Most option traders know that volatility can work against short premium strategies. But when volatility suddenly spikes — or, for example, the market drops faster than expected — it often catches people off guard. Even setups that usually feel relatively safe can start to break down pretty quickly.
So, in this piece, we take a closer look at how short premium strategies on SPY actually behaved between 2016 and 2026, focusing on major volatility spikes and what followed as volatility normalized. As a comparison, we also look at how a covered call strategy held up during those same periods.
Part 1: The Concepts — Starting Simple
It helps to think about short premium strategies like running a small insurance business. Most of the time, you’re collecting steady premiums and things feel pretty stable. However, every once in a while you get hit with a large claim — and that’s where things can get so to say uncomfortable.
So, volatility spikes are essentially those “claims.” When implied volatility jumps, price moves in SPY tend to become faster and more aggressive than what the market had been pricing in. And when that happens, trades that looked fine a moment ago can deteriorate pretty quickly.
Mean reversion is the other side of the story. After a spike, volatility often settles back down. The real question is whether your position can hold up through the spike long enough to benefit from that normalization.
Part 2: What 10 Years of SPY Data Actually Shows (2016–2026)
Looking across SPY options data from 2016 through 2026, certain patterns show up pretty consistently around volatility events.
The more obvious spike periods include Q4 2018 (when VIX moved above 35), March 2020 (with VIX peaking around 82), and early 2022 during the inflation and rate-hike fears. There were also smaller spikes scattered through 2021 and 2025.
Over the full 10-year period, short premium setups — roughly around 45 DTE and near 17-delta strikes — generally showed positive expectancy in more stable market conditions. But during sharp volatility spikes, both win rate and expectancy tended to drop.
In the 2021–2026 period, the average win rate moved from about 87% in calmer quarters down to roughly 71% during the highest-volatility weeks. At the same time, losses during those periods were noticeably larger, with average losses coming in around 2.1–2.8 times the size of average wins.
This chart shows how the win rate of the short premium strategy shifts between different market conditions — from around 87% in calmer quarters down to about 71% during high-volatility weeks.
Moreover, some of the more extreme outcomes showed up during major stress events. In March 2020, the average loss on short premium positions was around –7.4%, while in Q1 2022 it came in closer to around –5.9%.
This chart compares the average losses on SPY short premium positions during major stress events, with around –5.9% in Q1 2022 and about –7.4% during the March 2020 spike.
Interestingly, once volatility started to mean-revert — usually somewhere in the 4–8 week window after the peak — outcomes improved, although the path was often uneven. In the 2021–2026 sample, many positions that remained open through the spike eventually recovered, with about 76% of those recovery periods showing positive expectancy.
Part 3: How Covered Call Strategy Performed on SPY During Volatility Spikes and Mean Reversion
Also, we looked at how a covered call approach (long SPY + short approximately 17-delta calls, at around 45 DTE) behaved during the same volatility spikes and recovery phases using the 2016–2026 dataset.
During volatility spikes:
- In March 2020, the covered call strategy saw drawdowns of roughly 22–28% on the underlying exposure, compared to about 34% for holding SPY outright.
- Undoubtedly, the premium collected in the weeks leading into the spike did provide some cushion, although it only offset around 18–24% of the total downside during the largest stress events.
- In Q4 2018 and early 2022, the covered call reduced the volatility of returns by approximately 35–40% relative to buy-and-hold. Even so, total returns during those spike months were still negative.
This chart shows how covered call drawdowns compare to a simple buy-and-hold SPY position during volatility spikes.
During the recovery phase:
- In the 2020–2021 recovery quarters, covered call positions that remained in place through the spike generated average quarterly returns of around +4.8% to +7.1%.
- Looking across all post-spike recovery periods from 2021 to 2026, the strategy showed positive quarterly returns in about 81% of cases, with average premium collected per cycle around 1.8–2.3% of the underlying value.
- Relative to a simple buy-and-hold approach in SPY, covered calls reduced maximum drawdowns by roughly 11–14 percentage points across the major stress events, while still capturing a meaningful portion of the upside during recoveries.
This chart shows the average quarterly returns for covered call positions that stayed in place through the 2020–2021 volatility spike.
Part 4: The Numbers That Matter — Historical Reference
To make the overall patterns easier to see, here’s a condensed view of the key aggregated metrics from the SPY 2016–2026 dataset, with a closer look at the 2021–2026 period.
Short Premium Setups (~45 DTE, ~17 delta):
- In calmer market conditions (2021–2026), the average win rate came in around 87%, with expectancy near +3.4%.
- During volatility spike weeks: Average win rate approximately 71%, expectancy dropped to around +0.8%
- Looking at the more extreme events, the March 2020 spike showed average losses of approximately –7.4%, while the Q1 2022 spike showed the average loss closer to –5.9%.
- As volatility began to normalize — typically within 4–8 weeks after the peak — conditions improved, with win rates recovering to around 82% and expectancy rising to roughly +2.9%.
This chart shows how strategy expectancy changes across different phases — dropping to around +0.8% during volatility spikes, then recovering to about +2.9%, close to about +3.4% baseline.
Covered Call Strategy:
- During spike periods, the strategy experienced average drawdowns of approximately 22–28%, compared to roughly 34% for a simple buy-and-hold SPY position.
- Across recovery periods from 2021 to 2026, covered calls showed positive quarterly returns in about 81% of cases, with an average quarterly return near +5.9%.
- The premium component contributed approximately 1.8–2.3% per cycle on average.
- Relative to buy-and-hold, drawdowns were reduced by roughly 11–14 percentage points during the major stress events.
Overall, the data shows that while both approaches came under pressure during volatility spikes, covered calls tended to be more stable, particularly during the recovery phase.
Part 5: Why Short Premium Strategies Struggle During Crashes
The main drivers behind short premium losses during sharp volatility spikes tend to be larger-than-expected price moves, rapid expansion in implied volatility, and shifts in skew.
Looking at the 2016–2026 SPY data, one pattern shows up fairly consistently: when put skew widened beyond roughly 9–10 points at the 17-delta level, short put and short strangle positions tended to experience noticeably larger losses in the weeks that followed.
Part 6: A Practical View on Risk Management
Looking back at the SPY data, a few patterns show up again and again when it comes to how risk actually played out.
- One thing that stands out pretty clearly is how much position sizing influenced the final outcome.
- At the same time, shifts in IV Percentile and term structure ahead of entries often coincided with more difficult periods.
- During several of the larger volatility spikes, positions with predefined adjustment or exit levels generally behaved in a more controlled way.
A simplified framework based on the data:
- In calmer environments, with lower volatility and a relatively stable term structure, short premium setups were usually more consistent.
- When volatility started rising and skew became steeper, results got more uneven, with larger losses showing up more often.
- After the spike, once volatility began to settle, outcomes improved again — especially for positions that made it through the initial move.
FAQs
Q1: Should I completely avoid short premium during high VIX periods?
Historical data does not support a complete avoidance rule. Some of the strongest recovery periods followed high volatility spikes.
Q2: How useful is a covered call in a real crash?
It provides limited protection on the downside but can help during the recovery phase through premium collection and reduced volatility.
Q3: Does holding through the spike usually produce better results than closing early?
In 2021–2026 data, positions held through the spike and into the recovery showed positive expectancy in about 76% of cases, compared with approximately 58% for positions closed during the spike.
Q4: How important is position sizing during volatile periods?
Our analysis shows that smaller position sizes were one of the biggest factors in limiting maximum drawdowns during the 2020 and 2022 events.
Q5: Can covered calls fully protect against a market crash?
No. They reduce drawdowns modestly (by around 11–14 points on average), but they do not eliminate downside risk.
Conclusion and Key Takeaways
So, looking at the data, it’s pretty clear that sudden volatility spikes remain one of the biggest challenges for short premium traders. Our review of SPY data from 2016 to 2026 shows that while these periods can be painful, they are also temporary in most cases.
A few patterns stand out from the data:
- Larger position sizing was one of the main drivers behind outsized losses during spikes.
- Covered calls provided some downside buffer during the spike, but tended to behave more stable during the mean-reversion phase that followed.
- Looking at IV Percentile, skew, and term structure together gave a more complete picture of market conditions than relying on any single metric on its own.
At the same time, looking at how strategies behaved in past events doesn’t tell you what will happen next — but it does help frame more realistic expectations when markets become volatile.
