Tag Archives: Investing

10.20.26
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39-Years Ago!

By: Russ Kamp, CEO, Ryan ALM, Inc.

Black Monday’s 39th anniversary came and went with little fanfare. I can recall quite vividly the events surrounding the U.S. equity market’s largest single day decline and wondering at the time if I was going to have a job by the end of that week. For those of you who were working on Wall Street (or even born) at that time, you’ll remember that the Dow declined 108.35 points (-4.6%) on Friday, October 16, 1987, making for a very long weekend, as we wondered what might happen next. I certainly didn’t expect a 508-point decline (-22.6%), and I suspect that most didn’t either. Importantly, the crash didn’t emerge from a weak market. The Dow had risen an extraordinary 44% in the first seven months of 1987, before peaking in August.

As I reflect on that time, I wonder if there are similarities to today’s investing environment, including valuations, interest rates, market concentration, and a powerful theme driving market enthusiasm that should give us some pause.

1. Valuations: Current valuations are stretched, and perhaps more so than in 1987. The Shiller CAPE is currently about 40.7, versus a historical mean around 18. The only comparable recent example was the 1999–2000 technology bubble (44). Another period of note was in September 1929, when the CAPE was about 32.6. If you aren’t a fan of the Shiller CAPE, another current valuation measure puts the S&P 500 at roughly 21× forward earnings. Like any valuation measure, they aren’t timing tools, but they do tell us investors are paying a very high price for future earnings that might limit future gains.

2. Interest Rates: U.S Treasury yields have risen significantly since bottoming in 2020, achieving a level that makes bonds serious competition for stocks. In 1987, the 10-year Treasury note began the year with a yield of 7.2%. By September 30, 1987, that yield hit 9.63%, providing an extremely attractive alternative to equities. Today the absolute yield is much lower at 5.11% (9:13 am) but that’s up considerably from the near-zero-rate environment in which many of today’s equity valuations were established.

3. Market Leadership: Today’s S&P 500 has become increasingly dependent upon a handful of mega-cap technology/AI companies. S&P Global specifically warns that the Magnificent Seven increasingly behave like a single AI-related risk factor, rather than seven independent sources of diversification. In a note from Glen Eagle, they point our that the five largest companies in the S&P 500 are currently so massive that they are worth the same as the bottom 434 stocks in the index combined.

4. Powerful Narrative: Today’s investing narrative surrounding AI may be more obvious than that which was driving markets in the mid-’80s, but not necessarily more powerful. In 1987, markets had experienced years of deregulation, financial innovation, globalization, and economic expansion following a prolonged period of rising rates, that began to reverse in 1981. As I’ve written in previous blog posts, I don’t question AI’s transformative potential. I question whether today’s prices and enormous capital expenditures can generate sufficient economic returns to justify those investments.

I’m certainly not suggesting that equity markets may see another -22% drop in a single day, as I witnessed 39-years ago. Importantly, today’s markets have circuit breakers. A 7% S&P 500 decline triggers a Level 1 halt, while a -13% triggers Level 2, and -20% triggers Level 3, ending trading for that day. These circuit breakers don’t prevent a major decline, but it makes a repeat of October 19th’s –22.6% single day decline much harder to replicate.

Final thought: In 1987, the market crash itself created the crisis. Today, I wonder whether the capital cycle could create the equity correction, as everything AI is consuming enormous amounts of capital and driving interest rates up in the process. Hyperscalers are spending hundreds of billions of dollars, with potentially trillions of $s yet to be invested. Data-center developers are borrowing heavily well before they are likely to see a return on that investment. Power infrastructure requires still more capital, as capacity seems inadequate to meet future demand. As I wrote about last week, CoreWeave debt has repriced dramatically, where their bonds issued at a yield of 9+% during the summer are now trading at roughly 16%. If AI infrastructure returns ultimately fail to exceed these increasingly expensive financing costs, investors may begin questioning the earnings assumptions embedded in AI-related equity valuations. If that happens, all bets are off!

10.16.26
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Are Cracks Forming?

By: Russ Kamp, CEO, Ryan ALM, Inc.

On September 30, 2026, I wrote my first post regarding my concerns about capacity within the AI trade, as hyperscalers and other businesses associated with AI and data center buildout were rapidly seeking financing through the credit markets. Since that post, I’ve produced one additional update as well as track daily developments in the credit markets that might impact not only Ryan ALM’s business, but bonds/spreads in general.

I’m taking the time to write today because there has been a meaningful development, and this may be the clearest credit-market warning I’ve seen since I began tracking the AI buildout.

The critical development is CoreWeave’s bond selloff. CoreWeave is a publicly traded cloud-computing company built specifically around GPU-intensive AI workloads rather than the general-purpose cloud model of AWS, Azure or Google Cloud. It provides GPU computing, storage, networking and software used to train and run large AI models.

Here’s the story. CoreWeave issued bonds in June at a yield of roughly 9.7%, which are now yielding around 15%! Reuters describes the move as a test of the market’s willingness to continue financing highly leveraged AI infrastructure and says investors are increasingly questioning whether future cash flows justify the debt required to build it.

And CoreWeave isn’t an isolated indicator. Data-center bonds associated with projects backed by major AI participants, including Meta Platforms, Oracle and Microsoft have fallen below par as investors reassess leverage, project the potential economics of these buildouts, and the enormous amount of financing still required.

Demand for the physical infrastructure remains extremely strong. Schneider Electric reported triple-digit data-center demand growth today and raised its 2026 forecasts again; Q3 organic revenue increased 16.9%. So this is not evidence that demand for AI capacity has suddenly disappeared. It is, however, evidence that investors are becoming less willing to finance that capacity at almost any price, and rightfully so.

For AI equities, I would consider this a genuine warning signal. Companies dependent upon repeated external financing should now be valued very differently from cash-generative hyperscalers. CoreWeave’s shares are down about 15% this week even as the underlying demand story remains strong.

For bonds, we’re seeing the beginnings of exactly the differentiation that we anticipated. A 15% yield represents substantial credit, refinancing, and execution risk. If this repricing spreads from “neoclouds” into SPVs and data-center project debt, the marginal cost of AI capital could rise substantially.

For data-center real estate, this adds a second scarcity test to the one we’ve been discussing. A project increasingly needs both secured power and secured economical financing. Having electricity but needing 12%–15% debt doesn’t necessarily produce an economically viable data center.

10.02.26
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Ryan ALM, Inc.’s Concern: Stagflation

By: Russ Kamp, CEO, Ryan ALM, Inc.

The U.S. capital markets are sending some interesting, and perhaps conflicting, signals. Treasury yields have risen dramatically, energy prices remain elevated, diesel supplies continue to be constrained, and corporate credit spreads are beginning to widen. Yet inflation expectations remain relatively well anchored and economic activity has held up surprisingly well. What are we to make of all this? I believe we may be witnessing the early stages of an environment tilting toward stagflation.

The problem, as I’ve written before, is that much of today’s inflation isn’t being created by excessive demand. It is being driven by supply issues, particularly within energy. The Fed can raise the Fed Funds rate by 25 basis points, 50 basis points, or perhaps much more, but none of those actions will produce another barrel of oil, gallon of diesel, or unit of refining capacity. Clearly, we aren’t going to plow fewer acres, ship less food, or stop moving goods around the country simply because interest rates have increased. Energy sources are embedded in virtually everything we produce and consume. Higher interest rates don’t fix that problem.

What higher rates can do is reduce demand elsewhere. Unfortunately, that means households get hit from both directions. They pay more for gasoline, food, utilities, and transportation because of the current energy supply issues, while simultaneously paying more for mortgages, auto loans, credit cards, and other financing because of the Fed. Businesses face the same squeeze through higher operating costs combined with a higher cost of capital. Is that really the prescription we want when the original inflationary driver is primarily a supply problem?

The markets are beginning to reflect this tension. The 10-year Treasury yield has moved well above 5% (currently 5.27% at 12:07 pm), producing an extraordinarily high real yield given that longer-term inflation expectations remain near the mid-2% range. At the same time, credit spreads have begun widening, while oil remains expensive and diesel markets remain stressed. Credit spreads aren’t signaling a crisis today, but the combination of these many factors bears careful watching. If credit conditions continue deteriorating while energy costs remain elevated, we’ll have an increasingly powerful stagflation cocktail based on stubborn inflation accompanied by weakening economic activity.

The Fed should obviously be concerned about inflation. However, I still question whether monetary policy can effectively address the inflationary environment that we’re experiencing without creating other problems in the process. The Fed can diminish demand. It cannot create supply. If energy prices remain elevated while real interest rates stay near more restrictive levels and credit conditions continue to deteriorate, we shouldn’t be surprised to see economic growth suffer. We’ll continue watching Treasury yields, inflation expectations, oil and diesel prices, and credit spreads closely as we monitor conditions for stagflation. Current economic conditions are beginning to get very interesting.

10.01.26
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Kudos to Florida and Its Liquidity Statute

By: Russ Kamp, CEO, Ryan ALM, Inc.

You are not likely to know about Florida Statute §112.661(6) unless you reside in Florida and sit on a pension board, and even then, you still might not have heard or read about this statute. It became effective October 1, 2000, as part of Chapter 2000-264, Laws of Florida, enacted through CS/SB 372, “Investment of Public Funds”, which Governor Jeb Bush approved on June 14, 2000,

This provision is the only one of its type among the 50 U.S. states. Florida should be commended for its inclusion in the management of public pension plans. The subsection for this statute is titled “Maturity and Liquidity Requirements.” 

It provides: “The investment policy shall require that the investment portfolio be structured in such manner as to provide sufficient liquidity to pay obligations as they come due.”

It then goes a meaningful step further: “To that end, the investment policy should direct that, to the extent possible, an attempt will be made to MATCH (the statute’s word, not mine) investment maturities (that says bonds to me) with known cash needs and anticipated cash-flow requirements.” As Phil Rizzuto would say, “Holy Cow”! If given the opportunity, I couldn’t have written this requirement any more clearly.

Again, the Investment Policy Statement (IPS) should direct that an attempt will be made to match investment maturities through bonds with known cash needs and anticipated cash-flow requirements. That sounds a lot like Cash Flow Matching (CFM) to me.

So, I ask, within your (IPS) do you have an explicit Liquidity Policy? If so, does it consider Florida Statute 112.661? At the most recent FPPTA conference in Orlando, I was asked to speak to liquidity management practices currently used in Florida. What I discovered is the there are two fundamentally different philosophies:

Asset-driven liquidity

“When we need cash, where can we get it?”

Liability-driven liquidity

“We know when benefits must be paid, so why don’t we arrange the assets today to produce the cash when those payments occur?”

Here are the seven strategies that I was able to identify that are currently being utilized. I’d be interested to hear from those of you that might have adopted some other means to secure liquidity.

Only #7 falls under the category of liability-driven liquidity, which comes closest to adhering to statute 112:661. Given the rapid rise in U.S. interest rates, creating a cash flow matching portfolio for some period of time (10-years) not only SECURES the necessary liquidity, it extends the investing horizon for the plan’s residual assets, while dramatically reducing the cost to fund those future benefits. We are always happy to provide a free analysis on what CFM could accomplish for you and your fund. Don’t let this wonderful rate environment pass you by.

09.30.26
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Is AI Investment Reaching A Natural Limit?

By: Russ Kamp, CEO, Ryan ALM, Inc.

I’ve been spending a lot of time recently thinking about the incredible amount of capital being thrown at Artificial Intelligence (AI). There is no question that AI has the potential to dramatically change how we live and work. But does that mean that every dollar being invested in AI infrastructure is going to generate an acceptable return? I’m not so sure. As interest rates continue to rise, I think investors need to start asking a different question. Instead of asking, “How big can AI become?”, perhaps we should be asking, “How much AI capacity can actually be built economically?”

AI investment is staggering. Microsoft, Amazon, Alphabet/Google, Meta, and Oracle (the Hyperscalers) are at the center of this massive infrastructure buildout. Until recently, these companies generated so much cash that they could fund most of their capital spending internally. That situation is changing rapidly. AI-related capital expenditures are consuming an enormous percentage of their operating cash flow, and the hyperscalers are increasingly turning to the bond market and other forms of financing to keep the spending machine going. Four of the five major hyperscalers have issued significant amounts of bonds in 2026, with Microsoft being the notable exception. Collectively, hyperscaler borrowing has already reached roughly $200–$220 billion this year. Wow!

Why should we care? Because the cost of money matters and this massive investment could profoundly impact equities, bonds, real estate, private equity, private credit, etc. DB Pension plans need to take notice! When Treasury yields were 1%-2%, financing massive data centers and other AI infrastructure was relatively inexpensive. Today, Treasury yields have climbed above 5%, and the 30-year Treasury bond is closing in on 5.7%, while some long-term hyperscaler debt is being issued at 6% or more. Oracle has recently  issued long-dated debt carrying coupons approaching 8%. This reality changes the economics dramatically. It isn’t enough for a $10 billion or $20 billion AI project to generate revenue. It needs to generate a return sufficient to compensate investors for the cost of the capital, operating expenses, electricity, depreciation, technological obsolescence, and the risk associated with the project. What is that return likely to be and where is that return going to come from?

Capital isn’t the only potential constraint. AI requires enormous amounts of electricity, generation capacity, transmission, transformers, land, cooling, water, semiconductors, construction, and, of course, data centers. A large AI campus can require hundreds of megawatts of electricity. High-density data centers can cost roughly $14-$16 million per megawatt, meaning that a 500 MW facility could cost approximately $7.5 billion to construct before considering the broader power infrastructure necessary to support it. We keep hearing about seemingly unlimited demand for AI. Fine! But there certainly isn’t unlimited electricity, grid capacity, construction capability, or CAPITAL. Why does the investment community seem to assume otherwise?

Furthermore, the AI trade may be creating its own headwind. Think about this for a minute. Massive AI capital expenditures consumed free cash flow from most of the hyperscalers. Declining or exhausted free cash flow creates a need for external financing. Greater borrowing produces more corporate bond supply. More bond supply can contribute to higher yields and wider credit spreads. Higher financing costs increase the hurdle rate on the next AI project. Eventually, some projects simply won’t make economic sense. That seems like the beginning of a vicious cycle to me.

As mentioned previously, the implications extend well beyond technology stocks. Equity investors need to determine whether these enormous capital expenditures are actually producing an acceptable return on invested capital. Bond investors are being asked to absorb hundreds of billions of dollars of new AI-related debt and need to be compensated appropriately. Real estate investors financing data centers must compete against a >5% risk-free Treasury yield while dealing with higher construction and financing costs. 

I’m certainly not suggesting that the AI boom is about to end. But I do believe that the AI investment thesis may be entering a very different phase. The first phase was about AI models, semiconductors, hyperscalers, and data centers. The next phase may increasingly be about the scarce resources necessary to support all of that growth, beginning with capital and including electricity, generation, transmission, transformers, cooling, powered land and water. The winners may ultimately be those controlling the scarce resources rather than simply those spending the most money.

Markets have an interesting habit of believing that trends can continue indefinitely. From my 45-years in the investment industry, I’ve come to appreciate that they don’t. There is always a natural capacity to every investment. AI will prove to be no different. At today’s cost of capital, the important question isn’t how much AI infrastructure companies want to build. It is how much they can afford to build while still generating an acceptable return. Are today’s investors and pension plans adequately considering that distinction? I’m not convinced that they are.

I have an idea. While you wait for the AI thesis to play out, buy time (extend the investing horizon) by creating a cash flow matching (CFM) portfolio that will secure the monthly benefits and expenses for some time – say 10-years. This will enable that AI thesis to perhaps generate the desired return while it grows unencumbered.

09.22.26
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Negative Cash Flow

By: Russ Kamp, CEO, Ryan ALM, Inc.

Negative cash flow occurs when a defined benefit pension plan pays out more in benefits and expenses than it receives in contributions. Don’t panic if your DB plan is experiencing this phenomenon, as negative cash flow is often a perfectly natural consequence of pension-plan maturity. In fact, as a defined benefit plan ages, you would generally expect its cash-flow profile to move in that direction. The issue isn’t the fact that the pension plan is experiencing negative cash flow, the potential problem is how the negative cash flow (liquidity) is financed.

I’ll be addressing this topic at both the FPPTA (9/29 in Orlando) and the IFEBP (10/26 in New Orleans). According to the Public Plans Data (publicplansdata.org), which has robust information on roughly 250 public pension plans covering about 95% of the public assets, 87.2% of the plans are currently in negative cash flow. There are many ways that pension plans are funding monthly benefits and expenses, including:

Liquidity strategyHow it works
1. Cash / money-market reserveMaintain cash, STIFs or money-market funds for near-term benefit payments
2. Contributions + investment incomeEmployer/employee contributions, dividends, and bond coupons fund benefits
3. Fixed-income liquidity sleeveBonds serve as both investment allocation and source of liquidity
4. Rebalancing to fund benefitsSell overweight asset classes and use proceeds for benefit payments
5. Public-market liquidationSell stocks, bonds, ETFs, or other liquid assets as cash is needed
6. Distribution harvestingUse dividends, interest, real estate/private-market capital distributions
7. Cash-flow matching / bond laddersBond coupons and maturities are deliberately aligned with projected benefits

The strategies above highlight two fundamentally different philosophies. The first category are the Asset-driven liquidity group whose practitioners believe that when they need liquidity, they can get it. They are the “When we need cash, where can we get it?” crowd. The strategies that fall under that philosophy include items 1-6 in the above matrix.

The second category is the Liability-driven liquidity cohort, whose supporters claim that “they know when benefits must be paid, so why don’t we arrange the assets today to produce the cash when those payments occur?”. This category includes the Cash Flow Matching and Bond Ladder folks.

The latter strategy is what Ryan ALM espouses for plans with negative cash flow. If you’d like to learn why or to receive a copy of my presentation, don’t hesitate to either reply to this post or email me at rkamp@ryanalm.com, and I’ll be happy to share it with you.

09.10.26
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Pension Alert: 6.09%!

By: Russ Kamp, CEO, Ryan ALM, Inc.

We just completed an analysis for a DB pension plan in which we were able to defease the fund’s liabilities for 30-years at a YTW of 6.09%. That is an incredible yield, especially given the fact that the YTW is basically what a pension plan will earn over the life of the cash flow matching (CFM) program. While core fixed income strategies are highly interest rate sensitive, defeasing pension liability cash flows (benefits and expenses) with asset cash flows of bond interest and principal eliminates interest rate risk, as future benefits are not interest rate sensitive.

The more extraordinary aspect of this analysis is the fact that the cost to fund FV benefits (and expenses) will be reduced by 70.5% versus the present value of assets needed to fund those liabilities, if the 30-year assignment is fully implemented. You read that correctly: there is a 70.5% reduction in the cost to fund those future value benefits given today’s interest rate environment.

Are you thinking that we must be injecting significant risk into the bond portfolio in order to achieve that level of interest? Well, the average quality rating on our 100% investment grade corporate bond portfolio is an A-. Furthermore, we have as an internal risk control prohibiting purchasing bonds rated below BBB+.

The rates below are from the WSJ as of 9:52 am on 9/10/26

We don’t know where U.S. interest rates are headed, but the beauty in building CFM portfolios is the fact that we don’t need to forecast rates. Once the asset cash flows are matched against the liabilities, the relationship is maintained whether rates rise or fall.

Few pension plans took advantage of the last de-risking opportunity back in 2020. Please don’t waste this chance to SECURE the promises made to your participants, while protecting the plan’s funded status and contribution requirements.

09.02.26
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Still Think That They Are Performance Drivers?

By: Russ Kamp, CEO, Ryan ALM, Inc.

Bonds enjoyed a nearly 4-decade bull market as U.S. interest rates plummeted from historic highs to an environment of negative real rates. It was unprecedented. As a result, bonds were perceived to be performance drivers. But are they?

We are often told by plan sponsors or their advisors that they can’t invest in a cash flow matching (CFM) strategy because de-risking the portfolio will negatively impact the fund’s ability to achieve the annual return on asset (ROA) assumption. Is that reality?

Facts:

  • The Aggregate bond index has produced a -0.29% annualized return for the 5-years ending August 31, 2026!
  • A CFM portfolio would have generated a return commensurate with its YTW (or YTM) during that 5-years. Shorter maturity (1-5-year defeasement) CFM portfolios were yielding about 1.6% at that time. That equates to a nearly 2% per year return advantage. Still think that CFM is a drag on performance?
  • U.S. inflation remains elevated. A CFM portfolio is the perfect pension inflation hedge since it is fully funding liabilities that have inflation in the projected benefits to be funded.
  • The direction of U.S. rates is uncertain, although rates have been trending higher, putting more strain on core fixed income strategies that tend to underperform when rates rise.
  • For the 28-years prior to the bond bull market (1953-1981), U.S. rates rose. Are we in a secular long-term rising rate environment?
  • Bonds should only be used for their cash flows of interest and principal upon maturity, which can be modeled to match and FUND a pension plan’s liabilities (benefits and expenses), with certainty barring any defaults.

Plan sponsors have not had this level of U.S. interest rates in roughly 20-years, providing them with a wonderful opportunity to protect the improved funded status, while securing the liquidity necessary to meet those pesky monthly obligations. Will this opportunity go unheeded just as the one presented in 2000 did? We know that failing to protect and preserve DB plans in 2000 was followed by two major equity market corrections that crushed pension funding and caused contributions to skyrocket. Do you think that sponsors of DB plans have the financial wherewithal to see contributions escalate once more? I don’t!

We recommend converting your current core fixed income allocation, with all of its interest rate risk, to a cash flow matching bond portfolio, that will carefully match and fund all of the monthly obligations as they come due. A CFM portfolio matches interest and principal against future obligations, and in doing so, eliminates interest rate risk as future values are not interest rate sensitive. If you owe a plan participant $2,000 in benefits next month, it is $2k whether interest rates are at 2% or 10%. The higher rates reduce the future value cost of the promised benefits in present value $s. We are seeing roughly 6% YTMs in our recent 30-year assignments and a >50% reduction in the cost of those future benefit payments.

You could continue to use a core fixed income allocation with all of its uncertainty or you could create certainty within a portion of your plan that doesn’t exist today. I suspect that your participants would appreciate knowing that the promised benefits are secure no matter what transpires in global markets.

08.28.26
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About Time!

By: Russ Kamp, CEO, Ryan ALM, Inc.

FINALLY!!!

Yesterday, there appeared a P&I article with the headline: “Ohio State Teachers says beating peers isn’t the point — paying benefits is”

YESSSSS! The only reason that a defined benefit pension plan exists is to fund a promise given to the participant. Managing a pension plan isn’t about achieving an ROA or beating a hybrid total fund index or eclipsing the performance of a peer group (silly concept). It is truly only about SECURING the liquidity necessary to match and fund benefits (and expenses) when they come due!

The pursuit of a return objective has only guaranteed volatility and NOT success. That is volatility of returns, contributions, and funded status. It is time to get off the performance rollercoaster.

The higher U.S. interest rate environment is providing plan sponsors with a great opportunity to de-risk and enhance liquidity through cash flow matching (CFM), which is designed to secure the liability cash flows (benefits and expenses) through the careful matching of asset cash flows (principal and interest) from bonds. 

An opportunity such as this hasn’t existed since 2000, when the average pension plan was well-overfunded and contribution expenses well-contained. It has been 26-years since the first market crash of the aughts began and public pension funds have only clawed back to an average funded status of 88% (Milliman). They can’t afford another crash that will only lead to a deterioration in the funded status and an escalation in contributions.

No one knows when that next correction may be just around the corner. Given that reality, don’t leave your pension plan vulnerable to this uncertainty. Put in place today a CFM strategy that will SECURE the promised benefits with certainty (barring an IG default), while buying time for the return-seeking assets to wade through the next market crisis. The time to act is now and not after the next market correction.

08.27.26
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Deja Vu All Over Again? Just Saying!

By: Russ Kamp, CEO, Ryan ALM, Inc.

Yogi Berra, the great Yankee catcher, but also a NY Mets player/coach in 1965, is credited with the saying it’s “Deja Vu all over again”, which he supposedly uttered back in 1961. Are we potentially witnessing in 2026, with AI investments soaring and equity valuations that may be stretched, a replay to what transpired in March 2000? Now, I’ve heard many arguments that today’s technology companies aren’t your fathers’ or even your grandfathers’ but anytime I hear the phrase “this time is different”, I want to run and hide.

Let’s explore. At the peak of the dot-com bubble in March 2000, Information Technology represented approximately 35% of the capitalization-weighted S&P 500. That level of concentration within the S&P 500 was deemed extraordinary at that time. Remember when Cisco Systems was the largest stock in the S&P 500 index? What transpired from March 2000 to October 2002, proved incredibly painful to those investors that believed that “this time was different”. Unfortunately, it wasn’t! The result was a significant reduction in the weight of the technology sector within the S&P 500 from 2000-2002 by an incredible 21.7%. The technology bubble burst took down Tech’s exposure from roughly one-third of the index to about 13% by the 2002 bear-market bottom.

PeriodTechnology weight in S&P 500
1995~10%
March 2000~34.5%
Oct. 2002~12.8%

That leads to today’s discussion comparing March 2000’s Technology exposure versus August 2026’s broader “technology-related” weight when you include Meta, both classes of Alphabet, Amazon, and Tesla. As you can see by the information displayed below, roughly 50% of the S&P 500’s weight is now in technology-related entities.

ComponentS&P 500 weight
Official Information Technology37.15%
Amazon3.84%
Alphabet Class A3.06%
Alphabet Class C2.45%
Meta Platforms1.83%
Tesla1.55%
Broader technology exposure49.88%

In other words, today’s exposure is about 15.4 percentage points higher in technology than at the peak of the dot-com bubble.

However, the exposure to Technology and AI is not limited to the S&P 500 (equities), as massive investment in data centers (real estate) done through significant debt financing (fixed income) might be subjecting a pension plan’s entire asset allocation to significant risks.

Is your portfolio prepared for the next significant market correction?