DER 2 – Valuation of Contingent Claims
A contingent claim gives its owner a right, but never an obligation, to a payoff that depends on some underlying asset, rate or other derivative. Options are the contingent claims this reading values. The material matters well beyond the listed options market, because a very large number of ordinary investments contain options that have simply been bundled into something else: a callable bond, a convertible, an employee share scheme, a project that can be abandoned.
Every valuation model in this reading rests on one idea. The correct price of an option is the price at which nobody can extract a riskless profit from anybody else. That single condition, applied carefully, pins the value down exactly. Two families of models implement it. The binomial model works in discrete time and can handle early exercise. The Black–Scholes–Merton model, usually shortened to BSM, works in continuous time and values only options that cannot be exercised early.
Thinking like an arbitrageur
The quickest route into option valuation is to adopt the mindset of a trader hunting for free money. Such a trader prefers more wealth to less and works under two self-imposed constraints.
- Constraint one: commit no capital of your own. Positions are funded by borrowing or by the proceeds of a short sale, and those proceeds stay inside the trade.
- Constraint two: carry no exposure to the price of the underlying. Only market price risk on the underlying and the derivatives used is considered here. Liquidity risk and counterparty credit risk are set aside.
A position satisfying both constraints and still throwing off cash today would be a machine that prints money. Because everybody would want one, such positions cannot survive. Equivalently, if two portfolios deliver identical cash flows in every future state, they must cost the same today. That statement is the law of one price, and it is the engine behind every formula that follows.
Note that an arbitrage is always a wonderful opportunity, but not every wonderful opportunity is an arbitrage. Paying one euro today for a 99 percent chance of one million euros tomorrow and a 1 percent chance of nothing is a superb bet, yet it commits capital and carries risk, so it is not arbitrage.
The standing assumptions
Five assumptions run through the whole reading and are worth memorising as a set.
- Instruments that replicate the option are identifiable and can actually be traded.
- Market frictions such as transaction costs and taxes are absent.
- Short selling is permitted and the seller has full use of the proceeds.
- The underlying follows a known statistical distribution.
- Borrowing and lending at a risk-free rate is available.
Cash flows are tracked in tables throughout, with a consistent sign convention: money leaving the arbitrageur is negative, money arriving is positive. An initial outlay of 100 euros appears as −€100, and a payoff of 1,000 yen appears as +¥1,000.
Notation and the value of an option at expiration
Let St be the price of the underlying observed at time t, with t measured as a fraction of a year, and let ST be the price at expiration. A lower-case c or p denotes a European-style call or put, an upper-case C or P denotes the American-style version, and X is the exercise price, also called the strike. At initiation the subscript is dropped, so c means c0.
At expiration there is no uncertainty left, so the option must be worth exactly what exercising it yields.
Before expiration a European option cannot technically be exercised, so it has no exercise value in a legal sense. The quantity Max(0, St − X) is still a useful reference point, because the difference between the option price and that quantity is the time value: the market valuation of the chance that the option finishes further in the money, net of the chance that it finishes lower. Time value cannot be negative, because option payoffs are asymmetric. A call has unlimited upside and a floor of zero on the downside. Time value shrinks to zero at expiration.
On 15 April a 90-day European-style call option expiring on 14 July is written at a price of c = €2.50.
The simplest possible model of an uncertain future allows the underlying to do exactly two things over one period. Drawn as a lattice, the starting price sits at a node, and two arcs lead to the two possible outcomes. The upper outcome is written S+ and the lower one S−. Crude as this is, everything important about option valuation is already visible in it.
The two outcomes are usually expressed as multiplicative factors on the starting price.
Both factors are gross returns rather than net returns, so an up factor of 1.35 means the underlying gains 35 percent. Their size is governed by the volatility of the underlying: a more volatile underlying produces a larger u and a smaller d.
Building a hedge, then reading the price off it
Suppose a trader writes one call. A call gains when the underlying gains, so a written call loses in the up state and gains in the down state. To cancel that exposure, the trader must hold something that gains in the up state, which means buying the underlying. Let h be the number of units bought, chosen so that the position is worth the same whichever branch occurs.
| Trade | Time step 0 | Time step 1, down | Time step 1, up |
|---|---|---|---|
| Write one call | +c | −c− | −c+ |
| Buy h units of the underlying | −hS | +hS− | +hS+ |
| Borrow or lend | −PV(−hS− + c−) | −hS− + c− | −hS+ + c+ |
| Net | +c − hS − PV(−hS− + c−) | 0 | 0 |
PV denotes discounting one period at the risk-free rate r, so PV(1) = 1/(1 + r).
Setting the two time-step-1 cash flows equal to each other, −c+ + hS+ = −c− + hS−, and solving for h gives the hedge ratio.
The mnemonic is worth carrying into the exam: option value if the underlying rises minus option value if it falls, divided by underlying value if it rises minus underlying value if it falls. Because call values move with the underlying, the call hedge ratio can never be negative.
Once the future cash flows are zero in both states, the time-zero net must also be zero, otherwise the strategy is a money machine. If the net were positive, arbitrageurs would pile in, forcing the call price down and the underlying price up until the profit vanished. If it were negative, they would run the mirror strategy, buying calls, short selling the underlying and lending, until the gap closed. Setting the time-zero net to zero and rearranging produces the valuation equation.
Read the equation in words and it says something concrete: a long call is a holding of h units of the underlying, partly paid for with a loan of PV(−hS− + c−). A call is a geared position in the underlying, nothing more exotic.
The same machinery for puts
Puts follow identical logic with one sign flipped. Because a put loses value when the underlying rises, p+ is below p− while S+ is above S−, so the hedge ratio comes out negative.
Trading h units when h is negative means selling short. Since −h is then positive, the term −hS is a cash inflow at time zero. So a long put is a short position in the underlying combined with lending, which is the mirror image of the call. Writing options simply reverses these trades: the writer of a call short sells the underlying and lends, while the writer of a put buys the underlying on margin.
Two questions on the replicating strategy inside the single-period binomial framework.
The replication equations are exact, but they are fiddly to compute. A little algebra converts them into a form that is far quicker to use and that generalises cleanly to many periods. The option value equals a discounted expected payoff, where the expectation uses a particular probability that falls out of the arbitrage argument rather than out of anybody’s forecast.
Written most compactly, c = PVr[E(c1)] and p = PVr[E(p1)], where the expected terminal payoffs are E(c1) = πc+ + (1 − π)c− and E(p1) = πp+ + (1 − π)p−. The subscript on PV is a reminder that discounting happens at the risk-free rate.
Why this is not ordinary discounted cash flow
Two features separate this from the discounted cash flow valuation used on equities and bonds, and both are examinable.
- The probability is not a forecast. π is determined objectively by u, d and r. It has nothing to do with what anybody thinks the underlying will do. It is called a risk-neutral probability precisely because no assumption about risk preferences was ever made; the number is a by-product of the arbitrage argument. Calling π a probability is a convenience, not a claim that up moves really happen that often.
- The discount rate carries no risk premium. Discounting is at the risk-free rate. Both of the subjective ingredients of discounted cash flow, the expected cash flow and the risk-adjusted discount rate, have been replaced by objective quantities. That is why practitioners generally prefer this route.
Put–call parity as a shortcut
Once a call has been valued, the matching put with the same exercise price follows without further modelling work.
The relationship holds whatever valuation model is being used, because it is itself an arbitrage relationship. Rearranged as c = S − PV(X) + p, it says a call is the underlying, financed, plus a put.
A non-dividend-paying stock trades at €100. A one-year option has exercise price €100, the periodically compounded risk-free rate is 5.15 percent, and a single-period binomial model is assumed with u = 1.35 and d = 0.74.
S+ = uS = 1.35(100) = 135 and S− = dS = 0.74(100) = 74.
c+ = Max(0, 135 − 100) = 35 and c− = Max(0, 74 − 100) = 0.
Then h = (35 − 0)/(135 − 74) = 35/61 = 0.573770.
π = (1.0515 − 0.74)/(1.35 − 0.74) = 0.3115/0.61 = 0.510656.
The one-period discount factor is PV(1) = 1/1.0515 = 0.951022. So
c = 0.951022[(0.510656)35 + (1 − 0.510656)0] = 0.951022(17.87296) = €16.998.
The no-arbitrage route must agree, and it does:
c = 0.573770(100) + 0.951022[−0.573770(74) + 0] = 57.3770 − 40.3794 = €16.998.
Long 0.573770 shares costing 57.38, funded with a loan of 40.38, leaves a net outlay equal to the call price.
p = 0.951022[(0.510656)0 + (1 − 0.510656)26] = 0.951022(12.72294) = €12.10.
Nothing new was estimated. Once π and the discount factor are known they serve every option on that underlying with that maturity.
Adding a second period changes nothing conceptually. A two-period lattice is three one-period lattices: one starting at time 0, and one starting at each of the two time-1 nodes. Solve the two later ones first, then use their answers as the payoffs for the earlier one.
Keeping u and d constant throughout the lattice guarantees recombination, because udS equals duS. Take u = 1.25, d = 0.8 and S0 = 100. An up move then a down move gives 1.25(0.8)100 = 100, and a down move then an up move gives 0.8(1.25)100 = 100. The two paths land on the same node.
This matters computationally, not just aesthetically. A recombining lattice with n time steps has exactly n + 1 terminal nodes. A lattice that fails to recombine has 2n of them, which becomes impossible to handle long before n gets interesting.
Self-financing and dynamic replication
Two properties of the replicating strategy carry names worth knowing. Dynamic replication means the option payoff is matched exactly by a trading plan laid out in advance, with the position adjusted at each node. Self-financing means those adjustments never require fresh money from outside: whatever extra units of the underlying are needed can be paid for by adjusting the borrowing. If outside money were needed, it would have to be financed externally and the arbitrage argument would break down.
Working backward
At time 2 the call is worth its exercise value at each of the three nodes: c++ = Max(0, u2S − X), c+− = Max(0, udS − X) and c−− = Max(0, d2S − X). Puts are the same with the arguments reversed. At time 1 the single-period equations are applied twice, and at time 0 once more.
The annual rate is 3 percent, the non-dividend-paying underlying trades at 72, u = 1.356, d = 0.541, the exercise price is 75 and the call expires in two years. The completed lattice is set out below.
| Node | Underlying | Call | Hedge ratio |
|---|---|---|---|
| Time 0 | 72 | 19.47407 | 0.56971 |
| Time 1, up | 97.632 | 33.43048 | 0.72124 |
| Time 1, down | 38.952 | 0 | 0 |
| Time 2, up up | 132.389 | 57.389 | |
| Time 2, up down | 52.81891 | 0 | |
| Time 2, down down | 21.07303 | 0 |
h+ = (57.389 − 0)/(132.389 − 52.81891) = 57.389/79.57009 = 0.72124.
π = (1.03 − 0.541)/(1.356 − 0.541) = 0.489/0.815 = 0.6.
At the upper time-1 node, c+ = (1/1.03)[(0.6)57.389 + (0.4)0] = (1/1.03)(34.4334) = 33.43048. At the lower node both time-2 payoffs are zero, so c− = 0.
The time-0 hedge ratio is h = (33.43048 − 0)/(97.632 − 38.952) = 33.43048/58.68 = 0.56971, and
c = (1/1.03)[(0.6)33.43048 + (0.4)0] = 19.47.
Move to time 1 after an up move. The shares are now worth 55.622 = 0.56971(97.632) and the loan has grown to 22.191 = 1.03(21.545). The portfolio is worth 55.622 − 22.191 = 33.431, equal to the call value of 33.43048 up to rounding. Dynamic replication holds.
The hedge ratio has risen from 0.56971 to 0.72124, so more shares must be bought. Required borrowing at the new node is 36.98554 = −(1/1.03)[−0.72124(52.81891) + 0]. The old loan due is 22.191, so the new borrowing covers the repayment and funds the extra shares with nothing left over and nothing missing. The strategy is self-financing.
The expectations form over two periods
Repeated substitution collapses the backward induction into a single expression. Because the middle node is reached by two paths, it carries twice the weight.
Here PV discounts over two periods, so with discrete rates the factor is 1/(1 + r)2. Forgetting to square the discount factor is one of the most frequent errors on this calculation.
A non-dividend-paying stock trades at €50. The options have two years to run, the periodically compounded risk-free rate is 5 percent, the exercise price is €50, u = 1.356 and d = 0.744. Assume European-style exercise.
c++ = Max[0, 1.3562(50) − 50] = 91.9368 − 50 = 41.9368.
c+− = Max[0, 1.356(0.744)(50) − 50] = 50.4432 − 50 = 0.44320.
c−− = Max[0, 0.7442(50) − 50] = 0.0, since 27.6768 is below the strike.
Then apply the two-period expectations formula:
c = [1/(1.05)]2[0.52(41.9368) + 2(0.5)(0.5)(0.44320) + 0.52(0.0)]
= 0.907029[10.4842 + 0.2216] = 0.907029(10.7058) = €9.71.
p = c + PV(X) − S = 9.71 + [1/(1.05)]2(50) − 50 = 9.71 + 45.35 − 50 = €5.06.
This shortcut is legitimate only for European-style options, since parity in this form assumes no early exercise.
Dividends reduce the value of the shares on the ex-dividend date, which hurts a call holder. Most listed option contracts offer no protection against ordinary dividends, so the effect has to be modelled. The technique used here is the escrow method: assume the dividends are perfectly predictable, then split the underlying into the part that is uncertain and the part that is not.
The lattice is built on the hatted quantity, the underlying stripped of its known dividends, rather than on S. At expiration the two coincide, since any dividends have already been paid by then, so the terminal node values need no adjustment. An investor who actually held the shares would finish with ST plus the reinvested dividends. Note that exchanges may adjust the exercise price for very large special dividends, but the reading deals with regular, predictable payments.
Consider a call on a US$100 stock with exercise price US$95. The periodically compounded rate is 1.0 percent, the stock pays a US$3 dividend at time step 1, u = 1.224, d = 0.796, and the call expires in two years.
| Node | Underlying without dividends | Call, model value | Call, exercise value | Hedge ratio |
|---|---|---|---|---|
| Time 0 | 100 | 12.3438 | 13.2497 | 0.6004 or 0.6445 |
| Time 1, up | 118.7644 | 24.9344 | 26.7644 | 0.9909 |
| Time 1, down | 77.2356 | 0 | 0 | |
| Time 2, up up | 145.3676 | 50.3676 | ||
| Time 2, up down | 94.5364 | 0 | ||
| Time 2, down down | 61.4796 | 0 |
At time 0 the first hedge ratio applies to the European-style call and the second to the American-style call. The lattice involves technical details beyond the scope of the learning outcomes; the objective is to see how dividend-driven early exercise works.
The upper time-1 node is the interesting one. The present value of the US$3 dividend at time 0 is US$2.970297 = 3/1.01, so the dividend-stripped price after an up move is 118.7644 = (100 − 2.970297)(1.224). Just before the shares go ex-dividend they are worth 118.7644 + 3 = 121.7644, so exercising then yields 121.7644 − 95 = 26.7644. If the holder does not exercise, the shares drop as they go ex-dividend and the call is worth only 24.9344 at the lower, ex-dividend price.
Exercising early therefore captures the dividend that the call holder would otherwise never receive. That is the whole reason an American-style call can be worth more than a European-style one: not the passage of time, but the dividend. Here the American-style call is worth 13.2497 against 12.3438 for the European-style call, and the time-0 hedge ratio rises from 0.6004 to 0.6445.
Using the same inputs, verify the key figures in the lattice above.
Two up moves take the dividend-stripped price to 118.7644(1.224) = 145.3676, so the call pays 145.3676 − 95 = 50.3676. An up then a down gives 118.7644(0.796) = 94.5364, below the strike, so that node pays zero.
The model value at the upper time-1 node is (1/1.01)[(0.5)50.3676 + (0.5)0] = 25.1838/1.01 = 24.9344.
European style: c = (1/1.01)[(0.5)24.9344 + (0.5)0] = 12.3438.
American style: replace 24.9344 with the exercise value 26.7644, giving c = (1/1.01)[(0.5)26.7644] = 13.2497.
The gap of 0.9059 is the value of the right to grab the US$3 dividend at time step 1. The hedge ratio moves in step, from (24.9344 − 0)/(118.7644 − 77.2356) = 0.6004 to (26.7644 − 0)/41.5288 = 0.6445.
The following exercise pulls together everything in the binomial sections: the expectations approach, hedge ratios at every node, the component interpretation of the model, and the difference American-style exercise makes. It is worth working through slowly, because examiners like this exact shape of question.
A non-dividend-paying Australian equity trades at A$7.35. Call and put options have two years to expiry, the periodically compounded risk-free rate is 4.35 percent, and the exercise price is A$8.0. The estimated factors are u = 1.445 and d = 0.715.
π = [(1 + 0.0435) − 0.715]/(1.445 − 0.715) = 0.3285/0.730 = 0.45.
Terminal payoffs:
c++ = Max[0, 1.4452(7.35) − 8.0] = 7.347; c+− = Max[0, 1.445(0.715)(7.35) − 8.0] = 0; c−− = Max[0, 0.7152(7.35) − 8.0] = 0.
p++ = Max[0, 8.0 − 1.4452(7.35)] = 0; p+− = Max[0, 8.0 − 1.445(0.715)(7.35)] = 0.406; p−− = Max[0, 8.0 − 0.7152(7.35)] = 4.24.
Expected payoffs seen from each time-1 node:
for the call after an up move, 0.45(7.347) + 0.55(0) = 3.31; after a down move, 0.45(0) + 0.55(0) = 0.0.
For the put after an up move, 0.45(0) + 0.55(0.406) = 0.2233; after a down move, 0.45(0.406) + 0.55(4.24) = 2.51.
With a one-period discount factor of 1/1.0435 = 0.958313:
c+ = 0.958313(3.31) = 3.17, c− = 0.0, p+ = 0.958313(0.2233) = 0.214, p− = 0.958313(2.51) = 2.41.
At time 0 the two-period expectations are
E(c2) = 0.452(7.347) + 2(0.45)(0.55)(0) + 0.552(0) = 1.488, and
E(p2) = 0.452(0) + 2(0.45)(0.55)(0.406) + 0.552(4.24) = 1.484.
Discounting two periods at 0.91836 gives c = 0.91836(1.488) = A$1.37 and p = 0.91836(1.484) = A$1.36.
The call and put are almost equal here by design. The spot price sits close to the present value of the exercise price, 7.35 versus 8.0/1.04352, and put–call parity written as c − p = S − PV(X) then makes the two values coincide.
Time-1 hedge ratios:
call, up node: (7.347 − 0.0)/(15.347 − 7.594) = 0.9476; call, down node: (0.0 − 0.0)/(7.594 − 3.758) = 0.0.
put, up node: (0.0 − 0.406)/(15.347 − 7.594) = −0.05237; put, down node: (0.406 − 4.24)/(7.594 − 3.758) = −1.0, because both put payoffs below that node are in the money.
Now read the components. For the call after an up move,
c+ = 0.9476(10.621) + (1/1.0435)[−0.9476(7.594) + 0.0] = 10.0645 − 6.8961 = 3.1684.
That is long 0.9476 shares costing 10.0645, funded by a loan of 6.8961. The loan can also be read straight off as cost of shares minus option value, 10.0645 − 3.1684.
For the put after an up move,
p+ = (1/1.0435)[−(−0.05237)15.347 + 0.0] + (−0.05237)(10.621) = 0.77022 − 0.55622 = 0.2140.
That is short 0.05237 shares raising 0.55622, with 0.77022 placed on deposit. Lending equals short-sale proceeds plus the option value.
After a down move, p− = (1/1.0435)[−(−1.0)7.594 + 0.406] + (−1.0)(5.255) = 7.6665 − 5.255 = 2.4115, that is short 1.0 share with 7.6665 lent.
At time 0, hc = (3.1684 − 0)/(10.621 − 5.255) = 0.5905 and hp = (0.2140 − 2.4115)/(10.621 − 5.255) = −0.4095. Then
c = 0.5905(7.35) + (1/1.0435)[−0.5905(5.255) + 0.0] = 4.3402 − 2.97 = 1.37, long 0.5905 shares with a 2.97 loan, and
p = (1/1.0435){−[−0.4095(10.621)] + 0.214} + (−0.4095)(7.35) = 4.37 − 3.01 = 1.36, short 0.4095 shares with 4.37 lent.
Max(0, 10.621 − 8.0) = 2.621 against 3.1684; Max(0, 5.255 − 8.0) = 0.0 against 0.0; Max(0, 7.35 − 8.0) = 0.0 against 1.37.
Neither the hedge ratios nor the values move.
The put is different. At time 1 the hedge ratios are unchanged, because only one period remains, so p+ = 0.214 and p− = 2.41 initially. The exercise values are Max(0, 8.0 − 10.621) = 0, below 0.214, but Max(0, 8.0 − 5.255) = 2.745, above 2.41. So the lower node is replaced by 2.745.
The hedge ratio becomes hp = (0.2140 − 2.745)/(10.621 − 5.255) = −0.4717, and
p = (1/1.0435)[0.45(0.214) + 0.55(2.745)] = 1.54.
Early exercise lifts the put from 1.36 to 1.54 and steepens the hedge ratio from −0.4095 to −0.4717.
Two general lessons survive from this exercise. An option is always a position in the underlying combined with financing, and the binomial value is always a present value of expected payoffs taken under the risk-neutral measure and discounted at the risk-free rate. The binomial framework extends to other underlyings with modest surgery: currency options bring in the foreign interest rate, futures options need a lattice of futures prices. Interest rate options need something more, and that is the next topic.
When the underlying is an interest rate rather than an asset price, one convenient feature of the equity lattice disappears. The discount rate is no longer a constant sitting outside the tree; it is the very thing moving inside the tree. Valuation therefore requires a whole term structure, which is usually supplied as an arbitrage-free interest rate lattice. How such lattices are built is outside the scope here. The version used sets the risk-neutral probability of an up move at 50 percent at every node.
| Node | Maturity | Rate, percent | Value of a one-period zero |
|---|---|---|---|
| Time 0 | 1 | 3.0454 | 0.970446 |
| Time 1, up | 1 | 3.9084 | 0.962386 |
| Time 1, down | 1 | 2.6034 | 0.974627 |
| Time 2, up up | 1 | 3.9706 | 0.961810 |
| Time 2, up down | 1 | 3.2542 | 0.968484 |
| Time 2, down down | 1 | 2.2593 | 0.977906 |
Maturity here means time remaining on the bond, not calendar time, so every entry is a one-period bond. The time-0 spot rate follows from the bond value: (1.0/0.970446) − 1 = 3.04540 percent.
The underlying for these options is the spot rate itself. An interest rate call is in the money when the spot rate is above the exercise rate, and an interest rate put is in the money when the spot rate is below it. That is the opposite orientation to a bond option, and confusing the two is a classic error.
The valuation procedure is the familiar expectations approach applied one period at a time. The one change is that the discount factor is taken from the node you are standing on, not from a single rate applied everywhere.
Using the lattice above, price a call and a put that expire in two years, are European in style, and reference the one-year spot rate on a periodically compounded basis. The notional is US$1,000,000, the exercise rate is 3.25 percent of par, the risk-neutral probability is 50 percent, and settlement is in cash at time 2 against the rate observed then.
c++ = Max[0, 0.039706 − 0.0325] = 0.007206.
c+− = Max[0, 0.032542 − 0.0325] = 0.000042. Note how narrowly this node finishes in the money.
c−− = Max[0, 0.022593 − 0.0325] = 0.0.
p++ = Max[0, 0.0325 − 0.039706] = 0.0.
p+− = Max[0, 0.0325 − 0.032542] = 0.0.
p−− = Max[0, 0.0325 − 0.022593] = 0.009907.
c+ = 0.962386[0.5(0.007206) + 0.5(0.000042)] = 0.962386(0.003624) = 0.003488.
c− = 0.974627[0.5(0.000042) + 0.5(0.0)] = 0.00002.
p+ = 0.962386[0.5(0.0) + 0.5(0.0)] = 0.0.
p− = 0.974627[0.5(0.0) + 0.5(0.009907)] = 0.004828.
The up node discounts at 0.962386 and the down node at 0.974627. Because the underlying is the rate itself, the discount factor has to move with it.
c = 0.970446[0.5(0.003488) + 0.5(0.00002)] = 0.00170216.
p = 0.970446[0.5(0.0) + 0.5(0.004828)] = 0.00234266.
Scaling by the US$1,000,000 notional gives a call value of US$1,702.16 and a put value of US$2,342.66. The whole calculation is three one-period problems chained together.
From two periods to many
Nothing stops the slicing at two. Divide the option life T into n equal steps of length T/n and the same backward induction runs on a bigger lattice. For American-style options every node gets the exercise test, taking the larger of the model value and the exercise value. As n grows the model becomes both more realistic and more laborious, and in the limit it converges on the continuous-time model in the next section.
Keep the division of labour clear. The expectations approach is quick and applies to European-style options. The no-arbitrage approach applies to both styles, handles early exercise, and is the one that explains what the option actually is.
Louis Bachelier published the first mathematically rigorous option model in 1900. Several quantitative models existed by the late 1960s, but the breakthrough came in 1973, when Fischer Black and Myron Scholes published one paper and Robert Merton another. What the BSM model adds is not a new principle but a new setting: the same no-arbitrage replication argument, run in continuous time. It is the limiting case of a binomial model as the time step shrinks toward zero, which is consistent with the statistical result that a binomial process with many steps converges toward the normal distribution. Scholes and Merton received the 1997 Nobel Prize partly for this work; Black had died in 1995, and the prize is not awarded posthumously.
Choosing a distribution
The central modelling decision is how to describe the randomness of the underlying. Bachelier proposed the normal distribution, which has real attractions: zero is attainable so bankruptcy is allowed, it is symmetric, it is easy to manipulate, and sums of normal variables stay normal. Its fatal flaw for equities is that it permits negative prices, which conflicts with limited liability. Research on stock prices through the 1950s and 1960s moved opinion toward the lognormal distribution, under which the logarithm of the return is normally distributed. Black, Scholes and Merton adopted it.
A terminal distribution is not enough, though, because replication has to be dynamic and self-financing. The model needs a description of how the price evolves at every instant, which is what a stochastic process provides. The one chosen is geometric Brownian motion.
Picture a simulation starting at S = 50 with a geometrically compounded growth rate of μ = 3 percent a year and a volatility of σ = 45 percent. Volatility here means the annualised standard deviation of the continuously compounded percentage change, that is the log return. Two features stand out. Paths that drift upward become more variable in absolute terms while paths that drift downward become less variable, because a 10 percent move on a price of 100 is 10 units but only 1 unit on a price of 10. And the price can never reach zero or go below it, which suits instruments with limited liability. Movements are erratic but never jump.
Within the model, investors are assumed to agree about everything in the distribution except the growth rate of the underlying. The standard version holds both the growth rate and the volatility constant.
The assumption list
- The underlying follows geometric Brownian motion, so the continuously compounded return is normally distributed.
- Prices are continuous. They move smoothly from one value to the next rather than jumping.
- The underlying is liquid and can be bought and sold easily.
- Trading is continuous, in the strict sense that a position can be adjusted at every instant.
- Short selling of the underlying is permitted with full use of the proceeds.
- There are no market frictions: no transaction costs, no regulatory constraints, no taxes.
- No arbitrage opportunities exist in the market.
- The options are European-style, so early exercise is ruled out.
- The continuously compounded risk-free rate is known and constant, and borrowing and lending at that rate is available.
- The volatility of the return on the underlying is known and constant.
- Any yield on the underlying is a continuous, known and constant annualised rate.
None of these is literally true. The test of a financial model is not realism of assumptions but whether it is tractable and useful, and on that test the BSM model has done very well.
Because the setting is continuous time, the interest rate r throughout this section is the annualised continuously compounded rate, and σ is annualised volatility. Start with a non-dividend-paying stock.
N(x) returns the probability of drawing a value below x from a standard normal distribution, which has mean 0 and standard deviation 1. Read off a table or a spreadsheet, N(−1.645) = 0.05, so a d of −1.645 corresponds to 5 percent. Any negative d gives an N below 0.5, and symmetry gives the identity N(−x) = 1 − N(x), which is why the put formula can be written with negative arguments. Note that although the underlying is lognormally distributed, the N functions inside the model are standard normal.
Three ways to read the formula
As a discounted expected payoff. The model can be written c = PVr[E(cT)] with E(cT) = SerTN(d1) − XN(d2), and for puts E(pT) = XN(−d2) − SerTN(−d1). The present value factor is simply e−rT. As with the binomial model, the expectation is taken under the risk-neutral measure and the discounting uses the risk-free rate, not a required return that reflects risk.
As two components. For a call, the stock component is SN(d1) and the bond component is e−rTXN(d2); the call is the first minus the second. For a put, the stock component is SN(−d1) and the bond component is e−rTXN(−d2); the put is the bond component minus the stock component.
As a dynamically managed portfolio. This is the interpretation the learning outcome asks for. The replicating portfolio costs nSS + nBB, where the bond is a zero-coupon bond priced at B = e−rTX. A positive n means buying and a negative n means selling short.
| Instrument | Call | Put |
|---|---|---|
| Units of the underlying, nS | N(d1), positive | −N(−d1), negative |
| Units of the zero-coupon bond, nB | −N(d2), negative | N(−d2), positive |
For a call, the underlying is bought and the bond is sold short, which is borrowing. So a call is a leveraged position in the underlying, exactly as the binomial model said. For a put, the underlying is sold short and the proceeds buy bonds, so a put is lending funded by a short sale. A written put is the reverse: cash is received today, the position is long the underlying and short the bond, and the borrowing exceeds the full cost of the underlying, so a short put is an over-geared long position.
| Model | Call: underlying | Call: financing | Put: underlying | Put: financing |
|---|---|---|---|---|
| Binomial | hS | PV(−hS− + c−) | hS | PV(−hS− + p−) |
| BSM | N(d1)S | −N(d2)e−rTX | −N(−d1)S | N(−d2)e−rTX |
The parallel between the binomial hedge ratio h and N(d1) is exact in the limit.
What N(d2) means, and what replication costs in practice
N(d2) has a second reading: it is the risk-neutral probability that the call finishes in the money, so N(−d2) is the risk-neutral probability that the put does. It is emphatically not your own estimate of that probability, nor the market consensus estimate. It is the probability under the unique measure implied by the absence of arbitrage.
Because S pushes d1 upward, N(d1) rises as the underlying rises. Replicating a call therefore means buying more of the underlying into a rising market and selling into a falling one. Inside the theory, the accumulated losses from that buy-high, sell-low discipline add up over the option life to exactly the premium received at inception, which they must, or an arbitrage would exist. In practice transaction costs are not zero, so frequent rebalancing is expensive, and markets do jump, so hedges are imperfect. A merger announcement can move a share price discontinuously, which the model rules out by assumption. Volatility is also unknown in advance. For these reasons traded options tend to be dearer than the theory predicts, and practitioners often feed the formula a volatility a point or two above what they truly expect.
For options on a stock with S = 100, X = 100, r = 5 percent, T = 1.0 and σ = 30 percent, the BSM model gives PV(X) = 95.123, d1 = 0.317, d2 = 0.017, N(d1) = 0.624, N(d2) = 0.507, N(−d1) = 0.376, N(−d2) = 0.493, c = 14.23 and p = 9.35.
Holding the underlying instead of the derivative can produce a benefit or impose a cost. Dividends on shares, foreign interest on a currency and coupons on a bond are benefits. Storage and insurance on an agricultural commodity are costs, which enter as negative benefits. Because the model works in continuous time, these are handled as a continuous yield, written γ.
Read as a discounted expectation, the expected payoffs become E(cT) = Se(r−γ)TN(d1) − XN(d2) and E(pT) = XN(−d2) − Se(r−γ)TN(−d1), while the discount factor stays e−rT. Carry lowers the expected future value of the underlying, and the consequences are worth stating plainly: a larger carry benefit lowers the value of a call and raises the value of a put. Since carry pushes d2 down, the risk-neutral probability that a call finishes in the money also falls.
Equity options
For stocks, γ = δ, the continuously compounded dividend yield. The replicating portfolio adapts: for calls nS = e−δTN(d1), still positive, and for puts nS = −e−δTN(−d1), still negative. The bond counts are unchanged at nB = −N(d2) for calls and nB = N(−d2) for puts.
The economics behind that adjustment is simple. A long position in the shares collects the dividends, and a short position has to pay them, so the burden of carrying a long position is lighter. Dividends therefore reduce the number of shares needed to replicate a call and increase the number that must be sold short to replicate a put. Higher dividends also lower d1 and hence N(d1), reduce the number of bonds to short for calls, and raise the number to buy for puts.
Currency options
For foreign exchange, γ = rf, the continuously compounded foreign risk-free rate, because idle foreign currency can be placed in the foreign risk-free instrument. The quoting convention is domestic currency per unit of foreign currency, so a euro trading for 135 Japanese yen is written 135¥/€, with the euro as the foreign currency and the yen as the domestic one. This is the natural convention for a Japanese firm reporting euro holdings in yen.
A few practical points follow. The underlying is the spot exchange rate. The underlying and the exercise price must be quoted in the same units. The volatility is the volatility of the log return on the spot rate. Each contract covers a notional amount of foreign currency, and the total premium is the formula value multiplied by that notional, exactly as an equity option value is multiplied by the number of shares covered.
The two-component reading carries across: for a call the foreign exchange component is Se−rfTN(d1) and the bond component is e−rTXN(d2), with r the domestic rate; the call is the first minus the second, and the put reverses the order using the negative arguments.
Three short applications of the carry-adjusted model.
If instead δ = 0 percent, the values change, and not only because the stock component loses its adjustment. Both d1 and d2 depend on γ, so all three moving parts shift together.
In 1976 Fischer Black adapted the BSM approach to underlyings that cost nothing to carry, of which futures and forward contracts are the leading examples. The family covered is large: equity index futures options, and, through forwards, interest rate instruments such as caps, floors and swaptions.
Assume the futures price also follows geometric Brownian motion, and set aside margin and marking to market.
F0(T) is the futures price observed at time 0 for delivery at time T, and σ is the volatility of the futures price. In effect this is the BSM model with the futures price standing in for the carry-arbitrage-adjusted spot price. Put–call parity for futures options is
The component reading survives intact. For a call, the futures component is F0(T)e−rTN(d1) and the bond component is e−rTXN(d2), with the call being the difference. For a put the futures component uses N(−d1), the bond component uses N(−d2), and the bond component comes first. Equivalently, the option value is the present value of the gap between the futures price and the exercise price, with each of the two adjusted by the appropriate N term.
The S&P 500 Index, a spot index, stands at 1,860 and the futures contract expiring in 0.25 years trades at 1,851.65. The exercise price is 1,860, the continuously compounded risk-free rate is 0.2 percent, time to expiration is 0.25, volatility is 15 percent and the dividend yield is 2.0 percent. The model output is as follows.
| Term | Call | Put |
|---|---|---|
| N(d1) and N(−d1) | 0.491 | 0.509 |
| N(d2) and N(−d2) | 0.461 | 0.539 |
| Value | US$51.41 | US$59.76 |
The contract multiplier, 250 for this contract at the time of writing, is ignored. In practice the premium would be 250 times the figures shown.
With interest rate options the underlying is a reference rate such as three-month MRR. An interest rate call gains when the reference rate rises and an interest rate put gains when it falls. These options are the raw material for a great deal else in the fixed income toolkit.
For a one-year interest rate call on three-month MRR, the underlying is the rate on a forward rate agreement expiring in one year. That FRA is observable today and is the rate fed into the model. The deposit underlying the FRA is a three-month deposit placed in 12 months and maturing in 15 months, and as the year passes the FRA rate normally converges on the three-month spot rate.
Advanced set, settled in arrears
Interest rates are fixed at the start of a period but paid at the end, a convention described as advanced set, settled in arrears. A bank deposit made at time tj−1 has its rate fixed then, but the interest arrives at time tj, so the deposit runs for tm = tj − tj−1. Floating rate loans work the same way. So does the settlement of many interest rate options: if a payment of US$5,000 based on three-month MRR is determined on 15 January, the money changes hands on 15 April.
Rates are quoted annually while the underlying deposit is usually shorter, so an accrual period adjustment is needed. A quarterly reset FRA on a 30/360 day count has an accrual period of 0.25 = 90/360. On an actual/360 basis with 91 days in the period it becomes 0.252778 = 91/360. Typically the FRA accrual uses 30/360 while the option side uses actual days over actual days, or actual over 365.
The model
Write FRA(0, tj−1, tm) for the fixed rate available today on a forward rate agreement that expires at tj−1 and whose underlying deposit matures at tj = tj−1 + tm. For instance FRA(0, 0.25, 0.5) = 2 percent means a 2 percent fixed rate on an agreement expiring in 0.25 years with settlement in 0.75 years. Let RX be the exercise rate and σ the annualised standard deviation of the continuously compounded change in the FRA rate.
Five differences from the plain Black model deserve memorising.
- The discount factor runs to the FRA maturity date tj, written as tj−1 + tm to keep the settlement in arrears visible, and not merely to option expiration.
- The underlying is a forward interest rate, not a futures price.
- The exercise price is really an exercise rate.
- The time to option expiration, tj−1, is what enters d1 and d2.
- The rates must be entered in decimals, so 0.02 rather than 2.0, unless the notional adjustment is divided by 100 instead.
The formulas price a notional of 1, so the actual premium is the formula value multiplied by the notional, just as a stock option value is multiplied by the number of shares covered. As with every other model here, the value is a discounted expected payoff, with the present value factor e−rtj running from the settlement date.
Combinations worth knowing
- With the exercise rate set at the current FRA rate, long a call and short a put reproduces a receive-floating, pay-fixed FRA.
- With the same exercise rate, long a put and short a call reproduces a receive-fixed, pay-floating FRA. Since FRAs are the building blocks of swaps, this is the bridge to the next section.
- An interest rate cap is a strip of interest rate calls, individually called caplets, with sequential maturities. A borrower on a floating rate loan can hedge with a long cap.
- An interest rate floor is a strip of interest rate puts, individually called floorlets. A holder of a floating rate bond, or any floating rate lender, can hedge with a long floor.
- Long a cap and short a floor struck at the swap rate is a receive-floating, pay-fixed swap. Above the strike both the cap and the swap pay the holder; below the strike the short floor requires a payment, exactly as the swap would. Reversing both legs gives the pay-floating, receive-fixed swap.
- Set the exercise rate at the swap rate and the cap and the floor must have equal value at inception. A new swap has zero value, so the cost of being long the cap and short the floor is also zero.
You are a speculative investor in Singapore. On 15 May you expect regulatory changes and wish to profit. On 15 June you intend to borrow 10,000,000 Singapore dollars to buy an asset you expect to resell three months later, on 15 September. Three-month SORA, the Singapore reference rate, is currently 0.55 percent. The FRA rate covering 15 June to 15 September is 0.68 percent. Worried that rates will rise, you buy an interest rate call struck at 0.60 percent.
A swaption is an option on a swap. The holder has the right, not the obligation, to enter a swap at a pre-agreed fixed rate, which serves as the exercise rate. Since swaps come in two directions, so do swaptions.
- A payer swaption is an option to enter a swap paying fixed and receiving floating.
- A receiver swaption is an option to enter a swap receiving fixed and paying floating.
The words call and put are usually avoided here, because it is easy to lose track of what the underlying is. The naming convention keys off the fixed leg.
Follow the buyer of a payer swaption, who profits when fixed rates rise. On exercise, that buyer enters a pay-fixed, receive-floating swap at the exercise rate RX, then immediately enters an offsetting at-market receive-fixed, pay-floating swap at the prevailing fixed rate. The two floating legs cancel. What remains is a stream of payments equal to the difference between the current fixed swap rate and the exercise rate. That is why a swaption is valued as an annuity rather than as a single payoff.
Four differences from the Black model matter. There is no separate discount factor, because the annuity term already embeds the discounting over the swaption life and the payoff is a series rather than a single amount. The underlying is the fixed rate on a forward interest rate swap rather than a futures price. The exercise price is an interest rate. And the rates go in as decimals.
Component reading: for a payer swaption the swap component is (AP)PVA(RFIX)N(d1) and the bond component is (AP)PVA(RX)N(d2), with the value being the first minus the second. For a receiver swaption the same two components use the negative arguments and the bond component comes first. Written as an expectation, the swaption value is the present value of the expected payoff at expiration, where the expected payoff is the current value grossed up at the risk-free rate, since the annuity term has already done the discounting.
Equivalences
- Hold a receiver swaption and write a payer swaption, both struck at one rate, and the combination behaves as a forward swap that receives fixed and pays floating.
- Reverse the pair, holding the payer and writing the receiver at that same rate, and the combination behaves as a forward swap that pays fixed and receives floating.
- Choose the exercise rate so that the two swaptions have equal value and that rate is the at-market forward swap rate. This is the put–call parity of the swaption market.
- A long position in a callable fixed-rate bond is a long straight fixed-rate bond plus a short receiver swaption.
The last relationship rewards a moment of thought. A receiver swaption gives its buyer the right to receive fixed, so the seller must pay fixed when the buyer exercises, which happens when rates have fallen. That is precisely when a bond issuer would call the bonds. An issuer who sells a receiver swaption on matching terms has effectively converted the callable bond into a straight bond: the issuer pays the fixed rate on the underlying swap, and the floating rate received offsets the floating rate loan created by refinancing. The embedded call feature and the short receiver swaption are two descriptions of the same exposure.
An Australian company carries floating rate debt and has benefited from falling rates. It now fears the central bank will tighten within three months. Rather than lock in borrowing costs with a swap today, it prefers to buy a swaption expiring in three months giving the right, but not the obligation, to enter a five-year swap. The current three-month forward, five-year swap rate is 2.65 percent. The current five-year swap rate is 2.55 percent. The current three-month risk-free rate is 2.25 percent.
Once a valuation model exists, it can be differentiated with respect to each of its inputs. The resulting sensitivities are known collectively as the Greeks: delta, gamma, theta, vega and rho. They are static risk measures, capturing the effect of moving one factor while holding every other factor fixed. Because they come out of a model, they are model dependent, so a manager must choose a model suited to the instrument. The discussion below uses European stock options on an underlying with a continuous dividend yield δ, where δ = 0 covers non-dividend-paying stock.
Delta measures how much an instrument changes for a small change in the underlying. A long share has a delta of exactly +1.0 and a short share exactly −1.0. For options,
Since N(d1) lies between 0 and 1, call delta ranges from 0 to e−δT and put delta from −e−δT to 0. As the underlying rises, a call moves deeper in the money and N(d1) heads toward 1; as it falls, N(d1) heads toward zero. As expiration approaches, delta drifts toward 0 for an out-of-the-money option and toward 1 for one that is in the money. Delta answers how much, not how likely: it says nothing about the probability of the move it describes.
Executing a hedge
Delta hedging means taking a position in the underlying, sized by delta, so that small moves in the underlying leave the total position unchanged. For a single option, compute the delta and buy or sell that many units of the underlying. In practice a manager holds many positions at once, so delta hedging really means steering the delta of the whole portfolio. Driving it to zero produces a delta neutral portfolio.
Three quick illustrations fix the mechanics. A portfolio of 100,000 shares at US$10 has a portfolio delta of 100,000, and with stock as the hedging instrument the delta of the hedge is +1, so NH = −100,000: short 100,000 shares. A portfolio delta of 5,000 hedged with a call whose delta is 0.5 requires NH = −5,000/0.5 = −10,000, so sell 10,000 calls. A portfolio of options with a delta of −1,500 hedged with stock requires NH = −(−1,500)/1 = 1,500, so buy 1,500 shares.
Delta as an approximation
Delta also forecasts option price changes. Writing the new values with hats, the delta approximation is
For a small move the approximation is excellent. Push the underlying from 100 to 101 and the delta line and the model value are barely distinguishable. Push it from 100 to 150 and the model value sits well above the delta line. The error grows with the size of the move, and it is biased low in both directions, upward moves and downward moves alike, because the model value curves away from its own tangent. That is the same statement as saying delta hedging is imperfect, and it explains why continuous trading matters so much inside the theory: the hedging risk is exactly the gap between the two lines, and it is realised when the underlying moves a long way at once.
Apple stock trades at US$125. You write calls on 1,000 Apple shares, so you lose if Apple rises and gain if it falls. The call delta is 0.50, meaning a US$0.10 rise in Apple lifts a call on one share by US$0.05. You buy 500 Apple shares to hedge, so a US$0.10 rise costs US$50 on the written calls and earns US$50 on the shares.
NH = −(4,190/1) = −4,190, that is short sell 4,190 shares.
NH = −(4,190/0.532) = −7,875.9, that is sell 7,876 call options. Both hedges neutralise the same exposure; only the instrument differs.
Delta is a straight line drawn through a curve, so it degrades as the move gets larger. Gamma measures how fast delta itself changes when the underlying moves, and therefore how much curvature the delta line is failing to capture.
Note the change of case. Throughout the reading N denotes the cumulative distribution, while n denotes the density that generates it. Confusing them produces a badly wrong number.
A share has zero gamma, since its delta is fixed at +1 for a long position and −1 for a short one and never moves. Call gamma equals put gamma, and put–call parity shows why. Parity says c − p = S0 − e−rTX. Neither term on the right depends on delta, so the right-hand side has a constant delta of 1 and is insensitive to further moves in the underlying. The left-hand side must therefore have zero net gamma, which means the two gammas are equal.
Gamma is never negative and reaches its maximum near the money. Deep in the money or deep out of the money, delta barely responds to small moves, so gamma is small. Like delta, gamma changes as the underlying moves and as expiration approaches.
Gamma as a risk measure
Gamma quantifies the error left in the delta approximation, so it is a measure of non-linearity risk: the exposure that survives after a portfolio has been made delta neutral. A gamma neutral portfolio has gamma of zero.
The practical sequence is gamma first, delta second. Shares have gamma of zero, so gamma can only be changed by trading options. Once option trades have brought portfolio gamma to the desired level, the portfolio delta can be moved to its target by buying or selling shares, and because shares carry no gamma this second step leaves the gamma untouched. Doing it the other way round means the option trades needed for gamma would disturb the delta already set.
Adding the quadratic term transforms the accuracy. For small moves both approximations track the model value closely. Move the underlying from 100 to 150 and the model value is far above the delta line but now sits slightly below the delta-plus-gamma line, so the second-order estimate is much the better of the two. The direction of the residual error changes, though: the delta-plus-gamma approximation is biased low for a downward move and biased high for an upward move, whereas the plain delta approximation was biased low in both directions.
Gamma also names a real trading hazard. If the BSM assumptions held exactly, an option position could be managed without risk. Prices jump instead of gliding, and a jump leaves a delta-hedged book suddenly unhedged, because the delta that was correct a moment ago is now wrong. That exposure is what traders call gamma risk.
Theta
Theta measures the change in value for a small advance in calendar time, everything else held constant. That last phrase carries a lot of weight: the theta calculation assumes literally nothing changes except the date. As calendar time advances, the time remaining to expiration falls. Shares do not expire, so a share has zero theta, and like gamma, theta cannot be adjusted by trading shares.
The profit or loss produced by the mere passage of time is called time decay. Long option positions can lose real money without the underlying moving at all, which is why managers with large option books watch theta closely. Theta is unlike delta and gamma in one important respect: there is no uncertainty about it. The underlying may or may not move, but time passes with certainty and never runs backward.
Theta is typically negative for options: as the date advances, the option loses value. Plot an at-the-money call and an at-the-money put against time to expiration and both decline toward zero, on the assumption that the underlying does not move. The decline is not linear. The nearer expiration comes, the faster value is lost.
Vega
Vega measures the change in value for a small change in volatility, everything else held constant. Vega is positive for options: more volatility means a more valuable call and a more valuable put alike. Call vega equals put vega, by the same parity argument used for gamma, since neither S0 nor e−rTX depends on volatility, so the vega of the right-hand side is zero and the two option vegas must offset.
Vega is different from the other Greeks in a fundamental way: the parameter it differentiates with respect to cannot be observed. Historical volatility can be computed, but the model wants future volatility, and there is no objective measure of that. Vega therefore measures sensitivity to the volatility number fed into the model rather than to any observable quantity. Of the five BSM inputs, value is most sensitive to volatility, which makes vega the most important Greek for many option books.
Vega is largest at or near the money. Volatility can generally be hedged only with other options, and volatility is itself volatile, so it is often treated as a separate asset class or risk factor. That makes it worth managing explicitly, and worth explaining to risk managers, board members and clients before, rather than after, it produces a loss.
Take at-the-money European options with S = 100, X = 100, r = 5 percent, T = 1 and δ = 0.
100 − 100e−0.05(1) = 100 − 95.12 = 4.88.
For a European put the lower bound is the larger of zero and the present value of the exercise price less the underlying:
95.12 − 100 is negative, so the bound is 0.
The two differ by 4.88, which is exactly what put–call parity predicts, since c − p = S − PV(X). The call retains value at zero volatility because the exercise price is paid later; the put does not, because it would have the holder receiving that money later.
Rho
Rho measures the change in value for a small change in the risk-free rate, everything else held constant. Call rho is positive. Buying a call rather than the underlying avoids the financing cost of the shares, leaving money to earn interest, and the higher the rate the more that is worth. Put rho is negative. Buying a put rather than selling the underlying postpones receipt of the sale proceeds and the interest they would earn, so a higher rate makes the put less attractive.
At a zero interest rate, at-the-money calls and puts have the same value, because c − p = S0 − e−rTX collapses to S0 − X, which is zero at the money. As rates rise the gap between call and put values widens. In practice the effect of rate changes on option prices is small next to the effect of changes in volatility or in the underlying, so rho is rarely the manager’s first concern. One exception matters: for interest rate options the rate is the underlying, so its influence on value is captured by delta, not rho. Rho is best understood generally as sensitivity to the rate used for discounting.
Every input to an option model is observable except one. The underlying price, the exercise price, the expiration date, the risk-free rate and the dividend yield are all known or agreed. Volatility over the life of the option, looking forward, is not. It can be estimated from history, for example by measuring the realised volatility of the past three months and using it for the next three, but history is a frail guide, and different investors will hold different views. The investor with the best forecast has the best estimate of value.
There is another way round the problem. Option prices are observable and plentiful, so the model can be inverted: hold every other input fixed and solve for the volatility that reproduces the traded price. That number is the implied volatility, and the exercise is analogous to computing yield to maturity from a bond price. There is a one-to-one relationship between implied volatility and price, so nothing is lost in the translation.
What is gained is information. Implied volatility summarises the market view of uncertainty ahead, and it also reflects demand. If buying pressure for options is not fully arbitraged away, because of transaction costs or other frictions, prices rise and implied volatility rises with them. Traders read that as a signal in its own right.
The surface is not flat
The BSM model assumes everybody agrees on a single, non-stochastic volatility. Reality disagrees. Implied volatilities differ across exercise prices, and they differ between calls and puts written on identical terms. They also differ across expirations.
- Implied volatility plotted against time to expiration is the term structure of volatility.
- Implied volatility plotted against exercise price is the volatility smile, or the skew when the shape is lopsided.
- Plotting against both at once gives a three-dimensional volatility surface.
If the model assumptions held, the surface would be flat. It is not.
Implied volatility also moves through calendar time. A rise signals that participants are charging more for risk. If put implied volatility rises, downside protection has become dearer, so the market price of hedging has gone up. Index option markets have spawned volatility indexes that track this collective opinion, and futures and options on those indexes let managers hedge vega exposure elsewhere in a book.
The best known is the Chicago Board Options Exchange S&P 500 Volatility Index, the VIX, quoted in percentage points and designed to approximate the implied volatility of the S&P 500 over the next 30 days. It is often called the fear index, since a higher reading is read as greater investor uncertainty. Daily values over roughly two and a half decades from 2 January 1990 show long calm stretches punctuated by spikes, with an extreme reading during the 2008 global financial crisis. Remember what such a reading contains: both a higher expectation of future volatility and a stronger preference for owning rather than writing options.
Volatility as a quoting convention
Because the mapping from volatility to price is one-to-one given the other inputs, market participants quote options in volatility rather than in currency. A call trading at €14.23 might be quoted as 30.00, meaning an implied volatility of 30 percentage points. Any counterparty using the agreed model and the agreed other inputs recovers the price.
The advantage is comparability. Volatility tends to be of similar magnitude across exercise prices and expirations, so quoting in volatility strips out the effects of moneyness and time and leaves a common unit. Ask which of two calls on the same stock is more expensive when one has a longer expiration and a lower exercise price and the other has a shorter expiration and a higher exercise price, and the raw prices cannot answer. The implied volatilities can. This is also why regulators, banks, compliance teams and traders communicate about option portfolios in volatility terms: together with an agreed model it delivers a market consensus valuation, in the same way that market prices value other assets.