Max Pain Calculation
A step-by-step method for computing the strike price at which all outstanding option contracts in Nifty or any F&O series would expire worthless at the greatest aggregate value, representing the maximum financial loss to collective option buyers.
Max pain, also called the maximum pain price or option pain, was derived from the hypothesis that option sellers (writers), who were often well-capitalised entities such as market makers and institutions, influenced or were correlated with expiry-day price outcomes. The calculation identified the strike where the total payout to option buyers was minimised.
The step-by-step calculation for Nifty proceeded as follows. First, collect the open interest data for all call strikes and all put strikes from NSE for the current expiry. Second, for each possible expiry price (each listed strike), compute the total loss to call holders: for every call strike below the hypothetical expiry price, multiply the OI by the difference between the expiry price and that call strike, times the lot size. Sum all these values. Third, perform the same computation for put holders: for every put strike above the hypothetical expiry price, multiply OI by the difference between the put strike and the expiry price, times the lot size. Fourth, add the call holder loss and put holder loss for each hypothetical expiry price. The hypothetical expiry price that produces the largest combined loss to option buyers (or equivalently, the largest combined gain to option writers) was the max pain strike.
Practitioners graphed this calculation as a curve, with strike prices on the x-axis and total option buyer loss on the y-axis. The trough of the curve identified the max pain strike. In Nifty, this was typically computed weekly near each Thursday expiry and published by multiple analytics platforms and brokers.
The max pain theory was not a deterministic price target. Empirical observation in Nifty found that expiry prices clustered around max pain more often than pure random chance would suggest, particularly in low-volatility, range-bound market phases. In high-volatility phases or when a significant news event landed near expiry, actual expiry prices diverged widely from the max pain level.
The calculation gained practical relevance because it was widely tracked and itself influenced participant behaviour — a self-referential dynamic. Sellers who were net short options near max pain had incentive to hedge accordingly, which could contribute to price convergence toward that level.