The Money Habits I Learned From My Parents

My memory of when I first learned about stocks is fuzzy. I was in my early 20s, and my mother sat me down at our kitchen table, helped me open a brokerage account, and showed me how to buy and sell on the platform. The lesson I walked away with: Tread carefully, invest only “play money,” not money you need to survive, and only target companies that sell resources.

I also thought: This is too risky; I’ll never touch this account.

Years later, I still approach stocks with trepidation—no doubt coloured by that 30-minute conversation with my mom.

As I’ve talked to my family and friends, I realize that so much of what we know about personal finance—how we invest, how we spend—comes from our parents.

“We get our money personalities from our childhood,” says financial planner Angela Dorsey of Dorsey Wealth Management. “So if in our childhood there was a lot of hesitancy around it, then that shapes how you feel about money and taking calculated risks.”

Learning by watching

Sometimes, these lessons are learned through specific conversations, like the one I had with my mother. But more often than not, they come simply through observing. In fact, Dorsey says that many of her clients don’t have any money conversations with their parents. “It comes from seeing what happened to their parents, seeing what happened to their uncle,” she says. “A lot of times, they’re not even aware of it.”

But that lack of awareness comes with a price: When people don’t know where their money habits come from, they can often undermine good intentions. You may want to invest and spend wisely, but these unconscious, ingrained tendencies can create financial problems down the road. So it’s useful to uncover those unspoken lessons, and figure out which ones serve us well—and which ones don’t.

To expose those habits, Dorsey offers her clients a money-personality quiz, which can unveil attitudes about money developed from childhood. So I decided to take one. For good measure, I had my sister take it as well.

Both of us ended up falling into the “Bon vivant” pool—with traits like “Workaholics with long hours” and “Spends money on anything that saves them time.” Our issues? “Ad hoc investments,” “Panic with market ups and downs,” and “Confuse hobbies with investments.” (We both really felt that last one.)

Looking back, the traits that mark my financial personality are pretty much the same traits that my parents had. They worked long hours. They did give priority to spending on things that saved them time. They were happy to buy me new books or help me tackle a new hobby or skill. New clothes or makeup? Not so much.

Unlearning some lessons

Friends I spoke with mostly echoed what my sister and I experienced. While their parents might not have given them specific advice, they did influence their spending and budgeting tendencies just by being who they were.

“I didn’t get any money lessons from my parents, but I certainly picked up habits,” a former co-worker told me. “I saw my dad pack lunch every day for work, so I pack lunch every day for work now.” This friend was particularly thrifty in my years working with her, primarily using a debit card so as to not carry debt and eating her packed lunches as the rest of us spent $15 on salads and sandwiches.

She now has a credit card, but to this day she’d rather cobble together a lunch of office snacks than go out to buy lunch. “It has helped me in the long run because it keeps a baseline of healthy spending habits,” she says. She prefers meals out as a conscious choice for special occasions, rather than a standard practice.

Another friend watched how his parents, who were small-business owners, scrimped and saved at home. He summed up what he learned from that in three bullet points:

He says he is now trying to loosen up and feel comfortable spending some of his hard-earned money to improve his quality of life, especially as he has become more successful in his career.

This is a common lesson Dorsey says she teaches her clients to unlearn. “It’s really interesting how frequently I run into situations where they have enough, but when it comes time to spending, they’re terrified,” she says. “And so I have to tell them, ‘You have my permission to spend your money.’ ”

On the brink of burnout

For my part, I’ve certainly benefited from watching my parents’ work ethic over the years. Doing so gave me the drive to establish my own career goals. Seeing their productivity inspired my own. But in the past few years, I’ve found myself on the brink of burnout—both at work and with all my extracurricular activities.

That has led me to the realization that my work and personal lives could actually benefit more from me enjoying my weekends, and not always packing them full of events or extra work. I now know that it’s just as important to step back from things and take a moment to recharge as it is to charge ahead. And my wallet would certainly appreciate buying less crochet yarn and concert tickets.

Mostly, though, I’ve had to work to get over my stock-market fears. My mother sitting down to explain how the market works was more than what some of my friends learned from their parents. But while it was a well-intentioned lesson, it didn’t have the desired effect at the time.

As a more fully-formed adult, I began to rethink that conversation. And thanks to my colleagues and my friends, I’ve started to put money into something beyond a basic savings account. I began contributing to a Roth IRA after a friend explained the tax benefits. A former boss clued me into high-yield savings accounts. A colleague encouraged me to invest—but in more-diversified ways, such as ETFs.

And I finally logged into that brokerage account my mother helped me open. While I still veer toward the more risk-averse side, following my mother’s cautious footsteps, learning more on my own has allowed me to think of investing as a way to make my savings grow, not just a way to experiment with “play money.”

In the end, sometimes the most well-intentioned parental lessons backfire. One friend invested in specific mutual funds that his father recommended. But those mutual funds didn’t do well and started dropping in value. So when my friend was later eligible to contribute to his employer-sponsored retirement account, he chose not to—feeling burned by those earlier losses. Instead, he used his extra money to be able to live without a roommate.

While my friend eventually ended up contributing to a retirement plan, he says the earlier experience taught him that sometimes you just need to “reject the things your parents tell you to do.”

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

The Money Habits I Learned From My Parents—for Better or Worse

We absorb our financial personalities from listening to, and watching, our parents. Sometimes they serve us well. Other times, not so much.