Model, not market data

Priced fairly, the premium from winning weeks is about matched by the losses in the others

Model, not market data. Priced fairly, the premium from winning weeks is about matched by the losses in the othersProfit: 83 weeks in 100 2,51,056; Loss, all 17 weeks in 100 −2,51,316; of which up to 3x premium −29,093; of which 3 to 10x premium −1,36,424; of which over 10x premium −85,800.Per 100 weeks, one lot, before costs; L is lakhProfit: 83 weeksin 100+2.51LLoss, all 17weeks in 100−2.51Lof which up to 3xpremium−0.29Lof which 3 to 10xpremium−1.36Lof which over 10xpremium−0.86L
Model of one lot sold each week for a hundred weeks at its fair price, from the 10 Jun 2026 chain, expiry 16 Jun 2026. Before costs. The bands count losses as multiples of the premium. Inputs: one lot of 65 units of the Nifty 23,600 call sold at its settlement premium of Rs 47.05 a unit on 10 Jun 2026, expiry 16 Jun 2026; the forward 23,229.26 and the option's own implied volatility 14.42% over 6 calendar days; the index at expiry follows a lognormal curve around the forward; 100 weeks; before costs and interest. Source: RupeeCase model, inputs from NSE end of day data. As of 10 Jun 2026.

Theta is real, and a seller does collect it. The option loses value as time passes, and the seller keeps the premium if the index stays on the right side of the strike. The question is what the losses look like on the other side of the same trade.

The chart is a model, not market data. It takes one NIFTY weekly call from the 10 Jun 2026 chain, expiry 16 Jun 2026, priced at its own implied volatility, so the premium equals its fair value. It sells one lot a week for a hundred weeks, each week a new sale at that price. The bars show the total from winning weeks and from losing weeks, with the losses split into bands by size.

The bars net off. The model gives the seller no edge by design, so the premium from winning weeks is matched by the losses in the others, and the result is close to nothing before costs. Costs then take their share: brokerage, exchange charges, GST, STT and the margin tied up. Whether real markets pay sellers somewhat more than fair for carrying this risk is a separate question, and any such extra arrives with the large losses.

Losses above three times the premium carry most of the total. SEBI's August 2026 study of FY25 and FY26 found that options made up 92% of individual losses. A second SEBI study that month, on trading behaviour, found that among traders active in all five years from FY22 to FY26, only 0.5% were profitable in every year. The income story leaves out the band that matters.

Before you trade. Derivatives trading carries a high risk of loss. SEBI's study "Profitability of Individual Traders in the Equity Derivatives Segment (FY25 to FY26)" (August 2026) found that 87.7% of individual traders in equity F&O made net losses in FY26, with aggregate net losses of Rs 91,685 crore. Read the SEBI study