistically less risk than the market over time. It will catch up.”

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