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Consider a Black Scholes model with $r \geq 0$. Show that the price of an American Put Option with maturity $T > 0$ is bounded by $\frac{K}{1 + \alpha} {(\frac{\alpha K}{1 + \alpha})}^{\alpha}{S_{0}^{-\alpha}}$. Hint: find $\alpha > 0$ such that $e^{-rt}S_{t}^{-\alpha}$ is a martingale.

I am trying to work through the hint and when rewriting $e^{-rt}S_{t}^{-\alpha}$ I get $e^{-rt}S_{t}^{-\alpha} = exp(-\alpha \sigma W_t - t(r + \alpha (r-\frac{{\sigma}^2}{2})))$

I know that in case of the GBM the drift has to equal zero for it to be a martingale, which property has to be fulfilled here?

Edit: the condition that my professor wrote:

$r + \alpha (r-\frac{{\sigma}^2}{2}) = \frac{\alpha^2 \sigma^2}{2}$

which leads to a quadratic equation for $\alpha$, but O do not quite understand where is equation comes from.

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    $\begingroup$ There are too many $r$s in that exponential. Hint: It is well known that for a stock not paying dividends $e^{-rt}S_t$ is a martingale under the risk-neutral measure. $\endgroup$
    – Kurt G.
    Commented Oct 30, 2023 at 10:46
  • $\begingroup$ @KurtG., thank you very much, of course there was a mistake with the $rt$ and I corrected it now. And regarding your hint I know that a probability measure Q is risk neutral if $E_{Q}[S_t | F_s] = S_s e^{r(t-s)}$, with that information how can I calculate $\alpha$? $\endgroup$
    – Parinn
    Commented Oct 30, 2023 at 20:42
  • $\begingroup$ What we both know now boils down to $\alpha=1\,.$ $\endgroup$
    – Kurt G.
    Commented Oct 31, 2023 at 8:57
  • $\begingroup$ @KurtG., thank you for coming back to this thread, I would have $\alpha = -1$, if we use the condition that $e^{-rt}S_t = e^{-rt}{S_t}^{-(-1)}$ is a martingale. My professor wrote a condition today which I don’t quite understand, I edited the post. Do you maybe know where this property comes from?(The quadratic equation also leads to $\alpha = -1$ as one solution.) $\endgroup$
    – Parinn
    Commented Oct 31, 2023 at 11:11
  • $\begingroup$ Correct. My mistake. See answer for further details. $\endgroup$
    – Kurt G.
    Commented Oct 31, 2023 at 12:20

1 Answer 1

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Too long for a comment.

\begin{align} S_t&=S_0\,e^{rt+\sigma W_t-\sigma^2t/2}\,,&S_t^{-\alpha}=S_0^{-\alpha}\,e^{-\alpha\, r\,t\,-\,\alpha\,\sigma\, W_t\,+\,\alpha\,\sigma^2\,t/2}\,, \end{align} \begin{align} e^{-rt}S_t^{-\alpha}&=S_0^{-\alpha}e^{-(1+\alpha)\,r\,t\,-\,\alpha\,\sigma\, W_t\,+\,\alpha\,\sigma^2\,t/2}\\ &=S_0^{-\alpha}e^{-(1+\alpha)\,r\,t\,+\,(\alpha^2+\alpha)\,\sigma^2\,t/2}\,\underbrace{e^{-\,\alpha\,\sigma\, W_t\,-\,\alpha^2\sigma^2\,t/2}}_{\text{martingale}}\,. \end{align} For the whole expression to be a martingale we must have (your professor's quadratic equation): \begin{align} -(1+\alpha)r+(\alpha^2+\alpha)\sigma^2/2=0\,. \end{align} One solution of that is $\alpha=-1$ but your professor wants a positive solution. This is \begin{align} \alpha&=\frac{-\frac{\sigma^2}{2}+r+\sqrt{(\frac{\sigma^2}{2}-r)^2+2\sigma^2r}}{\sigma^2}\\ &=\frac{-\frac{\sigma^2}{2}+r+\frac{\sigma^2}{2}+r}{\sigma^2}=\frac{2r}{\sigma^2}\,. \end{align}

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  • $\begingroup$ Thank you very much! Could you please just tell me the step from the second equality to the third, if I understand correctly you set $-\alpha \sigma W_t$ equal to $\alpha^2 \sigma ^2 t/2$, could you tell me what rule this is? $\endgroup$
    – Parinn
    Commented Oct 31, 2023 at 15:03
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    $\begingroup$ The rule for that is that $\mathbb E[e^{X-{\rm Var}(X)/2}]=1$ whenever $X$ is a normal random variable with mean zero. This can easily be verified by applying the normal PDF and completing the square. Its analogue in the martingale world is that $e^{M_t-\langle M\rangle_t/2}$ is a (local) martingale when $M_t$ is one. Proof: Ito's formula. $\endgroup$
    – Kurt G.
    Commented Oct 31, 2023 at 15:29
  • $\begingroup$ Thank you very much $\endgroup$
    – Parinn
    Commented Nov 1, 2023 at 11:50

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