Options

Options explained: calls, puts, moneyness, premium, time decay, implied volatility, Black-Scholes, the Greeks, exercise, settlement and the risks of buying and writing.

An option is a contract that gives its buyer the right, but not the obligation, to buy or sell something at a specified price, under specified terms. The seller, or writer, takes on the corresponding obligation if the option is exercised and assigned.

That single asymmetry is what separates an option from a futures contract, where both sides are bound.

• The buyer pays a premium to acquire a contractual right.
• The writer receives the premium and accepts an obligation.

A standalone buyer’s loss is generally capped at the premium paid. A writer’s loss is not capped that way, and writing normally carries a substantial margin requirement.

But there is a second thing that makes options different, and it is the subject of most of this chapter. An option’s price depends on more than the direction of the underlying. Time, volatility, the strike and interest rates all contribute.

This is an educational overview, not financial, tax or legal advice. The calculations below are illustrative examples, not live quotes. Options involve substantial financial risk. Exchange rules, margins, settlement procedures and trading conditions must be verified before trading.

If you are new to derivatives, start with derivatives. The other major exchange-traded derivative is futures.

Calls and puts

There are two kinds of option.

• A call gives the buyer the right to buy the underlying at the strike price, or to receive the equivalent cash payoff under the contract’s terms.
• A put gives the buyer the right to sell the underlying at the strike price, or to receive the equivalent cash payoff.

Suppose a share trades at ₹1,000. A ₹1,000 call gains payoff as the share rises above ₹1,000. A ₹1,000 put gains payoff as the share falls below ₹1,000. On the NSE, call and put series carry the identifiers CE and PE.

The four basic positions:

A long position means you bought the option. A short position means you sold, or wrote, it.

Note the third row against the first: a long put is a long option position with bearish exposure. Whether you own or owe the contract, and which direction you are betting on, are two different questions.

Strike price and moneyness

Every conventional call or put has a strike price, set when the option series is created. Moneyness describes where the strike sits relative to the current underlying price.

For an option with a strike of ₹1,000:

• If the underlying rises to ₹1,050, the ₹1,000 call is ₹50 in the money and the ₹1,000 put is out of the money.
• If the underlying falls to ₹950, the call is out of the money and the put is ₹50 in the money.

The payoff of a standard option is its intrinsic value:

Call intrinsic value = max( S − K , 0 )
Put  intrinsic value = max( K − S , 0 )

Here S is the underlying price and K is the strike.

An out-of-the-money option has no intrinsic value, but it can still have a market price, because there is time left in which the underlying could move favourably.

Being in the money does not mean the buyer has made a profit. The premium paid still has to be recovered first, which is the subject of the next few sections.

What the premium is made of

The premium is the market price of the option. A buyer pays it and a writer receives it. Unlike margin, it is the price paid for the right, not collateral that comes back when the position closes.

One trade executes at a fixed premium, but the same option’s market premium keeps moving for the rest of the session. What you paid is locked; what the option is currently worth is not.

A standard premium has two components:

Option premium = Intrinsic value + Extrinsic value

Extrinsic value is often called time value, though volatility and other pricing factors contribute to it as well.

Example. An underlying at ₹1,010, a call strike of ₹1,000, and a premium of ₹25:

• Intrinsic value: ₹10
• Extrinsic value: ₹15

That ₹15 is the market’s valuation of what might still happen before expiry.

A premium responds to six things:

1. The underlying price.
2. The strike price.
3. Time remaining until expiry.
4. Expected future volatility.
5. Interest rates.
6. Expected dividends or distributions, where relevant.

These interact, which is why an option can move substantially without a large move in the underlying.

How an option buyer makes or loses money

Take a hypothetical European-style call.

The trader pays ₹20,000 for one contract representing 1,000 shares. At expiry the net result per share is:

Long call net = max( ST − K , 0 ) − P

where S_T is the settlement price at expiry, K the strike and P the premium paid.

All figures are before costs and taxes.

The breakeven is K + P = ₹1,020. At ₹1,010 the call expires in the money and still loses ₹10 per share.

Being right about direction is not enough. The move also has to be big enough, and fast enough, to beat the premium.

Before expiry the position can generally be closed by selling the option at its prevailing premium, subject to liquidity. That premium includes extrinsic value, so pre-expiry profit and loss is not determined by intrinsic value alone.

Premium is not leverage

The ₹20,000 premium is 2% of the ₹10,00,000 notional, which is 50 times smaller. It is tempting to treat that as 50 times leverage.

An option does not behave like that. Its sensitivity is nonlinear: the exposure changes as the underlying moves, as volatility changes and as time passes. The ratio of premium to notional is not a measure of effective exposure, and the Greeks below are the right way to think about it.

Time decay and implied volatility

Time passing changes an option’s value. All else equal, the extrinsic value of a conventional option declines as expiry approaches. This is time decay, measured by theta.

But a premium does not have to fall every day. A long call can gain value because the underlying rose, or because implied volatility rose, even while time passed against it.

Implied volatility (IV) is the volatility that makes a pricing model reproduce an option’s observed market price. For comparable standard options:

• Higher implied volatility generally raises both call and put prices.
• Lower implied volatility generally lowers them.

IV is not a forecast of what volatility will actually be.

This is how a buyer loses money while being right. If the movement you expected was already priced in, the IV you bought was high, and the option can fall as the market gets what it wanted. It also works the other way: a buyer can profit from a rise in IV without much movement in the underlying at all.

Volatility crush

Suppose a market expects a major announcement. Demand for options ahead of it can push IV and premiums up. After the announcement the uncertainty is gone, and IV can fall sharply.

The buyer can be directionally right and still lose part or all of the gain, because the drop in IV offsets it. This is called volatility crush, and it is the reason options are not simply bets on direction. Their prices reflect the market’s valuation of uncertainty.

How options are priced: Black–Scholes–Merton

The Black–Scholes–Merton (BSM) model is one of the foundational models for valuing options. It gives theoretical prices for European-style options under assumptions about the price process, volatility, interest rates and dividends.

For a European call on an underlying paying a continuous dividend yield:

C = S × e−qT N(d1) − K × e−rT N(d2)

For a European put:

P = K × e−rT N(−d2) − S × e−qT N(−d1)

where:

d1 = [ ln(S / K) + (r − q + σ²/2) × T ] ÷ ( σ × √T )
d2 = d1 − σ × √T

The variables

N(x) is the cumulative probability of a standard normal distribution up to x. The model uses it to discount the expected payoff under a risk-neutral pricing assumption. It does not assume anyone knows which way the underlying will move.

A worked example

Hypothetical inputs.

First:

d1 = [ ln(1000/1000) + (0.06 − 0.01 + 0.20²/2) × (30/365) ] ÷ ( 0.20 × √(30/365) )
= 0.0057534 ÷ 0.0573382
= 0.10034
d2 = 0.10034 − 0.0573382
= 0.04300

Substituting into the call and put formulas:

These are model values per underlying unit, before costs. They are not quotes and they are not guaranteed to be available.

If the same call trades at ₹28, the model has not proved the option is overpriced. The market may be using a higher volatility, a different dividend assumption, or inputs you cannot see. An option trading below the model value is not automatically a free arbitrage either.

Why the formula matters

The model’s real practical use is rarely the theoretical price. It is the implied volatility and the Greeks it lets you derive from a market price. It also explains, structurally:

• why longer-dated options usually carry more extrinsic value,
• why option prices generally rise with volatility,
• why strike selection changes sensitivity,
• why rates and dividends matter,
• why an option does not simply follow the underlying.

Put-call parity

For comparable European options on the same underlying, strike and expiry, BSM also satisfies a no-arbitrage relationship:

C − P = S × e−qT − K × e−rT

This is put-call parity, and it describes the no-arbitrage relationship between European calls, puts, the underlying and financing. It is useful for understanding synthetic positions, relative pricing, the effect of financing and dividends, and inconsistencies between related prices.

In real trading, bid-ask spreads, funding costs, taxes, short-selling restrictions and execution risk can stop anyone exploiting a small apparent difference. Do not apply it unchanged to American-style options or to contracts with materially different settlement terms.

Variations and other pricing models

BSM matters, but it is not the only model, and different contracts need different approaches.

Black-76: options on futures

For European options whose underlying is a futures contract, the model is Black-76, also called Black’s model:

C = e−rT [ F0 N(d1) − K N(d2) ]
P = e−rT [ K N(−d2) − F0 N(−d1) ]

where:

d1 = [ ln(F0 / K) + σ² × T/2 ] ÷ ( σ × √T )
d2 = d1 − σ × √T

F₀ is the current futures price. This matters because you should not apply the spot-based BSM formula unchanged just because the product is called an option. The link to futures pricing is direct: with F₀ set to S × e^((r − q)T), the two models return the same call price.

Binomial and tree models

A binomial model divides time into small steps. At each step the underlying moves up or down, and the model works backwards from the possible payoffs to a present value.

Its real advantage is early exercise: it can compare exercising now against continuing to hold. It can also price European options, and as the number of steps increases its value converges toward the BSM value.

Stochastic volatility and jump models

More advanced models try to capture what basic BSM misses: volatility that changes randomly, sudden jumps, or an implied-volatility surface that varies by strike and maturity.

They add flexibility, and they also add parameters, estimation difficulty and model risk. A more complicated formula is not a more accurate prediction.

Where Black–Scholes goes wrong

This is the most important qualification in the chapter. BSM is a model of market behaviour, not a law of prices. Its usefulness depends on assumptions that real markets do not always satisfy.

1. Volatility is not constant. BSM assumes a fixed volatility over the option’s life. An option that looked cheap on yesterday’s volatility can look expensive after uncertainty rises.

2. One volatility does not fit every strike. Options with different strikes frequently trade at different implied volatilities, which produces a smile or skew. Downside puts often carry higher IV than comparable upside calls, because traders pay more for downside protection. A single volatility number cannot reproduce an entire option chain.

3. Prices jump. BSM assumes continuous diffusion. Markets gap after earnings, regulatory decisions or geopolitical events, and the resulting loss can be far larger than the model’s return assumptions suggest.

4. Real returns have heavier tails. BSM assumes lognormal prices. Actual returns produce more extreme outcomes than that implies, so rare events arrive more often than a simple model suggests.

5. Markets are not frictionless. Real traders face brokerage and statutory charges, bid-ask spreads, slippage, funding and borrowing costs, market impact, liquidity limits, margin requirements and trading interruptions. A theoretical difference often disappears after costs.

6. Continuous hedging is impossible. The replication argument assumes ideal rebalancing. In practice hedging is discrete, and the market can move a long way between adjustments.

7. Dividends are not continuous. Individual shares pay dividends on discrete dates, and the timing and size affect theoretical values. Models using expected discrete dividends are usually more appropriate.

8. Early exercise needs a different method. The European BSM formulas are not a general solution for American-style options, which can have early-exercise value. A binomial tree or other numerical method is needed.

9. Rates and volatility are uncertain inputs. Small changes in the chosen values can move the calculated fair value, and for some contracts the correct discount curve is not obvious.

10. The market is not obliged to match the model. Quotes reflect supply and demand, hedging pressure, dealer inventory and liquidity. This is why professionals use models to manage and compare risk rather than assuming every gap from a model value is a mispricing.

Model risk is the possibility that a model gives misleading results because its assumptions, parameters or implementation are inadequate. It is a separate risk from market movement, and a precise mathematical answer can still be economically wrong if the assumptions behind it are inappropriate.

The Greeks

The Greeks describe how an option’s theoretical value responds to each market variable. They are local sensitivities: a number computed at one point, for one set of inputs.

All formulas below follow the Black–Scholes–Merton convention for a European option on an underlying paying a continuous dividend yield q, where N is the standard normal cumulative distribution and φ is the standard normal density.

Delta

Delta is the approximate change in option value for a small change in the underlying, holding everything else constant.

Δcall = e−qT · N(d1)
Δput  = e−qT · [ N(d1) − 1 ]

A delta of 0.50 means the option is expected to gain or lose roughly ₹0.50 for a ₹1 move in the underlying, for a small move.

Long and short exposures are mirror images. A long call has positive delta and a long put negative delta, so the two make money in opposite conditions. Selling an option negates its delta: a short call has delta −0.54, a short put +0.46.

Limitations. Delta is a local approximation, so it degrades on large moves. It is not a prediction of realised price movement, it changes as the underlying moves, and for a standalone long option it does not capture the risk of losing the whole premium. Note also that put and call delta differ by a small amount, e⁻ᑫᵀ, rather than summing to exactly zero.

Gamma

Gamma is the change in delta for a small change in the underlying. It is the same for a call and a put at the same strike and expiry.

Γ = e−qT · φ(d1) ÷ ( S · σ · √T )

Why it matters: gamma is smallest for long-dated at-the-money options and largest for very short-dated at-the-money ones. The √T in the denominator is the reason. Holding everything else at the values in the worked example below, moving the expiry from 30 days to 7 days raises gamma from 0.006917 to 0.014384, roughly 2.1 times. At one day to expiry it reaches 0.038101, about 5.5 times.

That is the practical meaning of gamma risk: for a position that is short gamma, the closer to expiry an at-the-money option gets, the faster the delta of that option moves, and the faster the position’s own risk profile changes.

Limitations. Gamma is the second derivative, so it is a curvature measure around a point, not a forecast. It can be large in magnitude and still be overwhelmed by a delta move or a volatility shock in the same moment.

Theta

Theta is the sensitivity to time passing. The standard convention is calendar time, so a long option has negative theta and loses value as time passes, all else equal.

Θcall = −S·φ(d1)·σ·e−qT ÷ (2√T)  −  r·K·e−rT·N(d2)  +  q·S·e−qT·N(d1)
Θput  = −S·φ(d1)·σ·e−qT ÷ (2√T)  +  r·K·e−rT·N(−d2)  −  q·S·e−qT·N(−d1)

The units matter, and they are a common source of confusion. Theta above is per year. The daily figure, which is what most software shows and what most people mean, is the annual value divided by 365.

Time decay is not linear. For a conventional long option the decay is gentle far from expiry and then accelerates into the final days, which is where the 2√T in the denominator again drives the behaviour. The same acceleration appears in gamma.

A market premium does not have to fall every day. Theta is one of several forces. A long call can gain value because the underlying rose, or because implied volatility rose, even while time passes against the position.

Limitations. Theta assumes everything else is held constant, so it is not a forecast of an option’s market price on any given day.

Vega

Vega is the sensitivity to implied volatility, and it is identical for a call and a put at the same strike and expiry.

ν = S · e−qT · φ(d1) · √T

Volatility units. The formula above is quoted per 1.00 change in σ, where σ is expressed as a decimal. Because markets quote volatility in percentage points, a 20% volatility is σ = 0.20, and a “one volatility point” move is 0.01, or 1 percentage point. Per percentage point, vega is one hundredth of the value above.

Long and short exposures are mirror images. A long option gains as implied volatility rises and loses as it falls. A short option has the opposite sign, which is why a writer profits from a falling IV and is hurt by a rise.

Limitations. Vega is a sensitivity to a model input, not to an observable. Implied volatility is inferred from option prices, so if the market’s prices are moving, vega is measuring the response of a model to an inferred number.

Rho

Rho is the sensitivity to interest rates. It is quoted per 1.00 change in r, so per percentage point the value is one hundredth of the figures below.

ρcall = K · T · e−rT · N(d2)
ρput  = −K · T · e−rT · N(−d2)

A long call has positive rho and a long put negative rho: a call buyer benefits from higher rates, because the strike is effectively discounted more.

Rho grows with maturity. The T in the formula is direct, so long-dated options have much larger rho than short-dated ones. For the 30-day contract below, rho is small and usually irrelevant next to delta or vega. For a one-year option on the same strike it would be an order of magnitude larger, and in a rate-driven market it can matter.

Limitations. Which discount curve to use is not always obvious, and rho is only as good as that choice.

Vanna and Charm

Two higher-order Greeks exist because delta and theta, and gamma and vega, are themselves related. Vanna measures how vega changes as the underlying moves. Charm measures how delta changes as time passes, sometimes called delta decay.

They are used in professional volatility trading and in some risk systems, and they are not needed for the rest of this chapter.

Verified worked example

Every figure below is computed from the same hypothetical inputs used in the BSM worked example, and each was checked against a numerical derivative of the pricing formula.

Note the units, because they differ between pairs of rows and are the usual source of a wrong-looking answer. Theta is quoted per year, with the daily figure a hundred-and-sixty-fifth of it. Vega and rho are quoted per 1.00 of their input, with the percentage-point figure one hundredth. Gamma is the same for a call and a put, and so is vega.

Reading the table as plain sentences:

• A ₹10 rise in the underlying moves the call by about +₹5.40 and the put by about −₹4.60.
• Over that same ₹10 move, delta changes by about 0.069.
• One day of passing time costs the call roughly ₹0.45 and the put about ₹0.31.
• A one percentage point rise in implied volatility adds about ₹1.14 to either option.
• A one percentage point rise in rates adds about ₹0.42 to the call and costs the put about ₹0.39.

One internal consistency check is worth doing. Put-call parity requires the call’s delta to exceed the put’s by exactly e⁻ᑫᵀ, and 0.5395 − 0.999178 = −0.4597, which matches the put delta. Gamma and vega are identical for calls and puts, which is also a property of the model.

The Greeks are local sensitivities, not promises

No Greek predicts a realised price movement with certainty. Each is a slope at a single point, computed from a model, and each of these caveats applies:

• They move. Gamma, vega, theta and delta all change as spot, volatility, rates or time change. A Greeks table printed in the morning is not a description of the position in the afternoon.
• They assume the other inputs hold constant, which in a fast market none of them do.
• They inherit the model’s assumptions. If the model is a poor description of the option’s behaviour, its sensitivities will be too.
• They say nothing about liquidity or execution. Delta does not tell you whether you can actually trade that size at that price.
• A large gamma or vega figure is not a forecast of large movement. It describes sensitivity if movement occurs, and larger sensitivity usually goes with more time value, which is also what decays.

This is the same caution as the section on model limitations, applied to the numbers derived from the model.

The volatility smile and skew

Black–Scholes takes a single volatility number for the whole underlying. Real option markets do not work that way. The same underlying, on the same day, trades at different implied volatilities for different strikes.

• A smile is when implied volatility is lowest near the at-the-money strike and rises toward both the low and high strikes.
• A skew, often called a smirk, is when the rise is not symmetric: the two sides differ, and in equity index markets the low-strike side is usually the higher one.

Why the downside tends to be higher. Equity markets fall further and faster than they rise, so investors pay more for protection against a fall. Demand for puts at low strikes pushes their implied volatility up. The effect is strongest in index options and in single names that carry event risk.

In the hypothetical NIFTY example below, spot is 25,000, and implied volatility is quoted in percentage points:

Read across each row and both features are visible. In the one-week row, implied volatility falls from 20.5% at 23,000 to 17.0% at spot, which is the smile, then rises again to 19.0% at 27,000. And at equal distance from spot, the downside is higher than the upside: 20.5% against 19.0%, which is the skew.

A higher implied volatility does not mean an option is overpriced. It means the model needs a larger volatility assumption to reproduce that option’s price, which may reflect a real risk premium for that particular strike and maturity, or simply thinner trading in it. A price above a model value is a starting question, not a conclusion, for the reasons set out under model limitations.

Not every market, or every period, shows this pattern. A smile or skew is an empirical observation about a particular market at a particular time, not a law. It can be flatter, steeper, or differently shaped, and it can even be inverted in some periods or asset classes.

Volatility term structure

Implied volatility also varies with time to expiry. Options with different maturities on the same underlying trade at different implied volatilities, and the pattern across maturities is called the term structure.

• It can be upward-sloping, with short-dated options more volatile.
• It can be downward-sloping, with long-dated options more volatile.
• It can be irregular.

In the table above, looking only at the at-the-money strike of 25,000, the term structure runs 17.0% at one week, 15.5% at one month and 14.8% at three months. That is downward-sloping, and there is an obvious explanation in this hypothetical: an event is expected within the week, so near-dated uncertainty is higher and then fades as the event passes.

Scheduled events are the usual reason a term structure is not flat. An earnings date, a policy decision or a court ruling concentrates uncertainty into specific maturities, and the options expiring around it carry a higher implied volatility than longer-dated ones.

Do not assume short-dated implied volatility is always higher than long-dated. In a calm market with no pending event the relationship often inverts, and the long end can sit above the near end.

The volatility surface

Strike and time together give a surface. A volatility surface is implied volatility plotted against two axes at once:

• Strike or moneyness, horizontally
• Time to expiry, into the depth
• Implied volatility, vertically

Each expiry in the table above produces its own smile or skew. Stacking those curves by maturity produces a three-dimensional surface. The chart below shows the three curves side by side, which is a cross-section of that surface taken across the strike axis.

The same values appear in the table above, so nothing here depends on reading the chart. Illustrative data, not market quotes.

Comparing across maturities. Strikes are not directly comparable between a one-week and a one-year option, because the spot price will have moved. Professional pricing therefore usually works in terms of moneyness or delta rather than raw strike, so that “25% out of the money” means the same thing at both maturities.

How the surface changes

An implied volatility surface is not a fixed object. It moves for several reasons:

• Movement in the underlying price, which shifts which strikes are near the money.
• Scheduled announcements, which raise implied volatility in the maturities that bracket the event and then drop it afterwards.
• Changes in demand for downside protection.
• Market-wide volatility shocks, which can lift the whole surface at once.
• The passage of time, which rolls a position from one point on the surface toward another.
• Liquidity changes, which alter what implied volatility is actually being quoted and traded at.

Two different things are worth separating, because they are often confused. A position can lose money by moving along an unchanged surface, which is ordinary delta, gamma and vega effect. It can also lose money because the surface itself moved, shifting the implied volatility attached to that strike and maturity independently of the underlying. The Greeks do not describe the second effect, which is why an option can fall while the underlying is flat.

How this connects to the model limitations

The smile, skew and term structure are the practical reasons a single volatility parameter cannot generally reproduce the entire market surface. A trader or pricing system will commonly use a strike-specific and expiry-specific implied volatility instead of one number for the whole underlying. The local-volatility and stochastic-volatility models listed earlier exist largely to address this.

Two further qualifications matter when reading a surface:

• A surface is derived, not observed. It is inferred from market option prices, so it depends on quoting conventions, interpolation between sparse strikes, and data quality in less liquid expiries.
• A fitted surface is not a guaranteed forecast. It describes what implied volatility the market was pricing at a moment. It says nothing reliable about what volatility will actually be, and the same caution about models applies to models of the surface.

That is the same point as the model-risk section above, applied one level up: a model can be internally consistent and still describe a surface poorly.

These are expiry-payoff characteristics for a vanilla option held on its own.

A short put does not have unlimited downside loss, because an underlying price cannot fall below zero. And a defined-risk spread can cap its contractual loss, though execution, margin and settlement risks remain.

The writer’s position

A writer receives premium up front and may face a substantial margin requirement. The premium income is known when the position is opened. The loss is not bounded by it.

Time decay usually works in a writer’s favour, and a run of profitable weeks is not evidence the position is safe. A sharp move against the position, or a jump in implied volatility, can outweigh a great deal of accumulated decay.

Beware !!! Option Sellers examines this in detail, and Naked Option Buying Works argues the opposing case. Neither approach is inherently superior, and the answer depends on risk, position sizing, entry premium and market conditions rather than on which label is used.

Exercise, automatic exercise and settlement

Exercise rules determine when a buyer may use the right.

• European-style options can be exercised only at expiry.
• American-style options generally permit exercise at any time during the allowed period, including before expiry.

Exercise style does not determine whether an option settles in cash or by delivery. Those are separate rules.

NSE equity options

NSE’s index and individual-stock options are European-style, and NSE Clearing states that final exercise is automatic on expiry. Final exercise settlement is effected for in-the-money strikes at the close of trading on the expiration day, and long in-the-money positions are automatically assigned to short positions in the same series.

One nuance that NSCCL’s regulations make explicit: the framework recognises both automatic exercise, which covers in-the-money contracts, and voluntary exercise, which a clearing member may effect at its own discretion. The regulations also place the responsibility for giving a contrary instruction on the clearing member itself.

This is a mechanism between a clearing member and the clearing corporation, not a right the client holds directly. Whether any contrary instruction can be given at all, in what form, and by when, is determined by clearing-member procedures, applicable deadlines and the terms of the contract. Do not assume a retail client can submit one, or that the option will be left unexercised.

A holder should check the current exercise rules and the broker’s own expiry procedure before trading, because the broker’s process, not a general understanding of the rules, is what will actually apply on the day. And do not assume a broker will automatically close a position before settlement, or that an attempted square-off will execute.

Cash-settled index options

NSE index options are cash settled, because an index is not a deliverable security. Exercise produces a cash obligation based on the contractual payoff.

Physically settled stock options

NSE individual-stock options are physically settled. An in-the-money stock option left open at expiry can create a delivery obligation:

A long put can require delivery of shares, even though it was bought by paying a premium. The limited premium loss of a standalone long option does not mean physical settlement demands no further securities or funds.

Margin cannot replace a delivery obligation. A failure to deliver can bring penalties, an auction, a close-out or other consequences under the applicable clearing rules. Netting of eligible positions and other clearing rules may apply, and brokers may impose earlier square-off deadlines or extra margin, which are broker restrictions rather than exchange rules.

Commodity options

Some commodity options are options on futures, so exercise can produce a futures position rather than delivery of the physical. That is called devolvement, and it is covered in the commodities market.

Do not assume NSE stock options, commodity options and privately offered crypto options share the same settlement rules.

Expiry dates

There is no universal options expiry day. The date depends on the exchange, the underlying and the contract series.

Under the relevant published exchange specifications:

• NSE NIFTY weekly index options have Tuesday expiries, with four weekly contracts alongside three monthly.
• NSE individual-stock options follow a monthly Tuesday cycle.
• BSE index options use Thursday schedules.
• Currency options follow their own specifications.
• Commodity options may expire before the underlying futures contract.

When a scheduled expiry falls on a trading holiday, the applicable holiday-adjustment rule sets the revised date, and that rule is not uniform across exchanges. Contract availability and schedules change, so verify the specific listed contract rather than relying on a general calendar.

See futures, the forex market and the commodities market for the related details.

Risks worth understanding

Options carry more dimensions of risk than a plain directional position in the underlying.

• Premium loss. A fully paid long option can lose its entire premium.
• Time decay. Extrinsic value generally diminishes as expiry approaches.
• Implied volatility. A fall in IV can offset a favourable directional move.
• Gamma. Delta can change rapidly as the underlying moves.
• Gaps. Prices can move beyond expected levels before you can exit.
• Liquidity. Thin books and wide spreads raise costs and impair exits.
• Margin. Writers can face additional collateral requirements.
• Exercise and delivery. Physically settled options can create obligations beyond the money originally committed.
• Model risk. A theoretical valuation can mislead if its assumptions are wrong.
• Transaction costs. Frequent trading, wide spreads and statutory charges can erase an apparent edge.

The scale of losses recorded among individual traders in India’s equity derivatives market is in the reality of trading. Those aggregate statistics do not establish the profitability of any particular option strategy.

Before trading an option

Be able to answer these:

1. Is this a call or a put?
2. Am I buying or writing it?
3. What is the underlying, and what is the strike?
4. What is the lot size or contract multiplier?
5. What is the total premium, and what margin will be required?
6. How much can this position lose?
7. How will time decay and implied volatility affect it?
8. What is the bid-ask spread, and what is the realistic total cost?
9. When does it expire?
10. Is it cash settled or physically settled?
11. What happens if it expires in the money?
12. Can I close it before expiry, and what if my exit order does not execute?

Costs are explained in what it costs.

The central idea of this chapter: an option’s value depends not only on where the underlying moves, but on how much movement the market had already priced in, how much time is left, and what the contract requires at expiry. Black–Scholes and its variants quantify those relationships. They do not remove uncertainty, guarantee profit, or replace understanding the contract you are actually trading.