Pricing a Cash-or-Nothing Binary Call with Black–Scholes
Summary
The document works through a European cash-or-nothing call that pays a fixed amount if the underlying price finishes above the strike. It outlines the risk-neutral stock process when the asset pays a continuous dividend yield, identifies the market price of risk, and asks for the pricing partial differential equation and boundary conditions. The replies note that the Black–Scholes pricing equation is determined by the underlying risk-neutral process, not by the option's payoff shape.
For valuation, the replies give the discounted conditional risk-neutral expectation of the terminal indicator payoff. Under the no-dividend setup for the binary option, the probability of finishing above the strike is expressed using the normal cumulative distribution at d2, producing a price equal to the discounted cash payout times N(d2). The exchange is educational but leaves some derivations and boundary-condition details to the reader, and the displayed integral uses time notation inconsistently.
Key ideas
- Under the risk-neutral measure, a dividend-paying stock has drift equal to the risk-free rate less its continuous yield.
- The market price of risk compares the physical drift with the risk-neutral drift, scaled by volatility.
- A European option price is the discounted conditional risk-neutral expectation of its terminal payoff.
- A cash-or-nothing call is valued from the risk-neutral probability that the terminal stock price exceeds the strike.
- In the no-dividend Black–Scholes setting, that probability is represented by N(d2).
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Full text
# price of a "Cash-or-nothing binary call option"
# price of a "Cash-or-nothing binary call option"
I'm stuck with one homework problem here:
> Assume there is a geometric Brownian motion \begin{equation} dS_t=\mu S_t dt + \sigma S_t dW_t \end{equation} Assume the stock pays dividend, with the cont. compounded yield $q$. a) Find the risk-neutral version of the process for $S_t$. b) What is the market price of risk in this case? c) Assume no yield anymore. Now, there is a derivative written on this stock paying one unit of cash if the stock price is above the strike price $K$ at maturity time $T$, and 0 else (cash-or-nothing binary call option). Find the PDE followed by the price of this derivative. Write the appropriate boundary conditions. d) Write the expression for the price of this derivative at time $t<T$ as a risk-neutral expectation of the terminal payoff. e) Writte the price of this option in terms on $N(d_2)$, where $d_2$ has the usual Black-Scholes value.
Here is what I came up with by now:
for a): This should become $dS_t'=(r-q)S_t'dt + \sigma S_t'dW_t^\mathbb{Q}$ (is this correct?)
for b): This would be $\zeta=\frac{\mu-(r-q)}{\sigma}$ (?)
for c): The boundary conditions should be: Price at $t=T$ is $0$ if $S<K, 1$ else; I have no idea what to write for the PDE.
for d): I can only think of $C(S_t,t)=e^{-r(T-t)}\mathbb{E}[C(S_t),T]$, where $C(S_t,T)$ is the value at time $T$, i.e. the payoff.
for e): I don't know how to start here.
Can anybody help me and solve this with me?
## Answer by phubaba (score 7)
https://quant.stackexchange.com/a/4856
a. is correct, but you should derive it using appropriate logic, not just guessing the answer. Ie the drift of discounted stock should be 0. Define a bond dB = rBdt. d(S/B) should have no drift. This can help you find the correct mu. You can find the sde for S/B using two dimensional ito
b. don't really know about market price of risk.
c. In this case the pde is the same as the black scholes pde using your risk neutral process. Can you think of why this is? Does the type of call option change how the underlying changes? What are the other boundary conditions ie (for S = 0 and S = infinity). Take a look at dirichlet (also known as zero gamma condition) and other types of boundary conditions.
d. That is the right start, but what is the expectation? Lets define C = cash on payout. Then the payout(S) = C*I(S>K). Plug this into your formula. The expectation now looks like C*E(I(S>K)). The problem is that this expectation is in real probability space and you want it in your risk neutral space. You can use girsanov's theorem. Best proof (result to use) I found is (1) in http://math.ucsd.edu/~pfitz/downloads/courses/spring05/math280c/girsanov.pdf
e. In d you will basically find that E(I(S>K)) a function(t)*P(S>K) in your risk neutral space. You need to find P(S>k) this turns out to be N(d2). You can define a new variable (S-E(S))/std(S) = Normal(0,1) to transform P(S>k) into N(d2)
## Answer by wsw (score 6)
https://quant.stackexchange.com/a/8030
For part (d), instead of using Girsanov's theorem as phubaba suggested, I believe that we can state directly that the price is $$V_t = e^{-r(T-t)} \mathbb{E}^Q \left[ u(S_T-K) \middle \vert \mathcal{F}_t \right],$$ where $u$ is the step function, $Q$ is the risk-neutral probability measure, and $\mathcal{F}_t$ is the filtration at time $t$, since the value of any European-style option with a payoff $f(S_T)$ is given by $V_t = e^{-r(T-t)} \mathbb{E}^Q \left[ f(S_T) \middle \vert \mathcal{F}_t \right]$.
For part (e), note that for a general payoff function $f(S_T)$, we can write $$V_t = e^{-r(T-t)} \int_{-\infty}^\infty f(S_0 e^x) \frac{1}{\sigma \sqrt{2 \pi (T-t)}} \exp \left\{-\frac{\left[x-(r-\sigma^2/2)(T-t)\right]^2}{2 \sigma^2 (T-t)} \right\} dx,$$ where $x \sim \mathcal{N}((r-\sigma^2/2)(T-t), \sigma^2(T-t))$. Plugging in $f(S_0 e^x) = u(S_0 e^x-K)$, I get $V_t = e^{-r(T-t)}N(d_2)$.Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.