AMS 513 Financial Derivatives and Stochastic Calculus Practice Final Exam Spring 2021
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Practice Final Exam Spring 2021
AMS 513
Financial Derivatives and Stochastic Calculus
Problem 1. (20p) (Brownian Motion and Time Inversion)
Let (Ω , F, P) be a probability space and let Bt , for s > 0, be a Brownian motion.
(i) (5p+5p=10p)
Show that
CОu(Bs , Bt ) = min(s, r),
and that
CОoo(Bs , Bt ) = ì .
(Hint: Use the properties in the definition of the Brownian motion.)
(ii) (10p)
Show that the following process defined via time inversion
Wt = │0
『 sB
if s = 0
if s 0
is also a Brownian motion.
(Hint: Show the three properties from one of the definitions of the Brownian motion, use the first result from (i) above.)
Answer:
Problem 2. (20p) (Maximum of Brownian Motion)
Let (Ω , F, P) be a probability space and define
MT = max Bt
t←|d,T当
where Bt , for s > 0, is a Brownian motion. Then for all T > 0, show using the reflection principle, that
(i) (10p)
Φ( ¥ ¥ ¥『 0 |
a > 0, z s a a > 0, z > a a s 0 |
where Φ is the standard normal cdf;
(ii) (10p) and that the joint probability density function of (MT , BT ) is
/4/a]x) ] 甘(|) 4 甘〉)甘 a > 0, z s a
『 0 otherwise
Hint: Reflection Principle
Let ra = inf {s > 0 : Bt = a}, then
P(ra s T, BT s z) = P(ra s T, BT > 2a - z)
Answer:
(1)
(2)
Problem 3. (20p) (Ito’s Integrals)
Let (Ω , F, P) be a probability space and let {Wt : s > 0} be a standard Wiener process.
(i) (10p) Compute the integral and explain what is the distribution of it
(dt dWs .
Hint: Use the definition of Ito’s integral.
(ii) (10p) Using integration by parts, show that
(dt Ws dr = (dt (s - r)dWs
and prove that
E ┌(dt Ws dr┐ = 0 and E ┌ ╱(dt Ws dr、/ ┐ = .
Hint: The integration by parts formula is given by
( t ╱ 、dr = tu - ( u ╱ 、dr.
Answer:
Problem 4 (20p) (Digital Option - Probabilistic Approach)
Let {Wt : s > 0} be a P-standard Wiener process on the probability space (Ω , F, P) and let
the stock price st follow a GBM with the following SDE
dst = st uds + st adWt ,
where u is the drift parameter, a > 0 is the volatility parameter, and let o > 0 denote the risk-free interest rate.
A digital (or cash-or-nothing) call option is a contract that pays $1 at expiry time T if the spot price sT > K and nothing if sT s K .
(i) (7p) Find an equivalent martingale measure Q under which the discounted stock price e]rt st is a martingale (discuss why this is a martingale).
(ii) (7p) By denoting Cd (st , s; K, T) as the digital call and put option prices, at time s,
for s < T show that
Cd (st , s; K, T) = e]r4T ]t)Q (sT > K | Ft )
(iii) (6p) Using Ito lemma find the distribution of sT given Ft under Q, and show, using
the risk-neutral valuation approach from (i) and (ii) above, that
Cd (st , s; K, T) = e]r4T ]t)Φ(d] )
where
d] = and Φ(z) = (]x_ e] 甘(|)u甘 dt.
Answer:
Problem 5. (20p) (Geometric Mean-Reverting Process)
Let (Ω , F, P) be a probability space and let {Wt : s > 0} be a standard Wiener process. Suppose Xt follows the geometric mean-reverting process with SDE
dXt = s(θ - log Xt )Xt ds + aXt dWt , Xd > 0,
where s, θ, and a are constants.
(i) (7p) By applying Taylor’s formula to yt = log Xt , show that the diffusion process can be reduced to an Ornstein-Uhlenbeck process of the form
dyt = ┌ s(θ - yt ) - a/ ┐ ds + adWt .
(ii) (7p) Show also that for s < T,
log XT = (log Xt )e]κ4T ]t) + (θ - )(1 - eκ4T ]t)) + (t T aeκ4T ]s)dWs .
(iii) (6p) Using the properties of stochastic integrals on the above expression, find the
mean and variance of log XT , given log Xt = log z.
Hints:
(i) Using Taylor’s formula we can expand yt = log Xt as
d(log Xt ) = dXt - (dXt )/ + . . .
(ii) Apply Ito’s formula to Zt = eκt yt .
(iii) Use Ito’s isometry
E ┌ ╱(dt f (Ws , r)dWs、/ ┐ = E ┌(dt f (Ws , r)/ dr┐ .
2022-05-11