Martingale part of the discontinuous put payoff - MathOverflow most recent 30 from http://mathoverflow.net2013-05-25T14:05:38Zhttp://mathoverflow.net/feeds/question/57524http://www.creativecommons.org/licenses/by-nc/2.5/rdfhttp://mathoverflow.net/questions/57524/martingale-part-of-the-discontinuous-put-payoffMartingale part of the discontinuous put payoffSamuel A2011-03-06T02:07:24Z2011-03-07T17:14:36Z
<p>I need the martingale part of the put payoff (not $C^2$..). Where $S_t=exp(\sigma W_t -\frac{\sigma^2t}{2})$</p>
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<p>$d[(S_t -K)^+ ]$ ??</p>
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<p>I guess I need to use local times but how?</p>
http://mathoverflow.net/questions/57524/martingale-part-of-the-discontinuous-put-payoff/57581#57581Answer by The Bridge for Martingale part of the discontinuous put payoffThe Bridge 2011-03-06T15:40:55Z2011-03-07T17:14:36Z<p>Hi,</p>
<p>Simply use Itô-Tanaka's formula I guess this should give something like :
$df(S_t)=D_-f(S_t)dS_t+\frac{1}{2}dL^s_tf''(ds)$</p>
<p>with $f(S)=(S-K)^+$ so $D_-f(S)=1_{]K,+\infty}(S)$ and $f''(ds)=\delta_K(ds)$ </p>
<p>This gives if I am not mistaken :</p>
<p>$d(S_t-K)^+=df(S_t)=1_{]K,+\infty}(S_t)dS_t+\frac{1}{2}dL^K_t$</p>
<p>With $L^K_t$ being the local time of your geometric Brownian Motion $S$ around level $K$ at time $t$.</p>
<p>Regards</p>
<p>Edit
NB:<br>
-$D_-$ stands for the left derivative of $f$ </p>
<p>-$f''(ds)$ stands for second derivatives in the distribution-sense. </p>
<p>-The use of Itô-Tanaka's formula allows to avoid the derivation of the Mollifiers-type argument for the direct proof of the result (which is quite cumbersome in my opinion). I should add that Ito-Tanaka's formula is applicable to every $f$ that is the differnce of two convex functions if I remember well, which is the case here with $f(x)=(X-K)^+$. </p>
http://mathoverflow.net/questions/57524/martingale-part-of-the-discontinuous-put-payoff/57659#57659Answer by Samuel A for Martingale part of the discontinuous put payoffSamuel A2011-03-07T13:07:03Z2011-03-07T13:07:03Z<p>Thanks you all!</p>
<p>(proof, for $\phi(t,S_t)=(K-S_t)^+$:</p>
<p><strong>Step 1</strong> <em>smoothing</em> :
$\phi_\epsilon(x)=1_{S_t\leq K+\epsilon}\cdot\phi(x)+1_{S_t\in]K-\epsilon,K]} \cdot \psi(x)$, where $\psi(x)=-\frac{1}{\epsilon^2}(K-x)^2(K-x-2\epsilon)$ .</p>
<p>This function is $C^1$, and also $C^2$ excepting in a countable set.</p>
<p><strong>Step 2</strong> Itô on
$\phi_\epsilon(S_t)= \phi_\epsilon(S_0)+\int^t_0\phi_\epsilon^'(S_t)dS_t+\frac{1}{2}\int^t_0 1_{S_t\in[K-\epsilon,K]}\phi_\epsilon^{''}(S_t)d\langle S\rangle _t$
because $\phi _\epsilon=0$ out of $[K-\epsilon,K]$</p>
<p>Let's denote by $L_t=lim_{\epsilon \to0}{\frac{1}{2\epsilon^2}*\int{_{K-\epsilon}^K(3S_t+4\epsilon-3K)dS_t}}$ it's a finite variation process since it is increasing</p>
<p><strong>Step 3</strong> We have that $\phi_\epsilon(S_t)-\phi_\epsilon(S_0)-\int^t_0\phi_\epsilon^'(S_t)dS_t \space \xrightarrow {L^2} \space\phi(S_t) -\phi(S_0) -\int^t_0\phi^'(S_t)dS_t $ (because $\int^t_0\phi_\epsilon^'(S_t) 1_{S_u\in[0,K-\epsilon]}dS_u \xrightarrow {L^2}\int_0^t\phi^'(S_u)du$ by using Itô isometry)</p>
<p><strong>Finally</strong> We get the formula 'à la bridge' namely</p>
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<p>$(K-S_t)^+=(K-S_0)^+-\int_0^t1_{K\leq S_u}dS_u+L_t$ </p>
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<p>and the martingale part is </p>
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<p>$(K-S_0)^+-\int_0^t1_{K\leq S_u}\sigma S_u dB_u$</p>
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