Daily Leverage, Compounding, and Volatility Drag in Leveraged ETFs
Summary
The document explains how daily leverage and compounding shape leveraged ETF returns. An ETF resets its exposure at each rebalance, so its multi-day result is the product of daily leveraged returns, adjusted for fees. This means a 3× fund does not simply earn three times the index’s cumulative return; the outcome depends on the path of returns, including the sequence of gains and losses.
The answers use a steady daily rise, a reversal example, and a continuous-rebalancing model to illustrate the difference. The latter shows that volatility reduces compound growth relative to a simple multiple of the underlying’s return, even under idealized assumptions. One answer gives a CAGR approximation under normally distributed returns, while another points out that fees also affect realized performance. These formulas rely on stated modeling assumptions and should not be treated as universal forecasts. The document’s examples clarify the mechanics, but actual ETF outcomes also depend on expenses, financing, and tracking.
Key ideas
- Leveraged ETFs typically reset exposure daily, so cumulative returns depend on the path of underlying returns.
- A fund’s daily multiple does not translate into the same multiple of the underlying’s multi-day return.
- Volatility drag can reduce compound performance for both leveraged long and inverse funds.
- Fees and the timing of rebalancing affect the final return.
- Return approximations in the document depend on assumptions such as continuous rebalancing or normally distributed returns.
Tags
Full text
# How to calculate compound returns of leveraged ETFs?
# How to calculate compound returns of leveraged ETFs?
Forewarning: this is a complete newbie question :-)
I am starting to learn about ETFs by trying to do the numbers. When learning about the compounding effect in leveraged ETFs, I wanted to simulate the return for a simple ETF. Here is what I wanted to do: a hypothetical index ETF gains 1% every day for a 10-day range. I wanted to calculate the final return after the range for 1X, -1X, 3X and -3X ETF. Here are the numbers:
That means, at the end of 10 days, 1X gained 10.5%, 3X gained 34.4%, -1X lost 10.6% and -3X lost 26.3%. Two questions:
- Is the above statement/calculations correct, specifically w.r.t. -1X and -3X ETFs?
- Now if I consider a scenario where the 1X ETF loses 1% every day for 10 days, then can I say the following without additional calculations: at the end of 10 days, 1X lost 10.6%, 3X lost 26.3%, -1X gained 10.5% and -3X gained 34.4%?
Thanks for helping.
## Answer by bill_080 (score 4, accepted)
https://quant.stackexchange.com/a/2031
To answer your questions:
1) Yes, the above table is correct
2) Your results are correct except..... 1X loss = 9.6%.
When you combine both positive and negative changes, it is the MEDIAN value that is of interest. Here are some links:
http://www.futuresmag.com/Issues/2010/March-2010/Pages/Trading-with-leveraged-and-iinverse-ETFs.aspx
http://olympiainv.com/Memos/ETFs.pdf
http://math.nyu.edu/faculty/avellane/LeveragedETF20090515.pdf
http://www.slcg.com/pdf/workingpapers/Leveraged%20ETFs,%20Holding%20Periods%20and%20Investment%20Shortfalls.pdf
http://math.nyu.edu/faculty/avellane/LETFRISKPROF.pdf
## Answer by justin-- (score 3)
https://quant.stackexchange.com/a/4457
Even in a perfect world, a 3X leveraged ETF cannot achieve a compound return three times that of the underlying. In the case of periodic discrete rebalancing, we call this effect the "arithmetic of loss and recovery," but even in the limit of continuous rebalancing, this effect does not disappear. Ito's formula tells us that
$$\mathrm d \log(S_\textrm{Index})=\sigma \mathrm d B +\left(\mu-\dfrac 1 2 \sigma^2\right).$$
Assuming continuous rebalancing, and zero borrowing costs and other expenses, $$\mathrm d \log(S_\textrm{3X Bull})= 3\sigma\mathrm d B + \left(3\mu-\dfrac 9 2 \sigma^2 \right).$$ Therefore the compound performance of a "3X Bull" ETF that "perfectly" tracks its index must be less than triple that of the underlying index by $3\sigma^2,$ where $\sigma^2$ is the variance (here equal to the quadratic variation per unit time interval) of the price process of the underlying index.
For example, if $\sigma=15\%/\textrm{yr}^{1/2}$, which is within the order of magnitude of that assumed for a general stock market index, then we are talking about a rather unavoidable performance shortfall (due strictly to the mathematics of volatility) of $3\sigma^2=6.75\%/\textrm{yr}$ in logarithmic terms for a triple-leveraged ETF.
## Answer by Richard (score 2)
https://quant.stackexchange.com/a/2037
Your example could be correct but you're on the wrong track.
Leveraged ETFs are designed for day trading, it isn't a leveraged 3x position that will return 3x the long term average of the name. The leverage is reweighted each day which will affect your performance.
Eg if the market goes 100->99->100 the market is unchanged over 2 days. But a 3x ETF will go 100->97->99.9394 ((1 + (100/99 - 1) * 3) * 97)
## Answer by demully (score 2)
https://quant.stackexchange.com/a/58023
Yes, your table is correct... the proverbial "catch" is in your assumptions of small gains, with nil volatility. Because volatility is itself the catch with levered strategies in general (and levered ETFs very specifically).
Replicate these 1% returns with a 14.14% standard normal deviation, for a thousand, million, billion runs. Your 1% compound return will (or certainly should) go to zero.
Because if the stockmarket went up or down by 50% every day at random, there's a 25% chance of a 75% loss (0.50.5=0.25), a 50% chance of a 25% loss (1.50.5=0.75) and a 25% chance of a 125% gain (1.5*1.5=2.25). Net net, you'd expect to lose 25% on average every period... putting in "up or down 1% or 2% or 5%" are just milder expresssions of the same basic mathematical phenomenon.
If the arithmetic return is X with Y volatility, then the CAGR (assuming normally distributed returns) would be X - 0.5 * Y ^2.
And if you want to play this game with levered ETFs levered L to the underlying, it's: CAGR = L.X - 0.5.L.(L-1)*Y^2.
So for higher volatility assets, both the levered long and the levered short ETFs will both lose money. I know. Back in the day, I was playing this game with VIX, goldminers, and Natural Gas; back when it possible to get the borrow to short these bad boys in both directions! Sadly no more cheap lunches there these days ;-(
As a next step in your analysis, I would maybe look at the simulated difference in (1) returns from levered ETFs; versus (2) just generating some real leverage, by borrowing some real money and investing that; versus (3) just buying futures, if you want the same leverage. I've struggled to come up with ANY scenario where (1) is optimal. If you love (or hate) the asset in question that much, the future is nearly always preferable to the levered ETF...
## Answer by will (score 1)
https://quant.stackexchange.com/a/58019
For a leveraged ETF, with a a leverage of $L$, then the value of the ETF is:
$$ \mathrm{ETF}_{t_n} = \mathrm{ETF}_{t_0} \cdot \Pi_{i=1}^{i=n} \left[ 1+L\left(\frac{S_{t_i}}{S_{t_{i-1}}}-1\right) - f \cdot \mathrm{DCF}(t_{i-1}, t_i)\right]$$
where $t_i$ are the dates on which the ETF rebalances to restore the leverage. $f$ is the ETF management fee, and $\mathrm{DCF}(t_{i-1}, t_i)$ is the day count fraction used in the calcualtion of the fee for the ETF.Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.