Max Pain, also called Option Pain, is one of the more debated concepts in options trading.
The theory is based on the idea that option buyers and sellers participate in a zero-sum market: what one side gains, the other side loses.
The theory further assumes that option writers tend to make money more consistently than option buyers.
From this assumption, the theory tries to identify a price level at which option writers would experience the least amount of loss.
That price is referred to as the Max Pain level.
The theory follows a chain of assumptions.
If option sellers tend to make money more consistently, the theory reasons that:
The theory therefore attempts to answer a simple question:
At which strike would option writers collectively experience the least amount of loss at expiry?
Max Pain should not be treated as a guaranteed expiry prediction.
The source itself presents Option Pain as a controversial theory and explains that the author's own experience with it was mixed.
The calculated Max Pain level can change as open interest changes.
Therefore, a Max Pain level calculated today may not remain the same closer to expiry.
This is an important reason to treat the concept as an analytical reference, rather than a certainty.
The calculation is based on the Open Interest (OI) of Calls and Puts at different strikes.
The basic process can be broken into steps.
Start by listing the different option strike prices available on the exchange.
For each strike, record:
Now take one strike at a time.
For example, assume:
"What if the underlying expires exactly at this strike?"
Repeat this calculation for every relevant strike.
This allows you to determine the total loss that option writers would experience if expiry occurred at each possible price.
For every assumed expiry level, calculate the intrinsic value payable on the outstanding options.
The losses from Calls and Puts are then added together.
The process is repeated for all the strikes.
The strike producing the lowest total loss for option writers becomes the Max Pain level.
Suppose the calculations produce the following results:
| Assumed Expiry Level | Total Writer Loss |
| 7,600 | Higher |
| 7,700 | Lower |
| 7,800 | Lowest |
| 7,900 | Higher |
| 8,000 | Higher |
In this simplified example:
Max Pain = 7,800
According to the theory, 7,800 would be the level where option writers experience the least amount of loss.
The source gives an example where 7,800 was identified as the level at which option writers would lose the least amount of money.
Once a Max Pain level is identified, traders may use it as a reference for option-writing strategies.
For example, if the calculated Max Pain level is 7,800, one possible approach described in the source is:
The underlying assumption is that the market may gravitate towards the identified expiry level.
However, this should not be interpreted as a guaranteed strategy.
The Max Pain level itself can change as market positioning changes.
Open Interest is not fixed.
Traders continuously:
As a result, the OI distribution changes.
Since Max Pain is calculated from OI, the calculated Max Pain level can also change.
For example:
10 May β Max Pain = 7,800
20 May β Max Pain = 8,000
Both calculations can be correct for their respective dates because the underlying option positioning has changed.
The source describes a personal modification to the standard Max Pain approach.
The process involved:
For example, if Max Pain indicated 7,800, adding a 5% buffer produced approximately:
7,800 + 5% = 8,190
This was rounded to approximately 8,200.
The expected expiry range was therefore considered to be roughly:
7,800 to 8,200
Markets rarely move according to an exact number.
Even if Max Pain suggests a particular expiry level, the underlying can expire meaningfully above or below that level.
Using a range therefore provides some flexibility.
The source describes using the range to identify strikes for option writing rather than assuming that the market must expire exactly at the calculated Max Pain value.
The source describes avoiding Put writing as part of this particular modification.
The reasoning given is:
Panic spreads faster than greed.
In other words, markets can sometimes fall much faster than they rise.
Therefore, writing Calls beyond the upper end of the expected expiry range was preferred over writing Puts below the lower end.
This is a specific risk-management preference described in the source, rather than a universal rule for all traders.
The second major concept in this chapter is the Put-Call Ratio, commonly called PCR.
PCR is a simple ratio that compares:
Put Open Interest
with
Call Open Interest
PCR = Total Put Open Interest Γ· Total Call Open Interest
Suppose the total Open Interest is:
Then:
PCR = 37,016,925 Γ· 42,874,200
PCR β 0.86
This is the example provided in the source.
PCR is generally interpreted as an indicator of market sentiment.
The source treats it primarily as a contrarian indicator.
This means that extreme readings can potentially signal that the market has become excessively bullish or bearish.
The basic idea is:
Extreme bearishness β Look for possible bullish reversal
Extreme bullishness β Look for possible bearish reversal
A high PCR indicates that Put Open Interest is relatively large compared with Call Open Interest.
The source gives 1.3 as an example of a high PCR.
A value around or above this level can indicate extreme bearishness.
From a contrarian perspective, excessive bearishness may suggest that the market is oversold and could potentially reverse upward.
Therefore:
High PCR β Extreme bearishness β Possible bullish reversal
A low PCR indicates that Call Open Interest is relatively large compared with Put Open Interest.
The source gives 0.5 and below as an example of a low PCR.
This can indicate extreme bullishness.
From a contrarian perspective, excessive bullishness may suggest that the market is overbought and could potentially reverse downward.
Therefore:
Low PCR β Extreme bullishness β Possible bearish reversal
The source suggests that values between approximately 0.5 and 1 can generally be treated as normal trading activity.
Such readings do not necessarily represent extreme sentiment.
Therefore, the focus is primarily on unusually high or unusually low readings.
The reasoning is based on positioning.
Suppose traders become extremely bearish.
Many traders may already have taken bearish positions.
If most of the market is already positioned in one direction, there may be fewer participants left to create another strong move in that same direction.
Eventually, these positions may be closed.
This can contribute to a move in the opposite direction.
The same logic applies when the market becomes extremely bullish.
This is the basic reasoning behind using PCR as a contrarian indicator.
A single PCR number should not automatically be interpreted as extreme.
The appropriate level can differ between:
For example, a PCR of 1.3 may represent extreme bearishness for one underlying, while another underlying could normally trade around a different range.
The source therefore suggests historically plotting PCR values and identifying what constitutes extreme readings for the particular underlying.
Backtesting can help establish these ranges.
Although both concepts use option-market data, they answer different questions.
| Feature | Max Pain | PCR |
| Main input | Call & Put OI by strike | Total Put & Call OI |
| Main purpose | Identify potential expiry level | Assess market sentiment |
| Key concept | Least pain for option writers | Relative Put vs Call positioning |
| Interpretation | Possible expiry reference | Bullish/bearish sentiment |
| Approach | Expiry-level analysis | Contrarian sentiment analysis |
They can therefore be studied together, but they should not be confused with one another.
Neither Max Pain nor PCR should be treated as a standalone prediction tool.
Max Pain depends on changing Open Interest.
PCR can also change as traders alter their positions.
Therefore, these indicators are better understood as additional information about market positioning, rather than guaranteed signals.
The source's own discussion of Max Pain highlights how the calculated level can change and how practical modifications were required to make the approach more suitable for risk management.