Unit 6, lesson 44

The Black Scholes formula and put call parity

Derives the Black-Scholes call and put prices from truncated normal integrals, defines d1 and d2, proves put-call parity, and explains the in-the-money probability and the expiry and zero-volatility limits.

  • Video 44
  • Black-Scholes formulas, Greeks and hedging

A stock trades at 100 and pays a continuous dividend yield of 2 percent, and a one-year European call with strike 105 is offered. In the Black-Scholes model its price is a discounted expectation under the pricing measure, so two questions follow. How is that expectation evaluated in closed form, and how must the call price relate to the price of the put with the same strike and maturity? This lesson splits the payoff into a stock term and a strike term, evaluates both with one Gaussian integral, proves put-call parity from payoffs alone, identifies which normal probability is the pricing probability of exercise, and takes the expiry and zero-volatility limits.

Key terms

Standard normal CDF

Definition The standard normal density and the standard normal cumulative distribution function are

φ(z)=12π e−z2/2,Φ(x)=∫−∞xφ(z) dz.\begin{gathered} \varphi(z) = \frac{1}{\sqrt{2\pi}}\, e^{-z^2/2}, \\[0.4em] \Phi(x) = \int_{-\infty}^{x} \varphi(z)\,dz . \end{gathered}

If ZZ is standard normal, then P(Z≤x)=Φ(x)\mathbb{P}(Z \le x) = \Phi(x) for every real xx. The function Φ\Phi is continuous and strictly increasing from 00 to 11, with Φ(0)=12\Phi(0) = \tfrac12, and the symmetry φ(−z)=φ(z)\varphi(-z) = \varphi(z) gives Φ(−x)=1−Φ(x)\Phi(-x) = 1 - \Phi(x), so P(Z>b)=Φ(−b)\mathbb{P}(Z > b) = \Phi(-b). It has no expression in elementary functions and is evaluated numerically, for example as Φ(x)=12(1+erf⁡(x/2))\Phi(x) = \tfrac12\bigl(1 + \operatorname{erf}(x/\sqrt{2})\bigr). Every option formula below rests on one truncated Gaussian integral. For all real numbers aa and bb,

E[eaZ1{Z>b}]=ea2/2 Φ(a−b).\begin{aligned} &\mathbb{E}\bigl[e^{aZ}\mathbf{1}_{\{Z > b\}}\bigr] \\[0.4em] &\quad = e^{a^2/2}\,\Phi(a - b). \end{aligned}

To prove it, complete the square, az−12z2=−12(z−a)2+12a2az - \tfrac12 z^2 = -\tfrac12 (z - a)^2 + \tfrac12 a^2, so that eazφ(z)=ea2/2φ(z−a)e^{az}\varphi(z) = e^{a^2/2}\varphi(z - a) and

∫b∞eazφ(z) dz=ea2/2∫b−a∞φ(u) du=ea2/2 Φ(a−b),\begin{aligned} &\int_b^{\infty} e^{az}\varphi(z)\,dz \\[0.4em] &\quad = e^{a^2/2}\int_{b - a}^{\infty}\varphi(u)\,du \\[0.4em] &\quad = e^{a^2/2}\,\Phi(a - b), \end{aligned}

after the substitution u=z−au = z - a. The same steps give the lower tail E[eaZ1{Z<b}]=ea2/2 Φ(b−a)\mathbb{E}\bigl[e^{aZ}\mathbf{1}_{\{Z < b\}}\bigr] = e^{a^2/2}\,\Phi(b - a).

In plain words The value Φ(x)\Phi(x) is the probability that a standard normal draw lands at or below xx. Weighting the normal density by eaze^{az} moves its center from 00 to aa and multiplies its total mass by ea2/2e^{a^2/2}, so a weighted tail is an ordinary tail of a shifted normal, times that factor.

Example The values Φ(0.1)≈0.539828\Phi(0.1) \approx 0.539828 and Φ(−0.1)≈0.460172\Phi(-0.1) \approx 0.460172 add to 11. With a=1a = 1 and b=0b = 0 the truncated integral gives

E[eZ1{Z>0}]=e1/2 Φ(1)≈1.648721⋅0.841345≈1.387143.\begin{aligned} &\mathbb{E}\bigl[e^{Z}\mathbf{1}_{\{Z > 0\}}\bigr] = e^{1/2}\,\Phi(1) \\[0.4em] &\quad \approx 1.648721 \cdot 0.841345 \\[0.4em] &\quad \approx 1.387143 . \end{aligned}

Multiplying the mean E[eZ]=e1/2\mathbb{E}[e^{Z}] = e^{1/2} by the probability P(Z>0)=12\mathbb{P}(Z > 0) = \tfrac12 would give only 0.8243610.824361, because the large values of eZe^{Z} all sit in the upper tail. The stock term of the call has the same feature.

d1 and d2

Definition In the Black-Scholes model of the next card, fix t<Tt < T, write τ=T−t\tau = T - t and S=StS = S_t, and assume S>0S > 0, K>0K > 0, σ>0\sigma > 0 and τ>0\tau > 0, with constant rr and qq. Then

d1=1στ[ln⁡SK+(r−q+12σ2)τ],d2=d1−στ.\begin{aligned} d_1 &= \frac{1}{\sigma\sqrt{\tau}}\Bigl[\ln\frac{S}{K} \\[0.4em] &\qquad + \bigl(r - q + \tfrac12\sigma^2\bigr)\tau\Bigr], \\[0.4em] d_2 &= d_1 - \sigma\sqrt{\tau}. \end{aligned}

With the forward price F=Se(r−q)τF = S e^{(r - q)\tau} the same numbers are

d1,2=ln⁡(F/K)±12σ2τστ,d_{1,2} = \frac{\ln(F/K) \pm \tfrac12\sigma^2\tau}{\sigma\sqrt{\tau}},

so they depend on SS, rr and qq only through FF. Under the pricing measure Q\mathbb{Q} of the model the terminal price satisfies

ln⁡STSt=(r−q−12σ2)τ+στ Z,\begin{aligned} \ln\frac{S_T}{S_t} &= \bigl(r - q - \tfrac12\sigma^2\bigr)\tau \\[0.4em] &\quad + \sigma\sqrt{\tau}\,Z, \end{aligned}

where Z=(WTQ−WtQ)/τZ = (W^{\mathbb{Q}}_T - W^{\mathbb{Q}}_t)/\sqrt{\tau} is standard normal and independent of Ft\mathcal{F}_t. Solving ST>KS_T > K for ZZ gives the exercise event

A={ST>K}={Z>−d2}.A = \{S_T > K\} = \{Z > -d_2\}.

The difference d1−d2=στd_1 - d_2 = \sigma\sqrt{\tau} is positive, so d1>d2d_1 > d_2 always, and d1+d2=2ln⁡(F/K)/(στ)d_1 + d_2 = 2\ln(F/K)/(\sigma\sqrt{\tau}), so d1=−d2d_1 = -d_2 exactly when K=FK = F.

In plain words The number d2d_2 counts how many standard deviations of ln⁡ST\ln S_T the median of STS_T under Q\mathbb{Q}, which is Fe−σ2τ/2F e^{-\sigma^2\tau/2}, lies above the strike on the log scale, and it is negative when the median lies below. The call is exercised when the normal shock beats −d2-d_2. The number d1d_1 is one standard deviation στ\sigma\sqrt{\tau} larger, the shift produced by weighting outcomes by the stock price.

Example Take the constructed inputs S=100S = 100, K=105K = 105, r=0.05r = 0.05, q=0.02q = 0.02, σ=0.2\sigma = 0.2 and τ=1\tau = 1. Then ln⁡(S/K)≈−0.048790\ln(S/K) \approx -0.048790 and r−q+12σ2=0.05r - q + \tfrac12\sigma^2 = 0.05, so the bracket is about 0.0012100.001210 and

d1≈0.006049,d2≈−0.193951.\begin{gathered} d_1 \approx 0.006049, \\[0.4em] d_2 \approx -0.193951 . \end{gathered}

The forward F=100e0.03≈103.045F = 100e^{0.03} \approx 103.045 lies below the strike, which is why d2<0d_2 < 0. Although d1d_1 is close to zero, Φ(d1)≈0.502413\Phi(d_1) \approx 0.502413 and Φ(d2)≈0.423107\Phi(d_2) \approx 0.423107 differ by almost 0.080.08.

Black-Scholes formula

Definition A European call with strike K>0K > 0 and maturity TT pays (ST−K)+(S_T - K)^{+} at TT, a European put pays (K−ST)+(K - S_T)^{+} at TT, and neither can be exercised before TT. Assume the Black-Scholes model. The market is frictionless with continuous trading, the money-market account is Bt=ertB_t = e^{rt} with a constant continuously compounded rate rr, and the stock pays a constant continuous dividend yield qq and has constant volatility σ>0\sigma > 0, with ex-dividend price following

dSt=(r−q) St dt+σSt dWtQ\begin{aligned} dS_t &= (r - q)\,S_t\,dt \\[0.4em] &\quad + \sigma S_t\, dW^{\mathbb{Q}}_t \end{aligned}

under the pricing measure Q\mathbb{Q} for the numeraire BB. By the earlier lessons on replication and on the Feynman-Kac formula, a European claim whose payoff g(ST)g(S_T) grows at most polynomially in STS_T, such as a call or a put, has the price e−rτ EQ[g(ST)∣Ft]e^{-r\tau}\,\mathbb{E}^{\mathbb{Q}}[g(S_T) \mid \mathcal{F}_t]. For t<Tt < T and S=St>0S = S_t > 0 the call and put prices are

C=Se−qτ Φ(d1)−Ke−rτ Φ(d2),P=Ke−rτ Φ(−d2)−Se−qτ Φ(−d1).\begin{aligned} C &= S e^{-q\tau}\,\Phi(d_1) \\[0.4em] &\quad - K e^{-r\tau}\,\Phi(d_2), \\[0.4em] P &= K e^{-r\tau}\,\Phi(-d_2) \\[0.4em] &\quad - S e^{-q\tau}\,\Phi(-d_1). \end{aligned}

For the derivation, split the call payoff on the exercise event AA of the previous card,

C=e−rτ EQ[ST1A∣Ft]−Ke−rτ Q(A∣Ft).\begin{aligned} C &= e^{-r\tau}\,\mathbb{E}^{\mathbb{Q}}\bigl[S_T\mathbf{1}_{A} \mid \mathcal{F}_t\bigr] \\[0.4em] &\quad - K e^{-r\tau}\,\mathbb{Q}(A \mid \mathcal{F}_t). \end{aligned}

The strike term needs Q(A∣Ft)=Q(Z>−d2)=Φ(d2)\mathbb{Q}(A \mid \mathcal{F}_t) = \mathbb{Q}(Z > -d_2) = \Phi(d_2), since ZZ is independent of Ft\mathcal{F}_t. For the stock term write ST=Fe−σ2τ/2+στZS_T = F e^{-\sigma^2\tau/2 + \sigma\sqrt{\tau}Z} and apply the truncated integral with a=στa = \sigma\sqrt{\tau} and b=−d2b = -d_2, so that a−b=d1a - b = d_1 and

EQ[ST1A∣Ft]=Fe−σ2τ/2 eσ2τ/2 Φ(d1)=F Φ(d1).\begin{aligned} &\mathbb{E}^{\mathbb{Q}}\bigl[S_T\mathbf{1}_{A} \mid \mathcal{F}_t\bigr] \\[0.4em] &\quad = F e^{-\sigma^2\tau/2}\, e^{\sigma^2\tau/2}\,\Phi(d_1) \\[0.4em] &\quad = F\,\Phi(d_1). \end{aligned}

Discounting gives e−rτF=Se−qτe^{-r\tau}F = S e^{-q\tau}. The put uses the lower tail on {Z<−d2}\{Z < -d_2\}, which produces Φ(−d2)\Phi(-d_2) and Φ(−d2−στ)=Φ(−d1)\Phi(-d_2 - \sigma\sqrt{\tau}) = \Phi(-d_1). The stock term carries e−qτe^{-q\tau} because one share delivered at TT, without the dividends paid before TT, costs Se−qτS e^{-q\tau} today, and the strike term carries e−rτe^{-r\tau} because KK is cash paid at TT. With deterministic time-dependent rr, qq and σ\sigma the same formulas hold after replacing rτr\tau, qτq\tau and σ2τ\sigma^2\tau by ∫tTr(u) du\int_t^T r(u)\,du, ∫tTq(u) du\int_t^T q(u)\,du and ∫tTσ(u)2 du\int_t^T \sigma(u)^2\,du. Stochastic volatility, discrete cash dividends and American exercise are outside the formula, and averaging stochastic parameters inside it is not justified.

In plain words The call hands its holder the stock against payment of the strike, but only on the exercise event. The strike leg is the discounted strike times the pricing probability of exercise. The stock leg is the prepaid stock times a different probability, Φ(d1)\Phi(d_1), because STS_T is largest on exactly the outcomes where the call pays most, so those outcomes weigh more.

Example With the constructed inputs, Se−qτ≈98.019867S e^{-q\tau} \approx 98.019867 and Ke−rτ≈99.879090K e^{-r\tau} \approx 99.879090. The call has stock leg 98.019867⋅0.502413≈49.24648198.019867 \cdot 0.502413 \approx 49.246481 and strike leg 99.879090⋅0.423107≈42.25956199.879090 \cdot 0.423107 \approx 42.259561. The put has strike leg 99.879090⋅0.576893≈57.61952899.879090 \cdot 0.576893 \approx 57.619528 and stock leg 98.019867⋅0.497587≈48.77338698.019867 \cdot 0.497587 \approx 48.773386. Hence

C≈6.986920,P≈8.846142.\begin{gathered} C \approx 6.986920, \\[0.4em] P \approx 8.846142 . \end{gathered}

Multiplying the unconditional mean EQ[ST∣Ft]=F≈103.045\mathbb{E}^{\mathbb{Q}}[S_T \mid \mathcal{F}_t] = F \approx 103.045 by the exercise probability in the stock leg would give e−rτ(F−K) Φ(d2)≈−0.786650e^{-r\tau}(F - K)\,\Phi(d_2) \approx -0.786650, a negative price for a payoff that is never negative.

Put-call parity

Definition Let a European call and a European put have the same underlying stock, strike KK, maturity TT and settlement. For every value of STS_T,

(ST−K)+−(K−ST)+=ST−K,\begin{aligned} &(S_T - K)^{+} - (K - S_T)^{+} \\[0.4em] &\quad = S_T - K, \end{aligned}

since at most one of the two terms is nonzero, and both vanish at ST=KS_T = K. Suppose a claim to one share at TT, without the dividends paid before TT, costs Se−qτS e^{-q\tau} at time tt, a payment of KK at TT costs Ke−rτK e^{-r\tau}, and trading is frictionless. Then the law of one price gives

C−P=Se−qτ−Ke−rτ,C - P = S e^{-q\tau} - K e^{-r\tau},

or C−P=e−rτ(F−K)C - P = e^{-r\tau}(F - K). The argument uses only these two prices, not the lognormal law or σ\sigma, so parity holds in every arbitrage-free frictionless model with these prices for the prepaid share and the zero-coupon payment. With stochastic rates Ke−rτK e^{-r\tau} becomes KP(t,T)K P(t,T). The Black-Scholes formulas satisfy it because Φ(d)+Φ(−d)=1\Phi(d) + \Phi(-d) = 1. If a quoted call and put violate it, buying the cheap side, selling the expensive side and offsetting ST−KS_T - K with the share and the bond gives an arbitrage. Parity needs European exercise. For American options on a stock without dividends and with r≥0r \ge 0 only the inequalities

S−K≤CAm−PAm≤S−Ke−rτ\begin{aligned} S - K &\le C^{\mathrm{Am}} - P^{\mathrm{Am}} \\[0.4em] &\le S - K e^{-r\tau} \end{aligned}

hold, and with transaction costs or different borrowing and lending rates the equality widens into a band.

In plain words A long call and a short put with the same strike pay ST−KS_T - K in every state, which is the payoff of a forward contract with delivery price KK. Portfolios with the same payoff must cost the same, so the call minus the put equals the cost of a share delivered at TT minus the cost of KK paid at TT. The call and the put have equal prices exactly when the strike equals the forward.

Example In the constructed example C−P≈6.986920−8.846142=−1.859222C - P \approx 6.986920 - 8.846142 = -1.859222, and also Se−qτ−Ke−rτ≈98.019867−99.879090=−1.859222S e^{-q\tau} - K e^{-r\tau} \approx 98.019867 - 99.879090 = -1.859222. The difference is negative because K=105K = 105 exceeds F≈103.045F \approx 103.045. Suppose, as a constructed quote, that the put trades at 9.009.00 while the call trades at its model price. Sell the put, buy the call, sell short e−qτ≈0.980199e^{-q\tau} \approx 0.980199 shares and pay the dividends owed on them by shorting further shares, so the short position grows to one share at TT, and lend Ke−rτK e^{-r\tau}. The cash received today is

9.00−6.986920+98.019867−99.879090≈0.153858,\begin{aligned} &9.00 - 6.986920 \\[0.4em] &\quad + 98.019867 \\[0.4em] &\quad - 99.879090 \\[0.4em] &\quad \approx 0.153858, \end{aligned}

and at TT the options pay ST−KS_T - K, closing the short costs STS_T and the loan returns KK, so nothing is owed.

In-the-money probability

Definition Under the hypotheses of the Black-Scholes formula, with A={ST>K}A = \{S_T > K\},

Q(A∣Ft)=Φ(d2),\mathbb{Q}(A \mid \mathcal{F}_t) = \Phi(d_2),

the probability under the money-market pricing measure that the call finishes in the money. The put finishes in the money with Q\mathbb{Q}-probability Φ(−d2)\Phi(-d_2), since Q(ST=K)=0\mathbb{Q}(S_T = K) = 0, and e−rτΦ(d2)e^{-r\tau}\Phi(d_2) is the price of a claim that pays one unit of cash when ST>KS_T > K. The other factor is a probability under another measure. Define QS\mathbb{Q}^{S} on FT\mathcal{F}_T by the density dQS/dQ=e−(r−q)TST/S0d\mathbb{Q}^{S}/d\mathbb{Q} = e^{-(r - q)T} S_T/S_0, which is positive with Q\mathbb{Q}-mean 11 and makes the share with dividends reinvested, worth eqtSte^{qt}S_t, the numeraire. Its conditional density given Ft\mathcal{F}_t is e−(r−q)τST/Ste^{-(r - q)\tau} S_T/S_t, so the stock-term computation of the formula card gives QS(A∣Ft)=e−(r−q)τF Φ(d1)/St=Φ(d1)\mathbb{Q}^{S}(A \mid \mathcal{F}_t) = e^{-(r - q)\tau}F\,\Phi(d_1)/S_t = \Phi(d_1), and

C=Se−qτ QS(A∣Ft)−Ke−rτ Q(A∣Ft).\begin{aligned} C &= S e^{-q\tau}\,\mathbb{Q}^{S}(A \mid \mathcal{F}_t) \\[0.4em] &\quad - K e^{-r\tau}\,\mathbb{Q}(A \mid \mathcal{F}_t). \end{aligned}

Neither number is a physical probability. If under P\mathbb{P} the ex-dividend price follows dSt=mSt dt+σSt dWtdS_t = m S_t\,dt + \sigma S_t\,dW_t, then

P(A∣Ft)=Φ(d2P),d2P=d2+(m−r+q)τσ,\begin{aligned} &\mathbb{P}(A \mid \mathcal{F}_t) = \Phi(d_2^{\mathbb{P}}), \\[0.4em] &d_2^{\mathbb{P}} = d_2 + \frac{(m - r + q)\sqrt{\tau}}{\sigma}, \end{aligned}

which equals Φ(d2)\Phi(d_2) only when m=r−qm = r - q. The next lesson shows that e−qτΦ(d1)e^{-q\tau}\Phi(d_1) is the delta of the call.

In plain words The value Φ(d2)\Phi(d_2) is the chance of exercise under the pricing weights that make discounted prices martingales, a pricing weight and not a forecast. The value Φ(d1)\Phi(d_1) weights each outcome by the stock price reached there, so it is larger. Two people with different views of the expected return compute the same option price and different physical probabilities of exercise.

Example In the constructed example Φ(d2)≈0.423107\Phi(d_2) \approx 0.423107 and Φ(d1)≈0.502413\Phi(d_1) \approx 0.502413, and the claim paying one unit of cash on exercise is worth e−0.05⋅0.423107≈0.402472e^{-0.05} \cdot 0.423107 \approx 0.402472. If the constructed physical drift of the ex-dividend price is m=0.08m = 0.08, then d2P≈−0.193951+0.25=0.056049d_2^{\mathbb{P}} \approx -0.193951 + 0.25 = 0.056049 and the physical probability of exercise is about 0.5223490.522349, different from both. With m=r−q=0.03m = r - q = 0.03 it would equal Φ(d2)\Phi(d_2).

Expiry and zero-volatility limits

Definition Fix K>0K > 0, S>0S > 0 and constants rr and qq. The Black-Scholes prices have the following limits.

  1. Expiry. As τ↓0\tau \downarrow 0 with σ>0\sigma > 0 fixed, C→(S−K)+C \to (S - K)^{+} and P→(K−S)+P \to (K - S)^{+}.
  2. Zero volatility. As σ↓0\sigma \downarrow 0 with τ>0\tau > 0 fixed, C→e−rτ(F−K)+C \to e^{-r\tau}(F - K)^{+} and P→e−rτ(K−F)+P \to e^{-r\tau}(K - F)^{+}, where e−rτ(F−K)+=(Se−qτ−Ke−rτ)+e^{-r\tau}(F - K)^{+} = (S e^{-q\tau} - K e^{-r\tau})^{+}.
  3. Extreme spot prices. As S↓0S \downarrow 0, C→0C \to 0 and P→Ke−rτP \to K e^{-r\tau}. As S→∞S \to \infty, P→0P \to 0 and C−(Se−qτ−Ke−rτ)→0C - (S e^{-q\tau} - K e^{-r\tau}) \to 0.

In the expiry limit with S≠KS \ne K, the bracket in d1d_1 and d2d_2 tends to ln⁡(S/K)≠0\ln(S/K) \ne 0 while στ→0\sigma\sqrt{\tau} \to 0, so both tend to +∞+\infty or both to −∞-\infty with the sign of ln⁡(S/K)\ln(S/K), and the discount factors tend to 11. When S=KS = K, d1,2=(r−q±12σ2)τ/σ→0d_{1,2} = (r - q \pm \tfrac12\sigma^2)\sqrt{\tau}/\sigma \to 0, both probabilities tend to 12\tfrac12 and C→12(S−K)=0C \to \tfrac12(S - K) = 0. In the zero-volatility limit the forward form d1,2=(ln⁡(F/K)±12σ2τ)/(στ)d_{1,2} = (\ln(F/K) \pm \tfrac12\sigma^2\tau)/(\sigma\sqrt{\tau}) gives the same picture with FF in place of SS, applied to C=e−rτ(F Φ(d1)−K Φ(d2))C = e^{-r\tau}\bigl(F\,\Phi(d_1) - K\,\Phi(d_2)\bigr) with the discount factor held fixed. The formulas need σ>0\sigma > 0 and τ>0\tau > 0, and substituting σ=0\sigma = 0 or τ=0\tau = 0 into d1d_1 divides by zero. The values at the boundary come from the contract and the model. At τ=0\tau = 0 the option is its payoff, and with σ=0\sigma = 0 the stock price under Q\mathbb{Q} grows deterministically and ends at ST=FS_T = F, so the value is the discounted payoff e−rτ(F−K)+e^{-r\tau}(F - K)^{+}. Both agree with the limits. For σ>0\sigma > 0 and τ>0\tau > 0 the call lies strictly inside its bounds, (Se−qτ−Ke−rτ)+<C<Se−qτ(S e^{-q\tau} - K e^{-r\tau})^{+} < C < S e^{-q\tau}, because C>0C > 0, C−(Se−qτ−Ke−rτ)=P>0C - (S e^{-q\tau} - K e^{-r\tau}) = P > 0 and Ke−rτΦ(d2)>0K e^{-r\tau}\Phi(d_2) > 0.

In plain words With no time left or no randomness there is nothing to average. At expiry the option is worth its payoff, and with zero volatility the stock arrives exactly at the forward, so the option is worth the discounted payoff computed at the forward. At the money, meaning S=KS = K in the expiry limit or F=KF = K in the zero-volatility limit, both normal probabilities tend to one half rather than to 00 or 11, and the price still tends to the zero payoff.

Example In the constructed example F≈103.045<K=105F \approx 103.045 < K = 105, so the zero-volatility limits are C→0C \to 0 and P→Ke−rτ−Se−qτ≈1.859222P \to K e^{-r\tau} - S e^{-q\tau} \approx 1.859222. Along the way, σ=0.05\sigma = 0.05 gives C≈1.181649C \approx 1.181649 and P≈3.040871P \approx 3.040871, and σ=0.01\sigma = 0.01 gives C≈0.011548C \approx 0.011548 and P≈1.870771P \approx 1.870771. Keeping σ=0.2\sigma = 0.2 and shrinking the time to τ=0.01\tau = 0.01 gives C≈0.005175C \approx 0.005175 and P≈4.972686P \approx 4.972686, close to the payoffs 00 and 55 at the current price.

Check yourself

  1. A European call on a stock without dividends has S=50S = 50, K=48K = 48, r=0.04r = 0.04 and τ=0.5\tau = 0.5, and it trades at the constructed price 5.205.20. Which price of the European put with the same strike and maturity does parity require, and why is no volatility needed? If the put trades at 2.002.00, which trades lock in a riskless profit?
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The discounted strike is Ke−rτ=48e−0.02≈47.049536K e^{-r\tau} = 48e^{-0.02} \approx 47.049536, and with q=0q = 0 parity gives

P=C−S+Ke−rτ≈5.20−50+47.049536≈2.249536.\begin{aligned} P &= C - S + K e^{-r\tau} \\[0.4em] &\approx 5.20 - 50 + 47.049536 \\[0.4em] &\approx 2.249536 . \end{aligned}

No volatility is needed because parity follows from the payoff identity and from the prices of one share and of KK paid at TT, without any model for STS_T. A put at 2.002.00 is too cheap. Buy the put and one share, sell the call and borrow 47.04953647.049536. The cash today is 5.20−2.00−50+47.049536≈0.2495365.20 - 2.00 - 50 + 47.049536 \approx 0.249536. At TT the options pay K−STK - S_T, the share is worth STS_T and the loan costs KK, so the position owes nothing.

  1. A constructed call has S=100S = 100, K=105K = 105, r=0.05r = 0.05, q=0q = 0, σ=0.2\sigma = 0.2 and τ=1\tau = 1. A colleague says the probability that it is exercised is Φ(d1)\Phi(d_1). Compute Φ(d1)\Phi(d_1), Φ(d2)\Phi(d_2) and, for a physical drift m=0.10m = 0.10, the physical probability of exercise. Which of these does the option price depend on?
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The bracket is ln⁡(100/105)+(r−q+12σ2)τ≈−0.048790+0.07=0.021210\ln(100/105) + (r - q + \tfrac12\sigma^2)\tau \approx -0.048790 + 0.07 = 0.021210, so d1≈0.106049d_1 \approx 0.106049 and d2≈−0.093951d_2 \approx -0.093951. Then Φ(d1)≈0.542228\Phi(d_1) \approx 0.542228 and Φ(d2)≈0.462574\Phi(d_2) \approx 0.462574. The pricing probability of exercise under Q\mathbb{Q} is Φ(d2)\Phi(d_2), since exercise is the event Z>−d2Z > -d_2. The number Φ(d1)\Phi(d_1) is the probability of the same event under the stock-numeraire measure, and with q=0q = 0 it is the delta of the call, which is a hedge ratio. Under P\mathbb{P} the drift term is (m−12σ2)τ=0.08(m - \tfrac12\sigma^2)\tau = 0.08, so

d2P=−0.048790+0.080.2≈0.156049,\begin{aligned} d_2^{\mathbb{P}} &= \frac{-0.048790 + 0.08}{0.2} \\[0.4em] &\approx 0.156049, \end{aligned}

so the physical probability is Φ(0.156049)≈0.562003\Phi(0.156049) \approx 0.562003. The price C≈8.021352C \approx 8.021352 uses only Φ(d1)\Phi(d_1) and Φ(d2)\Phi(d_2) and is the same for every value of mm.

  1. Take S=K=100S = K = 100, r=0.05r = 0.05, q=0.02q = 0.02 and τ=1\tau = 1. Find the limits of the call and put prices as σ↓0\sigma \downarrow 0. Then set the strike equal to the forward and find the limits again. A classmate argues that the call in the second case should tend to half of something positive, since both normal probabilities tend to one half. Is that right?
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The forward is F=100e0.03≈103.045453>KF = 100e^{0.03} \approx 103.045453 > K, so ln⁡(F/K)>0\ln(F/K) > 0 and d1,d2→+∞d_1, d_2 \to +\infty. The call tends to

Se−qτ−Ke−rτ≈98.019867−95.122942≈2.896925,\begin{aligned} &S e^{-q\tau} - K e^{-r\tau} \\[0.4em] &\quad \approx 98.019867 - 95.122942 \\[0.4em] &\quad \approx 2.896925, \end{aligned}

and the put tends to 00. At σ=0.01\sigma = 0.01 the formulas already give C≈2.897294C \approx 2.897294 and P≈0.000369P \approx 0.000369. With K=FK = F, parity gives C=PC = P for every σ\sigma. Here d1=12στd_1 = \tfrac12\sigma\sqrt{\tau} and d2=−12στd_2 = -\tfrac12\sigma\sqrt{\tau}, so

C=e−rτF(Φ(d1)−Φ(d2))=e−rτF(2Φ(12στ)−1),\begin{aligned} C &= e^{-r\tau}F\bigl(\Phi(d_1) - \Phi(d_2)\bigr) \\[0.4em] &= e^{-r\tau}F\bigl(2\Phi(\tfrac12\sigma\sqrt{\tau}) - 1\bigr), \end{aligned}

which tends to 00, the discounted payoff e−rτ(F−K)+e^{-r\tau}(F - K)^{+} at the forward. The classmate’s argument fails because both legs tend to half of the same amount, 12e−rτF\tfrac12 e^{-r\tau}F, and cancel. At σ=0.2\sigma = 0.2 the formula gives C=P≈7.807839C = P \approx 7.807839, and the price decreases to 00 as σ\sigma decreases.

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