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The two companies also struck a chip deal.

Retirement readiness in America depends heavily on where a household is located. A 2026 SmartAsset study of Census Bureau data shows the typical household holds roughly $80,000 in tax-advantaged retirement accounts, approximately one year of current income. That national median obscures a striking geographic divide across the country, and the top-ranked state reports a median balance of $150,000 in retirement savings. The bottom-ranked state holds just $35,000, a gap of $115,000 between them. Workplace retirement plan access, not individual behavior, drives most of that disparity.Massachusetts leads while Mississippi trails by $115,000Massachusetts holds the top position among all 40 states with available data, with a median retirement savings balance of $150,000 and a median household income of $104,828, the SmartAsset analysis found.The state’s dominance is not accidental; nearly 75% of Massachusetts households use tax-advantaged retirement accounts, the highest adoption rate in the study, the Census Bureau data showed.At the other end, Mississippi reported median retirement savings of just $35,000 on a median household income of $59,127, with only 41.8% of households using retirement-specific accounts, the lowest participation rate among all states measured.Between those extremes, the pattern is consistent: states where more households use tax-advantaged accounts accumulate significantly more savings, according to the Census Bureau’s Survey of Income and Program Participation data.States with higher workplace plan participation also show larger median balancesMaryland recorded the highest rate of 401(k) and Thrift Savings Plan usage at 65% of households, and its median retirement balance reached $120,000, ranking fifth nationally, the SmartAsset study confirmed.Washington followed closely, with 60.2% of households contributing to 401(k)s or Thrift Savings Plans and a median balance of $143,400, the third-highest nationally, the research showed.Alabama reported just 33.7% of households using 401(k) plans and a median retirement balance of $46,000, while Louisiana’s 401(k) participation stood at 38.3% alongside a $50,000 median balance, the data indicated.More Retirement:Delaying Social Security to a certain age could cost you $144,000Dave Ramsey warns Americans on 401(k)s, IRAs (he’s not wrong)Vanguard reveals health account best for retirementAARP has quantified the scope of this structural barrier at the national level, reporting that roughly 56 million private-sector workers currently lack access to any employer-sponsored retirement plan.”Older Americans consistently tell us they want policies that expand opportunity and help people build financial security over a lifetime,” said Nancy LeaMond, AARP Chief Advocacy and Engagement Officer.

Workplace retirement plan access, not income alone, explains why some states build significantly larger retirement savings than others.Pressmaster/Getty Images

Cost of living complicates the state-by-state pictureHigher savings balances in states such as Hawaii and Washington do not automatically translate into greater purchasing power, because the cost of living in those states is among the highest in the nation.Hawaii reported the second-highest median retirement savings at $149,000, but median home prices hover above $722,000, according to Redfin’s May 2026 data.Washington’s median home price exceeds $612,000 with an overall cost of living roughly 11% above the national average, according to the C2ER Cost of Living Index. This means a $143,400 retirement balance stretches far less than it would in Oklahoma, where median home prices sit near $264,000.Key retirement savings figures by stateMassachusetts: $150,000 median savings, 74.8% account prevalence, $104,828 median incomeHawaii: $149,000 median savings, 65% account prevalence, $100,745 median incomeWashington: $143,400 median savings, 70.3% account prevalence, $99,389 median incomeNew Jersey: $134,000 median savings, 66.7% account prevalence, $104,294 median incomeOklahoma: $39,450 median savings, 47.9% account prevalence, $66,148 median incomeMississippi: $35,000 median savings, 41.8% account prevalence, $59,127 median incomeSource: SmartAsset analysis of U.S. Census Bureau data, published 2026State-facilitated retirement programs aim to close the access gapRecognizing that employer inaction leaves millions of workers without retirement vehicles, 22 states have now enacted state-facilitated retirement savings programs for private-sector workers, the Georgetown University Center for Retirement Initiatives reported as of mid-2026.Nancy LeaMond, AARP Chief Advocacy and Engagement Officer, noted that simplified automatic enrollment drives higher retirement participation.These programs show that when saving for retirement is easy and automatic, people do itThese programs typically use automatic payroll deduction to enroll workers whose employers do not offer a 401(k) or similar plan, and nearly 1.2 million employees had enrolled in state “work and save” programs as of January 2026, AARP reported.”Expanding access to retirement savings accounts directly advances these goals,” LeaMond wrote in a letter to administration leaders earlier this year, urging national adoption of the model that state programs have tested.Census data reveals the first hurdle is the account itselfThe AARP 2026 Financial Security Trends Survey found that 42% of Americans aged 50 and older who have not yet retired reported having less than $50,000 in retirement savings, while 60% expressed concern about having enough money to last through their post-working years.”With prices rising for everyday essentials like groceries, housing, utilities and health care, current and future retirees are counting on Social Security now more than ever,” LeaMond noted in the survey findings.Among the bottom 10 states in the SmartAsset rankings, retirement account prevalence averaged below 50%, meaning that more than half of households in those states did not use any tax-advantaged retirement account at all.The national conversation around retirement readiness tends to focus on contribution rates and investment returns, but the Census Bureau’s state-by-state breakdown points to a prior question raised by AARP and Georgetown researchers: whether workers have access to a tax-advantaged account at all.Related: Medicare’s costliest gap threatens retirement savings

A regular S&P 500 index fund gives you the market’s return. A 3x leveraged ETF promises three times that. If the market averages 10% a year, triple sounds like a shortcut to retiring a decade early.

That’s not what these funds deliver, and the reason is a single word buried in every leveraged ETF’s prospectus.

What a Leveraged ETF Is

A leveraged ETF is a type of exchange-traded fund that aims to amplify the daily return of an index or stock. For example, a 2x S&P 500 ETF seeks to gain about 2% when the S&P 500 rises 1% in a day. A 3x fund aims for about 3%. There are also inverse leveraged ETFs designed to rise when the market falls.

To achieve those amplified returns, these funds use complex financial instruments such as swaps and futures rather than simply owning the underlying investments. That structure allows them to magnify gains, but it also magnifies losses and creates risks that don’t exist with traditional index funds.

These products have exploded in popularity. Leveraged ETFs now hold roughly $198 billion in assets, and some of the largest trade hundreds of millions of shares each day. In the United States, leveraged ETFs generally top out at 3x exposure for broad indexes and 2x for individual stocks.

The Word Is “Daily”

Every leveraged ETF’s prospectus says the fund seeks a multiple of its index’s daily return. Not its annual return. Not its return over whatever period you plan to hold it. Its return each day, with the fund resetting its leverage every night.

That one word changes what you own. A regular index fund doesn’t care what route the market takes to a destination. If the S&P 500 ends the year up 10%, you’re up 10%, whether the ride was smooth or a rollercoaster. A leveraged fund’s return depends on both the destination and the route. Because it multiplies each day’s move and then compounds from the new balance, two paths that end at the same place can produce very different results in the fund.

Markets zigzag even in good years. Every zigzag takes a small bite out of a leveraged fund, and the bites add up.

What One Zigzag Costs

Here’s the smallest possible zigzag. An index starts at 100. On Monday it rises 10%, so it gains 10 points and closes at 110. On Tuesday it falls 10%. But Tuesday’s 10% comes off the new, higher number: 10% of 110 is 11 points, so the index closes at 99. Over two days, the index lost 1%.

Now run the same two days in a 3x fund, which triples each daily move. Monday it gains 30%, going from 100 to 130. Tuesday it loses 30%, and again the percentage comes off the higher number: 30% of 130 is 39 points, dropping the fund from 130 to 91. The index lost 1%. The 3x fund lost 9%.

Notice what happened. The bigger Monday’s gain, the more dollars Tuesday’s identical percentage drop takes away. At 1x, that mismatch cost the index 1 point. At 3x, the gain and the loss were both tripled, and the mismatch tripled twice over, costing 9 points.

The fund lost nine times more than the index. That’s not a fluke of this example. It’s the built-in nature of a leveraged loss: every drop gets tripled, and every drop lands on a balance the previous gain inflated. Stretch that effect across the hundreds of up-and-down days in a typical year and you get what the industry calls volatility decay. In a volatile market where the index ultimately finishes flat, a 3x fund can still lose a meaningful amount because of volatility decay.

The market doesn’t even have to end flat or down to lose money in a 3X ETF. In a choppy year where the index gains 6.5%, a 3x fund can still finish with a loss. You can be underwater in a year when everyone around you made money.

Why They Look Like Free Money Right Now

In a smooth, steady uptrend, leveraged funds don’t just work; they outperform their own promise. When the market rises day after day with few pullbacks, the daily compounding works in the fund’s favor, and a 3x fund can return more than 3 times the index.

That’s been the recent story. Semiconductor and tech-focused 3x funds were up more than 300% at the time of this writing, powered by an AI-driven rally with unusually few down days. Anyone holding them looks like a genius, and their brokerage screenshots are all over social media.

The same math that supercharged those returns in a trend is what destroys them in chop. The market decides which one you get, and it doesn’t announce the switch in advance.

The Drawdown Math

Leverage multiplies losses the same way it multiplies gains, and losses are harder to climb out of. Wes Moss, a fiduciary financial advisor and host of Ask an Advisor on the Clark Howard Podcast, says that’s the core danger.

“These funds can rack up massive losses in a single day, and the arithmetic of loss means climbing back out takes an even bigger gain just to break even,” Wes says.

A 33% single-day drop in an index would theoretically take a 3x fund to zero. Circuit breakers make a one-day wipeout unlikely for broad indexes, but fast multi-day declines do nearly the same damage. In past sector downturns, 3x funds have lost more than 90% of their value. Recovering from a 90% loss requires a 900% gain. Some leveraged funds that existed before the 2008 financial crisis or the 2022 tech decline never got back to their old highs, even after the underlying indexes fully recovered.

The Costs You Don’t See

Leveraged ETFs typically charge expense ratios of 0.75% to 1.00%, roughly 20 to 30 times what you’d pay for a broad index fund. On top of that, the funds pay financing costs on the swaps that create the leverage, and those costs are baked into the returns rather than listed as a fee. Higher interest rates make that drag bigger.

Trading Tools, Not Investments

The fund companies themselves state in their prospectuses and marketing materials that these products are designed for daily trading objectives and that investors who hold them longer should not expect the stated multiple of the index’s return. These are trading instruments built for professionals who manage positions by the day, not investments to buy and hold.

Wes draws the same line, explaining, “I’ve never been a fan of double or triple leveraged ETFs, and I say the same thing to a family I work with as I would to a buddy on the golf course: Triple leveraged ETFs are built for traders, not long-term investors. They reset daily, so the path the market takes matters as much as where it ends up.”

That puts them squarely outside the approach money expert Clark Howard has recommended for decades:

Buy low-cost index funds

Add money steadily

Hold for the long term

Everything about a leveraged ETF works against that strategy. The costs are high, the holding period is measured in days, and the outcome depends on short-term market paths that nobody can predict.

Wes lands where Clark does. “There’s already plenty of risk in the stock market,” he says. “I don’t need to go looking for more with the use of excessive leverage.”

What To Do Instead

The appeal of leveraged ETFs is usually a desire to reach a goal faster. There are better tools for that.

Raise your savings rate. Adding more to a boring index fund is a guaranteed multiplier. Leverage is not.

Check your asset allocation. If you’re young with a long horizon, holding more stocks and fewer bonds gives you more market exposure without the daily reset problem.

If you must speculate, cap it. Limit any trading money to 5% or less of your portfolio, in an account separate from your retirement savings, and treat losses as the cost of the lesson.

Leave leveraged ETFs to day traders. If your holding period is longer than a few days, these products are not built for you, and the companies that sell them say so themselves.

Final Thoughts

Leveraged ETFs are doing exactly what they’re designed to do. The catch is that they’re designed for daily trading, not long-term investing. If your goal is building wealth over years or decades, you’re much more likely to succeed by consistently investing in low-cost index funds than by trying to amplify short-term market moves.
The post ETFs That Give You 3X The Market Returns? Not So Fast appeared first on Clark Howard.

Lawmakers have circulated text of the latest draft that will be pushed toward a Senate finish line, but they’re still debating a core government-ethics piece.

Micron Technology (MU) stock investors had plenty of reason to expect another ‘DeepSeek moment’ following the launch of Kimi K3.The concerns weren’t new, though, and pretty straightforward.Cost-effective, more efficient AI could weaken demand for the expensive hardware powering the boom. Wall Street was questioning the relentless AI spending cycle, but in a note shared with me, Bank of America moved in the opposite direction.The bank reiterated its Buy rating and $1,550 price target on Micron, arguing the latest AI disruption doesn’t break the memory thesis.Instead, BofA sees the market focusing on the wrong part of the equation.

Micron Technology logo at a semiconductor facility as Bank of America reiterates its bullish Micron stock outlook following the Kimi K3 AI launch Kyle Green/Bloomberg via Getty Images

Kimi K3 raises the stakes in the AI raceAccording to Wikipedia, Chinese AI startup Moonshot AI, which launched Kimi K3 on July 16, was viewed as a major escalation in the country’s push to narrow the gap with U.S. AI developers. More AI:Workers just sent AI companies an ultimatumPalantir CEO has a blunt verdict on OpenAI and AnthropicElon Musk pulls no punches with AI rivals as Grok 4.5 debutsReuters described Kimi K3 as the world’s largest open-weight AI model, with Moonshot claiming it has 2.8 trillion parameters, a 1 million-token context window, and capabilities designed for coding, knowledge work, and deep reasoning.What stood out was Kimi efficiently combining frontier-level performance claims with open weights and considerably lower deployment costs than most of its Western alternatives. Users can download, customize, and operate the model according to their specific requirements rather than relying on closed APIs. On top of that, the release underscored how China’s open-model ecosystem is rapidly advancing, increasing competitive pressure on OpenAI and Anthropic while potentially broadening demand for the chips, memory, and storage needed to run powerful models.Interestingly, as I recently covered, Microsoft CEO Satya Nadella has been sounding the alarm over customers effectively paying AI companies twice, indirectly supporting the rationale behind Kimi K3’s open-weight release. Businesses can eventually deploy models privately while retaining greater control over prompts, corrections, and workflows that create institutional knowledge. Why does BofA think Kimi’s efficiency still increases memory demand? BofA’s argument hinges on separating compute efficiency and memory capacity.For perspective, Kimi K3 is a 2.8 trillion-parameter mixture-of-experts model, but it activates roughly 50 billion parameters per token, or roughly 1.8% of the total. Naturally, that substantially reduces the amount of computation needed for inference.However, it hardly has an impact on the entire expert pool needed in fast memory.BofA estimates Kimi K3 still requires about 1.4 TB of HBM at native MXFP4 precision and at least 64 accelerators per serving instance. In comparison, OpenAI’s 120-billion-parameter open model needs around 63 GB (roughly 23 times lower).The broader trend is perhaps even more important. DeepSeek V3 had 671 billion parameters, Kimi K2 reached 1 trillion, DeepSeek V4 Pro rose to 1.6 trillion, and Kimi K3 reached 2.8 trillion. Compression can reduce memory per parameter by 50%, but model sizes are growing almost in tandem. That means, even though efficiency per computation is rising, things are getting a lot more memory-intensive per deployment.What happened to U.S. tech stocks?DeepSeek and Kimi K3 sparked similar “China AI shock” moments, sending shockwaves through U.S. tech stocks. When DeepSeek’s R1 gained attention in January 2025, AI poster childNvidia (NVDA) plummeted 17%, losing $589 billion in one session, according to Yahoo Finance, while AI-linked chip, power, and infrastructure stocks collectively lost over $1 trillion.Kimi K3 stoked those fears in July 2026. On July 17, according to Investopedia reporting, the Nasdaq fell 1.4%, the S&P 500 lost 1.01%, and the semiconductor index slid 1.6%, as geopolitical tensions pressured stocks and the market entered a bear market.Why could open-weight AI expand Micron’s addressable market?BofA feels open-weight models are a multiplier for memory demand, as they effectively shift infrastructure ownership from a handful of hyperscalers to thousands of individual users.If users opt for self-hosting models such as Kimi or DeepSeek, they must provision for a tremendous amount of memory.That switches up the economics of the market. An enterprise deployment needs roughly 80 GB of HBM3E; a DeepSeek V3 cluster might require roughly 1.1 TB, and each Kimi K3 instance entails a 64-plus-accelerator system. Ten thousand customers making use of one closed API might share a limited number of model copies. Ten thousand self-hosted deployments create ten thousand separate memory endpoints.The benefit extends beyond HBM. Hot weights sit in HBM; inactive experts spill into DDR5 or LPDDR5X, while cold KV cache and model files shift into enterprise NAND. Context windows between 128,000 and 1 million tokens can push KV-cache requirements above 40 GB per active session.Cheaper pricing increases usage. BofA says global token volume jumped from about 9% per week in 2026, while multi-agent workloads can generate nearly 200,000 output tokens per query versus 200 for basic chat.What does Bank of America think Micron is worth? According to Seeking Alpha, Micron stock is currently trading at $970.82, which means BofA’s $1,550 price target implies approximately 60% upside.BofA used a sum-of-the-parts valuation, which includes the following:$1,040 per share for Micron’s traditional cyclical memory business, valued at 3 times estimated calendar-2028 book valueAn AI HBM component valued at 31 times calendar-2028 earnings, in line with the median AI compute peer multiple..By subtraction, the HBM component accounts for roughly $510 of the $1,550 price target, although BofA doesn’t separately state that figure.BofA also states that Micron’s CHIPS Act-related buyback restrictions are expected to expire around December 2026. Against its projected $120 billion to $130 billion-plusfree cash flow outlook, the bank estimates a 40% payout policy to support $50 billion to $60 billion in share buybacks, equivalent to around 4.5% to 5.3% of the current market cap.Despite its nosebleed valuation, Micron stock is still trading at 13.2 times forward non-GAAP earnings, 46% lower than the sector median and 82% lower than its 5-year average, according to Seeking Alpha.Related: Microsoft CEO’s Anthropic criticism reveals bigger AI power struggle

The company reported strong 2025 performance, with a $2.3 billion pre-tax profit, $6 billion in revenue, and over 75 million customers.

“We live in a house that I purchased entirely with money I had before we were married.”

The commissioner said onchain vaults and lending strategies could resemble investment funds or advisers, depending on how they are structured.

Experts say Britain’s digital gilt pilot can unlock trapped liquidity in financial markets only if regulators approve an onchain stablecoin.

Future debuts The Real Me atop the Billboard 200, earning his twelfth No. 1 album. He now claims the fifth-most champions of all time.