I personally like CTA style trend following strategies but generally advise people who are not very familiar against that exposure. If you think about leverage in percentage terms and not eg in volatility units I would be a bit nervous.
Levered risk parity (bonds + equities) can get very spicy if correlations break (eg high inflation), but it has worked well in the secular declining rates environment from the 80s to 2010s.
I think Corey Hoffstein’s work and podcast are great!
Executive summary: The author argues that return stacked ETFs are a promising, lower-cost way for altruists to obtain leveraged exposure to multiple asset classes simultaneously, presenting evidence that these funds have so far been more cost-effective than conventional leveraged ETFs while noting remaining uncertainties and limitations.
Key points:
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This summary is accurate.
Last updated 2026-02-04.
Some people (including me) have argued that altruists often benefit from leveraging their investments. Recently, it has become easier to use leverage thanks to the emergence of return stacking funds.
This is not financial advice.
Cross-posted from my website.
Return stacking is a way of getting up to leveraged exposure to multiple return streams simultaneously. For example, RSSB invests 100% into global equities and 100% into US Treasury bonds, effectively giving it 2:1 leverage on a diversified stock/bond portfolio.
A return stacking ETF is a type of leveraged ETF. But whereas traditional leveraged ETFs (such as SPXL) lever up a single index like the S&P 500, a return stacking fund holds multiple asset classes.
Return stacking ETFs have lower management fees than single-index leveraged ETFs, and (with low confidence) they appear to have lower overhead costs for reasons that are not entirely clear to me (my guess is a combination of cheaper borrowing costs + transaction costs).
There are four brands of return stacking funds that I know of:
The PIMCO fund has been around since 2007, but the others only launched within the last few years.
What do each of these funds invest in?
Seven of the funds stack traditional asset classes:
| Fund | first asset class | second asset class | leverage |
|---|---|---|---|
| RSSB | 100% global stocks | 100% US Treasury bonds | 2:1 |
| NTSX | 90% US stocks | 60% US Treasury bonds | 1.5:1 |
| NTSI | 90% international stocks | 60% US Treasury bonds | 1.5:1 |
| NTSE | 90% emerging market stocks | 60% US Treasury bonds | 1.5:1 |
| UPAR | too many for this table* | 1.68:1 | |
| PSLDX | ~100% US stocks** | ~100% bonds** | ~2:1** |
| SPLS | ~100% US stocks** | ~100% bonds** | ~2:1** |
*As of 2025, UPAR targets 17.5% U.S. equities, 7% international equities, 10.5% emerging markets equities, 21% commodity producer equities, 14% gold, 49% TIPS, and 49% Treasuries for a total allocation of 168%.
**PSLDX and SPLS percentages are only approximate because the funds are actively managed and their holdings may vary over time.
These funds stack traditional asset classes with alternatives:
| Fund | first asset class | second asset class | leverage |
|---|---|---|---|
| RSST | 100% US stocks | 100% managed futures* | 2:1* |
| RSBT | 100% US bonds[1] | 100% managed futures* | 2:1* |
| RSSY | 100% US stocks | 100% futures yield* | 2:1* |
| RSBY | 100% US bonds | 100% futures yield* | 2:1* |
| RSBA | 100% US Treasury bonds | 100% merger arbitrage* | 2:1* |
| RDMIX | 50/50 US stocks/bonds | 100% systematic macro* | 2:1* |
| BTGD | 100% bitcoin | 100% gold | 2:1 |
| GDE | 90% US stocks | 90% gold | 1.8:1 |
| GDMN | 90% gold miner stocks | 90% gold | 1.8:1 |
*Managed futures (a.k.a. trendfollowing), futures yield (a.k.a. carry or roll yield), merger arbitrage, and systematic macro are all long/short strategies, not simple assets that you can buy and hold. So it's somewhat arbitrary to say that the funds invest 100% into those strategies.
In a previous post, I looked at how a leveraged index fund should perform and compared that against how leveraged ETFs actually did perform. I found that the ETFs consistently cost more than expected, by an average of about one percentage point.
I attempted to do the same analysis for return stacking ETFs. These ETFs are harder to replicate because they don't track indexes, so I don't have high confidence in the results. That said, my numbers suggest that return stacking ETFs are more cost-effective than conventional leveraged ETFs.
I was able to replicate RSSB and NTSX:
| ETF | Leverage | Stock ETF(s) | Bond Fund(s) |
|---|---|---|---|
| RSSB | 100% + 100% | VTI + VXUS[2] | bond futures ladder[3] |
| NTSX | 90% + 60% | SPY (S&P 500) | bond futures ladder[4] |
I also attempted to replicate NTSI, PSLDX, and GDE, but I couldn't find benchmarks that tracked them well enough.
Update 2026-01-17: SPLS is a newly launched 100% US stocks + 100% bonds ETF. It just launched as of this writing, so it has no history to replicate. It's now the fund with the lowest expense ratio, but it holds swaps on PIMCO bond ETFs that have their own expense ratios (as of this writing, SPLS holds swaps on BOND at 0.40% and PYLD at 0.55%, among others). Different funds may also have different financing rates on the instruments they use to get leverage.
I calculated excess costs of RSSB and NTSX as the hypothetical return you'd get if you levered up the benchmark (borrowing at the 3-month T-bill rate), minus the actual historical return of the fund.
The following table shows the total excess cost and after-fee cost for the return stacking ETFs. Excess cost is shown per 100% leverage (the excess on NTSX is multiplied by two because it only has 50% leverage). After-fee cost gives the excess cost minus the difference expense ratios between the ETF and the benchmark—this represents the "unexpected" portion of the cost, since you expect to pay the expense ratio no matter what. r gives the correlation between the return stacking ETF and the benchmark. I calculated the average annual cost for each ETF starting from the earliest year for which the ETF had a full year of data.
| ETF | Excess Cost | After Fee | r | Start Year |
|---|---|---|---|---|
| RSSB | -0.55% | -0.84% | 0.998 | 2024 |
| NTSX | -0.17% | -0.41% | 0.997 | 2019 |
(The costs were negative, which means the real-life funds outperformed the benchmarks.)
Excess costs for each individual year for NTSX:
| 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | |
|---|---|---|---|---|---|---|
| NTSX | -0.48 | -3.50 | 2.72 | 1.92 | -0.93 | -2.15 |
As we can see, excess costs varied quite a bit from year to year. However, they were still generally lower than the costs of conventional leveraged ETFs.
In fact, the excess costs were negative most years. That's surprising, since the benchmark does not account for transaction costs.
Why were return stacking funds (apparently) more cost-effective than conventional leveraged ETFs?
Those factors explain why return stacking ETFs are cheaper than 3x leveraged index ETFs. But how is it possible for a return stacking ETF to outperform a leveraged combination of index funds?
My benchmarks have some margin of error—they do not perfectly track the return stacking ETFs. Based on playing around with the implementation details of the benchmark, I believe it could be off by perhaps one percentage point.[5]
The most likely source of tracking error is rebalance timing. Small changes in when you rebalance can significantly change year-to-year performance, especially in years like 2024 where some asset classes perform much better than others. If stocks outpaced bonds for most of the year, and the fund was supposed to rebalance from stocks to bonds, then the real-life fund might have gained an edge over the benchmark by delaying rebalancing a little longer.
Even if these (apparently) negative costs might not persist, this still provides evidence that the return stacking ETFs have lower costs than single-asset leveraged ETFs.
The first version of this post, published in February 2025, only included a year of history for RSSB. I'm writing this update in January 2026, and RSSB has now existed for twice as long. Has it maintained its low cost?
Yes. Here's the excess cost of RSSB from inception (2023-12-05) to yesterday (2026-01-15):[6]
| Excess Cost | After Fee | |
|---|---|---|
| RSSB | -0.58% | -0.87% |
As was the case in 2024, RSSB has a negative excess cost, i.e., it was cheaper than its benchmark.
The excess costs by year:
| 2024 | 2025 | |
|---|---|---|
| RSSB | -0.75 | -0.61 |
NTSX also had good operations in 2025, with an excess cost of –0.50%.
Pros:
Cons:
Most of the return stacking funds hold bonds. A question that some people ask:
Does it make sense to own return stacking stocks + bonds? Wouldn't I rather have pure leveraged stocks instead?
Good question! I don't know!
An argument against buying bonds:
Right now, the yield curve is nearly flat: yields on long-term bonds are only slightly higher than on short-term bonds. Why would you borrow at the short-term rate to earn the long-term rate if those rates are (nearly) the same?
Two counter-arguments:
- The efficient market hypothesis predicts that you can't time the bond market, so you shouldn't change how you invest based on what the yield curve looks like.
- A flat or inverted yield curve suggests that short-term rates will go down in the future. You might want to "lock in" the current rate by buying long-term bonds.
(Really these counter-arguments are the same—the (presumed) reason why the yield curve is flat is because the market is pricing in future changes in bond yields.)
Another argument against bonds:
In the long run, bonds have only earned a little bit of a premium over short-term T-bills. Given the overhead costs of using leverage, leveraged bonds might have near-zero or even negative expected return.
And two counter-arguments:
- If you can borrow at close to the risk-free rate, bonds should still have a positive long-run premium.
- Even if leveraged bonds have ~zero expected return, they still add value to a portfolio if they perform well during equity downturns.
Which side of the argument is correct is left as an exercise to the reader.
If you don't want to hold bonds, there are some bondless return stacked stacking available:
I am a big fan of managed futures trendfollowing—it's a strategy with strong historical performance that provided protection during market downturns, and I think it's likely to continue working in the future (for more, see Hurst et al. (2017), "A Century of Evidence on Trend-Following Investing"[7]). I'm ambivalent about carry (I've heard good arguments both for and against using it). I personally wouldn't invest in bitcoin or gold, but if that's your thing, return stacking ETFs give you a way to do it.
(I don't own RSST, but I hold something similar in my own portfolio—equities (AAVM) with managed futures stacked on top.)
Source code is available on GitHub.
Thanks to Corey Hoffstein for helping me work out the implementation details of my benchmark.[8]
"bonds" means any sort of bonds, including Treasury or corporate bonds. "Treasury bonds" means just Treasury bonds. ↩︎
I weighted VTI at 62% and VXUS at 38% as of the beginning of 2024 because those are the weightings I get if I reverse-engineer from RSSB's current weightings.
It would be simpler to use VT which includes all the same stocks as VTI + VXUS. But RSSB itself holds VTI + VXUS, and I found that breaking out equities into two separate ETFs produces slightly more accurate benchmark. ↩︎
RSSB gets exposure to bonds via an equal-weighted combination of bond futures at four maturities: 2-year, 5-year, 10-year, and long (i.e. 25- to 30-year). I replicated this using:
These indexes should exactly match the bond futures that RSSB holds. ↩︎
I wasn't entirely sure what position to use to replicate NTSX's bond holdings. Its materials include illustrative figures that use a 7-10 year Treasury index as a benchmark, which suggests I should use IEF or perhaps 10-year Treasury futures. But the latest holdings show that it uses a combination of bond futures of different durations.
I found the best correlation to NTSX when using a weighted combination of four Treasury futures:
As of this writing, NTSX holds 12% in 10-Year U.S. Treasury Note Futures and 12% in Ultra 10-Year U.S. Treasury Note Futures (which are like the normal 10-year futures except that they are more closely tied to a 10-year maturity). I did not use Ultra futures in my benchmark because they only launched a few years ago. ↩︎
Some minor changes that affect the return of the benchmark:
My original analysis used NAV, but for these tables I switched to using the ETF's market value instead. NAV has a 10x tighter correlation to my benchmark (0.997 vs. 0.96), but my NAV data is rounded to two significant figures and my price data has many significant figures, so the NAV return is less accurate. ↩︎
Hurst, B., Ooi, Y. H., & Pedersen, L. H. (2017). A Century of Evidence on Trend-Following Investing. ↩︎
Originally I couldn't figure out how to get my benchmark's correlation to RSSB higher than 0.976. Turns out I needed to compare the benchmark to RSSB's NAV, not its daily closing price. Corey explained to me that NAV and price diverge because daily futures prices settle at 3pm but exchanges close at 4pm, so any market movements in that hour will show up in RSSB's price but not in its NAV or in the benchmark.
I had the same problem with my NTSX benchmark and was able to fix it the same way.
I also originally implemented rebalancing using an incorrect method, and Corey clarified the correct method to use. (This did not improve the correlation.) ↩︎
These ETFs seem better than leveraged ETFs, for reasons related to the excessive trading by leveraged ETFs.
I see multiple reasons why bonds are likely to be bad investments over the next few years:
Markets may be efficiently pricing a few of these risks, but I'm pretty sure they're underestimating AI.
I've been shorting t-bond futures, currently 6% of my net worth, and I'm likely to short more soon.
Do you have an opinion about what maturity is best to short?
(My first thought is that if you have a view about what interest rates will do over the next 5–10 years, then you should short 5–10 year bonds. But I'm not sure that's right.)
I haven't given that a lot of thought. AI is likely to have the strongest effects further out. A year ago I was mainly betting on interest rates going up around 2030 via SOFR futures, because I expected interest rates to go down in 2025-6. But now I'm guessing there's little difference in which durations go up.
“Trump is pressuring the Fed to adopt policies that would cause inflation.”
That’s more cleanly expressed as a curve steepener (front lower, back higher), so bullish short end vs bearish back.
“AI-induced job loss might cause the Fed to be less concerned about inflation.”
This sounds more bullish bonds because low inflation concerns -> fed can cut. Also (more importantly) the fed has a dual mandate so low employment -> cut.
That's mostly bearish for bonds because it increases inflation.