Leveraged ETFs (corresponding to SPXL – (Direxion Every day S&P 500 Bull 3X Shares) provide amplified publicity to the S&P 500, promising excessive returns however exposing buyers to volatility drag brought on by each day rebalancing. This impact can considerably erode efficiency over longer horizons, notably during times of elevated market volatility. Impressed by latest analysis, The Volatility Edge, A Twin Strategy For VIX ETNs Buying and selling, targeted on volatility-linked ETNs, we suggest a volatility filter that adjusts ETF publicity based mostly on the connection between short-term realized volatility and implied volatility. By lowering publicity in high-volatility durations and sustaining it in calmer markets, this strategy goals to harness leverage successfully whereas mitigating probably the most damaging drawdowns.
Introduction
Lately, exchange-traded merchandise have change into more and more refined, providing buyers publicity not solely to broad fairness indices but additionally to extra advanced methods that amplify and even invert each day returns. Amongst these devices, leveraged ETFs stand out for his or her promise of magnified good points but additionally for the hidden dangers embedded of their design.
A distinguished instance may be present in SPXL (Direxion Every day S&P 500 Bull 3X Shares) and SPXU (Direxion Every day S&P 500 Bear 3X Shares), which search to ship 3 times the each day return of the S&P 500, within the lengthy and inverse instructions, respectively. To attain this leverage, the funds rebalance their by-product publicity every day. Whereas this mechanism ensures that the leverage goal is met every day, it additionally introduces a well-documented phenomenon often known as volatility drag: over prolonged horizons, compounding of each day returns causes realized efficiency to diverge considerably from the “theoretical” triple return of the index. Durations of excessive volatility are inclined to speed up this erosion, making such merchandise particularly fragile throughout turbulent markets.
Current analysis The Volatility Edge, A Twin Strategy For VIX ETNs Buying and selling by Zarattini, Mele, and Aziz (2025) suggests a possible path to mitigating this drawback. Their examine on volatility-linked ETNs launched the concept of a volatility filter, which compares short-term realized volatility, estimated utilizing a rolling window of latest returns, with the implied volatility mirrored within the VIX index. The VIX, usually referred to as the “worry index”, is a monetary indicator that measures the anticipated volatility of the U.S. inventory market over the following 30 days based mostly on S&P 500 possibility costs. It displays short-term market uncertainty or threat, with increased values indicating higher anticipated volatility and elevated investor worry, whereas decrease values counsel a calmer market with smaller worth fluctuations. Importantly, the VIX doesn’t predict the market’s path, solely how a lot costs are anticipated to maneuver. When implied volatility exceeds the short-term realized measure, the technique maintains publicity, when the filter alerts elevated realized threat, publicity is diminished or lower completely. This easy mechanism proved efficient at avoiding among the most damaging drawdowns of their backtests.
This strategy gave us an concept that leveraged fairness ETFs like SPXL and SPXU may benefit from the same filter. Reasonably than sustaining publicity unconditionally, one might use the connection between short-term realized volatility and implied volatility as a information for investing. On this method, the technique goals to harness leverage throughout favorable developments whereas avoiding among the most damaging durations of volatility drag.
Methodology
On this examine, the backtest covers the interval from January 17, 2013, to July 31, 2025. We used each day knowledge for SPXU and SPXL obtained from EODHD.com – the sponsor of our weblog. EODHD affords seamless entry to +30 years of historic costs and elementary knowledge for shares, ETFs, foreign exchange, and cryptocurrencies throughout 60+ exchanges, obtainable through API or no-code add-ons for Excel and Google Sheets. As a particular provide, our weblog readers can get pleasure from an unique 30% low cost on premium EODHD plans..
As a benchmark to evaluate the risk-adjusted returns for our buying and selling methods, we employed SPY’s complete each day knowledge returns from the identical supply. We take into account SPY probably the most acceptable benchmark, on condition that the analyzed ETFs present 3 times the each day return of the S&P 500.
VIX knowledge had been obtained from the FRED, overlaying the identical interval.
As talked about within the Introduction, the analysis The Volatility Edge, A Twin Strategy For VIX ETNs Buying and selling impressed us to design the next technique. Since our aim is to check short-term realized volatility with implied volatility, it’s essential to outline each phrases. Brief-term realized volatility was calculated because the annualized customary deviation of SPY returns over latest days, which is easy given the provision of the info. Against this, implied volatility is represented by the VIX, which is out there with a one-day lag. We then use a median of latest VIX values to clean SPY’s implied volatility.
As soon as each variables are obtained, their comparability determines whether or not or to not spend money on leveraged ETFs corresponding to SPXL (or SPXU for the aim of hedging). This process is repeated every day. The ultimate step is to optimize the size of the time window for each metrics with a purpose to obtain the perfect efficiency relative to the benchmark. We subsequently start by inspecting the ETFs individually.
Primary efficiency traits in tables are offered as follows: the notation perf represents the annual return of the technique, st dev stands for the annual customary deviation, max dd is the utmost drawdown, adjusted Sharpe r is calculated because the ratio of perf to st dev and adjusted Calmar r because the ratio of perf to max dd.
SPXL in Low-Volatility Enviroment
Let’s start with the ETF SPXL (Direxion Every day S&P 500 Bull 3X Shares). SPXL, as a triple-leveraged ETF on the S&P 500 index, performs greatest during times of regular development when each day market strikes are comparatively small and the development is evident. In such circumstances, leverage works in favor of the investor with out being offset by volatility drag, which in any other case erodes the fund’s worth in choppier markets.
It’s subsequently essential to determine a easy indicator that helps distinguish favorable environments from turbulent ones. One strategy is to check short-term realized volatility with implied volatility as measured by the VIX index. When VIX is increased than realized volatility, it signifies that the market expects bigger strikes than are literally occurring—in different phrases, buyers are “overpaying for insurance coverage.” For SPXL, this creates a supportive setting: realized swings stay contained, volatility drag is restricted, and if the market is trending upward, the triple publicity amplifies these good points.
Due to this fact, we designed a method for investing in SPXL based mostly on the connection between realized and implied volatility. Particularly, when the typical VIX worth (implied volatility) exceeds SPY’s annualized X-day customary deviation (realized volatility), we take this as a sign to spend money on SPXL. In any other case (realized volatility is increased then implied), we stay out of the market. Every place is held for sooner or later, after which the process is repeated.
Constructing on the paper that guided our pondering, the preliminary technique’s parameters are arrange as SPY’s 10-day annualized customary deviation, whereas the shifting common of the VIX is calculated over the newest 60 days.
Each the graph in Determine 3 and the leads to Desk 3 point out that the SPXL technique delivered considerably increased efficiency, with returns double these of the benchmark. Nonetheless, these good points had been accompanied by elevated customary deviation and bigger drawdowns, that are clearly seen within the graph. Whereas these unfavourable features barely scale back the Sharpe ratio, the Calmar ratio nonetheless displays the effectivity of the strategy. Nonetheless, this end result didn’t absolutely align with our targets, and we subsequently determined to check the robustness and modify the technique.
The technique was adjusted via two modifications. First, we mounted the 60-day window for the shifting common of VIX values and various solely the size of SPY’s annualized customary deviation, particularly utilizing the 5-, 10-, and 20-day measures.
The outcomes present that extending the variety of days used to calculate the usual deviation results in increased annualized returns, whereas drawdowns and volatility decline. This impact may be defined by the truth that shorter home windows (5 or 10 days) are extremely delicate to one-off swings in SPY, which ends up in extra frequent exits from the market, whereas an extended window supplies a smoother and extra steady estimate of realized volatility. In consequence, it’s extra widespread for the typical VIX to exceed realized volatility, resulting in extra frequent entries into SPXL throughout upward-trending durations and thus increased returns, whereas the extra steady sign concurrently reduces volatility and drawdowns.
This results in increased Sharpe and Calmar ratios, reaching values exceeding 1 and 0.80, respectively, within the technique based mostly on the 20-day customary deviation. These outcomes outperform the benchmark and meet our expectations. Whereas the modification of realized volatility yielded favorable outcomes, the query stays whether or not adjusting the implied volatility will show equally profitable.
The second modification of the SPXL technique focuses on implied volatility, represented by the typical VIX worth over the newest 60 days. On this case, the realized volatility is mounted at a 10-day window, whereas the averaging interval for VIX values varies throughout 10, 20, 30, 40, 60, 80, and 120 days.
Within the case of implied volatility represented by the VIX index, shorter averages produced higher outcomes, which may be defined by the totally different nature of this measure. Whereas realized volatility is backward-looking and requires longer durations to clean out random fluctuations, the VIX responds instantly to present occasions and investor sentiment. When a protracted averaging window is utilized, the sign turns into overly smoothed and loses timeliness. Against this, shorter home windows, corresponding to 10 or 20 days, seize prevailing market expectations extra precisely and permit faster identification of conditions the place implied volatility exceeds realized volatility. This will increase the chance of well timed entries into SPXL throughout favorable durations, thereby enhancing the technique’s efficiency, whereas the extra noise launched by shorter home windows is much less detrimental on this context. The strongest outcomes had been achieved with the 10-day shifting common of the VIX, yielding a Sharpe ratio near 1 and a Calmar ratio of just about 0.9. These outcomes are akin to the perfect outcomes obtained within the earlier modification, though the Calmar ratio is noticeably increased.
The outcomes point out that the effectiveness of the SPXL technique is dependent upon a cautious stability between the horizons used for realized and implied volatility. Longer home windows for realized volatility scale back noise and stabilize the sign, whereas shorter home windows for implied volatility protect its responsiveness. Nonetheless, combining the longest realized-volatility window (20 days) with the shortest VIX window (10 days) doesn’t yield the perfect efficiency, suggesting that the 2 parameters work together and should be collectively optimized. General, the technique performs greatest when realized volatility is measured over a reasonable horizon (10 days) whereas implied volatility is averaged over a brief window (10–20 days), balancing stability and adaptableness.
Our strategy for SPXL proved efficient, efficiently figuring out durations when it’s favorable to speculate based mostly on the connection between realized and implied volatility. However what if the market strikes in the other way? In that case, SPXU, with its inverse and leveraged publicity, might doubtlessly profit, elevating the query of whether or not the same volatility-based indicator may be utilized to information funding choices for SPXU.
SPXU in Low-Volatility Enviroment
On this half, we targeted on the SPXU. SPXU (ProShares UltraPro Brief S&P 500) is a triple-leveraged inverse ETF designed to ship 3 times the inverse each day return of the S&P 500 index. Which means that SPXU good points when the S&P 500 declines and loses when the index rises. As a consequence of its leverage, SPXU is extremely delicate to short-term market fluctuations and each day volatility. It performs greatest throughout sustained downward developments available in the market, whereas in uneven or bullish durations, volatility drag and compounding results can considerably erode returns.
SPXU, as a triple-leveraged inverse ETF, good points when the S&P 500 declines and loses when the index rises. When short-term realized volatility of SPY exceeds the typical VIX, it signifies that the market is shifting greater than buyers had anticipated, reflecting heightened turbulence and sudden swings. Such circumstances usually coincide with downward actions available in the market, creating a good setting for SPXU. In different phrases, excessive realized volatility (SPY’s customary deviation) relative to implied volatility (VIX shifting common) might sign short-term uncertainty and potential declines within the S&P 500, which an inverse leveraged ETF like SPXU can exploit.
Due to this fact, the technique for investing in SPXU is designed as the other of the SPXL strategy. Particularly, when the typical VIX worth (implied volatility) is decrease than SPY’s customary deviation (realized volatility), this serves as a sign to spend money on SPXU, in any other case, the place is averted. Every place is held for sooner or later, after which the process is repeated. Once more, for this evaluation, SPY’s 10-day annualized customary deviation is used as the premise, whereas the shifting common of the VIX is calculated over the newest 60 days. Benchmark additionally stays unchanged.
As we are able to see from the outcomes, this technique didn’t ship extremely worthwhile outcomes, however in comparison with the efficiency of the SPXU ETF alone, it achieved enhancements throughout all measures. Due to this fact, on this case as nicely, we try to change the technique with respect to each implied and realized volatility.
We start once more by first fixing the window for implied volatility, calculating the VIX shifting common over 60 days, whereas various realized volatility, measured as SPY’s customary deviation, throughout 5, 10, and 20 days.
We will see that the modification led to an enchancment when the variety of days used to calculate the usual deviation was diminished, particularly to five days. Since this technique operates on the other precept to SPXL, the place longer home windows produced higher outcomes, it’s logical that right here shorter home windows work extra successfully. On this case, the modification improves funding in SPXU, nevertheless, it’s nonetheless not enough to outperform the benchmark.
Now allow us to check the case the place realized volatility, measured as SPY’s customary deviation, is mounted at 10 days, whereas the implied volatility is various by altering the window for the VIX shifting common, particularly throughout 10, 20, 30, 40, 60, 80, and 120 days.
We will see that not one of the modifications show to be efficient, because the ratios stay unfavourable in all circumstances, clearly indicating inefficiency. Whereas the efficiency of SPXU improves considerably via these changes, it nonetheless doesn’t come near surpassing the benchmark.
It’s onerous to beat the efficiency of SPY by simply utilizing the triple-leverage quick ETF within the sturdy bull market (as was the case for the interval of 2013 to 2025). The entire variants had outcomes from -8% to +1%. Nonetheless, what we are able to anticipate is that these variants could have a unfavourable correlation with the SPY ETF itself, and alerts can subsequently be used as entries to make use of a selective hedge. The worth of the hedge (-8% to +1%) will not be excessively excessive. Nonetheless, we don’t plan to pursue these selective hedging methods additional, as we are going to dedicate an unbiased article on the subject of hedging sooner or later.
Conclusion
Our evaluation demonstrates that volatility-based filters can enhance the efficiency of leveraged ETFs by figuring out favorable circumstances for publicity. For SPXL, evaluating realized and implied volatility proved to be an efficient strategy. The technique delivered returns considerably above the benchmark, notably when realized volatility was measured over longer horizons and implied volatility over shorter ones. This mixture allowed for steady but responsive alerts, lowering noise whereas capturing well timed alternatives.
In distinction, making use of the identical framework to SPXU produced weaker outcomes, suggesting that bearish leveraged publicity is harder to use systematically. Whereas the technique improved efficiency relative to holding SPXU outright, it didn’t produce constantly constructive outcomes. Nonetheless, the efficiency of the SPXU systematic methods means that we could possibly use this strategy as a selective hedge sooner or later.
Writer: Sona Beluska, Junior Quant Analyst
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