last updated: October 16, 2024

Stochastic Processes and Financial Mathematics
(part two)

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12.5 Exercises on Chapter 12

In all the following questions, \(B_t\) denotes a Brownian motion and \(\mc {F}_t\) denotes its generated filtration.

On Ito integration
  • 12.1 Using (12.8), find \(\int _v^t 1\,dB_u\), where \(0\leq v\leq t\).

  • 12.2 Show that the process \(e^{B_t}\) is in \(\mc {H}^2\). (Hint: Use (11.2).)

  • 12.3

    • (a) Let \(Z\sim N(0,1)\). Show that the expectation of \(e^{\frac {Z^2}{2}}\) is infinite.

    • (b) Give an example of a continuous, adapted, stochastic process that is not in \(\mc {H}^2\).

  • 12.4 Let \(X_t\) be an Ito process satisfying

    \[X_t=2+\int _0^t t+B_u^2\,du+\int _0^t B_u^2\,dB_u.\]

    Find \(\E [X_t]\).

  • 12.5 Which of the following stochastic processes are Ito processes?

    • (a) \(X_t=0\),

    • (b) \(Y_t=t^2+B_t\),

    • (c) The symmetric random walk from Section 4.1.

  • 12.6 Let \(V_t\) be the stochastic process given by

    \[V_t=e^{-kt}v+\sigma e^{-kt}\int _0^t e^{ku}\,dB_u\]

    where \(k,\sigma ,v>0\) are deterministic constants. Find the mean and variance of \(V_t\).

  • 12.7 Suppose that \(\mu >0\) is a deterministic constant and that \(\sigma _t\in \mc {H}^2\). Let \(X_t\) be given by

    \[X_t=\int _0^t\mu \,du+\int _0^t\sigma _u\,dB_u.\]

    Show that \(X_t\) is a submartingale.

  • 12.8

    • (a) Give an example of a stochastic process \(F_t\) such that \(\int _0^t \E [F_s]\,ds=\E [\int _0^t F_s\,dB_s]\).

    • (b) Give an example of a stochastic process \(F_t\) such that \(\int _0^t \E [F_s]\,ds\neq \E [\int _0^t F_s\,dB_s]\).

Challenge Questions
  • 12.9

    • (a) Let \(X\) and \(Y\) be random variables in \(L^2\). Show that

      \[2|\E [XY]|\leq \E [X^2]+\E [Y^2]\]

    • (b) Show that \(\mc {H}^2\) is a real vector space.

  • 12.10 \(\offsyl \) Prove Lemma 12.3.3.