New LETF slippage tool in testfolio, and examining WLDU slippage
Testfol.io released a free tool to calculate LETF slippage by comparing real returns against synthetic LETFs factoring in borrowing costs.
testfolio just rolled out a new free (requires sign in) tool: LETF slippage.
The purpose of this tool is to compare real daily-reset LETFs against a theoretical synthetic LETF based on the underlying's returns, financing costs and other expenses.
For example, UPRO is 3x daily S&P500 total returns. So, we should expect UPRO's daily returns to be 3x SPY's daily returns minus borrowing costs and other expenses.
On a daily basis, borrowing and expenses are quite small, and can be dwarfed by returns. but over long periods, they add up to a lot.
If an LETF is 3x, we should expect it to invest 100% in the underlying directly, and borrow 200% to buy the additional 200% exposure to the underlying (through total return swaps). LETFs usually borrow at the Fed Funds Rate plus a spread. Due to inefficiencies and some LETFs not buying 100% directly, they might end up borrowing 220%, investing 80% directly and holding 20% in cash. A good rule of thumb looking at many prospectuses is that LETFs have around 1.1 swap exposure per unit of additional leverage.
So, for UPRO specifically, we should expect to pay 1.1 x (L - 1) x (FFR + spread) daily to achieve the 3x returns. In addition to that UPRO has to also pay the expense ratio which is 0.91% per year.
Today, FFR = 3.65%. Assuming spread = 0.5%, we get that the borrowing expenses + expense ratio are
1.1 x (3-1) x (3.65% + 0.5%) + 0.91% = 10.04% annually, and dividing by 252, we get 0.04% per trading day.
That is a tiny amount compared to how much UPRO moves per day, but over a year, it's 10%, a very consequential amount.
In testfolio's new tool, the user can input:
- The LETF ticker the want to examine (e.g. UPRO)
- The underlying ticker (e.g. SPYSIM <- using SPYSIM instead of SPY because SPYSIM is already 0% ER S&P 500, but we can also use SPY and backout its ER later)
- The daily leverage factor (e.g. 3x)
- The LETF expense ratio (e.g 0.91%)
- The underlying expense ratio to backout (If the LETF is leveraging the ETF with its expense ratio, then this should be 0%, but if the LETF is leveraging a 0% ER total return index that the underlying ETF tracks, then input field should be the underlying ETF's ER)
- The financing rate (e.g. Fed Funds rate)
- The borrowing spread (e.g. 0.5%)
- Swap exposure factor (e.g. 1.1)
Then, testfolio will show you the synthetic ticker to replicate the assumptions we just inputted (the custom ticker format testfolio pioneered over 2 years ago), and the equation it uses to create the daily returns of the synthetic.
Analyzing further, testfolio will show the performance and chart of the real LETF and the synthetic. In this case you can see that they track each other pretty well, suggesting the real LETF is following what is expected of it on a daily basis.
You can further see the tell-tale chart between the real and synthetic LETF. This chart is the value of the first portfolio divided by the second over time and shows how they deviated (if any) from each other over time.
From the tell-tale chart, we can see that the biggest deviations happened at market stress periods. March 2020 and April 2025 when the LETF struggles to replicate 3x daily exactly every day of the market crash/recovery.
Digging further, testfolio will perform a linear regression between the LETF returns and the underlying returns to see how faithful the LETF is, on average, to what is promised.
For UPRO, the the best fit linear regression gives a slope of 2.99 (very close to the claimed 3x daily) and an intercept of -0.0201% which annualized to -5.06%.
UPRO's implied daily expenses from the formula 1.1 x (L - 1) x (avg FFR + spread) + 0.91% ends up being 5.16%.
So, the intercept we get is very much in the ballpark of what is expected, and it looks like UPRO is a very clean and lean LETF, performing in line with expectations, and with very minimal slippage, outside stressful market events where it can deviate 1 or 2%... which once or twice a decade is not something to worry much about, in my opinion.
Unfortunately, that is not the same situation with every LETF out there.
WLDU was a very promising LETF. It is 2x VT which is a really great choice. 2x is about the optimal amount of leverage if you want to maximize CAGR over a long period of time. And VT is an excellent choice for investors who want the largest amount of equity diversification. The LETF has only been around for 3 months, so maybe too early to judge, but let's put it into testfolio's LETF slippage tool:
https://testfol.io/letf-slippage?s=3ngH12ciVWq
First, we can see from the tell tale chart below that WLDU already drifted 1-2% from where it should have been, and it's only been 3 months. That is a concerning amount, especially because the drift seems systematic and linear.
Looking at the regression tab, we see the following:
For WLDU, the the best fit linear regression gives a slope of 1.99 (very close to the claimed 2x daily) and an intercept of -0.0449% which annualizes to -11.31%.
WLDU's implied daily expenses from the formula 1.1 x (L - 1) x (avg FFR + spread) + 0.75% ends up being 5.3% for the period since its inception. That is a LOT less than the 11.31% observed from the regression of the first 3 months.
This is a very big and consequential difference. I am not sure if this is an issue of hidden expenses or if they are paying huge spreads for borrowing.
Paying 6% more for borrowing/expenses/transactions or whatever makes the leverage completely not worth it.
Using testfolio's optimal daily leverage calculator:
The optimal daily leverage for the following assumptions is about 2.00x:
However, if we change the borrowing spread to 6.5%, the optimal leverage is exactly 1.00x.
Even a 3.5% borrowing spread makes any leverage above 1.0 not worth with the above assumptions, which I think are reasonable assumptions for long term investors holding a broad market index.
Thank you for reading, and I hope you enjoy this new tool and find it useful. If you would like me to make more posts about other testfolio features or tools, please let me know which ones!
Cheers!
All is good - but most of the time people will just use SPYSIM?L=2 to design their strategies, instead of SPYSIM?L=2&SP=0.5&SW=1.1&FR=EFFRX&E=0.91.
The former is 0.6% CAGR better...
These values bounce around from fund to fund. The holdings and swap fractions vary quite a lot.
Testfolio allows defining custom tickers, where SSOMY might be shorthand for SPYSIM?L=2&SP=0.5&SW=1.1&FR=EFFRX&E=0.91 (or whatever). Then you just use SSOMY with precise values.
IMO it's valuable to have a good handle on the relative efficiencies of the funds if you are going to be investing in them, which doing the fitting kinda forces you to.
most of these modifiers have reasonable defaults
SPYSIM?L=2 will translate to SPYSIM?L=2&SP=0.5&SW=1.1&FR=EFFRX&E=0.5
E=0.5 is the default for L=2, but that varies fund to fund, so I can't really make a mapping that works for all funds.
But, SPYSIM?L=2&E=0.91 would be enough.
And as hydromod mentioned, testfolio allows users to define ticker aliases, so a user could define MYSSO to mean SPYSIM?L=2&E=0.91 or whatever they want.
I get it all.
But somehow when opened the left slippage tool there is 0.91 by default that matches performance of a real life fund...
I realize that SSO or UPRO are different than TQQQ - but you came out with the 0.91 in the slippage from somewhere and it actually is very accurate...
Yeah, you're right. I just know it for UPRO because it is a popular one!
Great review, thanks
Great post. Would love to see some more examples on how the tools can be used for evaluating investing ideas. Maybe something using the signal analyzer to develop a tactical strategy?
Thank you! Yes, definitely. I agree… testfolio has a lot of powerful features that are less known and rarely used.
Is this using NAV or closing price for the value? I wonder if the low liquidity on WLDU is causing an overstatement of its estimate cost, it is consistently trades or closes at a discount
This is using the closing price for the value. I wondered the same thing, but that doesn't seem to be the issue. On their website, I see the NAV has gone up less than the price since inception, but only by a small amount.
https://preview.redd.it/qbnls4mw2y6h1.png?width=2226&format=png&auto=webp&s=3cf61b84848cabc55382e73afd8a5375beec3df8
Do you think the quarterly reset products (GDE, NT family from WisdomTree, etc.) are worth evaluating from a slippage standpoint?
Definitely, from what I've seen, GDE, NT family and RSSB are highly efficient and the slippage is very low. They can't be run through this tool because they aren't one asset and not daily reset.
But you can still see GDE here
https://testfol.io/?s=3sP0jeKnnDQ
And you can use the regression tool in portfolio backtester to find the best fit on monthly returns, and it looks reasonable. The intercept is -0.01% monthly, which is basically nothing.
https://preview.redd.it/wb1mi85wqv6h1.png?width=1590&format=png&auto=webp&s=75e6f7f3c39699de5273a3ef36ad7d60022babd6
Amazing work! Thank you!

r/letfs