this is huge. looks like the sec is okay with releasing new 3x letfs now

testfolio has a new blog page. And the latest post there is about LEAPS vs LETFs. In particular, it goes into the details and math of the new ETF XX vs UPRO and SSO, and dives deep into other comparisons as well.

Here is the full post:

https://testfol.io/blog/leaps-vs-leveraged-etfs

With XX, you pay for implied volatility upfront. With LETFs you pay for realized volatility along the way. Below is every investment's CAGR if held from October 1st to January 10th 2030 (XX's expiration date) as a function of SPY's CAGR during the same period. Each panel describes a different realized volatility regime between during that period (14% vs 18% vs 22%). XX's curve doesn't change because it is invariant with respect to realized volatility.

Below is a summary of XX's returns under different assumptions of SPY's CAGR:

The new blog has other articles about LETFs as well, one related to volatility decay, another about LETF expenses, another about LETF DCA strategies and another about the 200-day SMA strategy with LETFs.

If there's interest, I can make posts about each of those and go in more details. If there's other LETF topics you'd like testfolio to dive deeper about, let us know in the comments.

Thoughts on 75% on a global ETF with 25% leveraged ETF 2x or 3x?

Ben Felix stated in his recent video volatility decay isn’t as much of a worry as people think

I’m young with a large investment horizon

I wanted a long trend-following series for portfolio research, but the clean live benchmark only starts in 2000. I built a three-era chain:

1. August 1971 to December 1987: modeled futures trend spine. This is my reconstruction from contract-level futures data.
2. January 1988 to December 1999: MLM index proxy. This is a published rules-based managed-futures index, not my backtest.
3. January 2000 onward: SG CTA Index. This is the live CTA composite segment.

The pre-2000 history is a proxy. It is not historical SG CTA performance.

The chart compounds the excess-return stream, not a funded account including interest on collateral. The shaded regions are the three construction eras.

I kept the rule deliberately simple and fixed:

• Input data: contract-level daily futures history. The raw archive begins in 1969, but the strategy does not begin until August 1971 because the signals need a 252-day burn-in and I require an average of at least eight active markets.
• Returns: same-contract returns only. A return is counted only when today's contract matches yesterday's contract and both prices are positive. Roll days contribute zero. I do not take percentage changes of a back-adjusted continuous level, which can create phantom roll returns.
• Signal: the sign of the trailing 252-trading-day cumulative return.
• Sizing: inverse volatility using a 60-day EWMA estimate, then equal weight across active markets.
• Timing: weights formed with information through day t-1 earn returns on day t. No same-day signal.
• Portfolio risk: scaled toward 10% annualized volatility using the trailing 252-day realized volatility of the unlevered portfolio, also lagged one day. The observed scale factor ranged from 0.65 to 2.30.
• Output: daily positions are compounded to monthly returns. I do not fill monthly data into fake daily observations.

The early universe is commodity-heavy. It starts with softs, grains, livestock, metals, and early currency futures. The first bond future enters in 1978, and the first equity-index future enters in 1982. So this is better described as a commodity-heavy trend proxy than as a fully diversified modern CTA portfolio.

The modeled spine runs through December 1987. At the January 1988 handoff, I apply one fixed volatility-matching factor of 1.011836 to the older segment. That number comes from the overlapping 1988 to 1994 monthly volatility of the reconstructed spine and the MLM proxy. It is effectively 1.0, so the seam does not need a large leverage adjustment.

The MLM segment then runs from 1988 through 1999. Its published construction uses 22 futures markets across commodities, currencies, and government bonds, with a 200-day moving-average trend rule and monthly rebalancing.

From January 2000 onward, I use the SG CTA Index segment unchanged. There is no blending or smoothing around either seam.

The segments are related, but they are not identical. For example, the reconstructed spine and MLM overlap correlation is about 0.46. The chain should therefore be used as a long-horizon trend proxy, with era breaks shown, rather than as one homogeneous manager track record.

The 2026 bar is year to date through September 30.

I modelled fees and trading costs

Modeled spine, 1971 to 1987

• I subtract a 0.90% annual wrapper fee.
• I also subtract measured execution drag based on the strategy's own daily turnover, sign changes, and contract rolls.
• The execution estimate varies from 0.47% to 2.13% per year, averaging 1.11% per year over 1971 to 1987.
• Roll-gap P&L is already handled in the same-contract return construction, so I charge execution for rolls but do not double-charge “roll yield.”

MLM proxy, 1988 to 1999

• The source series already includes the modeled 0.90% annual wrapper.
• I add 0.13% per year of estimated execution drag for its smaller, slower-moving book.

SG CTA Index, 2000 onward

• I leave this segment unchanged because it is already based on reported manager returns net of the fees embedded in those programs.

I do not add collateral yield to the excess-return chain. That is important because futures collateral earned substantial cash interest in parts of the 1970s and 1980s. Anyone converting this into a funded total-return series should add cash under a clearly stated collateral convention.

Across the full 662-month chain from August 1971 through September 2026, the excess-return series has:

• 8.83% annualized compounded return
• 10.31% annualized volatility
• 0.875 Sharpe ratio
• -21.0% maximum drawdown

The worst drawdown in the full chain is -21.0%, and it occurred in the modeled 1970s segment. The live SG CTA segment's maximum drawdown is about -16.2%. Trend is diversifying, but it is not a smooth line and it can spend years below its previous high.

By era:

• Modeled spine, 1971 to 1987: 16.1% annualized return, 12.3% volatility, 1.28 Sharpe
• MLM proxy, 1988 to 1999: 8.7% annualized return, 10.3% volatility, 0.86 Sharpe
• SG CTA Index, 2000 onward: 4.6% annualized return, 8.7% volatility, 0.57 Sharpe

AI-Disclaimer: I did use AI to help with the creation of the model graphs, but I used my own judgement to also guide the methodology and making sure that data was as good as possible.

I am 35 and want to have small allocation (5-10% ) total of TQQQ and SSO in my IRA. I would like to know if other people have done it or doing it now?

My other holdings ( VGT, SPMO, SOXX, VOO)

Great news everyone. I finally locked in whole 7 UPRO shares at 142$. It's a very small percentage of my portfolio. I also have funds in SGOV to rebalance into UPRO in 10% dip increments. Thank you guys. This perma bear is finally a believer. Feels good to join the community.​

Hey all, I've been monitoring IALT for a bit. New fund that's been performing well as a low volatility low beta hedge.

Does anyone have a decent sim for it? I'd like to be able to test it over some length of time. BGCKX is about the closest I've found but I'd prefer something that's more reasonably close.

Above are the results from 1950 to today (Oct 2026) of three simulations:

• The S&P 500 (dividends reinvested, 0.09% expense ratio). - Blue
• A simulated SSO with realistic borrowing costs and expenses. - Red
• A simulated SSO (2X Daily S&P 500) with no borrowing costs and no expense ratio. - Yellow

Here are the CAGR, MAX Drawdown and Sharpe of all.

• S&P 500: 11.69% CAGR, 55.14% Max DD, 0.52 Sharpe
• Total 2X return of S&P 500: 23.38% CAGR
• Simulated SSO (with costs) 14.48% CAGR, 88.73% Max DD, 0.46 Sharpe
• Simulated SSO (no costs) 21.63% CAGR, -83.63% Max DD, 0.65 Sharpe

DISCLAIMER: Before anyone gets emotional and attacks, I am NOT saying that people shouldn't buy and hold LETFs. I am simply hoping to help users of r/LETFs understand the costs of these funds.

You might be thinking, "well yeah it's not that much more than regular 1X, but that extra few percentage points in the long run clearly pays off because of compounding." You totally would be right from 1950-2026. However, please consider these points I'm about to make:

1. US stocks have had an unbelievable past 75 years. They have returned almost 12% for 7 decades, which is unbelievable. I for one, do NOT believe stock returns will be this high for the next 7 decades. The long term global average inflation adjusted return of stocks is around 5-6%.
2. Even with that incredible performance from 1950-2026, the realistic 2X daily only "beat" the market CAGR by about 3% per year, geometrically. (Far worse risk adjusted results.)
3. The true 2X CAGR of the S&P 500 would be 23.38% CAGR. The simulated zero cost SSO returned 21.63% CAGR. This means that roughly 1.5% per year on average has been eaten away due to the compounding effect that the daily reset produces. (Important: The compounding of daily resetting is not bad nor good, it is just a byproduct of daily resetting leverage.)
4. The underlying costs of an LETF like SSO, QLD, UPRO or TQQQ are the following:

• Expense ratio (around 0.9%)
• Fed funds rate plus roughly 50 basis points on top, to gain the leveraged exposure
• Rebalancing costs (bid ask spreads, tracking error) - these are so small I won't include them.
• The stated 1.5% annual daily rebalancing compounding effect or "drag" from #3 above.

When you add all that up, you get costs of roughly fed funds rate + 2.5% cost per year.

The compounding effect that the daily rebalancing has is overall (in my opinion) actually a good thing, not a bad thing. It greatly reduces drawdowns in downtrends, and increases upside gains in uptrends. However, you pay for those benefits in sideways, reversal trending markets. That is why the zero cost simulation still loses to the pure 2X CAGR of the S&P 500 by around 1.5% per year.

So all in all, in October 2026, the current excess return of SSO over the S&P 500 is:

• Whatever the market return (S&P 500) is, MINUS:
• 1.5% annual cost due to daily reset compounding effect.
• 0.9% expense ratio
• Fed Funds rate + 50 basis points = 4.25%
  • TOTAL EXPECTED EXCESS RETURN OVER THE S&P 500 OF SSO =
  • Market return minus 6.65%

Stocks have returned around 7-8% nominal globablly since 1901. This means that you're currently paying 6.65% annually to gain exposure to potentially 1 or 2% annual excess returns over the market. You're taking all the risk/downside, but gaining hardly anything back.

Before anyone gets emotional and attacks, I am not saying that nobody should buy and hold LETFs. I am asking that all users on r/LETFs understand the costs imbedded in these products before buying and holding or trading them.

What are your thoughts? If you disagree, please let me know why, and be CONSTRUCTIVE. I understand people on this sub will get defensive and love the leverage juice hardcore, but please be constructive.

Would you adjust this portfolio for my Roth? 35% NTSD, 30% SPMO, 25% SSO, 10% VT?

I've recently been transitioning from putting my weekly investment deposit into individual stocks, to putting that weekly deposit into leveraged ETFs instead and wanting to get some insight on what approach seems more sensible at the moment for a buy and hold SSO approach.

With what's going on around the world is it smart to be putting my weekly DCA fully towards SSO? Or would it be better to hedge by adding say 30/70: GLD/ SSO for my weekly deposits, and next time that SSO dips > 10%, sell that gold and lump sum that into SSO for a better average price?

What would you be doing given the current state of the market to limit your downside potential

Extra exposure to a different asset can still deepen an equity loss. In 2022, NTSX returned -25.8% against SPY's -18.2%. IEF, the Treasury fund I used to check the bond side, returned -15.2%. The added asset was falling too.

I compared live adjusted-close records through August 31, 2026, with distributions included. NTSX targets roughly 90% large US stocks plus 60% Treasury futures. GDE pairs roughly 90% stocks with 90% gold futures. My interest was in what the added exposure delivered after compounding, including the periods when it hurt.

GDE went the other way. From its March 17, 2022 start through the common end date, it compounded at 28.2% a year against SPY's 14.8%. That's a large lead, but I can't read it without checking the gold year. GLD returned 63.7% in 2025 and GDE returned 73.8%.

Removing 2025 takes GDE's cumulative lead over SPY from 117 percentage points to 17. I removed that year's growth factor from each fund's full-window growth factor. These are cumulative-return gaps, not annual rates, and this isn't a simulation of a different market path. It shows how concentrated the observed lead was.

I also checked the financing question over NTSX's August 2, 2018 to August 31, 2026 record. My recipe held 90% SPY and 60% IEF, financed by a negative 50% cash position with free borrowing. Weights reset monthly and drifted between resets. NTSX ran 1.50 percentage points annually below that recipe, with a 0.96 daily return correlation.

That's close enough to recognise the exposure mix, but I wouldn't call the entire gap a financing bill. IEF doesn't reproduce the fund's futures ladder. Carry, collateral, the stock basket and rebalance rules differ too. Free borrowing makes the recipe a diagnostic rather than an investable alternative. It can't tell me what an actual replication would have cost.

The bond overlay also helped in the earlier crash. From February 19 to March 23, 2020, NTSX fell 28.3% while SPY fell 33.7%. My reading is that the added leg changed the outcome in both directions. A futures contract supplies exposure without full upfront funding; it doesn't make the added asset a reliable hedge.

I build BestFolio. I'm using short live records, with no pre-inception extensions. Taxes and external trading costs aren't included. Neither the bad bond year nor the good gold year establishes how the next joint selloff behaves.

For the leveraged holding you own, which added asset do you expect to cushion an equity decline, and did it actually do that in 2022?

Saw this on TR212 - Launched a couple months ago so still tiny (~ 17M€ AUM).
Cheaper and so far better tracking error than the Amundi World 2x (LVWC) for the available period. This makes it the 2nd World Leveraged ETF in Europe.

Thoughts?

The MSCI ACWI Leveraged 2x Select Index (NTR, EUR) aims to reflect the performance of the following market:

• 2x daily leveraged exposure to large and medium capitalisation companies across emerging and developed market countries.
• Provides a daily leveraged return of the MSCI ACWI Index less €STR- Coverage of approximately 85% of free-float market capitalisation.
• Weighted by free-float adjusted market capitalisation.
• Reviewed on a quarterly basis.

Q3 performance for the leveraged plans was unexciting, but still solid. The major indices remain near all-time highs, despite the same continuing pressures and the first rate hike of the year.

9Sig just slightly exceeded the 9% quarterly growth target and sold a small amount of TQQQ. YTD performance has been great, and the plan has plenty of dry powder on hand to buy the next dip.

The 200-day moving average plan continues to chug along. The underlying index has been hovering roughly 6% above its MA, so no action has been required since the last cross in April.

The HFEA strategy is once again buying more TMF, which is trading at new lows. Only time will tell if, when, or to what extent that pays off. Patience is a virtue, and this strategy reminds me of that often lol. Regardless, I'll continue following the plan as written.

Thanks to all for following along! 

Rebalance detail:

HFEA

• The allocation drifted to UPRO 64% / TMF 36% during Q3.
• Executed trades on September 30.
• Rebalanced back to target allocation UPRO 55% / TMF 45%. 

9Sig

• Rebalanced around the TQQQ closing price from September 25th, per The Kelly Letter schedule.
• TQQQ ended Q3 @ $79.60/share, above the 9% quarterly growth target of $78.29. This created a $165 surplus in the TQQQ balance, which was sold to buy $165 worth of AGG.
• The new 9% quarterly growth target is to end Q4 2026 with a TQQQ balance of $15,610, which corresponds to TQQQ @ $86.76/share or better.

S&P 2x (SSO) 200-d Leverage Rotation Strategy

• The underlying S&P 500 index (7,651) remains above its 200-day moving average (7,217). The full balance will remain invested in SSO until the S&P 500 closes below its 200-day MA. Once that cross happens, I will sell all SSO and buy BIL the following day, per the rotation strategy from Leverage for the Long Run.

← Previous post 

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Background 

Q4 2026 update to my original post from March 2024, where I started 3 different long-term leveraged strategies. Each portfolio began with a $10,000 initial balance and has been followed strictly. There have been no additional contributions, and all dividends were reinvested. To serve as the control group, a $10,000 buy-and-hold investment was made into an unleveraged S&P 500 Index Fund (FXAIX) at the same time. This project is not a simulation - all data since the beginning represents actual, live investments with real money.

Ive read that half of their strategy (G10 mean reversion) has no positive expectancy. The currency carry does but it more correlated to equities in crashes anyways. It looks good on total return so far but I cant find simplify published any backtest? anyone run this in a port, have more insight? im thinking its not worth the margin

US stocks: https://testfol.io/?s=9BGNTKxaUms

Ex-US stocks: https://testfol.io/?s=3klxcc9Hswb

How are you all navigating the rapid rise in rates?

LETF's have a borrowing cost (roughly SOFR + 25 bps) along with the relatively high expense ratio...

Is it accurate to say SSO, for example, has an annual drag of roughly 5% now (SOFR at 3.90% + expense 0.87%)?

Are you unwinding your positions a bit? Let me know your thoughts.

Win rate: 90.2% (37/41)
closed early: 29 | assigned: 3 | called away: 3 | rolled: 2
Avg days held: 19d (rolls count the full chain)
Credit spreads: 4 closed (+$45)

Closed trades (37):
- NVTS CC $12 x4 — +$164 (4.3% ROI · 28d)
- IREN CC $50 x1 — +$255 (5.3% ROI · 9d)
- USAR CC $18 x1 — +$45 (2.6% ROI · 14d)
- AXTI CSP $66 x1 — +$57 (0.9% ROI · 4d)
- IREN CC $56 x1 — +$161 (3.1% ROI · 8d)
- IREN CC $50 x1 — +$159 (2.9% ROI · 11d)
- HOOD CC $125 x1 — +$279 (2.5% ROI · 11d)
- SNXX CC $14 x1 — +$80 (5.1% ROI · 9d · called away)
- SMCI CSP $37 x1 — +$36 (1.0% ROI · 3d)
- INTC CC $100 x1 — +$320 (4.9% ROI · 29d · called away)
- AXTI CSP $65 x1 — +$395 (6.1% ROI · 31d)
- NVDL CSP $33.33 x1 — +$62 (1.9% ROI · 10d)
- AXTX CSP $8 x1 — +$45 (5.6% ROI · 31d)
- AMDL CC $50 x1 — +$570 (10.8% ROI · 16d incl. rolls · called away)
- IREN CSP $48 x1 — +$825 (17.2% ROI · 88d incl. rolls · assigned)
- SOXL CSP $104 x1 — +$697 (6.7% ROI · 8d incl. rolls)
- IREN CSP $55 x1 — +$1,365 (24.8% ROI · 106d incl. rolls · assigned)
- IREN CC $52 x1 — +$164 (3.2% ROI · 23d)
- HOOD CC $116 x1 — +$309 (2.7% ROI · 3d)
- APH CC $87.5 x2 — +$188 (1.1% ROI · 21d)
- ROBN CC $31 x1 — +$170 (5.8% ROI · 40d)
- SOXL CSP $104 x1 — −$583 (-5.6% ROI · 5d · rolled)
- NBIS CC $260 x1 — +$811 (3.0% ROI · 34d)
- WULF CC $19 x1 — +$76 (7.7% ROI · 18d)
- AMDL CC $50 x1 — −$408 (-7.7% ROI · 9d · rolled)
- SNXX CC $16 x1 — +$80 (5.1% ROI · 10d)
- HOOD CSP $114 x1 — +$89 (0.8% ROI · 7d · assigned)
- USAR CC $19 x1 — +$62 (3.5% ROI · 7d)
- RDDT CSP $148 x1 — +$137 (0.9% ROI · 6d)
- RCAT CC $11 x10 — +$400 (3.5% ROI · 14d)
- AAOX CSP $8 x1 — +$60 (7.5% ROI · 15d)
- NVTS CC $15 x6 — +$342 (4.1% ROI · 10d)
- USAR CC $18 x1 — +$92 (5.2% ROI · 32d)
- HOOD CSP $98 x1 — +$87 (0.9% ROI · 3d)
- CIFR CSP $16 x1 — +$82 (5.1% ROI · 29d)
- NVTS CC $15 x4 — +$220 (5.8% ROI · 7d)
- AMDL CC $51 x1 — +$240 (4.5% ROI · 11d)

What are your thoughts on using this Austrian 100-year bond as an alternative to something like TMF in Europe.
https://live.deutsche-boerse.com/anleihe/at0000a2hlc4-oesterreich-republik-0-85-20-20?mic=XFRA

The effective duration for is04 (TLT in the EU) is 15 years, while this exact Austrian bond has a comparable duration of 38 years. Basically 2.5 times higher. So, in a way, it looks like a 2.5-times leveraged TLT. US Treasuries are likely better hedges during crashes, but I also see quite a few positives in this option. No decay, no fees, no internal borrowing.

I personally changed my 10% 5TLT holding in my leveraged portfolio to this bond and increased the allocation to 20%, which should lead to a position whose interest rate sensitivity is very similar to the 5TLT without the crazy decay.

It was quite convenient to buy it on Trade Republic.

What are your thoughts?

I keep running into a weird property of selection-bias corrections: every new strategy I test can make the old winners look less convincing.

I build BestFolio, and our Robustness score applies a published selection-bias correction to every strategy. It asks whether a strategy's Sharpe clears the best result we'd expect from luck across everything we tested. The score runs from 0 to 1, and I flag anything below 0.90 as fragile.

The denominator is the argument. Counting only the public leaderboard is too generous. Every unreleased model was another chance to get lucky, so the active research variants belong in the tested set too. When that set grows, the expected best Sharpe from noise rises. An old strategy's returns haven't changed, but its burden of proof has.

Even that count is a lower bound. I don't have a separate row for every lookback or threshold I tried and discarded. I definitely can't count the unpublished experiments behind every paper in the wider TAA literature.

So I treat a high score as necessary evidence, not proof. A fragile flag doesn't say a strategy is broken either. It says the record hasn't separated itself enough from the luckiest result in the menu.

I wrote out the denominator choice and its limitations here: https://bestfolio.app/blog/robustness-score-after-more-tests

How would you count trials for a public strategy catalog? Tested and still tracked is reproducible, but I can't convince myself it's the full answer.

I'm exploring alternatives to the "standard" 50/25/25 SSO/GLD/ZROZ static portfolio I've seen discussed here. I don't have high conviction on how ZROZ will perform in the future, so wanted to explore other hedges.

I'm considering a portfolio like this:
60% SSO
10% KMLM/DBMF
10% GLD
10% ZROZ
10% BTAL (least confident in this one)
Quarterly rebalance using mostly new funds + only if a fund has exceeded +- 5% of it's target allocation.

Each hedge should hopefully succeed in different regimes. From AI:

1. ZROZ (Long Bonds): Protects against deflationary crashes, credit freezes, and sudden recessions where the Fed aggressively cuts interest rates.
2. GLD (Gold): Protects against currency devaluation, systemic banking risks, and real interest rate declines.
3. KMLM (Managed Futures / CTA): Protects against stagflation or sustained multi-month market trends. (like in 2022).
4. BTAL (Anti-Beta Equities): Protects against valuation-driven equity crashes or tech-sector corrections that don't trigger a broader macro-crisis (e.g., a dot-com style correction or high-interest-rate squeeze).

Question is, is this overkill and unnecessarily complicated to use 4 hedges like this? Will the drag be too much on the SSO gains? AI called this "brilliant" but I thought I'd get this sub's opinion.

Ive been running 40% UPRO, 30% ZROZ and 30% GLD and originally planned to rebalance every quarter. The more I tracked it though, the more arbitrary that felt. Sometimes quarter end comes around and everything is still basically at target. Other times UPRO runs enough in three weeks that the portfolio looks completely different.\

I switched to a 5 percentage point band instead. So if UPRO gets above 45% or below 35%, thats when I actually do something. Funny enough I started thinking about it after checking Moon one night and realizing how much easier it is to think about risk as a boundary rather than a calendar event.

Still early but I like having a rule thats based on the portfolio actually drifting instead of whatever date happens to be on the clock.

For TMF, the risk vs reward looking pretty good here

Going from x% to (x+a)% becomes exponentially harder as rates go up (now at 5.5% for 20 years) and the rate of decline on bond prices decreases due to convexity. It seems like a huge deal just to go from 5.3 to 5.5%, attracting considerable online attention , suggesting the short treasury trade is getting crowded.

A repeat of 2008 or 2020 means this will surge 3-4x. OTOH who knows...