A client recently said something to me that I've been thinking about ever since.
A friend had told them there really wasn't much reason to use an advisor because advisors can't beat the indexes.
Why wouldn't I just buy an S&P 500 or Nasdaq index fund? Then I'm diversified.
It's a fair question.
And frankly, there's plenty of evidence supporting part of the argument.
Over long periods of time, most actively managed large-cap funds have failed to outperform the S&P 500. In 2025 alone, 79% of actively managed U.S. large-cap funds underperformed the index.¹
Indexing has provided investors with an incredibly efficient, low-cost way to participate in the growth of some of the world's greatest companies.
But there's another part of that statement worth examining.
What exactly do we mean by diversified?
Owning hundreds of companies certainly provides diversification across individual businesses.
But those companies aren't represented equally.
As of July 31, 2026, the ten largest stocks represented 37.6% of the entire S&P 500.²
At the same time, Americans have embraced equities at historic levels. According to a recent Goldman Sachs analysis, equities have now surpassed real estate as the largest component of U.S. household wealth for the first time since World War II.³
None of this means indexing is a bad strategy.
And it certainly doesn't mean a market correction is coming.
But it does mean an enormous amount of household wealth is now exposed to a market increasingly influenced by a relatively small number of very large companies.
After years of strong returns, I think there's a more interesting question worth asking.
Has our perception of the risk changed along with the returns?
Success has an interesting effect on human behavior.
The more often we're right, the more confident we become that we understand why we're right.
The longer something works, the easier it becomes to believe it will continue working.
Risk doesn't disappear.
It just starts feeling less risky.
And that's not unique to indexing.
It can happen with an investment strategy.
A business.
A forecast.
Even a mathematical model.
There's something comforting about precision.
A forecast telling us there's a 70% probability of something happening somehow feels more reassuring than someone simply saying, "We think this is probably going to happen."
I understand the appeal because we use probability-based tools ourselves.
When building financial plans, we use Monte Carlo simulations to test plans against thousands of potential scenarios.
When helping clients understand investment risk, we use software that calculates a six-month 95% historical range to illustrate the type of volatility a portfolio might reasonably experience. The methodology explicitly acknowledges that there's another 5% of risk that can't be quantified.⁴
They're incredibly valuable tools.
But there's an important word buried in all of them.
Probability.
A 95% range doesn't mean the other 5% can't happen.
A Monte Carlo simulation doesn't know what the future holds.
And a model isn't a promise.
It's a tool designed to help us make better decisions despite uncertainty.
The danger begins when better tools don't just make us better informed.
They make us more certain.
Few stories in financial history illustrate that distinction better than what happened in 1998 at a hedge fund called Long-Term Capital Management.
LTCM wasn't run by amateurs.
Quite the opposite.
Founded in 1994 by legendary bond trader John Meriwether, its team included some of the most respected financial minds in the world, including Myron Scholes and Robert Merton, who shared the 1997 Nobel Prize in Economic Sciences for their work involving the valuation of derivatives.⁵
These were mathematicians, economists and traders using extraordinarily sophisticated models to identify small pricing discrepancies across global financial markets.
The basic strategy was relatively straightforward.
LTCM would identify similar securities whose prices had temporarily moved apart and bet that they would eventually move back together.
The potential profit on each trade was often very small.
To turn those small opportunities into enormous returns, LTCM used leverage.
A lot of it.
By the end of 1997, the fund had roughly $30 of debt for every $1 of capital.⁵
And for several years, it worked spectacularly.
LTCM returned approximately 20% in 1994.
43% in 1995.
41% in 1996.
17% in 1997.⁵
Think about what repeated success like that can do to human psychology.
The models appeared to work.
The profits reinforced the models.
The models reinforced confidence.
And confidence made it increasingly easy to believe they understood the risks they were taking.
Success has a way of making risk feel smaller without actually making it smaller.
That's where two very human tendencies can begin feeding off one another.
The illusion of control tells us we've figured it out.
Hubris tells us we can't be wrong.
And leverage allowed LTCM to bet accordingly.
Then came 1998.
Financial turmoil that had begun in Asia intensified. In August, Russia devalued the ruble and defaulted on portions of its domestic debt.
Fear spread quickly.
Investors rushed toward safety and liquidity.
And many of the relationships LTCM expected to converge...
did exactly the opposite.
They diverged.
At the same time.
Across markets.
LTCM lost approximately 44% of its value in August alone.⁵
But here's the part of the story I find most interesting.
The smartest people in the room hadn't suddenly become stupid.
Their mathematics hadn't suddenly become useless.
And some of the relationships they expected to normalize eventually did.
Their problem was much more fundamental.
They had built a portfolio that couldn't afford for the future to take an unexpected path on the way there.
You don't necessarily have to be wrong forever to lose.
Sometimes you just have to be too certain, too leveraged...
and wrong for long enough.
Within weeks, the situation became serious enough that officials at the Federal Reserve Bank of New York became concerned an uncontrolled collapse could force enormous positions to be liquidated into already fragile markets.
On September 23, fourteen banks and securities firms agreed to inject approximately $3.6 billion into LTCM in exchange for 90% ownership of the fund. Despite how the story is sometimes told, taxpayers did not bail out LTCM. The Federal Reserve helped facilitate the agreement, but the capital came from private financial institutions.⁵
For me, though, the rescue isn't the most important part of the story.
It's how they got there.
LTCM had brilliant people.
Sophisticated mathematics.
Enormous amounts of historical data.
And models designed specifically to understand risk.
The models weren't the problem.
Forgetting what the models couldn't tell them was.
That's where I think the story becomes relevant today.
Today's markets and LTCM are obviously very different.
The parallel isn't financial.
It's behavioral.
The fact that indexing has worked extraordinarily well doesn't mean it will stop working.
The fact that active managers have struggled to outperform doesn't mean they're destined to struggle forever.
And today's market concentration doesn't tell us what happens tomorrow.
The lesson is much simpler.
Past success is evidence.
It isn't certainty.
That's also why I don't view probability forecasting as a way of predicting the future.
I view it as a way of preparing for different versions of it.
There's a meaningful difference.
One says:
"Here's what will happen."
The other says:
"Here's what could happen, and here's how we prepare for it."
At Perennial, that's why diversification, financial planning and risk management matter far more to us than perfectly predicting what happens next.
A good financial plan shouldn't require our forecasts to be exactly right.
It should acknowledge from the beginning that sometimes they won't be.
The lesson from LTCM isn't that models don't work.
It isn't that indexing doesn't work.
And it certainly isn't that success should make us suspicious.
The lesson isn't that what worked yesterday won't work tomorrow.
It's that yesterday's success can make us far too certain that it will.
The illusion of control tells us we've figured it out.
Hubris tells us we can't be wrong.
History reminds us that neither makes the future any more certain.
The strategies change.
The models improve.
The technology evolves.
Markets evolve.
Human nature doesn't.
And perhaps the greatest risk isn't uncertainty itself.
It's becoming so comfortable with what's been working...
that we forget uncertainty was there all along.
Sources
¹ S&P Dow Jones Indices, SPIVA U.S. Year-End 2025. 79% of active U.S. large-cap equity funds underperformed the S&P 500 in 2025.
² S&P Dow Jones Indices, S&P 500 Index Characteristics, July 31, 2026. Top 10 constituents represented 37.6% of index weight.
³ Goldman Sachs analysis reported by Reuters, July 23, 2026, Equities surpass real estate as top U.S. wealth driver for first time since WWII.
⁴ Nitrogen, Advanced Methodology: 95% Historical Range. Nitrogen describes its six-month 95% Historical Range and notes that 5% of risk cannot be quantified.
⁵ Federal Reserve History, Near Failure of Long-Term Capital Management. Historical account of LTCM's principals, strategy, leverage, annual returns, 1998 losses and privately funded recapitalization.
Important Disclosures
John B. Petrick is a registered representative with and securities offered through LPL Financial. MemberFINRA/SIPC. Investment advice offered through Perennial Investment Advisors, a registered investment advisor. Perennial Investment Advisors and Perennial Financial Services are separate entities from LPL Financial.
This material is for general information only and is not intended to provide specific advice or recommendations for any individual. There is no assurance that the views or strategies discussed are suitable for all investors or will yield positive outcomes. Investing involves risks including possible loss of principal. Any economic forecasts set forth may not develop as predicted and are subject to change. References to markets, asset classes, and sectors are generally regarding the corresponding market index. Indexes are unmanaged statistical composites and cannot be invested into directly. Index performance is not indicative of the performance of any investment and do not reflect fees, expenses, or sales charges. All performance referenced is historical and is no guarantee of future results.
There is no guarantee that a diversified portfolio will enhance overall returns or outperform a non-diversified portfolio. Diversification does not protect against market risk.