Determine $Bbb E[langle S rangle]$ where $S$ is simple symmetric random walk

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Let $(Z_k)_k in Bbb N$ be i.i.d. with $Bbb P[Z_1 = 1] = Bbb P[Z_1 = -1] = 1 over 2$. Consider the process $S = (S_n)_n in Bbb N_0$ with $S_n = sum_k=1^n Z_k$. I want to determine $Bbb E[langle S rangle]$ for $n ge 0$, where $langle S rangle := (A_n)_n in Bbb N$ which is given by the Doob decomposition $X_n = M_n + A_n$ with $M_n$ a martingal, $A_n$ is predictable and $X_n := S_n²$ (quadratic variation process).







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  • 2




    Any thoughts on the problem? What do you get if you compute $mathbbE(S_n^2 mid mathcalF_n-1)$?
    – saz
    Jul 21 at 18:40










  • I think that I get $M_n-1 + A_n$.
    – Pazu
    Jul 21 at 18:58










  • @saz If you know how the solution works, please share it with me!
    – Pazu
    Jul 22 at 0:20






  • 1




    I do know the answer, I simply have other things on my mind on a saturday evening. Re your 1st comment: That's correct, but it doesn't help you. Try to use the very definition of $S_n$, i.e. $S_n = sum_k=1^n Z_k$. Write $$S_n^2 = (S_n-S_n-1+S_n-1)^2 = (S_n-S_n-1)^2 + 2 S_n-1 (S_n-S_n-1) + S_n-1^2$$ plug this into $mathbbE(S_n^2 mid mathcalF_n-1)$, and then compute each of the terms separately using $S_n = sum_k=1^n Z_k$.
    – saz
    Jul 22 at 6:07















up vote
0
down vote

favorite












Let $(Z_k)_k in Bbb N$ be i.i.d. with $Bbb P[Z_1 = 1] = Bbb P[Z_1 = -1] = 1 over 2$. Consider the process $S = (S_n)_n in Bbb N_0$ with $S_n = sum_k=1^n Z_k$. I want to determine $Bbb E[langle S rangle]$ for $n ge 0$, where $langle S rangle := (A_n)_n in Bbb N$ which is given by the Doob decomposition $X_n = M_n + A_n$ with $M_n$ a martingal, $A_n$ is predictable and $X_n := S_n²$ (quadratic variation process).







share|cite|improve this question

















  • 2




    Any thoughts on the problem? What do you get if you compute $mathbbE(S_n^2 mid mathcalF_n-1)$?
    – saz
    Jul 21 at 18:40










  • I think that I get $M_n-1 + A_n$.
    – Pazu
    Jul 21 at 18:58










  • @saz If you know how the solution works, please share it with me!
    – Pazu
    Jul 22 at 0:20






  • 1




    I do know the answer, I simply have other things on my mind on a saturday evening. Re your 1st comment: That's correct, but it doesn't help you. Try to use the very definition of $S_n$, i.e. $S_n = sum_k=1^n Z_k$. Write $$S_n^2 = (S_n-S_n-1+S_n-1)^2 = (S_n-S_n-1)^2 + 2 S_n-1 (S_n-S_n-1) + S_n-1^2$$ plug this into $mathbbE(S_n^2 mid mathcalF_n-1)$, and then compute each of the terms separately using $S_n = sum_k=1^n Z_k$.
    – saz
    Jul 22 at 6:07













up vote
0
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favorite









up vote
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Let $(Z_k)_k in Bbb N$ be i.i.d. with $Bbb P[Z_1 = 1] = Bbb P[Z_1 = -1] = 1 over 2$. Consider the process $S = (S_n)_n in Bbb N_0$ with $S_n = sum_k=1^n Z_k$. I want to determine $Bbb E[langle S rangle]$ for $n ge 0$, where $langle S rangle := (A_n)_n in Bbb N$ which is given by the Doob decomposition $X_n = M_n + A_n$ with $M_n$ a martingal, $A_n$ is predictable and $X_n := S_n²$ (quadratic variation process).







share|cite|improve this question













Let $(Z_k)_k in Bbb N$ be i.i.d. with $Bbb P[Z_1 = 1] = Bbb P[Z_1 = -1] = 1 over 2$. Consider the process $S = (S_n)_n in Bbb N_0$ with $S_n = sum_k=1^n Z_k$. I want to determine $Bbb E[langle S rangle]$ for $n ge 0$, where $langle S rangle := (A_n)_n in Bbb N$ which is given by the Doob decomposition $X_n = M_n + A_n$ with $M_n$ a martingal, $A_n$ is predictable and $X_n := S_n²$ (quadratic variation process).









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edited Jul 21 at 19:39
























asked Jul 21 at 17:51









Pazu

359213




359213







  • 2




    Any thoughts on the problem? What do you get if you compute $mathbbE(S_n^2 mid mathcalF_n-1)$?
    – saz
    Jul 21 at 18:40










  • I think that I get $M_n-1 + A_n$.
    – Pazu
    Jul 21 at 18:58










  • @saz If you know how the solution works, please share it with me!
    – Pazu
    Jul 22 at 0:20






  • 1




    I do know the answer, I simply have other things on my mind on a saturday evening. Re your 1st comment: That's correct, but it doesn't help you. Try to use the very definition of $S_n$, i.e. $S_n = sum_k=1^n Z_k$. Write $$S_n^2 = (S_n-S_n-1+S_n-1)^2 = (S_n-S_n-1)^2 + 2 S_n-1 (S_n-S_n-1) + S_n-1^2$$ plug this into $mathbbE(S_n^2 mid mathcalF_n-1)$, and then compute each of the terms separately using $S_n = sum_k=1^n Z_k$.
    – saz
    Jul 22 at 6:07













  • 2




    Any thoughts on the problem? What do you get if you compute $mathbbE(S_n^2 mid mathcalF_n-1)$?
    – saz
    Jul 21 at 18:40










  • I think that I get $M_n-1 + A_n$.
    – Pazu
    Jul 21 at 18:58










  • @saz If you know how the solution works, please share it with me!
    – Pazu
    Jul 22 at 0:20






  • 1




    I do know the answer, I simply have other things on my mind on a saturday evening. Re your 1st comment: That's correct, but it doesn't help you. Try to use the very definition of $S_n$, i.e. $S_n = sum_k=1^n Z_k$. Write $$S_n^2 = (S_n-S_n-1+S_n-1)^2 = (S_n-S_n-1)^2 + 2 S_n-1 (S_n-S_n-1) + S_n-1^2$$ plug this into $mathbbE(S_n^2 mid mathcalF_n-1)$, and then compute each of the terms separately using $S_n = sum_k=1^n Z_k$.
    – saz
    Jul 22 at 6:07








2




2




Any thoughts on the problem? What do you get if you compute $mathbbE(S_n^2 mid mathcalF_n-1)$?
– saz
Jul 21 at 18:40




Any thoughts on the problem? What do you get if you compute $mathbbE(S_n^2 mid mathcalF_n-1)$?
– saz
Jul 21 at 18:40












I think that I get $M_n-1 + A_n$.
– Pazu
Jul 21 at 18:58




I think that I get $M_n-1 + A_n$.
– Pazu
Jul 21 at 18:58












@saz If you know how the solution works, please share it with me!
– Pazu
Jul 22 at 0:20




@saz If you know how the solution works, please share it with me!
– Pazu
Jul 22 at 0:20




1




1




I do know the answer, I simply have other things on my mind on a saturday evening. Re your 1st comment: That's correct, but it doesn't help you. Try to use the very definition of $S_n$, i.e. $S_n = sum_k=1^n Z_k$. Write $$S_n^2 = (S_n-S_n-1+S_n-1)^2 = (S_n-S_n-1)^2 + 2 S_n-1 (S_n-S_n-1) + S_n-1^2$$ plug this into $mathbbE(S_n^2 mid mathcalF_n-1)$, and then compute each of the terms separately using $S_n = sum_k=1^n Z_k$.
– saz
Jul 22 at 6:07





I do know the answer, I simply have other things on my mind on a saturday evening. Re your 1st comment: That's correct, but it doesn't help you. Try to use the very definition of $S_n$, i.e. $S_n = sum_k=1^n Z_k$. Write $$S_n^2 = (S_n-S_n-1+S_n-1)^2 = (S_n-S_n-1)^2 + 2 S_n-1 (S_n-S_n-1) + S_n-1^2$$ plug this into $mathbbE(S_n^2 mid mathcalF_n-1)$, and then compute each of the terms separately using $S_n = sum_k=1^n Z_k$.
– saz
Jul 22 at 6:07











1 Answer
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Elaborating on @saz's hint, we can write
beginalign
S_n^2 &= (S_n-S_n-1)^2 + 2S_n-1(S_n-S_n-1) + S_n-1^2\
&= Z_n^2 + 2S_n-1Z_n + S_n-1^2.
endalign
Letting $mathcal F_n$ be the filtration generated by $Z_n$, it is clear that $Z_n^2$ is independent of $mathcal F_n-1$ and $S_n-1$, $S_n-1^2$ are $mathcal F_n-1$ measurable, hence
beginalign
mathbb E[X_nmidmathcal F_n-1] &= mathbb E[S_n^2midmathcal F_n-1]\
&= mathbb E[Z_n^2 + 2S_n-1Z_n + S_n-1^2mid mathcal F_n-1]\
&= mathbb E[Z_n^2] + 2S_n-1mathbb E[Z_n] + S_n-1^2\
&= 1 + S_n-1^2.
endalign
It follows that the (predictable) quadratic variation of $X_n$ is
beginalign
A_n &= sum_k=1^n (mathbb E[X_kmidmathcal F_k-1] - X_k-1)\
&= sum_k=1^n (1 + S_n-1^2-S_n-1^2)\
&= n.
endalign



It follows that $M_n=S_n^2-n$ as expected (since $S_n$ is a martingale).






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    Elaborating on @saz's hint, we can write
    beginalign
    S_n^2 &= (S_n-S_n-1)^2 + 2S_n-1(S_n-S_n-1) + S_n-1^2\
    &= Z_n^2 + 2S_n-1Z_n + S_n-1^2.
    endalign
    Letting $mathcal F_n$ be the filtration generated by $Z_n$, it is clear that $Z_n^2$ is independent of $mathcal F_n-1$ and $S_n-1$, $S_n-1^2$ are $mathcal F_n-1$ measurable, hence
    beginalign
    mathbb E[X_nmidmathcal F_n-1] &= mathbb E[S_n^2midmathcal F_n-1]\
    &= mathbb E[Z_n^2 + 2S_n-1Z_n + S_n-1^2mid mathcal F_n-1]\
    &= mathbb E[Z_n^2] + 2S_n-1mathbb E[Z_n] + S_n-1^2\
    &= 1 + S_n-1^2.
    endalign
    It follows that the (predictable) quadratic variation of $X_n$ is
    beginalign
    A_n &= sum_k=1^n (mathbb E[X_kmidmathcal F_k-1] - X_k-1)\
    &= sum_k=1^n (1 + S_n-1^2-S_n-1^2)\
    &= n.
    endalign



    It follows that $M_n=S_n^2-n$ as expected (since $S_n$ is a martingale).






    share|cite|improve this answer

























      up vote
      0
      down vote













      Elaborating on @saz's hint, we can write
      beginalign
      S_n^2 &= (S_n-S_n-1)^2 + 2S_n-1(S_n-S_n-1) + S_n-1^2\
      &= Z_n^2 + 2S_n-1Z_n + S_n-1^2.
      endalign
      Letting $mathcal F_n$ be the filtration generated by $Z_n$, it is clear that $Z_n^2$ is independent of $mathcal F_n-1$ and $S_n-1$, $S_n-1^2$ are $mathcal F_n-1$ measurable, hence
      beginalign
      mathbb E[X_nmidmathcal F_n-1] &= mathbb E[S_n^2midmathcal F_n-1]\
      &= mathbb E[Z_n^2 + 2S_n-1Z_n + S_n-1^2mid mathcal F_n-1]\
      &= mathbb E[Z_n^2] + 2S_n-1mathbb E[Z_n] + S_n-1^2\
      &= 1 + S_n-1^2.
      endalign
      It follows that the (predictable) quadratic variation of $X_n$ is
      beginalign
      A_n &= sum_k=1^n (mathbb E[X_kmidmathcal F_k-1] - X_k-1)\
      &= sum_k=1^n (1 + S_n-1^2-S_n-1^2)\
      &= n.
      endalign



      It follows that $M_n=S_n^2-n$ as expected (since $S_n$ is a martingale).






      share|cite|improve this answer























        up vote
        0
        down vote










        up vote
        0
        down vote









        Elaborating on @saz's hint, we can write
        beginalign
        S_n^2 &= (S_n-S_n-1)^2 + 2S_n-1(S_n-S_n-1) + S_n-1^2\
        &= Z_n^2 + 2S_n-1Z_n + S_n-1^2.
        endalign
        Letting $mathcal F_n$ be the filtration generated by $Z_n$, it is clear that $Z_n^2$ is independent of $mathcal F_n-1$ and $S_n-1$, $S_n-1^2$ are $mathcal F_n-1$ measurable, hence
        beginalign
        mathbb E[X_nmidmathcal F_n-1] &= mathbb E[S_n^2midmathcal F_n-1]\
        &= mathbb E[Z_n^2 + 2S_n-1Z_n + S_n-1^2mid mathcal F_n-1]\
        &= mathbb E[Z_n^2] + 2S_n-1mathbb E[Z_n] + S_n-1^2\
        &= 1 + S_n-1^2.
        endalign
        It follows that the (predictable) quadratic variation of $X_n$ is
        beginalign
        A_n &= sum_k=1^n (mathbb E[X_kmidmathcal F_k-1] - X_k-1)\
        &= sum_k=1^n (1 + S_n-1^2-S_n-1^2)\
        &= n.
        endalign



        It follows that $M_n=S_n^2-n$ as expected (since $S_n$ is a martingale).






        share|cite|improve this answer













        Elaborating on @saz's hint, we can write
        beginalign
        S_n^2 &= (S_n-S_n-1)^2 + 2S_n-1(S_n-S_n-1) + S_n-1^2\
        &= Z_n^2 + 2S_n-1Z_n + S_n-1^2.
        endalign
        Letting $mathcal F_n$ be the filtration generated by $Z_n$, it is clear that $Z_n^2$ is independent of $mathcal F_n-1$ and $S_n-1$, $S_n-1^2$ are $mathcal F_n-1$ measurable, hence
        beginalign
        mathbb E[X_nmidmathcal F_n-1] &= mathbb E[S_n^2midmathcal F_n-1]\
        &= mathbb E[Z_n^2 + 2S_n-1Z_n + S_n-1^2mid mathcal F_n-1]\
        &= mathbb E[Z_n^2] + 2S_n-1mathbb E[Z_n] + S_n-1^2\
        &= 1 + S_n-1^2.
        endalign
        It follows that the (predictable) quadratic variation of $X_n$ is
        beginalign
        A_n &= sum_k=1^n (mathbb E[X_kmidmathcal F_k-1] - X_k-1)\
        &= sum_k=1^n (1 + S_n-1^2-S_n-1^2)\
        &= n.
        endalign



        It follows that $M_n=S_n^2-n$ as expected (since $S_n$ is a martingale).







        share|cite|improve this answer













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        answered Jul 24 at 2:24









        Math1000

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