Does Max Pain Really Work? Data From 100 SPX Expirations

If you spend any time around options traders, you’ll hear the term “max pain” over and over.
Some traders swear by it as a reliable expiration “magnet.” Others roll their eyes and call it just another trading myth that falls apart the moment the market gets volatile.

As someone who has traded SPX options for many years and now runs automated spread strategies, I’ve seen both sides in real time. There are expirations where the index seems glued to a max pain level into the close, and others where one macro headline blows straight through it as if it never existed.

That’s why I prefer data over opinions. Instead of arguing about whether max pain “should” work, I wanted to know how often it actually does in live markets. So I looked at a sample of 100 recent SPX expirations to see how often the index finished near its max pain level — and under what conditions it completely failed.

In this article, I’ll walk you through:

• What max pain really claims to predict
• How I structured a simple 100-expiration SPX study
• Why the results matter more for spread traders than for pure directionals

The goal here isn’t to sell you on a magic indicator. It’s to give you a realistic, data-backed view of
what max pain can and cannot do, so you can decide how (or if) to use it in your own SPX and SPY strategies.

If you’re completely new to the idea of max pain, you may want to start with my plain-English guides on the max pain strategy and what max pain is and how I use it in SPX and SPY options. This article builds on those foundations and focuses on whether the concept actually holds up in real expiration data.

What Max Pain Claims to Predict

At a basic level, max pain is the price at expiration where the greatest total value of outstanding
options (calls plus puts) would expire worthless. That’s the point where option buyers feel the most “pain” and option sellers keep the most premium.

The theory behind a max pain strategy usually goes like this:

• Market makers and large liquidity providers are often net short options.
• They hedge their exposure as price moves, buying or selling futures or stock to stay close to delta-neutral.
• As expiration approaches, their hedging flows can sometimes nudge price toward the level that minimizes their payouts – the max pain price.

If that mechanism is strong enough, SPX or SPY should have a tendency to “pin” near their respective max pain levels on expiration days. That’s the appeal: a clean, simple level that offers a probabilistic target for spread traders, short premium traders, or anyone managing risk into expiry.

If you’d like a textbook-style explanation alongside this more practical view, you can also read Investopedia’s article on the max pain theory and compare it with the data I’m about to walk you through.

But that’s the theory. In the real world, other forces compete with market-maker hedging: macro news, large directional flows, ETF activity, gamma positioning, liquidity gaps, and plain old fear and greed. So the real question isn’t “Is max pain a neat concept?” — it’s “How often does price actually finish near that level in live trading conditions?”

To answer that, I treated max pain as a hypothesis and tested it against real SPX expiration data.

Methodology: How I Studied 100 SPX Expirations

To keep this study grounded and transparent, I used a simple, rule-based approach. The goal wasn’t to build a perfect academic model, but to run a clean, practical check that reflects how a real trader might evaluate max pain.

Step 1: Select the Expirations

I looked at a sample of 100 SPX expiration days, including a mix of:

• Monday expirations
• Wednesday expirations
• Friday expirations

This gave a balanced view across the weekly cycle, rather than cherry-picking just one “favorable” day of the week.

Step 2: Record the Max Pain Level

For each expiration, I recorded the max pain level for that specific options chain before expiration.
In other words, I treated max pain as a forward-looking reference level – the same way a trader would see it on their screen ahead of the close.

Step 3: Compare SPX Close to Max Pain

Once the expiration day closed, I compared the final SPX settlement/closing price to the pre-recorded max pain level. To make the results meaningful, I measured how far SPX finished from max pain using simple percentage bands:

• Within ±0.50% of max pain
• Within ±1.00% of max pain
• Within ±2.00% of max pain

These bands roughly capture three different regimes:

• ±0.50%: Very tight pinning – the kind spread traders love.
• ±1.00%: Reasonably close – useful for ranges and defined-risk trades.
• ±2.00%: Loose but not completely off – borderline helpful context.

Step 4: Keep It Realistic

This was an observational trading study, not a backtest with hindsight-optimized parameters.
I didn’t filter out “ugly” days, I didn’t curve-fit, and I didn’t assume you could always trade perfectly at
the exact settlement level. The aim was to answer a very practical question:

Over a broad sample of expirations, does SPX show a real tendency to finish near its max pain level, or is that mostly a story traders tell themselves?

In the next section of the article, I break down the actual percentages from those 100 expirations and show where max pain helped, where it did nothing, and where it completely failed – especially during high-volatility and major news weeks.

All of this is framed from the perspective of a defined-risk spread trader. My goal wasn’t to prove a perfect prediction model, but to test whether max pain provides a useful edge for structures like credit spreads and iron condors. If that’s your focus too, you’ll also want to see how I plug max pain directly into credit spread and iron condor construction.

Results Summary: What the Data Actually Showed

Once I compared the SPX closing price against the recorded max pain levels across 100 expirations,
the pattern was surprisingly consistent. Max pain didn’t “predict” the exact settlement price —
but it wasn’t random noise either.

Here’s the high-level breakdown:

The most important takeaway for traders is this:

SPX finished within ±1% of max pain in 48 out of 100 expirations.

That means max pain isn’t a magic magnet — but it’s far from useless.
It behaves like a soft gravitational pull that becomes meaningful especially in calm or balanced markets.

For defined-risk spreads or neutral strategies, knowing the statistical tendency helps you lean into
higher-probability setups — as long as you avoid the conditions where max pain historically breaks down.

For spread traders, that ±1% behavior is exactly where the edge lives. You don’t need a perfect pin; you just need price to stay inside a sensible range around your short strikes. In my own trading, I use this tendency as a background assumption when I’m choosing SPX credit spread and iron condor strikes with max pain as a filter.

SPX vs SPY: Which One Pinned More Often?

One pattern that jumped out immediately: SPX pinned more consistently than SPY.

This lines up with what I’ve seen in my own live trading and automated systems.
SPX is institution-driven and cash-settled, while SPY is share-settled and heavily influenced by ETF flows and retail activity.

Here’s the side-by-side comparison:

One pattern that jumped out immediately: SPX pinned more consistently than SPY. SPX finished within ±1% of its max pain level 48% of the time, while SPY did so only 37% of the time. That lines up with what I see live — SPX is cash-settled and institution-driven, while SPY is share-settled and full of ETF and retail noise. I break down those structural differences in detail in my SPX vs SPY max pain comparison, and I cover SPY’s unique quirks more deeply in the SPY max pain guide.

Max Pain Accuracy by Day of Week

Not all expirations behave the same. One of the more interesting findings in the 100-expiration dataset was
how pinning varied depending on the day of the week.

Wednesdays showed the strongest pinning behavior — something I’ve noticed repeatedly in my own trading.
Mid-week flows tend to be more balanced, market makers have clearer hedging requirements,
and there are fewer extreme overnight gaps compared to Mondays.

It’s not that Wednesday is a guaranteed pin day — there’s no such thing —
but the probabilities generally favor more controlled price action.

For traders running weekly credit spreads or iron condors, this kind of pattern is useful context,
especially when deciding which expirations to target for tighter-range strategies.

This is one of the reasons I like structuring most of my defined-risk SPX spreads around mid-week expirations. Many of the signals inside my automated services lean on this pattern: use Wednesday expirations when the tape is calm, and be much more selective on Mondays and high-event Fridays.

…Many of the signals inside my Weekly Premium SPX service lean on this pattern…

High-Vol vs Low-Vol Weeks: Why Max Pain Works Better in Calm Markets

If there’s one factor that consistently determines whether max pain behaves well or completely falls apart,
it’s volatility. When markets are calm, hedging flows are smooth and predictable.
When volatility spikes, max pain becomes almost meaningless.

Here’s what the data from 100 SPX expirations showed:

These numbers match exactly what I’ve observed in real trading.
When VIX is under 15 and the market is grinding sideways, SPX often drifts toward max pain naturally.

But when VIX jumps over 22, market makers aren’t guiding price — they’re reacting to it.
Their hedging becomes defensive and highly sensitive, and the market starts moving on directional flows,
news events, and momentum — not open interest.

This is why I tell traders:

“Max pain is a roadmap in calm markets, and just noise during high volatility.”

In my core max pain strategy, this is the first filter I apply: if VIX is elevated or a major macro event is on the calendar, max pain is background noise only. When volatility compresses again, it comes back onto the screen as a useful reference level.

When Max Pain Worked Best

During the 100-expiration study, there were clear scenarios where max pain showed strong, consistent influence.
These weren’t random — they aligned with specific types of market structure and behavior.

• Low Volatility Weeks: Calm markets allow hedging flows to dominate.
• No Major Economic Events: When CPI, FOMC, NFP, or earnings didn’t hit the calendar, SPX behaved more smoothly.
• Stable Gamma Exposure: When dealers were long gamma, price naturally gravitated toward balanced levels.
• Tight Trading Ranges: The market had no reason to break away from the strike clusters.
• Mid-Week Expirations: As seen earlier, Wednesdays displayed the most consistent pinning behavior.

In these conditions, SPX often closed within a tight range of its max pain level, giving spread traders
a statistical edge — not a guarantee, but a measurable advantage.

This is also why many systematic traders (and many of the automated models we run at Advanced AutoTrades)
treat max pain as a secondary filter that increases confidence in a neutral or range-bound setup.

When Max Pain Failed

Even though max pain worked roughly half the time in the 100-expiration sample, its failures were not random.
They followed very clear and predictable patterns — the same patterns I see repeatedly in my own automated SPX systems.

1. High-Volatility Weeks (VIX > 22)

When volatility spikes, price begins to move too aggressively for market makers to “pin” anything.
Their hedging becomes reactive rather than controlling, and max pain loses almost all influence.

2. CPI and FOMC Weeks

Major macro events inject massive uncertainty and directional flows.
CPI and FOMC are the two biggest culprits. During these weeks:

• Options volume surges
• Dealers hedge defensively
• Large institutional flows overpower open interest positioning

SPX commonly blows far past max pain in minutes following these announcements.

3. Fed Speeches and Rate Surprises

Even non-FOMC Fed commentary can move markets aggressively.
Powell, Williams, or other Fed members shifting tone → fast repricing → max pain becomes irrelevant.

4. Geopolitical Events

War headlines, sudden energy price spikes, sanctions, and similar global shocks
have historically produced the largest deviations from max pain.

5. Liquidity Gaps: Mondays & Holidays

Thin liquidity is kryptonite for max pain.
During holiday weeks, Monday opens, or overnight gaps:

• SPX moves too quickly
• Dealers cannot rebalance smoothly
• Price jumps outside hedging bands

Even Fridays — normally strong pinning days — can fail when liquidity dries up or futures move heavily overnight.

These patterns reinforce one simple rule:

Max pain is an influence, not a force. It helps until something bigger shows up.

These are also the conditions where automated systems tend to shine, because the rule-set can be built around stable dealer hedging behavior. In my automated options trading guide I show how max pain, volatility filters and open-interest structure all fit into a rules-based framework.

Practical Takeaways for Traders

After reviewing 100 SPX expirations — and comparing those results with years of my own live trading and automated system data —
the takeaway is clear:

Max pain is useful, but only if you understand when it works and when it absolutely doesn’t.

Here are the practical lessons every options trader should keep in mind:

1. Max Pain Is Context, Not a Prediction

Treat max pain like a reference level, not a target.
It offers probabilistic insight into where price may drift if conditions are stable,
but it should never be the sole basis for a trade.

2. Defined-Risk Spread Traders Benefit the Most

Credit spreads and iron condors naturally thrive in environments where price converges toward equilibrium levels.
Max pain helps by telling you where those equilibrium points tend to form.

• Range-bound spreads
• Neutral iron condors
• Short-term credit spreads

These strategies don’t require perfect pinning — just probability.
That’s where max pain shines.

3. Max Pain Works Better on SPX Than SPY

SPX is driven by institutional hedging and cash settlement.
SPY is influenced by retail flows, intraday ETF mechanics, and share settlement risk.
The data confirms what many pros already know:

Use SPX for cleaner max pain signals; use SPY only for intraday context.

4. Always Check the Volatility Regime

If VIX is elevated, ignore max pain.
Directional flows and volatility shocks completely overwhelm any pinning behavior.

5. Watch the Economic Calendar

CPI, FOMC, NFP, and Fed speeches override everything.
Don’t expect the market to “pin” when the macro backdrop is moving the entire market.

6. Don’t Trade Max Pain in Isolation

Use it as a confidence enhancer layered on top of:

• delta structure
• gamma exposure
• trend context
• volatility environment
• support/resistance levels

Max pain is the final check — not the starting point.

If that’s your playbook, make sure you also read my step-by-step guide on using max pain with credit spreads and iron condors, where I translate these findings into concrete entry and strike-selection rules.

Conclusion

So, does max pain really work?
The answer, based on 100 SPX expirations, is:

Yes — but only about half the time, and only under the right conditions.

It performs best in low-volatility environments, especially on SPX, and breaks down consistently during
high-volatility weeks or major economic events.
Used correctly, max pain helps you understand where the market wants to go — but it won’t force anything.

For traders running defined-risk spreads, it’s a valuable secondary filter.
But it becomes exponentially more powerful when paired with a systematic approach that manages risk, position sizing,
and execution automatically.

That’s exactly how our automated SPX systems operate.
If you want to integrate data-backed expirations, consistent entries, and institutional-level risk management
into your trading, you can start using our Weekly Premium SPX Iron Condor Signals.

Trade with confidence, not guesswork.
Your next step → Weekly Premium SPX Signals

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