If you’re selling options because implied volatility is rich relative to what’s likely to realize, which is the entire basis of any short-volatility strategy, then you need to understand an iron condor gives back a disproportionate share of the premium you set out to capture.

The premium isn’t evenly distributed

The market has a well-documented tendency to overprice options relative to the movement that actually occurs. But that overpricing isn’t spread evenly across all options. It’s heavily concentrated in deep out-of-the-money puts.

Why? Because the biggest fear in the market is a crash. Institutions, pension funds, and portfolio managers are constantly buying downside protection. That relentless demand inflates the price of puts that are far below the current market price. These options are the most “overpriced” relative to what’s likely to actually happen. They carry the fattest premium.

And when you build an iron condor, those are exactly the options you buy as your protective wings.

These deep OTM puts are the most expensive options relative to the movement they’re likely to capture. And when you construct an iron condor, you buy them back as your wings. You’re purchasing the richest insurance on the board.

Think of it this way. You run an insurance company. Your best product is flood insurance in a desert town. People pay huge premiums for it even though it almost never floods. Business is great. Then your risk manager walks in and says, “We should buy flood insurance on our own office, just in case.” So you turn around and buy the exact same overpriced product you’ve been selling. The premium you collected with one hand, you’re handing back with the other. That’s what an iron condor does when it buys back deep out-of-the-money puts.

A better way to hedge

If you want protection, the key insight is to buy it where it’s cheapest, not where it’s most expensive.

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• SLV: which tracks physical silver bullion ()

• SIL: which follows silver mining companies ()

While both provide exposure to silver prices, their performance characteristics are a bit different.

The Correlation Isn’t Perfect

Consider 2025’s remarkable rally. SLV posted an impressive 144.66% gain, but SIL surged 166.14%, adding an extra 21 percentage points to an already extraordinary move. This gives the impression that SIL is a leveraged play on SLV.

The year 2022 perfectly illustrates why SIL demands caution. While SLV managed a modest 2.37% gain, SIL plummeted 22.83%. That’s a 25-percentage-point divergence in the wrong direction. Investors who assumed the two would move in lockstep learned an expensive lesson about operational leverage, mining costs, and sector-specific risks.

Similarly, in 2018, SLV dropped 9.19%, painful, but manageable. SIL crashed 22.41%, more than doubling the losses. The pattern repeats in 2021: SLV down 12.45%, SIL down 18.36%.

This volatility stems from mining companies’ unique cost structures. When silver prices fall, mining operations don’t just see lower revenues but their profit margins also get crushed. Fixed costs, energy expenses, labor, and capital requirements don’t decrease proportionally with metal prices. Some miners operate at break-even or losses during downturns, leading to severe stock price declines that far exceed the underlying commodity’s move.

The Better Trade

SLV’s relative stability and deep options market make it more ideal for tactical trading strategies:

Covered Calls: During sideways or mildly bullish periods, selling monthly calls against SLV holdings can generate consistent income. The tighter bid-ask spreads mean you’re not giving away edge to market makers.

Directional Options Plays: Want to bet on a silver breakout? SLV’s weekly options provide precise timing tools with minimal friction costs. The liquidity allows for easy entry and exit.

Core Holdings: For long-term precious metals allocation, SLV offers silver exposure without the business risk inherent in individual mining companies.

On top of that, SIL only offers monthly options, and the spreads are significantly wider than SLV. If you’re trading SLV options, you might see spreads of $0.05 to $0.15 depending on strike and expiration. With SIL, you’re often looking at $0.20 to $0.50+ spreads. On a percentage basis, this can represent 5-10% slippage on entry and exit. Scale that across multiple trades, and you’re fighting a serious headwind.

The monthly-only structure also means you can’t make quick weekly adjustments.

Learn exactly how this unconvent…

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When we first heard about this strategy we decided to backtest it ourselves.

From 2013-2015, the strategy delivered approximately 11.2% annualized returns and maximum drawdown of only -19.56%, underperforming SPY’s raw returns by roughly 1% annually while exhibiting significantly superior risk-adjusted performance.

Wealth managers running target-allocation portfolios (such as 60/40 stock-bond funds) must periodically rebalance to maintain their mandated asset mixes. At month-end, they systematically purchase whichever asset class has underperformed, creating temporary price pressure disconnected from fundamental value. These flows are large, predictable, and price-insensitive.

Implementation Rules

Phase 1: Identify the Underperformer (Days 1-15)

Monitor the relative performance of SPY versus

TLT over the first 15 trading days of each month. The relative underperformer becomes the target.

Phase 2: Capture Rebalancing Flows (Day 16-End of month)

Take a long position in the underperformer for the remaining trading days of the month, positioning ahead of the expected institutional buying.

Phase 3: Mean Reversion Overlay (Next Month, Days 1-3)

Short the prior month’s underperformer during the first three trading days of the following month, capturing the reversal as artificial price pressure dissipates.

The strategy maintains market exposure only 28-30% of the time.

Aggregate Results (2013 - 2025)

• Total Return: ~284% (compounded)

• Annualized Return: ~11.2%

• Maximum Drawdown: -19.56%

• Win Rate: ~63% across 146 cycles

Over the same period, buy-and-hold SPY delivered:

• Annualized Return: ~12.2%

• Maximum Drawdown: -34.10%

While the strategy underperformed SPY by approximately 1% annually in absolute terms, it achieved this with 43% lower maximum drawdown and markedly superior risk-adjusted returns.

Annual Performance Breakdown

The 2022 performance is particularly notable: while traditional portfolios suffered significantly during the rapid rate-rise environment, this strategy delivered over 20% returns with far lower volatility than equity or bond alternatives.

Sample Monthly Cycle Returns

Each cycle comprises the month-end long position plus the early-next-month short position:

Why Some Institutional Investors Use This Strategy

Despite “modest” absolute returns compared to other strategies, this approach is actively implemented across hedge funds, proprietary trading desks, and multi-billion-dollar asset managers for the following reasons:

Elite Risk-Adjusted Returns

Professional allocators prioritize returns per unit of risk over raw returns, particularly when maximum drawdowns remain below 20%.

Structural Persistence

The mandatory rebalancing by rules-based wealth managers is embedded in regulatory and fiduciary frameworks. Unlike other edges that may erode with awareness, institutional rebalancing is a structural feature of the investment landscape unlikely to disappear.

• ProShares UltraPro QQQ (TQQQ), which aims for +3x daily moves.

• ProShares UltraPro Short QQQ (SQQQ), targeting -3x daily moves.

Below is a year-by-year comparison across 14 years:

Compounded Annual Growth Rate

• QQQ: ~19.1% (turned $1 into ~$13.5)

• TQQQ: ~38.8% (turned $1 into ~$137)

• SQQQ: ~-72% (turned $1 into nearly $0)

One strategy that emerges from these numbers is shorting SQQQ as a way to gain leveraged bullish exposure to the Nasdaq-100.

• In 13 of the 14 years shown, SQQQ posted negative returns compared to 11 out of 14 years for positive TQQQ returns.

This consistent pattern of annual negative returns for SQQQ in most years is exactly why some investors adopt the strategy of shorting SQQQ instead of going long TQQQ.

A risk reversal is a classic options strategy where you simultaneously buy a call option and sell a put option on the same underlying asset. Traders use it to get directional exposure at zero cost as the premium from selling the put finances the purchase of the call.

The Traditional Risk Reversal Example

In a standard bullish risk reversal on Tesla (TSLA) trading at $400:

• Buy a $410 call option for $3

• Sell a $390 put option for $3

Net cost: $0 (premiums offset)

You get upside if Tesla rises above $410, but you’re obligated to buy shares at $390 if it falls. Both legs are on the same stock.

CI Volatility’s Innovation:

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If you’ve ever wanted to control 100 shares of a stock with only a fraction of the cost then the ZEBRA trade might be for you.

Benefits of a Zebra Trade

• It’s like owning 100 shares of your favorite stock

• Uses far less money than buying 100 shares

• Pay almost zero time decay (unlike buying calls)

• Have a built-in stop-loss (your risk is capped)

• Massively leveraged even though you pay less

How to Open a Zebra Trade

• You buy 2 in-the-money (ITM) calls around 80 delta

• Sell 1 at-the-money (ATM) call around 50 delta

• Same expiration, usually 90+ days out

• Enter it as a single order

In the Video Below We Use TSLA as an Example on How to Open a Zebra Trade

For example, TSLA is currently trading at $450 and you are very bullish on it but you don’t want to spend $45,000 buying 100 shares:

From the video, you’ll see the cost for the Zebra trade was $13,020 instead of $45,000 to basically “own” 100 shares of Tesla for 99 days. That’s a 70% discount!

Leveraged Payoff Structure

Example: TSLA goes from $450 to $460

Buying Stock: You make $1,000 on $45,000 = 2.2% profit
Zebra Trade: You make the same $1,000 but on $13,020 = 7.7% profit

Non-Leveraged Loss Structure

Example: TSLA goes from $450 to $200

Buying Stock: You are down $25,000
Zebra Trade: You are down $13,020 (maximum you could ever be down)

When to Use a ZEBRA

• You’re very bullish and want stock-like exposure with 70% discount

• You want to replace expensive shares in a long-term account

Avoid when:

• Less than 30 days to expiration

• Don’t open a zebra trade on stocks that aren’t liquid because you’re dealing with 3 legs so that’s 3 separate bid/ask spreads you have to pay for. With liquid stocks the bid/ask spreads will be tighter.

Final Point

A ZEBRA is one of the cleanest, most capital-efficient ways to be aggressively directional with options. Once you do your first one, you’ll wonder why anyone ever buys 100 shares outright again.

• Just remember, never hold through expiration unless you want the shares

Every time the market panics, the options market shows the same pattern:

• Short-term implied volatility (1-month) spikes

• Longer-term implied volatility (2-month) barely moves

• This creates a volatility inversion meaning short term IV overreacts compared to long-dated IV.

The options market is basically telling you: “The next 30 days will be volatile, but after that…everything goes back to normal.”

And historically, when this inversion becomes extreme, the market is almost always wrong.

And when the volatility curve is wrong, it creates one of the most reliable profit making opportunities.

The Trade: Long Forward Volatility

To exploit the mispricing, we trade two positions on the same stock:

1. Buy the 2-month ATM straddle

(because longer-term IV is underpriced relative to the curve)

2. Sell the 1-month ATM straddle

(because short-term IV is overpriced due to panic)

This creates a forward volatility position:

It’s delta-neutral at entry.

It’s not a direction bet.

It’s a relative value arbitrage between two maturities.

And it’s one of the few places where options markets consistently misprice risk.

Yes, it’s a debit trade

Buying the 2-month straddle costs more than selling the 1-month.

So the position is a net debit, and your maximum loss is that debit.

But the entire point is not the credit or debit; it’s the relationship.

You’re not selling premium.
You’re buying mispricing.

What’s Great About This Strategy

✔ Defined risk (your max loss is the net debit)

✔ Delta-neutral

✔ No directional bias

✔ Not exposed to volatility crashes or gamma squeezes

✔ Negative beta (actually helps in selloffs)

✔ Weak correlation to almost every asset class

✔ No reliance on forecasting the market

✔ Pure mispricing, not speculation

Why Retail Traders Never Use This Strategy

Because:

• It’s not a credit spread

• It’s not directional

• It’s not sexy

• It requires understanding term structure

• It requires trading two expirations at once

• It isn’t marketed on YouTube or TikTok

But for sophisticated volatility funds, this is exactly the kind of anomaly worth harvesting.

At CI Volatility

We understand most investors struggle because they chase direction.

Mispricing is far more reliable than prediction.

This strategy doesn’t require you to be right about the market.
It only requires the market to behave like it always has:

• short-term panic,

• long-term calm,

• and a curve that always returns to equilibrium.

We analyzed 11+ years of QQQ daily data (2,886 trading periods from 2014-2025) to quantify exactly how safe it is to sell out-of-the-money options in different VIX regimes.

The video below demonstrates why the results make a compelling case for a systematic premium selling strategy.

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Entry Rules:
Trades are initiated at 11:00 AM EST only when our proprietary entry signal appears.

There are two versions of this trade:

• For Version 1:
  Do not open any trades if VIX is above 22.
  Sell SPX puts or put spreads 1.5% below 11am price only when bullish signal appears.

Don’t use more than 30% of buying power.
Don’t open trade on big binary event days.

• For Version 2:

  • If VIX is below 22: Sell SPX puts or put spreads 1.5% below 11am price only when bullish signal appears.

  • If VIX is between 23 and 30: Sell SPX puts or put spreads 2% below 11am price only when bullish signal appears.

  • If VIX is above 30: Sell SPX puts or put spreads 3% below 11am price only when bullish signal appears.

Don’t use more than 30% of buying power.
Don’t open trade on big binary event days.

Click Here to Obtain Our Entry Signal

Exit Rules:
Positions are closed at 2:00 PM EST regardless or when the option value drops to $0.10, whichever occurs first. This dual-exit approach locks in profits early when possible while capping maximum holding time.

Entry Rules:
Trades are initiated at 11:00 AM EST only when our proprietary entry signal appears. Strike selection dynamically adjusts based on current VIX levels:

• VIX above 35: No trades (market too volatile)

• VIX 30-35: Sell put 4.5% below 11am price

• VIX 25-30: Sell put 3.5% below 11am price

• VIX 20-25: Sell put 2.5% below 11am price

• VIX below 20: Sell put 1% below 11am price

All positions must provide a minimum credit of $0.20 to ensure adequate risk/reward.
Don’t use more than 50% of buying power.
Do not use this strategy the day of earnings.

Click Here to Obtain Our Entry Signal

Exit Rules:
Positions are closed at 3:30 PM EST regardless or when the option value drops to $0.10, whichever occurs first. This dual-exit approach locks in profits early when possible while capping maximum holding time.

1. Introduction

Traditional tail-risk hedging relies on S&P 500 index puts or VIX call options to offset portfolio losses during systemic stress. Yet both instruments have grown increasingly expensive and crowded, leading to persistent negative carry.

This paper and the video below explores a low-cost alternative: buying deep out-of-the-money (OTM) puts on

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• Total Trades: 501

• Total Profit: 4038%

• Average Annual Return: 67.64%

• Win Rate: 54.49% (273 wins, 180 losses)

• Avg P&L per Trade: 1.62%

• Win/Loss Ratio: 1.42x (winners are 42% bigger than losers)

• Avg Winning Trade: 5.76%

• Avg Losing Trade: -4.22%

Despite only slightly better than a coin-flip win rate, the average return per setup is large enough to make the strategy exponentially profitable over time.

We explain below how simple this strategy is to execute:

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To identify the sweet spot to short UVXY, we combine two separate research papers:

• A Probability Map showing how often a spike at one threshold goes on to the next.

• A Time Map showing how long a successful progression usually takes.

Together, they identify a consistent sweet spot. We explain below:

The Sweet Spot: The First Tag of +50% Off an ATL

Why +50%?

1. Momentum has likely finished its “inevitable” push.
   From +40% to +50% the continuation rate is very high (≈90%). Fading at +40% is usually fighting a final shove. Waiting for the first touch of +50% lets that last burst exhaust itself.

2. The odds flatten beyond +50%.
   From +50%, advancing to +75% is roughly a coin flip, and to +100% is closer to one-in-three. That’s the first rung where momentum no longer dominates—exactly where mean reversion starts to get a fair fight.

3. The time window is tradable.
   When +50% does keep running toward +100%, it typically decides within ~1–2 calendar weeks. That gives shorts a realistic holding window to see if momentum rolls or extends, and to manage risk accordingly.

How to Trade the +50% Zone (Without Getting Steamrolled)

Entry Triggers (use 1–2 together):

• First tag of +50% within the episode, followed by an intraday failure (breakout that can’t hold).

• Momentum rollover: RSI/MACD divergence or a lower high after the +50% tag.

• VIX term structure easing: backwardation abating toward flat/contango.

• Market stress gauges stabilizing (index breadth stops deteriorating, credit spreads stop widening).

Risk Framing:

• Initial stop: just above the next rung (+75%). If continuation triggers, the push to +75% often happens quickly—your stop should acknowledge that.

• Time stop: if UVXY grinds higher for ~8–12 days after the +50% tag without momentum fading or the curve easing, respect the odds of a further run and reassess.

• Optional hedge: pair the short with a protective UVXY call (cap the tail while preserving decay).

• Sizing: assume a non-trivial chance of a press to +75% and a smaller—but real—chance of +100%.

Targets / Exits:

• First scale-out on a decisive failure back below prior spike highs or on a return toward the episode’s rising base.

• Consider staggered covers (e.g., thirds) to harvest decay while keeping optionality if the unwind accelerates.

Why Not Short Earlier?

• +10% or +20% pops still carry substantial continuation risk; when they extend to +50%, they often do so within days—too fast for tight risk budgets.

• +40% specifically tends to “finish the job” to +50%. Shorting right there is statistically fighting the last push.

Practical Checklist

• First tag of +50% this episode

• Failed hold / momentum divergence appears

• VIX curve easing (backwardation cooling)

• Stop near +75%; consider protective call

• Time window: look for resolution within ~1–2 weeks

The highest-quality UVXY fades tend to cluster around the first +50% spike off an ATL—where the “inevitable” push from +40% is behind you, the odds of further extension flatten, and the time to find out is short enough to manage. Build entries around that zone, demand confirmation, and always price in the tail. (This is not investment advice.)

A quick look at BOIL’s historical chart and it’s obvious shorting BOIL has been remarkably profitable over the long term.

Across all 12 months, BOIL has declined an average of -3.32% per month. Which translates to a theoretical 3.32% monthly profit for short sellers.

BOIL finishes red an average of 62.9% of all months, but not all months are created equal.

Monthly Performance Breakdown

Note: Positive "Expected Short Profit" indicates months favorable for shorting

The Top 4 Shorting Months

November

November stands out as the absolute best month for shorting BOIL, with an extraordinary 22.06% expected profit and an 83.3% win rate. This makes sense from a fundamental perspective because November marks the transition from the injection season to the withdrawal season.

January

January delivers a solid 10.35% expected profit with a 75% win rate. The winter heating demand peak typically occurs in December and early January, making late January a natural inflection point as weather moderates and storage concerns ease.

December

Despite being a winter month, December shows 8.92% expected profits for shorts.

April

April's 7.41% expected profit and 73.3% win rate align with the beginning of the injection season, when natural gas demand typically falls as heating needs diminish and cooling season hasn't yet begun.

Seasonal Patterns

The data reveals distinct seasonal biases:

• Winter (Dec-Feb): -6.25% average return, 67.4% short win rate

• Fall (Sep-Nov): -7.37% average return, 62.8% short win rate

• Summer (Jun-Aug): -0.66% average return, 70.0% short win rate

• Spring (Mar-May): +1.42% average return, 51.2% short win rate

Key Insight: Avoid shorting during spring months, especially May, which shows the worst performance for shorts with a -7.81% expected loss.

The Volatility Factor: Risk and Reward

BOIL's 26.38% monthly volatility creates both opportunity and risk. While the average short position profits 3.32% per month, individual months have seen:

• Best month for shorts: +59.73% (November 2014)

• Worst month for shorts: -109.10% (June 2022)

This extreme volatility underscores the importance of position sizing and risk management. Even in historically favorable months, catastrophic losses remain possible.

Building a BOIL Shorting Strategy

If You’re Conservative

Focus exclusively on November and January shorts with tight stop losses and modest position sizes. This approach maximizes win rate while limiting exposure to extreme volatility.

Moderate Approach

Add December and April to the mix, potentially increasing allocation during November for maximum profit potential.

If You’re Aggressive

Include June and October shorts, but maintain strict risk management due to higher volatility in these months.

Forbidden Territory

Never short BOIL in May. May represents the worst possible month for shorts, with only a 41.7% win rate and an average loss of 7.81%.