Options Essentials & Hedging

1. What you'll learn and why it matters

In Chapter 9 you learned futures: a linear bet where every point the market moves is a point gained or lost. An option is different. It gives one side a choice, and that choice has a price. That changes everything about the payoff, and it makes options the main tool professionals use to insure positions.

This chapter is deliberately narrow. It covers what a swing trader, a long-term investor or a futures trader needs to know about options so they can (a) protect positions, (b) read what the options market is saying about risk, and (c) avoid the traps that cost most retail option traders their money. It does not try to turn you into an options trader.

By the end you will be able to:

• Explain calls and puts, buyers and sellers, and draw all four payoff diagrams with their breakevens.
• Split any premium into intrinsic value and time value, using the real Nifty option chain of 30 Sep 2026.
• Price an option with Black-Scholes, back out its implied volatility, and explain why the model and the market differ.
• Use delta, gamma, theta and vega to predict how a premium will move. We will reconcile a real one-day move to within half a point.
• Read open interest, PCR and max pain, and know how little weight to put on them.
• Build and size a protective put, covered call, collar, bull call spread and bear put spread, with real prices including the March 2026 fall.
• Understand why ~88% of individual F&O traders lost money in FY26 (SEBI), why option buying usually loses, and why option selling can wipe you out in one month.
• Handle expiry, physical settlement of stock options, margins and STT under the rules in force in October 2026.

2. Options in plain language: a right, not an obligation

Suppose you want to buy a flat that costs ₹80 lakh, but you will only know in three months whether you get a job transfer to that city. You pay the builder a non-refundable ₹1 lakh to hold the price at ₹80 lakh for three months. Three things can happen:

1. Prices in the area jump to ₹95 lakh. You use your right, buy at ₹80 lakh, and are ₹15 lakh better off before the ₹1 lakh fee, so ₹14 lakh net.
2. Prices fall to ₹70 lakh. You walk away. You lose only the ₹1 lakh.
3. Prices stay at ₹80 lakh. There is no reason to use the right. You lose the ₹1 lakh.

That fee bought a right without an obligation. The builder took the fee and accepted an obligation: he must sell at ₹80 lakh if you ask. He wins in two of the three scenarios, but his gain is capped at ₹1 lakh while his potential loss is large. That asymmetry between buyer and seller runs through this whole chapter.

The logic. An option splits the upside and downside of an asset and sells one side separately. A put buyer pays to give away the downside below the strike. A call buyer pays to get only the upside above the strike. The premium is the market's price for that slice of risk, so the hard part of options is judging whether the slice is fairly priced. Sections 6 to 8 deal with that.

You rarely have to hold until expiry. A buyer can sell the option back at any time before expiry and book the change in premium. That is how most option positions end.

3. The vocabulary, and how Indian contracts work today

• Underlying: the asset the option is written on, such as the Nifty 50 index or RELIANCE shares.
• Strike price (K): the fixed price at which the buyer may buy (call) or sell (put). NSE lists many strikes. On 30 Sep 2026, the 27-Oct Nifty series had strikes 50 points apart near the money.
• Expiry: the last day the contract lives. After it, the option is settled and disappears.
• Premium: the price of the option, quoted per unit of the underlying. The buyer pays premium × lot size.
• Lot size: the fixed quantity per contract. Nifty is 65 (since the January 2026 series) and RELIANCE is 500. Both figures come from the 30-Sep-2026 bhavcopy.
• Exercise style: all Indian exchange options are European. They are exercised only at expiry, though you can trade out at any time before.
• Settlement: index options are cash-settled at the final settlement price (the index close on expiry day). Stock options that finish in the money are physically settled, meaning shares change hands (Section 12).
• Open interest (OI): the number of contracts still open (Section 9).

4. Moneyness, intrinsic value and time value

4.1 Intrinsic value: what the option is worth if it expired right now

4.2 Moneyness

• In the money (ITM): the option has intrinsic value. Calls with \(K < S\), puts with \(K > S\).
• At the money (ATM): the strike closest to spot. On 30 Sep 2026 Nifty closed at 22,620.45, so the ATM strike was 22600.
• Out of the money (OTM): no intrinsic value. Calls with \(K > S\), puts with \(K < S\). Their premium is entirely time value.

The same strike is ITM for one type and OTM for the other. The 23000 strike was an OTM call but an ITM put on 30 Sep 2026.

4.3 Time value: the price of possibility

The logic. Before expiry there is still a chance the option ends up deeper in the money, while the buyer's loss is capped at the premium. The buyer pays for that chance, and the payment is the time value. It is largest at the money, where the outcome is most uncertain, and it shrinks to zero by expiry.

5. The four basic positions and their breakevens

Every option strategy is built from four blocks. Here they are with the real 22600 strike for 27-Oct-2026: call premium 372.90, put premium 258.05. \(S_T\) is the Nifty level at expiry.

5.1 Mapping a view to a position

Profit and loss before expiry (Varsity's M2M chapter) is simpler than it looks. For a buyer it is (exit premium − entry premium) × lot size × number of lots. Buyers pay the full premium upfront, so there is no daily mark-to-market. Sellers post margin, and that margin rises when the premium moves against them (Section 12).

6. What sets the premium: Black-Scholes on a real strike

6.1 The five inputs, and what each one does

Four of these are observable. Volatility is the only input nobody knows, which is why options trading is in large part volatility trading.

6.2 The Black-Scholes formula

6.3 Model vs market, and implied volatility

Run the formula backwards: find the \(\sigma\) that makes the model price equal the market price. That number is the implied volatility (IV), the volatility the market is charging for. For the 22600 CE at 372.90 it comes out at 12.85%, below India VIX at 13.49%.

Why the gaps? (1) India VIX blends many strikes across the two nearest monthly expiries, so it is not the IV of any single option. (2) The market charges more for downside puts (22000 PE at 14.14% IV) than for upside calls (23200 CE at 11.94%). Black-Scholes assumes one volatility for every strike, so it misprices both wings (Section 8.4). (3) Closing prices are snapshots, and the model ignores dividends. Treat Black-Scholes as a consistent ruler for comparing options, not as the true value. Varsity's Greek-calculator chapter uses it the same way: when the market price is well above the model at a sensible volatility, the option is expensive relative to that volatility.

6.4 Put-call parity: why calls and puts are tied together

Check with real numbers: \(C - P = 372.90 - 258.05 = 114.85\). The right side is \(22{,}620.45 - 22{,}509.90 = 110.55\). They differ by about 4 points (under 0.02% of spot). That is small enough to come from closing prices struck at slightly different moments and from our 5.4% interest-rate assumption. (Expected dividends would push the gap the other way, so they are not the explanation.) Rearranged, the implied forward is \(K + (C-P)e^{rT} = 22{,}715.31\), close to the actual October future at 22,707.30. If the gap were large, traders would buy the cheap side and sell the dear side until it closed. Varsity's "synthetic long & arbitrage" chapter covers this. One practical point follows: long futures + long put behaves like a long call, which is exactly what a protective put is.

7. The Greeks: delta, gamma, theta, vega

The Greeks measure how the premium responds when one input changes and the others are held still. Here are the Black-Scholes Greeks for our two ATM options (27-Oct, vol 13.49%):

7.1 Delta: how much the premium moves per point of the underlying

• Meaning: a delta of 0.56 means that if Nifty rises 100 points, the call gains about 56 points, other things equal. A put delta of −0.44 means the put gains about 44 points when Nifty falls 100.
• By moneyness: deep ITM is close to 1 (behaves like the underlying), ATM is about 0.5, deep OTM is close to 0. As expiry approaches, delta moves towards 0 or 1 more sharply (Figure 3).
• As a rough probability: traders read delta as the chance of finishing ITM. The cleaner model number is \(N(d_2)\) = 0.546 for the 22600 call, close to its delta of 0.560.
• Deltas add. A position's delta is the sum of its legs. Long one future (delta +1) plus a long 22600 PE (−0.44) gives net +0.56 per unit, the same as a call. Roughly two ATM calls (2 × 0.56 ≈ 1.1) carry the directional exposure of one future. This is how you measure how much directional exposure a hedge has left.

7.2 Gamma: how fast delta changes

Gamma is delta's rate of change, the "acceleration" to delta's "speed". With gamma 0.00048, a 100-point rise lifts the call's delta from about 0.56 to about 0.61. Gamma is highest at the money and, crucially, it explodes at the money as expiry approaches (right panel of Figure 3). On the last day, an ATM option can swing from nearly worthless to worth a lot within a few dozen index points. That is a gift to the buyer and a danger to the seller. Varsity's rule follows from it: avoid being short ATM options close to expiry.

7.3 Theta: time decay

Theta is how much premium is lost per day with everything else unchanged. Buyers have negative theta and sellers have positive theta. Decay is not linear: with spot held at 22,620 and vol at 13.49%, the ATM call's Black-Scholes theta is about −7.6 points a day with 30 days left, −13.8 with 7 days left and −33.4 with one day left. Even that understates the last day, because theta keeps speeding up through it: the ATM call still has about 56 points of time value with one day to go, and all 56 are gone by the close on expiry day.

7.4 Vega: sensitivity to volatility

Vega is the change in premium for a 1-percentage-point change in implied volatility. It is the same for a call and a put at the same strike, and both gain when volatility rises. The 22600 options have vega ≈ 24.26, so a rise in IV from 13% to 15% adds about 48 points to both the call and the put, even if Nifty does not move. Vega is larger for longer-dated options and shrinks towards expiry. For hedgers this means: buy protection when IV is calm, not in the middle of a panic. On 27 Feb 2026 India VIX was 13.70. By 30 Mar 2026 it was 27.89 and every put was far more expensive.

7.5 How the Greeks interact (Varsity's rules of thumb)

• Early in the series, gamma is low everywhere and theta is gentle. There is time for a view to play out, and ATM or slightly OTM strikes are reasonable for a buyer.
• Late in the series, ATM gamma and theta both spike. Buyers need the move quickly, and sellers face sudden delta jumps.
• When volatility is high, deep OTM options keep a meaningful delta. When it is low, they behave like lottery tickets.
• Strike choice for a directional buyer should depend on how soon you expect the move. If the move should come within a few days, OTM strikes give the most leverage. If it may take until expiry, ITM strikes are better because their intrinsic value cushions decay. A far-OTM buy that needs a large move and has plenty of time to wait is usually the worst combination.

8. Volatility: historical, implied, India VIX and the skew

8.1 Historical volatility: the calculation

8.2 Implied volatility and India VIX

Historical vol looks back. Implied vol is the forward-looking number embedded in option prices. India VIX is NSE's index of the 30-day implied volatility of Nifty, computed from the order book of near and next-month Nifty options. It is often called the "fear index" because it jumps when markets fall.

8.3 Using volatility to estimate an expected range

Which day count? India VIX and option-pricing time \(T\) are quoted on a calendar-day basis, so with VIX you scale by \(\sqrt{N/365}\) where \(N\) is calendar days. Historical volatility in 8.1 was built from trading-day returns, so it scales by \(\sqrt{252}\) and \(\sqrt{N_{trading}}\). Both give about the same answer for the same period. Mixing them, for example VIX with \(\sqrt{N/252}\) on calendar days, overstates the range.

8.4 The volatility skew (smile)

If Black-Scholes were exactly right, every strike would have the same IV. In reality, Nifty puts below spot carry higher IV than calls above it. On 30 Sep 2026 the 27-Oct 21600 PE traded at 15.44% IV, while the 23400 CE traded at 11.87%. The logic: markets fall faster than they rise, and institutions buy downside puts as insurance, so crash protection carries a premium. The weekly expiry shows a true "smile" (both wings up, from 11.59% at 22600 to 17.86% at 21600 and 15.95% at 23600) because very short options price jump risk on both sides.

Practical consequence: far-OTM puts cost more than a flat-volatility model suggests, so the "cheapest" hedge in rupees is not the cheapest in volatility terms. Selling an OTM call against a put (a collar, Section 10.3) partly pays for this expensive downside protection with cheaper upside.

9. Reading the option chain: OI, PCR and max pain

An option chain lists every strike for one expiry, with calls on the left and puts on the right: last price, change, volume, open interest (OI) and change in OI. On NSE's chain and broker apps, ITM strikes are shaded.

9.1 Open interest by strike

OI counts contracts open at the end of the day. Every contract has a buyer and a seller, so OI does not tell you who is "right". The common reading is that heavy call OI at a strike above spot is where call writers expect a ceiling, and heavy put OI below spot is where put writers expect a floor. It reflects positioning, not a guarantee.

9.2 Put-call ratio (PCR)

9.3 Max pain

Idea: at expiry, option writers as a group pay out the least if the index settles at one particular strike. "Max pain" theory says the market tends to drift towards that level into expiry.

10. Hedging with options: five structures with real prices

A hedge is something you hold alongside a position so that a bad outcome hurts less. It always costs something: cash (a premium), upside (a cap) or both. The question is never "is there a free hedge?" but "which cost am I willing to pay?"

10.1 Protective put: insurance with a fixed deductible

The logic. Below the strike, every rupee the asset loses is paid back by the put. Above it, you keep the upside minus the premium. The gap between the price and the strike works like an insurance deductible, and the premium is the insurance cost.

Sizing an index hedge for a stock portfolio

Most investors do not hold "the Nifty". To hedge a portfolio with Nifty puts, scale by its beta (Chapter 9):

Example: a ₹10,00,000 portfolio with beta 1.1 needs 10,00,000 × 1.1 / (22,620.45 × 65) = 0.748 lots. You cannot buy 0.748 lots, so one lot over-hedges (₹14.7 lakh notional) and zero leaves you unhedged. One 27-Oct 22000 PE cost 98.15 × 65 = ₹6,379.75 (0.64% of the portfolio). Lot granularity is a real practical limitation for small portfolios, and beta itself is unstable, so the protection is approximate.

Futures holder, today's prices: long one October Nifty future at 22,707.30 plus the 27-Oct 22300 PE at 161.70 (₹10,510.50) caps the loss to expiry at 22,707.30 − 22,300 + 161.70 = 569.00 points = ₹36,985 per lot, whatever happens overnight.

10.2 Covered call: earning a little on shares you hold

The logic. You sell someone the upside beyond a strike in exchange for cash now. It suits a stock you are happy to hold but do not expect to rally sharply within the month. It is not a hedge in any serious sense, because the premium cushions only a small fall.

10.3 Collar: a floor paid for with a cap

10.4 Bull call spread and bear put spread: cheaper directional views with defined risk

The logic: selling the further strike gives up profits beyond it in exchange for cutting the cost, the delta and, most importantly, the theta and vega of the position. For a hedger, a bear put spread is a cheaper partial hedge. It covers a moderate fall (say 2–4%) but not a crash beyond the lower strike.

Strike selection for spreads (Varsity's guidance, in brief): if you expect the move within a few days, early in the series, both strikes can be OTM. If you expect it by expiry, buy ATM and sell OTM. Late in the series, move the bought strike ITM or ATM because theta punishes OTM legs. Volatility matters less for spreads early in the series and more near expiry.

11. Why option buying mostly loses, and why selling has tail risk

11.1 What SEBI's data says

SEBI's study "Profitability of Individual Traders in the Equity Derivatives Segment (FY25–FY26)", released in August 2026, found that the share of losing individual traders was 87.7% in FY26, down from about 91% in FY25. The average loss was about ₹1.17 lakh per trader, nearly 97% of traders predominantly bought options, and individuals paid about ₹25,000 crore in transaction costs in FY26. Before costs, 82.1% were already loss-making, so charges alone turned roughly another 5.6% of all traders from a gross gain into a net loss. Trading was crowded into the last moments of a contract's life: about 59% of index-option turnover was in contracts expiring that same day ("zero days to expiry"), 75% within one day and 97% within a week. That is exactly where theta and gamma are most extreme (Section 7). The earlier study (FY22–FY24) found 93% of over one crore individual traders lost money. FY25 net losses were first reported at ₹1,05,603 crore in SEBI's July 2025 study and revised to about ₹1,11,788 crore in the 2026 study. The pattern holds year after year.

11.2 Why buyers lose: three forces against them

1. Theta. The option loses value every day the move does not happen. A buyer must be right about direction and size and timing.
2. The volatility risk premium. Implied vol is usually above what is later realised (81.1% of days since 2016, Section 8.2), so options are on average slightly overpriced.
3. Behaviour and costs. Most retail activity is in near-expiry OTM options: cheap tickets with low probability that decay fastest. Brokerage, STT (now 0.15% of premium on sales) and spreads take a larger share of a small premium.

11.3 Why sellers get hurt: the tail

12. Settlement, expiry, margins and costs (verified Oct 2026)

12.1 What happens at expiry

• Index options (Nifty): cash-settled. ITM options are automatically exercised at the final settlement price, the index close on expiry day. On 30 Mar 2026 every March Nifty option settled against 22,331.40. The 25000 PE's closing price that day was 2,682.90, but it settled at its intrinsic value, 2,668.60, and that is what holders received. OTM options expire worthless.
• Stock options: physically settled (mandatory for all stock F&O since October 2019). ITM long call: you buy the shares at the strike. ITM long put: you deliver the shares and receive the strike. Short positions have the mirror obligations. You need the full cash or the shares, not just margin.
• Opposite ITM positions in the same stock and expiry (for example long futures and a long ITM put) are netted, and only the difference is delivered.

12.2 Margins and upfront premium

• Buyers pay the full premium upfront. There is no mark-to-market, and the maximum loss is the premium. SEBI's October 2024 framework made upfront collection of net option premium mandatory at client level.
• Sellers post SPAN margin (the exchange's estimate of the worst one-day loss across a set of price and volatility scenarios) plus exposure margin (an extra safety buffer), of the same order as a futures margin (for a Nifty lot, typically well over ₹1 lakh; use your broker's margin calculator for the live figure). Margin rises when the premium or volatility moves against you, which can force exits at the worst time. Hedged positions such as spreads need much less margin.
• SEBI measures in force since late 2024 / early 2025: an extra 2% extreme-loss margin on short index options on expiry day, no calendar-spread margin benefit on expiry day, intraday monitoring of position limits, and a minimum contract value of ₹15 lakh at the time of lot-size reviews. Note that one Nifty lot (65 units) was worth only ₹14.70 lakh on 30 Sep 2026 after the fall, which is why exchanges revise lot sizes periodically.

12.3 Costs and STT (from 1 Apr 2026)

Example: selling one lot of the 22600 CE at 372.90 incurs STT of 372.90 × 65 × 0.15% = ₹36.36, plus brokerage, exchange charges, SEBI fees, stamp duty and GST. Chapter 13 computes the full stack and the tax treatment: F&O profits are normally taxed as non-speculative business income.

13. Try it yourself

These snippets need a copy of the course repository and Python with pandas and numpy (setup steps are in its framework/README.md). Run them from the repository's root folder, for example with .venv/bin/python, because the file paths are relative to that folder. Each reproduces numbers from this chapter.

(a) Intrinsic/time value, PCR and max pain from the real chain

import pandas as pd
chain = pd.read_csv("data/fno/nifty_options_2026-09-30.csv", parse_dates=["XpryDt"])
spot = chain.UndrlygPric.iloc[0]
oct27 = chain[chain.XpryDt == "2026-10-27"]
ce = oct27[oct27.OptnTp == "CE"].set_index("StrkPric")
pe = oct27[oct27.OptnTp == "PE"].set_index("StrkPric")

for k in [22200, 22600, 23000]:
    c_iv, p_iv = max(0, spot - k), max(0, k - spot)
    print(k, "CE", ce.loc[k, "ClsPric"], "TV", round(ce.loc[k, "ClsPric"] - c_iv, 2),
          "| PE", pe.loc[k, "ClsPric"], "TV", round(pe.loc[k, "ClsPric"] - p_iv, 2))

print("PCR:", round(pe.OpnIntrst.sum() / ce.OpnIntrst.sum(), 3))      # 1.012

def pain(x):
    k_c, k_p = ce.index.to_numpy(), pe.index.to_numpy()
    return ((x - k_c).clip(min=0) * ce.OpnIntrst.to_numpy()).sum() + \
           ((k_p - x).clip(min=0) * pe.OpnIntrst.to_numpy()).sum()
strikes = sorted(set(ce.index) | set(pe.index))
print("Max pain:", min(strikes, key=pain))                             # 23400

(b) Black-Scholes and implied volatility

import numpy as np
from scipy.stats import norm
from scipy.optimize import brentq

def bs_call(S, K, T, sigma, r=0.054):
    d1 = (np.log(S / K) + (r + sigma**2 / 2) * T) / (sigma * np.sqrt(T))
    d2 = d1 - sigma * np.sqrt(T)
    return S * norm.cdf(d1) - K * np.exp(-r * T) * norm.cdf(d2), norm.cdf(d1)

S, K, T = 22620.45, 22600, 27 / 365
price, delta = bs_call(S, K, T, 0.1349)        # India VIX as vol -> 388.48, delta 0.56
iv = brentq(lambda s: bs_call(S, K, T, s)[0] - 372.90, 0.01, 2)
print(round(price, 2), round(delta, 3), "IV", round(iv * 100, 2), "%")   # IV 12.85 %

(c) Hedge payoffs on RELIANCE at expiry (₹ per lot)

spot, put_k, put_prem, call_k, call_prem, lot = 1187.0, 1140, 11.80, 1250, 9.85, 500
for x in [1050, 1100, 1140, 1187, 1250, 1300]:
    stock = x - spot
    protective = stock + max(0, put_k - x) - put_prem
    covered = stock + call_prem - max(0, x - call_k)
    collar = stock + max(0, put_k - x) - put_prem + call_prem - max(0, x - call_k)
    print(x, stock * lot, round(protective * lot), round(covered * lot), round(collar * lot))
# at 1050: stock -68,500 | protective put -29,400 | covered call -63,575 | collar -24,475

Every chart in this chapter is reproduced by course/scripts/ch10_figures.py. The NSE bhavcopy extracts it needs are downloaded by course/scripts/ch10_data.py.

14. Practical checklist

Before using an option to hedge

• ☐ What exactly am I protecting against (gap on results, event, crash), and for how long?
• ☐ What maximum loss do I accept? Strike = entry − acceptable loss, before premium.
• ☐ Expiry: does it cover the risk window, with a margin of safety? Longer expiries cost less per day.
• ☐ Is IV calm or elevated? (Check India VIX and the strike's IV vs its recent history.) Avoid buying protection in a panic if you can plan ahead.
• ☐ Cost as % of the position, per month. Is that an acceptable running cost if nothing happens?
• ☐ Would a spread or collar give enough protection more cheaply?
• ☐ Liquidity: volume and OI at the strike, and a tight bid-ask. Use limit orders.
• ☐ Size: index hedge lots = value × beta / (index × lot). Check the over- or under-hedge from rounding.
• ☐ Stock options: the physical-settlement plan. Close before expiry week, or have the shares/cash ready. Know your broker's E−4 to E margin schedule.
• ☐ Costs: STT 0.15% on premium sold / intrinsic exercised (from 1 Apr 2026), plus other charges.

Before any directional option trade

• ☐ Breakeven computed. How far and how fast must the market move?
• ☐ Delta, theta and vega understood. What do I lose per day if nothing happens?
• ☐ Losing 100% of the premium is acceptable within my risk-per-trade rule (Chapter 11).
• ☐ No naked short options. Any short leg has a defined-risk hedge.
• ☐ Not trading same-day-expiry contracts "because they're cheap".

15. Key takeaways

16. Quiz and exercises

17. Sources

Primary concepts (explained here in our own words): Zerodha Varsity Module 5, Options Theory for Professional Trading: Ch 1 Call Option Basics · Ch 2 Basic Option Jargons · Ch 3 Buying a Call Option · Ch 4 Selling/Writing a Call Option · Ch 5 The Put Option Buying · Ch 6 The Put Option Selling · Ch 7 Summarizing Call & Put Options · Ch 8 Moneyness · Ch 9–11 Delta · Delta Part 3 · Ch 12–13 Gamma · Ch 14 Theta · Ch 15 Volatility Basics · Ch 16 Volatility Calculation · Ch 17 Volatility & Normal Distribution · Ch 18 Volatility Applications · Ch 19 Vega · Ch 20 Greek Interactions · Ch 21 Greek Calculator · Ch 22 Re-introducing Call & Put Options · Ch 24 Physical Settlement · Ch 25 Options M2M and P&L. Zerodha Varsity Module 6, Option Strategies: Orientation · Bull Call Spread · Synthetic Long & Arbitrage · Bear Put Spread · Max Pain & PCR Ratio. (Varsity has no dedicated protective-put, covered-call or collar chapters. Those sections combine the payoff logic of Module 5 with the hedging ideas in Module 4 and Module 9.)

Rules and statistics (verified Oct 2026): Zerodha: policy on physical settlement of equity derivatives · Zerodha Z-Connect: physical delivery of stock F&O · SEBI circular SEBI/HO/MRD/TPD-1/P/CIR/2024/132 (1 Oct 2024), measures to strengthen the equity index derivatives framework · NSE circular: revision in expiry day of index derivatives · Nifty lot size revised to 65 (Jan 2026 series) · STT rates after Union Budget 2026 (effective 1 Apr 2026) · SEBI FY26 study coverage (87.7% lost, ₹91,685 crore) · SEBI study release, 20 Aug 2026 · SEBI FY26 study: 92% of losses from options, 59% same-day-expiry turnover (Moneylife) · SEBI FY25 study (Business Standard, Jul 2025) · SEBI FY22–FY24 study (Business Standard, Sep 2024) · NSE holiday calendar 2026.

Data: NSE F&O UDiFF bhavcopies for 27-Feb-2026, 30-Mar-2026, 30-Sep-2026 and the first trading day of each month Oct 2024–Sep 2026 (nsearchives.nseindia.com), saved under data/extra/ch10_*.csv. Nifty option chain and futures: data/fno/. Nifty 50 and India VIX daily history: NSE via Yahoo Finance (data/ohlc/). Risk-free rate 5.4% approximates the 91-day T-bill yield in Sep 2026 (auction cut-offs ranged from about 5.2% to 5.5% that month; RBI repo held at 5.25% in the Aug 2026 policy). All computations: course/scripts/ch10_figures.py.