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Assume the risk-free bond $B_t$ and the stock $S_t$ follow the dynamics of the Black & Scholes model without dividends (with interest rate r, stock drift $\mu$ and volatility $\sigma$). Let $c(t; St;Gt;K)$ and $p(t; St;Gt;K)$ be the prices at time t of the (continuous) Geometric Asian call option and put option with strike $K$. Find a put-call parity relation for Geometric Asian options. In other terms, and an explicit expression for $c(t; St;Gt;K)-p(t; St;Gt;K)$.

So far, this is what I have: $G_T=\exp\{\frac{1}{T}\int_{0}^{T}\log S_udu\}\\ X_T=\frac{1}{T}\int_{0}^{T}\log S_udu\\ G_T=e^{X_T}$

Payoff functions are: $c_{fix}=(G_T-K)^+=(e^{X_T}-K)^+\\ p_{fix}=(K-G_T)^+=(K-e^{X_T})^+\\ c_{fix}-p_{fix}=G_{T}-K$

By risk neutral evaluation: $c_{fix}-p_{fix}=e^{-r(T-t)}E^{Q}[e^{X_T}-K]$.

Hoping to understand how to compute this without the standard normal variable.

Anon
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1 Answers1

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Whether arithmetic or geometric averaging, you always get \begin{align*} \mathrm{AsianCall} - \mathrm{AsianPut} = e^{-rT} (\mathbb{E}[\bar{S}]-K). \end{align*}

So, let’s compute the expectation. You know that $\bar{S}=\exp\left( \frac{1}{T} \int_0^T \ln(S_t)\mathrm{d}t \right)$ where $\ln(S_t) =\ln(S_0)+\left(r-q-\frac{1}{2}\sigma^2\right)t+ \sigma W_t$.

Thus,

\begin{align*} \ln(\bar{S}) &= \frac{1}{T} \int_0^T \ln(S_t)\mathrm{d}t \\ &= \frac{1}{T} \int_0^T \left( \ln(S_0)+\left(r-q-\frac{1}{2}\sigma^2\right)t + \sigma W_t \right) \mathrm{d}t \\ &= \frac{1}{T}\left( \ln(S_0)T + \frac{1}{2}\left(r-q-\frac{1}{2}\sigma^2\right)T^2+\sigma\sqrt{\frac{1}{3}T^3}Z \right) \\ &= \ln(S_0) + \frac{1}{2}\left(r-q-\frac{1}{2}\sigma^2\right)T+\frac{\sqrt{3}}{3}\sigma\sqrt{T}Z, \end{align*} using that $\int_0^T W_t\mathrm{d}t\sim N\left(0,\frac{1}{3}T^3\right)$ as shown here.

Consequently, \begin{align*} \ln(\bar{S}) \sim N\left( \ln(S_0) + \frac{1}{2}\left(r-q-\frac{1}{2}\sigma^2\right)T, \frac{1}{3}\sigma^2 T\right). \end{align*}

Hence, $\bar{S}$ is log-normally distributed and $\mathbb{E}[\bar{S}]=e^{m+\frac{1}{2}s^2}$, where $m$ and $s$ are the mean and standard deviation of $\ln(\bar{S})$ as computed above.

Kevin
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  • so the final answer would then be $e^{m+\frac{1}{2}s^2}-Ke^{-rT}$ right? – Anon Nov 03 '19 at 12:38
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    @Anon It would be $e^{-rT}(e^{m+\frac{1}{2}s^2}-K)=e^{m+\frac{1}{2}s^2-rT}-Ke^{-rT}$, where $m=\ln(S_0) + \frac{1}{2}\left(r-q-\frac{1}{2}\sigma^2\right)T$ and $s^2=\frac{1}{3}\sigma^2 T$ – Kevin Nov 03 '19 at 12:40
  • oh right, forgot to multiply $e^{-rT}$ to the first term! thank you! – Anon Nov 03 '19 at 12:41
  • @Anon Happens to the best of us :) – Kevin Nov 03 '19 at 12:42
  • Um, just have another question, this wouldn't lead to an answer with N(d) right? – Anon Nov 04 '19 at 08:18
  • @Anon Well, $N(d)$ is the probability of an event, right? But the point of the put-call parity is that it is independent about which option is exercised. It gives a more general relationship. The price of a single option typically involves $N(d)$ but compare this to the put-call parity between plain vanilla option, there is no $N(d)$ either – Kevin Nov 04 '19 at 08:20
  • @Anon is everything okay about the answer? – Kevin Nov 07 '19 at 21:21
  • yes yes, everything is okay about the answer! happened to click that accidentally! – Anon Nov 08 '19 at 06:39