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Given $M$ a continuous local martingale, and $M^\text{*} = \sup_{0 \leq s \leq t} M_s$ its running maximum, we consider the finite variation integral $$ I_T:= \int_0^T (M^\text{*}_s - M_s) \, \text{d}M^\text{*}_s $$ I'm seeking to show this integral is 0 a.s.. Intuitively, this is since $(M^\text{*}_s - M_s) \, \text{d}M^\text{*}_s$ is zero: if we're currently at our maximum then the bracket term zero, and otherwise $M^\text{*}_s$ is constant near $s$.

A little bit more rigorously, we have that is $$ I_T = \lim_{n \to \infty} \sum_{[s,t]\in \pi_n} (M^\text{*}_{t,s} - M_{t,s})M^\text{*}_{t,s} $$ (where the limit is in probability, and for a sequence of partitions $\pi_n$ with mesh tending to 0, and where we write $M_{t,s} = M_t - M_s$ and similarly for $M^\text{*}$) and that eventually we'll have "sufficiently small" (this is the part which I think needs more details) $t-s$. Then either we're reaching a new maximum, so that $M^\text{*}_t = M_t$ and $M^\text{*}_s = M_s$ and the difference in brackets is $0$. Or we're not reaching a new maximum, and so $M^\text{*}_{t,s} = 0$.

I think this isn't sufficient at the moment, since even if we could suppose $M$ is monotone on sufficiently small intervals we still need to choose our partitions $\pi_n$ uniformly in $\omega \in \Omega$ (for the convergence in probability).

I've also tried applying Itô's on $MM^\text{*}$, but it reduces this to a similar problem of reasoning for sufficiently small $t-s$ for a partition dependent on the outcome for the $\int M^\text{*} \, \text{d}M$ term.

(I've asked this question on MSE here, but gotten little traction. I thought Overflow might be more appropriate since I'm seeking to formalize and fill the gaps of the intuitive ideas I have - let me know if this isn't appropriate, for instance if the question particularly belongs on either site)

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    $\begingroup$ This problem for Brownian motion is I think prop vi.1.3 in revuz and yor, although it is stated for local time $\endgroup$
    – mike
    Commented Jun 14, 2023 at 15:45
  • $\begingroup$ @mike Thank you for your comment! I'm not seeing how to apply it in this case - I'm not very familiar with local times. It feels like I would want to apply this with (in their notation) $a=0$ and $X_t = M^\text{*}_t - M_t$ but I'm not sure how this corresponds to $dL_t^a$... Do you have any quick words about intuition in interpreting this local time? $\endgroup$
    – George
    Commented Jun 14, 2023 at 16:11
  • $\begingroup$ I thought , without saying, that if you use the reflected process $W^*_t - W_t$, for which the running max, $W^*_t$ is the local time, then it was exactly the same problem for brownian motion. $\endgroup$
    – mike
    Commented Jun 15, 2023 at 5:14

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The integral with regard do $\mathrm{d}M^*$ is a pathwise Stieltjès integral, so the question is an analysis problem.

Let $f : \mathbb{R}_+ \to \mathbb{R}$ be any continuous function, $F$ its current maximum, and $\mu$ the Stieltjès measure associated to $F$

One checks that $F$ is also continuous, so $O := \{s \in \mathbb{R}_+ : F(s)-f(s)>0\}$ is open subset in $\mathbb{R_+}$ and contained in $\mathbb{R_+}^*$ since $F(0)=f(0)$. Hence it is an at most countable union of disjoint open intervals. On each one of these open intervals, $F$ remains constant, so the $\mu$-measure of this interval is $0$. As a result $\mu(O)=0$, so $F-f$ is null $\mu$-almost everywhere and the integral $\int(F-f) \mathrm{d}\mu$ is $0$.

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  • $\begingroup$ That makes a lot of sense! Very clear answer, thank you :) taking it out of the probabilistic/reasoning for each outcome works surprisingly well $\endgroup$
    – George
    Commented Jun 15, 2023 at 10:51

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