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Tutorial Week 2

Math 5965 Discrete Time Financial Modelling

T1 2023

1. Find the Lebesgue measure µ0 of µ0 ([1/2, 2/3]), µ0 ({1/n : n = 1, 2, . . . }), µ0 (N), where N is set of natural numbers.

2. Let Ω = {1, 2, 3, 4, 5, 6} with uniform probability. Show that if A ⊂ Ω and B ⊂ Ω are independent and A has four elements, then B must have 0, 3, or 6 elements.

3. Let Ω = [0, 1] with Borel sets and Lebesgue measure. Find P(X ∈ [0, 1/2)) for X(ω) = ω 2 .

4. Show if X is a constant function, then it is a random variable with respect to any σ-algebra.

5. Let Ω = {1, 2, 3, 4} and F = {∅ , Ω , {1}, {2, 3, 4}}. Is X(ω) = 1 + ω a random variable with respect to the σ algebra F?  If not, give an example of a non-constant function which is.

6.  (Shreve, Exercise 2.4)  “Toss a coin repeatedly.  Assume the probability of head on each toss is , as is the probability of tail.  Let Xj   = 1 if the jth toss results in a head and Xj   = −1 if the jth toss results in a tail.  Consider the stochastic process M0 ,M1 ,M2 , . . . defined by M0  = 0 and

n

j=1

n ≥ 1.

This is called a symmetric random walk, with each head, it steps up one and with each tail, it steps down one.

(a) Show that M0 ,M1 ,M2 , . . . is a martingale

(b) Let σ be a positive constant and, for n ≥ 0, defined

Sn  = eσ Mn  ( )n .

Show that S0 ,S1 ,S2 , . . .  is a martingale.  Note that even though the symmetric random walk Mn   has no tendency to grow, the geometric  symmetric  random walk eσ Mn   does have a tendency to grow. This is result of putting a martingale into the (convex) exponential function (recall a convex function of a martingale is a submartingale).  In order to again have a martingale we must discount the geometric symmetric random walk, using the term  as the discount rate. This term is strictly less than one unless σ = 0”.