# Early Exercise of American Calls

## Full text

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### Consequences of Put-Call Parity

• There is only one kind of European option.

– The other can be replicated from it in combination with stock and riskless lending or borrowing.

– Combinations such as this create synthetic securities.

• S = C − P + PV(X): A stock is equivalent to a portfolio containing a long call, a short put, and lending PV(X).

• C − P = S − PV(X): A long call and a short put

amount to a long position in stock and borrowing the PV of the strike price (buying stock on margin).

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### Intrinsic Value

Lemma 3 An American call or a European call on a non-dividend-paying stock is never worth less than its intrinsic value.

• An American call cannot be worth less than its intrinsic value.a

• For European options, the put-call parity implies C = (S − X) + (X − PV(X)) + P ≥ S − X.

• Recall C ≥ 0 (p. 218).

• It follows that C ≥ max(S − X, 0), the intrinsic value.

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### Intrinsic Value (concluded)

A European put on a non-dividend-paying stock may be worth less than its intrinsic value.

Lemma 4 For European puts, P ≥ max(PV(X) − S, 0).

• Prove it with the put-call parity.a

• Can explain the right ﬁgure on p. 190 why P < X − S when S is small.

aSee Lemma 8.3.2 of the textbook.

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### Early Exercise of American Calls

European calls and American calls are identical when the underlying stock pays no dividends.

Theorem 5 (Merton, 1973) An American call on a non-dividend-paying stock should not be exercised before expiration.

• By Exercise 8.3.2 of the text, C ≥ max(S − PV(X), 0).

• If the call is exercised, the value is S − X.

• But

max(S − PV(X), 0) ≥ S − X.

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### Remarks

• The above theorem does not mean American calls should be kept until maturity.

• What it does imply is that when early exercise is being considered, a better alternative is to sell it.

• Early exercise may become optimal for American calls on a dividend-paying stock, however.

– Stock price declines as the stock goes ex-dividend.

– And recall that we assume options are unprotected.

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### Early Exercise of American Calls: Dividend Case

Surprisingly, an American call should be exercised only at a few dates.a

Theorem 6 An American call will only be exercised at expiration or just before an ex-dividend date.

In contrast, it might be optimal to exercise an American put even if the underlying stock does not pay dividends.

aSee Theorem 8.4.2 of the textbook.

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### A General Result

a

Theorem 7 (Cox & Rubinstein, 1985) Any piecewise linear payoﬀ function can be replicated using a portfolio of calls and puts.

Corollary 8 Any suﬃciently well-behaved payoﬀ function can be approximated by a portfolio of calls and puts.

aSee Exercise 8.3.6 of the textbook.

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### Option Pricing Models

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Black insisted that anything one could do with a mouse could be done better with macro redeﬁnitions of particular keys on the keyboard.

— Emanuel Derman, My Life as a Quant (2004)

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### The Setting

• The no-arbitrage principle is insuﬃcient to pin down the exact option value.

• Need a model of probabilistic behavior of stock prices.

• One major obstacle is that it seems a risk-adjusted interest rate is needed to discount the option’s payoﬀ.

• Breakthrough came in 1973 when Black (1938–1995) and Scholes with help from Merton published their celebrated option pricing model.a

– Known as the Black-Scholes option pricing model.

aThe results were obtained as early as June 1969. Merton and Scholes

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### Terms and Approach

• C: call value.

• P : put value.

• X: strike price

• S: stock price

• ˆr > 0: the continuously compounded riskless rate per period.

• R = eΔ ˆr: gross return.

• Start from the discrete-time binomial model.

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### Binomial Option Pricing Model (BOPM)

• Time is discrete and measured in periods.

• If the current stock price is S, it can go to Su with probability q and Sd with probability 1 − q, where 0 < q < 1 and d < u.

– In fact, d < R < u must hold to rule out arbitrage.a

• Six pieces of information will suﬃce to determine the option value based on arbitrage considerations:

S, u, d, X, ˆr, and the number of periods to expiration.

aSee Exercise 9.2.1 of the textbook.

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### Call on a Non-Dividend-Paying Stock: Single Period

• The expiration date is only one period from now.

• Cu is the call price at time 1 if the stock price moves to Su.

• Cd is the call price at time 1 if the stock price moves to Sd.

• Clearly,

Cu = max(0, Su − X), Cd = max(0, Sd − X).

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C

Cu= max( 0, Su X ) q

1 q

Cd = max( 0, Sd X )

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Call on a Non-Dividend-Paying Stock: Single Period (continued)

• Set up a portfolio of h shares of stock and B dollars in riskless bonds.

– This costs hS + B.

– We call h the hedge ratio or delta.

• The value of this portfolio at time one is hSu + RB, up move,

hSd + RB, down move.

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Call on a Non-Dividend-Paying Stock: Single Period (continued)

• Choose h and B such that the portfolio replicates the payoﬀ of the call,

hSu + RB = Cu, hSd + RB = Cd.

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Call on a Non-Dividend-Paying Stock: Single Period (concluded)

• Solve the above equations to obtain h = Cu − Cd

Su − Sd ≥ 0, (30)

B = uCd − dCu

(u − d) R . (31)

• By the no-arbitrage principle, the European call should cost the same as the equivalent portfolio,a

C = hS + B.

• As uCd − dCu < 0, the equivalent portfolio is a levered long position in stocks.

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### American Call Pricing in One Period

• Have to consider immediate exercise.

• C = max(hS + B, S − X).

– When hS + B ≥ S − X, the call should not be exercised immediately.

– When hS + B < S − X, the option should be exercised immediately.

• For non-dividend-paying stocks, early exercise is not optimal by Theorem 5 (p. 226).

• So

C = hS + B.

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### Put Pricing in One Period

• Puts can be similarly priced.

• The delta for the put is (Pu − Pd)/(Su − Sd) ≤ 0, where Pu = max(0, X − Su),

Pd = max(0, X − Sd).

• Let B = uP(u−d) Rd−dPu.

• The European put is worth hS + B.

• The American put is worth max(hS + B, X − S).

– Early exercise is always possible with American puts.

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### Risk

• Surprisingly, the option value is independent of q.a

• Hence it is independent of the expected gross return of the stock, qSu + (1 − q) Sd.

• The option value depends on the sizes of price changes, u and d, which the investors must agree upon.

• Then the set of possible stock prices is the same whatever q is.

aMore precisely, not directly dependent on q. Thanks to a lively class discussion on March 16, 2011.

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### Pseudo Probability

• After substitution and rearrangement,

hS + B =

R−d u−d



Cu +

u−R u−d

 Cd

R .

• Rewrite it as

hS + B = pCu + (1 − p) Cd

R ,

where

p =Δ R − d

u − d . (32)

• As 0 < p < 1, it may be interpreted as a probability.

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### Risk-Neutral Probability

• The expected rate of return for the stock is equal to the riskless rate ˆr under p as

pSu + (1 − p) Sd = RS. (33)

• The expected rates of return of all securities must be the riskless rate when investors are risk-neutral.

• For this reason, p is called the risk-neutral probability.

• The value of an option is the expectation of its

discounted future payoﬀ in a risk-neutral economy.

• So the rate used for discounting the FV is the riskless rate in a risk-neutral economy.

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### Option on a Non-Dividend-Paying Stock: Multi-Period

• Consider a call with two periods remaining before expiration.

• Under the binomial model, the stock can take on three possible prices at time two: Suu, Sud, and Sdd.

– There are 4 paths.

– But the tree combines or recombines.

• At any node, the next two stock prices only depend on the current price, not the prices of earlier times.a

aIt is Markovian.

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S

Su

Sd

Suu

Sud

Sdd

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### Option on a Non-Dividend-Paying Stock: Multi-Period (continued)

• Let Cuu be the call’s value at time two if the stock price is Suu.

• Thus,

Cuu = max(0, Suu − X).

• Cud and Cdd can be calculated analogously, Cud = max(0, Sud − X),

Cdd = max(0, Sdd − X).

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C

Cu

Cd

Cuu= max( 0, Suu X )

Cud = max( 0, Sud X )

Cdd = max( 0, Sdd X )

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### Option on a Non-Dividend-Paying Stock: Multi-Period (continued)

• The call values at time 1 can be obtained by applying the same logic:

Cu = pCuu + (1 − p) Cud

R , (34)

Cd = pCud + (1 − p) Cdd

R .

• Deltas can be derived from Eq. (30) on p. 240.

• For example, the delta at Cu is Cuu − Cud Suu − Sud.

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### Option on a Non-Dividend-Paying Stock: Multi-Period (concluded)

• We now reach the current period.

• Compute

pCu + (1 − p) Cd R

as the option price.

• The values of delta h and B can be derived from Eqs. (30)–(31) on p. 240.

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### Early Exercise

• Since the call will not be exercised at time 1 even if it is American, Cu ≥ Su − X and Cd ≥ Sd − X.

• Therefore,

hS + B = pCu + (1 − p) Cd

R ≥ [ pu + (1 − p) d ] S − X R

= S − X

R > S − X.

– The call again will not be exercised at present.a

• So

C = hS + B = pCu + (1 − p) Cd

R .

a

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### Backward Induction

a

• The above expression calculates C from the two successor nodes Cu and Cd and none beyond.

• The same computation happened at Cu and Cd, too, as demonstrated in Eq. (34) on p. 250.

• This recursive procedure is called backward induction.

• C equals

[ p2Cuu + 2p(1 − p) Cud + (1 − p)2Cdd](1/R2)

= [ p2 max

0, Su2 − X

+ 2p(1 − p) max (0, Sud − X) +(1 − p)2 max

0, Sd2 − X

]/R2.

aErnst Zermelo (1871–1953).

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S0

1

*

j

S0u p

*

j

S0d 1 − p

*

j

S0u2 p2

S0ud

2p(1 − p)

S0d2 (1 − p)2

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### Backward Induction (continued)

• In the n-period case, C =

n

j=0

n

j

pj(1 − p)n−j × max

0, Sujdn−j − X

Rn .

– The value of a call on a non-dividend-paying stock is the expected discounted payoﬀ at expiration in a

risk-neutral economy.

• Similarly, P =

n

j=0

n

j

pj(1 − p)n−j × max

0, X − Sujdn−j

Rn .

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### Backward Induction (concluded)

• Note that

pj =Δ

n

j

 pj(1 − p)n−j Rn

is the state pricea for the state Sujdn−j, j = 0, 1, . . . , n.

• In general,

option price = 

j

pj × payoﬀ at state j.

aRecall p. 205. One can obtain the undiscounted state price n

j

pj(1 p)n−j—the risk-neutral probability—for the state Sujdn−j with (XM XL)−1 units of the butterfly spread where XL = Suj−1dn−j+1, XM = Sujdn−j, and X = Suj−1+1dn−j−1. See Bahra (1997).

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### Risk-Neutral Pricing Methodology

• Every derivative can be priced as if the economy were risk-neutral.

• For a European-style derivative with the terminal payoﬀ function D, its value is

e−ˆrnEπ[D ]. (35) – Eπ means the expectation is taken under the

risk-neutral probability.

• The “equivalence” between arbitrage freedom in a model and the existence of a risk-neutral probability is called the (ﬁrst) fundamental theorem of asset pricing.

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### Self-Financing

• Delta changes over time.

• The maintenance of an equivalent portfolio is dynamic.

• But it does not depend on predicting future stock prices.

• The portfolio’s value at the end of the current period is precisely the amount needed to set up the next portfolio.

• The trading strategy is self-ﬁnancing because there is neither injection nor withdrawal of funds throughout.a

– Changes in value are due entirely to capital gains.

aExcept at the beginning, of course, when you have to put up the option value C or P before the replication starts.

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### Binomial Distribution

• Denote the binomial distribution with parameters n and p by

b(j; n, p) =Δ

n j

pj(1 − p)n−j = n!

j! (n − j)! pj(1 − p)n−j. – n! = 1 × 2 × · · · × n.

– Convention: 0! = 1.

• Suppose you ﬂip a coin n times with p being the probability of getting heads.

• Then b(j; n, p) is the probability of getting j heads.

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### The Binomial Option Pricing Formula

• The stock prices at time n are

Sun, Sun−1d, . . . , Sdn.

• Let a be the minimum number of upward price moves for the call to ﬁnish in the money.

• So a is the smallest nonnegative integer j such that Sujdn−j ≥ X,

or, equivalently,

a =

ln(X/Sdn) ln(u/d)

.

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### The Binomial Option Pricing Formula (concluded)

• Hence,

C

=

n

j=a

n

j

pj(1 − p)n−j 

Sujdn−j − X

Rn (36)

= S

n j=a

n j

(pu)j[ (1 − p) d ]n−j Rn

X Rn

n j=a

n j

pj(1 − p)n−j

= S

n j=a

b (j; n, pu/R) − Xe−ˆrn

n j=a

b(j; n, p). (37)

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### Numerical Examples

• A non-dividend-paying stock is selling for \$160.

• u = 1.5 and d = 0.5.

• r = 18.232% per period (R = e0.18232 = 1.2).

– Hence p = (R − d)/(u − d) = 0.7.

• Consider a European call on this stock with X = 150 and n = 3.

• The call value is \$85.069 by backward induction.

• Or, the PV of the expected payoﬀ at expiration:

390 × 0.343 + 30 × 0.441 + 0 × 0.189 + 0 × 0.027

(1.2)3 = 85.069.

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160

540 (0.343)

180 (0.441)

(0.189)60

(0.027)20 Binomial process for the stock price

(probabilities in parentheses)

(0.49)360

(0.42)120

40 (0.09) (0.7)240

80 (0.3)

85.069 (0.82031)

390

30

0

0 Binomial process for the call price

(hedge ratios in parentheses)

(1.0)235

(0.25)17.5

0 (0.0) 141.458

(0.90625)

10.208 (0.21875)

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### Numerical Examples (continued)

• Mispricing leads to arbitrage proﬁts.

• Suppose the option is selling for \$90 instead.

• Sell the call for \$90 and invest \$85.069 in the replicating portfolio with 0.82031 shares of stock required by delta.

• Borrow 0.82031 × 160 − 85.069 = 46.1806 dollars.

• The fund that remains,

90 − 85.069 = 4.931 dollars, is the arbitrage proﬁt as we will see.

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### Numerical Examples (continued)

Time 1:

• Suppose the stock price moves to \$240.

• The new delta is 0.90625.

0.90625 − 0.82031 = 0.08594

more shares at the cost of 0.08594 × 240 = 20.6256 dollars ﬁnanced by borrowing.

• Debt now totals 20.6256 + 46.1806 × 1.2 = 76.04232 dollars.

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### Numerical Examples (continued)

• The trading strategy is self-ﬁnancing because the portfolio has a value of

0.90625 × 240 − 76.04232 = 141.45768.

• It matches the corresponding call value!

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### Numerical Examples (continued)

Time 2:

• Suppose the stock price plunges to \$120.

• The new delta is 0.25.

• Sell 0.90625 − 0.25 = 0.65625 shares.

• This generates an income of 0.65625 × 120 = 78.75 dollars.

• Use this income to reduce the debt to

76.04232 × 1.2 − 78.75 = 12.5 dollars.

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### Numerical Examples (continued)

Time 3 (the case of rising price):

• The stock price moves to \$180.

• The call we wrote ﬁnishes in the money.

• For a loss of 180 − 150 = 30 dollars, close out the

position by either buying back the call or buying a share of stock for delivery.

• Financing this loss with borrowing brings the total debt to 12.5 × 1.2 + 30 = 45 dollars.

• It is repaid by selling the 0.25 shares of stock for 0.25 × 180 = 45 dollars.

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### Numerical Examples (concluded)

Time 3 (the case of declining price):

• The stock price moves to \$60.

• The call we wrote is worthless.

• Sell the 0.25 shares of stock for a total of 0.25 × 60 = 15

dollars.

• Use it to repay the debt of 12.5 × 1.2 = 15 dollars.

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### Applications besides Exploiting Arbitrage Opportunities

a

• Replicate an option using stocks and bonds.

– Set up a portfolio to replicate the call with \$85.069.

• Hedge the options we issued.

– Use \$85.069 to set up a portfolio to replicate the call to counterbalance its values exactly.b

• · · ·

• Without hedge, one may end up forking out \$390 in the worst case!c

aThanks to a lively class discussion on March 16, 2011.

bHedging and replication are mirror images.

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### Binomial Tree Algorithms for European Options

• The BOPM implies the binomial tree algorithm that applies backward induction.

• The total running time is O(n2) because there are

∼ n2/2 nodes.

• The memory requirement is O(n2).

– Can be easily reduced to O(n) by reusing space.a

• To price European puts, simply replace the payoﬀ.

aBut watch out for the proper updating of array entries.

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C[2][0]

C[2][1]

C[2][2]

C[1][0]

C[1][1]

C[0][0]

p

p

p p

p p

max ,

0 Sud2 X

max ,

0 Su d X2

max ,

0 Su3 X

max ,

0 Sd3 X

## D

1 p

1 p

1 p

1 p

1 p

1 p

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0

0 0

All zeros

X

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### Optimal Algorithm

• We can reduce the running time to O(n) and the memory requirement to O(1).

• Note that

b(j; n, p) = p(n − j + 1)

(1 − p) j b(j − 1; n, p).

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### Optimal Algorithm (continued)

• The following program computes b(j; n, p) in b[ j ]:

• It runs in O(n) steps.

1: b[ a ] := n

a

 pa(1 − p)n−a;

2: for j = a + 1, a + 2, . . . , n do

3: b[ j ] := b[ j − 1 ] × p × (n − j + 1)/((1 − p) × j);

4: end for

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### Optimal Algorithm (concluded)

• With the b(j; n, p) available, the risk-neutral valuation formula (36) on p. 261 is trivial to compute.

• But we only need a single variable to store the b(j; n, p)s as they are being sequentially computed.

• This linear-time algorithm computes the discounted expected value of max(Sn − X, 0).

• The above technique cannot be applied to American options because of early exercise.

• So binomial tree algorithms for American options usually run in O(n2) time.

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S

Su

Sd

Su2

Sud

Sdu

Sd2

2n

n

Sun Sun − 1 Su3

Su2d Su2d

Sud2 Su2d

Sud2 Sud2

Sd3

Sun − 1d

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### Toward the Black-Scholes Formula

• The binomial model seems to suﬀer from two unrealistic assumptions.

– The stock price takes on only two values in a period.

– Trading occurs at discrete points in time.

• As n increases, the stock price ranges over ever larger numbers of possible values, and trading takes place nearly continuously.a

• Need to calibrate the BOPM’s parameters u, d, and R to make it converge to the continuous-time model.

• We now skim through the proof.

aContinuous-time trading may create arbitrage opportunities in prac-

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### Toward the Black-Scholes Formula (continued)

• Let τ denote the time to expiration of the option measured in years.

• Let r be the continuously compounded annual rate.

• With n periods during the option’s life, each period represents a time interval of τ /n.

• Need to adjust the period-based u, d, and interest rate r to match the empirical results as n → ∞.ˆ

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### Toward the Black-Scholes Formula (continued)

• First, ˆr = rτ/n.

– Each period is τ /n years long.

– The period gross return R = eˆr.

• Let

μ =Δ 1 n E

ln Sτ S



denote the expected value of the continuously

compounded rate of return per period of the BOPM.

• Let

σ2 Δ= 1

n Var

ln Sτ S



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### Toward the Black-Scholes Formula (continued)

• Under the BOPM, it is not hard to show thata μ = q ln(u/d) + ln d,

σ2 = q(1 − q) ln2(u/d).

• Assume the stock’s true continuously compounded rate of return over τ years has mean μτ and variance σ2τ .

• Call σ the stock’s (annualized) volatility.

aThe Bernoulli distribution.

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### Toward the Black-Scholes Formula (continued)

• The BOPM converges to the distribution only if

n μ = n[ q ln(u/d) + ln d ] → μτ, (38) n σ2 = nq(1 − q) ln2(u/d) → σ2τ. (39)

• We need one more condition to have a solution for u, d, q.

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### Toward the Black-Scholes Formula (continued)

• Impose

ud = 1.

– It makes nodes at the same horizontal level of the tree have identical price (review p. 273).

– Other choices are possible (see text).

• Exact solutions for u, d, q are feasible if Eqs. (38)–(39) are replaced by equations: 3 equations for 3 variables.a

aChance (2008).

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### Toward the Black-Scholes Formula (continued)

• The above requirements can be satisﬁed by

u = eσ

τ /n, d = e−σ

τ /n, q = 1

2 + 1 2

μ σ

τ

n . (40)

• With Eqs. (40), it can be checked that n μ = μτ,

n σ2 =

1 μ σ

2 τ n



σ2τ → σ2τ.

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### Toward the Black-Scholes Formula (continued)

• The choices (40) result in the CRR binomial model.a

• With the above choice, even if u and d are not calibrated, the mean is still matched!b

aCox, Ross, & Rubinstein (1979).

bRecall Eq. (33) on p. 245. So u and d are related to volatility.

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### Toward the Black-Scholes Formula (continued)

• The no-arbitrage inequalities d < R < u may not hold under Eqs. (40) on p. 284 or Eq. (32) on p. 244.

– If this happens, the probabilities lie outside [ 0, 1 ].a

• The problem disappears when n satisﬁes eσ

τ /n > erτ /n,

i.e., when n > r2τ /σ2 (check it).

– So it goes away if n is large enough.

– Other solutions will be presented later.

aMany papers and programs forget to check this condition!

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### Toward the Black-Scholes Formula (continued)

• The central limit theorem says ln(Sτ/S) converges to N (μτ, σ2τ ).a

• So ln Sτ approaches N (μτ + ln S, σ2τ ).

• Conclusion: Sτ has a lognormal distribution in the limit.

aThe normal distribution with mean μτ and variance σ2τ .

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### Toward the Black-Scholes Formula (continued)

Lemma 9 The continuously compounded rate of return ln(Sτ/S) approaches the normal distribution with mean (r − σ2/2) τ and variance σ2τ in a risk-neutral economy.

• Let q equal the risk-neutral probability p = (eΔ rτ /n − d)/(u − d).

• Let n → ∞.a

• Then μ = r − σ2/2.

aSee Lemma 9.3.3 of the textbook.

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### Toward the Black-Scholes Formula (continued)

• The expected stock price at expiration in a risk-neutral economy isa

Se.

• The stock’s expected annual rate of returnb is thus the riskless rate r.

aBy Lemma 9 (p. 289) and Eq. (28) on p. 175.

bIn the sense of (1/τ ) ln E[ Sτ/S ] (arithmetic average rate of return) not (1/τ )E[ ln(Sτ/S) ] (geometric average rate of return). In the latter case, it would be r − σ2/2 by Lemma 9.

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### Toward the Black-Scholes Formula (continued)

a

Theorem 10 (The Black-Scholes Formula)

C = SN (x) − Xe−rτN (x − σ√ τ ), P = Xe−rτN (−x + σ√

τ ) − SN (−x), where

x =Δ ln(S/X) + 

r + σ2/2 τ σ√

τ .

aOn a United flight from San Francisco to Tokyo on March 7, 2010, a real-estate manager mentioned this formula to me!

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### Toward the Black-Scholes Formula (concluded)

• See Eq. (37) on p. 261 for the meaning of x.

• See Exercise 13.2.12 of the textbook for an

interpretation of the probability measure associated with N (x) and N (−x).

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### BOPM and Black-Scholes Model

• The Black-Scholes formula needs 5 parameters: S, X, σ, τ , and r.

• Binomial tree algorithms take 6 inputs: S, X, u, d, ˆr, and n.

• The connections are

u = eσ

τ /n, d = e−σ

τ /n, r = rτ /n.ˆ

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5 10 15 20 25 30 35 n

11.5 12 12.5 13

Call value

0 10 20 30 40 50 60 n

15.1 15.2 15.3 15.4 15.5

Call value

• S = 100, X = 100 (left), and X = 95 (right).

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### BOPM and Black-Scholes Model (concluded)

• The binomial tree algorithms converge reasonably fast.

• The error is O(1/n).a

• Oscillations are inherent, however.

• Oscillations can be dealt with by the judicious choices of u and d.b

aL. Chang & Palmer (2007).

bSee Exercise 9.3.8 of the textbook.

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### Implied Volatility

• Volatility is the sole parameter not directly observable.

• The Black-Scholes formula can be used to compute the market’s opinion of the volatility.a

– Solve for σ given the option price, S, X, τ , and r with numerical methods.

aImplied volatility is hard to compute when τ is small (why?).

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### Implied Volatility (concluded)

• Implied volatility is

the wrong number to put in the wrong formula to get the right price of plain-vanilla options.a

• Implied volatility is often preferred to historical volatility in practice.

– Using the historical volatility is like driving a car with your eyes on the rearview mirror?

aRebonato (2004).

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### Problems; the Smile

• Options written on the same underlying asset usually do not produce the same implied volatility.

• A typical pattern is a “smile” in relation to the strike price.

– The implied volatility is lowest for at-the-money options.

– It becomes higher the further the option is in- or out-of-the-money.

• Other patterns have also been observed.

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### TXO futures calls (September 25, 2015)

a

300

14 200 9000

8500 16

8000 100

7500 18

7000 0 20

22 24

ATM = \$8132

aThe index futures closed at 8132. Plot supplied by Mr. Lok, U Hou

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### Solutions to the Smile

• To address this issue, volatilities are often combined to produce a composite implied volatility.

• This practice is not sound theoretically.

• The existence of diﬀerent implied volatilities for options on the same underlying asset shows the Black-Scholes model cannot be literally true.

• So?

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### Binomial Tree Algorithms for American Puts

• Early exercise has to be considered.

• The binomial tree algorithm starts with the terminal payoﬀs

max(0, X − Sujdn−j) and applies backward induction.

• At each intermediate node, it compares the payoﬀ if exercised and the continuation value.

• It keeps the larger one.

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### Bermudan Options

• Some American options can be exercised only at discrete time points instead of continuously.

• They are called Bermudan options.

• Their pricing algorithm is identical to that for American options.

• But early exercise is considered for only those nodes when early exercise is permitted.

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### Time-Dependent Instantaneous Volatility

a

• Suppose the (instantaneous) volatility can change over time but otherwise predictable: σ(t) instead of σ.

• In the limit, the variance of ln(Sτ/S) is

 τ

0 σ2(t) dt rather than σ2τ .

• The annualized volatility to be used in the Black-Scholes formula should now be

 τ

0 σ2(t) dt

τ .

aMerton (1973).

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### Time-Dependent Instantaneous Volatility (concluded)

• There is no guarantee that the implied volatility is constant.

• For the binomial model,u and d depend on time:

u = eσ(t)

τ /n, d = e−σ(t)

τ /n.

• How to make the binomial tree combine?a

aAmin (1991); C. I. Chen (R98922127) (2011).

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### Volatility (1990–2016)

a

2-Jan-90 2-Jan-91 2-Jan-92 4-Jan-93 3-Jan-94 3-Jan-95 2-Jan-96 2-Jan-97 2-Jan-98 4-Jan-99 3-Jan-00 2-Jan-01 2-Jan-02 2-Jan-03 2-Jan-04 3-Jan-05 3-Jan-06 3-Jan-07 2-Jan-08 2-Jan-09 4-Jan-10 3-Jan-11 3-Jan-12 2-Jan-13 2-Jan-14 2-Jan-15 4-Jan-16 0

10 20 30 40 50 60 70 80 90

VIX

CBOE S&P 500 Volatility Index

Updating...

## References

Related subjects :