Example: a digital option; for a digital call with strike K , 1 - - PowerPoint PPT Presentation

example a digital option for a digital call with strike k
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Example: a digital option; for a digital call with strike K , 1 - - PowerPoint PPT Presentation

Different Payoffs Discontinuous Payoffs Same basic model, with two assets: The cash bond { B t } t 0 ; if the risk-free interest rate is a constant r and B 0 = 1, then B t = e rt , t 0. A risky asset with price { S t } t 0 ;


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SLIDE 1

Different Payoffs Discontinuous Payoffs

  • Same basic model, with two assets:

– The cash bond {Bt}t≥0; if the risk-free interest rate is a constant r and B0 = 1, then Bt = ert, t ≥ 0. – A risky asset with price {St}t≥0; we assume that under the market probability measure P, {St}t≥0 is geometric Brownian motion: dSt = µStdt + σStdWt where {St}t≥0 is P-Brownian motion.

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SLIDE 2
  • Recall:

– the value at time t of a European option whose payoff at time T is CT = f(ST) is Vt = F(t, St), where Vt = F(t, St) = EQ e−r(T−t)f(ST)

  • Ft
  • = e−r(T−t)

−∞f

  • x exp
  • r − σ2

2

  • (T − t) + σy

√ T − t

  • × exp(−y2/2)

√ 2π dy – The replicating portfolio consists of φt = ∂F ∂x (t, x)

  • x=St

shares and ψt = e−rt(Vt − φtSt) cash bonds.

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SLIDE 3
  • The Feynman-Kac representation shows that F is continuous

and differentiable for t ∈ [0, T) and x ∈ R.

  • But F(t, x) → f(x) as t → T, which is often not differentiable

(calls and puts) and may not be continuous.

  • So F may behave badly as t → T.

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SLIDE 4
  • Example: a digital option; for a digital call with strike K,

CT =

  

1 if ST ≥ K if ST < K

  • Calculus shows that

Vt = e−r(T−t)Φ(d2), where Φ is the standard normal cumulative distribution func- tion, and d2 = 1 σ√T − t

  • log

St

K

  • +
  • r − σ2

2

  • (T − t)
  • is the same constant that arises in the price of a normal call.

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SLIDE 5
  • More calculus gives

φt =e−r(T−t) × 1 St × 1

  • 2π(T − t)σ2

× exp

 −

1 2(T − t)σ2

  • log

St

K

  • +
  • r − σ2

2

  • (T − t)

2 

  • This is proportional to a lognormal density function in St,

centered approximately at K, with scale

  • (T − t)σ2.
  • As t approaches T, this is large for St close to K, and small
  • therwise, so the hedge may need large adjustments if St is

close to K; digital options are often booked as spreads to smooth the delta.

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SLIDE 6

Multistage Options

  • Some option definitions involve a maturity T1 and an inter-

mediate time T0, 0 < T0 < T1.

  • Example:

forward start call option; payoff at t = T1 is

  • ST1 − K
  • +, where the strike K = ST0.
  • Work backwards: for T0 ≤ t ≤ T1, it is a standard European

call with (known) strike ST0, and Vt = e−r(T1−t)EQ

  • ST1 − ST0
  • +
  • Ft
  • = StΦ(d1) − ST0e−r(T1−t)Φ(d2)

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SLIDE 7
  • Note that d1 and d2 depend on St, as well as K = ST0, r, σ,

and T1.

  • But at t = T0, the option is “at the money”, and d1 and d2

depend only on r, σ, T0, and T1.

  • So

VT0 = ST0

  • Φ(d1) − e−r(T1−T0)Φ(d2)
  • = c(r, σ, T0, T1)ST0.
  • So for 0 ≤ t < T0, Vt = c(r, σ, T0, T1)St.

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SLIDE 8

Compound options

  • Example: “Call on call”; the underlying is a call option on

some asset, initiated at time T0 > 0 and maturing at time T1 > T0, with strike K1.

  • The compound option is the option to buy the underlying

call at time T0, with a strike of K0.

  • The value of the underlying call, at time T0, is given by

Black-Scholes, as a function of ST0: say C

  • ST0, T0; K1, T1
  • .

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SLIDE 9
  • The value of the compound option at time T0 is

V

  • ST0, T0
  • =
  • C
  • ST0, T0; K1, T1
  • − K0
  • + .
  • The value of the compound option at a time t < T0 is the dis-

counted expected value of C under the risk-neutral measure:

EQ

e−r(T0−t)V

  • ST0, T0
  • .
  • No closed form expression–the integral is computed numeri-

cally.

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