Paper 1, Section II, 30K

Stochastic Financial Models
Part II, 2021

(a) What does it mean to say that a stochastic process (Xn)n0\left(X_{n}\right)_{n \geqslant 0} is a martingale with respect to a filtration (Fn)n0\left(\mathcal{F}_{n}\right)_{n \geqslant 0} ?

(b) Let (Xn)n0\left(X_{n}\right)_{n \geqslant 0} be a martingale, and let ξn=XnXn1\xi_{n}=X_{n}-X_{n-1} for n1n \geqslant 1. Suppose ξn\xi_{n} takes values in the set {1,+1}\{-1,+1\} almost surely for all n1n \geqslant 1. Show that (Xn)n0\left(X_{n}\right)_{n \geqslant 0} is a simple symmetric random walk, i.e. that the sequence (ξn)n1\left(\xi_{n}\right)_{n \geqslant 1} is IID\operatorname{IID} with P(ξ1=1)=1/2=\mathbb{P}\left(\xi_{1}=1\right)=1 / 2= P(ξ1=1).\mathbb{P}\left(\xi_{1}=-1\right) .

(c) Let (Xn)n0\left(X_{n}\right)_{n \geqslant 0} be a martingale and let the bounded process (Hn)n1\left(H_{n}\right)_{n \geqslant 1} be previsible.

Let X^0=0\hat{X}_{0}=0 and

X^n=k=1nHk(XkXk1) for n1\hat{X}_{n}=\sum_{k=1}^{n} H_{k}\left(X_{k}-X_{k-1}\right) \text { for } n \geqslant 1

Show that (X^n)n0\left(\hat{X}_{n}\right)_{n \geqslant 0} is a martingale.

(d) Let (Xn)n0\left(X_{n}\right)_{n \geqslant 0} be a simple symmetric random walk with X0=0X_{0}=0, and let

Ta=inf{n0:Xn=a}T_{a}=\inf \left\{n \geqslant 0: X_{n}=a\right\}

where aa is a positive integer. Let

X^n={Xn if nTa2aXn if n>Ta\hat{X}_{n}= \begin{cases}X_{n} & \text { if } n \leqslant T_{a} \\ 2 a-X_{n} & \text { if } n>T_{a}\end{cases}

Show that (X^n)n0\left(\hat{X}_{n}\right)_{n \geqslant 0} is a simple symmetric random walk.

(e) Let (Xn)n0\left(X_{n}\right)_{n \geqslant 0} be a simple symmetric random walk with X0=0X_{0}=0, and let Mn=max0knXkM_{n}=\max _{0 \leqslant k \leqslant n} X_{k}. Compute P(Mn=a)\mathbb{P}\left(M_{n}=a\right) for a positive integer aa.