Max pain is the index level at which option buyers, taken together, would receive the least money if all options expired there. Equivalently, it is the level where option writers as a group would pay out the least. Many option chain websites in India display it next to PCR.
The idea behind it
The theory says that because option writers are often large, well-capitalised participants, the underlying tends to drift towards the level that hurts option buyers most as expiry approaches. It is a popular idea; the evidence for it as a reliable predictor is weak, as discussed below.
How to calculate it
- Take every strike on the chain for one expiry, with its call OI and put OI.
- Pick a candidate settlement level, usually each strike in turn.
- For every call strike below that level, the payout is (level - strike) × call OI. For every put strike above it, the payout is (strike - level) × put OI. Options on the other side pay nothing.
- Add up all payouts for that level.
- Repeat for each candidate level. The level with the smallest total is max pain.
A worked example
Using the same made-up chain as in our PCR guide (OI in thousands of contracts at strikes from 24,800 to 25,200), the total payout at each level, in index points × thousands of contracts, is:
| Settlement level | Paid to call buyers | Paid to put buyers | Total |
|---|---|---|---|
| 24,800 | 0 | 35,000 | 35,000 |
| 24,900 | 2,000 | 17,000 | 19,000 |
| 25,000 | 7,500 | 6,000 | 13,500 |
| 25,100 | 19,000 | 1,500 | 20,500 |
| 25,200 | 38,500 | 0 | 38,500 |
The smallest total is at 25,000, so that is the max pain strike for this chain. Multiply by the lot size to convert points into rupees; the ranking does not change.
Illustrative only
The chain above is invented to show the method. We do not publish live max pain levels for any index or stock.
Reading the example
- Below the max pain level, payouts to put buyers grow quickly because the chain has large put OI at the lower strikes.
- Above it, payouts to call buyers grow because call OI is concentrated at the higher strikes.
- Max pain tends to sit between the strikes with heavy put OI and those with heavy call OI. With a different distribution of OI, it can land well away from the current index level.
- Because Nifty strikes near the money are typically 50 points apart and real chains have dozens of strikes, the calculation on a live chain uses many more rows than this example, but the method is the same.
Index vs stock options
Max pain is quoted for both index and stock options. For stock options, which are physically settled and often less liquid, open interest can be concentrated in a few strikes and the number can jump when a few large positions change. For indices it reflects a far larger and more diverse set of positions, many of them hedges. In both cases it is computed from the same open interest data and shares the same limits.
The limits of max pain
- It ignores premiums. Writers received premium when they sold; their actual profit depends on it, not only on the payout.
- It ignores hedges. Many positions are spreads or are hedged with futures, so the payout on one leg is offset elsewhere.
- It assumes writers act together and can move the index. Nifty and Sensex are large, liquid indices driven by the underlying shares, global markets and news; no group of option writers controls them.
- It keeps moving. OI changes all day, especially in the last sessions before expiry, so max pain calculated in the morning may be different by the afternoon.
- It is circular. If many traders act on max pain, their own positions change the OI that max pain is calculated from.
Not a forecast
The index frequently settles far from the max pain level. Treat max pain as a summary of where open interest is concentrated, not as a target for expiry.
If you use it at all
- Use it as one description of positioning alongside OI per strike and PCR.
- Note the time it was calculated and the expiry it refers to.
- Never size a position on the assumption that the index will settle at max pain.
Examples use illustrative values, not current market data. This is general education, not investment advice.