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Pricing an Asset-or-Nothing Option on an Independent Asset

Article Quant Q&A · Author: Archetupon

Summary

The document derives the risk-neutral price of a claim that pays the value of one asset when a second asset finishes below a strike. The key assumption is that the assets follow independent geometric Brownian motions. Conditional on current information, their terminal values are therefore independent, so the expected payoff separates into the expected value of the first asset and the probability that the second finishes below the strike.

Discounting the first asset’s risk-neutral expected value cancels its growth at the risk-free rate, leaving its current price multiplied by the cash-or-nothing put probability for the second asset. The result is the current value of the paying asset times the normal cumulative probability associated with negative d2 for the second asset. The derivation depends on independence under the risk-neutral measure; correlated assets would not allow this simple factorization.

Key ideas

  • The payoff is the first asset’s terminal value multiplied by an indicator that the second asset is below its strike.
  • Independence under the risk-neutral measure lets the conditional expected payoff factor into two expectations.
  • The price equals the current value of the paying asset times the cash-or-nothing put probability on the other asset.
  • The d2 term is calculated using the second asset’s process.
  • Correlation between the assets would invalidate the simple factorization.

Tags

Full text
# Pricing for an Odd Type of Asset or Nothing Option


# Pricing for an Odd Type of Asset or Nothing Option












Trying to derive the pricing function for a derivative on two assets $S^1$ and $S^2$ with the following payoff function:

$$\Phi(S^1_T,S^2_T)=S_T^1 \, \unicode{x1D7D9}\{S_T^2\le K\}$$

where I'm simply using $\unicode{x1D7D9}$ as the indicator function. Also, importantly, the two assets are driven by independent Wiener processes. So, effectively, we have a binary put option on $S_T^2$, where the payoff is $S_T^1$. So, I know a few things from the start. If the payoff was some fixed amount $K$, the pricing function would be $Ke^{-rT}N(-d_2)$. On the other hand, if the payoff was the asset $S_T^2$ itself, the pricing function would be $S_0^2N(-d_1)$.

So, given that we have independent Weiner processes, I feel like the pricing should be more similar to a fixed payoff binary. Furthermore, the payoff should be the risk-neutral expectation of the payoff asset. That is,

\begin{align} &\pi(t)=S_t^1e^{r(T-t)}e^{-r(T-t)}N(-d_2)\\ \iff& \pi(t)=S_t^1N(-d_2) \end{align}

with $d_2$ defined as it would be in the standard B-S model. I'm hoping someone could confirm/deny this and perhaps provide a more rigorous derivation. Thanks.

## Answer by spaceisdarkgreen (score 4, accepted)

https://quant.stackexchange.com/a/36211

The price is, under the risk-neutral measure, $$ P_t = e^{-r(T-t)}\mathbb E[S_T^1 \mathbb 1(S_T^2\le K)\mid \mathcal F_t].$$ Since the risk-neutral asset processes are independent geometric brownian motions, $S_T^1$ and $S_T^2$ are conditionally independent given $\mathcal F_t.$

So the conditional expectation factors and you get $$ P_t = e^{-r(T-t)}\mathbb E[S_T^1\mid \mathcal F_t]\mathbb E[\mathbb 1(S_T^2\le K)\mid \mathcal F_t] = S^1_t N(-d_2)$$ (where "$d_2$" is of course relative to the $S^2_t$ process) just like you say.

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.