MTH5510: QRM - Exercises Set 2
Due date: August 12, 2024;12:00pm;
Analysis the output of the
Matlab code is mandatory. I am not interested just to the Matlab code.
Hand in stapled hardcopy
at the beginning of the tutorial session
Note: You might want to use Matlab for this exercise;
adequately report and comment on your
results (For a quick introduction to Matlab visit
http://www.mathworks.com/access/helpdesk/
help/pdf_doc/matlab/getstart.pdf)
Exercise I: This
question deals with a portfolio of five stocks. At time t, the values of the stocks
are S1,t =
100, S2,t = 50, S3,t = 25, S4,t = 75, and S5,t = 150. The portfolio consists of 1 share
of S1, 3
shares of S2, 5 shares of S3, 2 shares of S4, and 4 shares of S5. These risk factors
are
logarithmic prices and the factor changes have mean zero and standard deviations 10?3, 2 ·
10?3,
3 · 10?3, 1.5 · 10?3, and 2.5 · 10?3, respectively. The risk factors are independent.
1.
Compute VaRα, VaR
mean
α , and ESα using Monte Carlo with 10,000 simulations. Do this for
α
= {0.90, 0.91, . . . , 0.99}. Also use the following distributions for the risk factor changes:
For each i ∈ {1, 2, 3, 4, 5}, Xi,t+δ ~ t(3, μ, σ) for appropriate values of μ and σ
For each i ∈
{1, 2, 3, 4, 5}, Xi,t+δ ~ t(10, μ, σ) for appropriate values of μ and σ
For each i ∈ {1, 2, 3, 4,
5}, Xi,t+δ ~ t(50, μ, σ) for appropriate values of μ and σ
For each i ∈ {1, 2, 3, 4, 5}, Xi,t+δ
~ N (μ, σ2)
Plot the results.
2. Comment on the following:
The value of VaRα compared to
VaRmeanα
The value of VaRα and ESα as compared between the four distributions. Are the
results
what you expected?
Exercise II: This question deals with delta hedged call option. The
following are the Black-
Scholes parameters for a European call option at time t = 0:
T =
0.5
rt = 0.05
σt = 0.2
St = 100
K = 100.
1
The portfolio consists of long position
on the call option, and the corresponding position in the
stock which makes the portfolio delta
neutral. Let ? = 1day, Z1 = log(S), and Z2 = σ (r
will be considered in this problem). The risk
factor changes are normally distributed with mean
zero. Their standard deviations over one day
are 10?3 and 10?4 and their correlation is ?0.5.
(a) Compute V aRα, V aR
mean
α , and ESα
for α = 0.95 and α = 0.99 using the following
methods:
Monte Carlo full revaluation with
10,000 simulations
Monte Carlo on the linearized loss with 10,000 simulations
Variance-covariance method
Do not neglect the time derivative in any linearizion in this
question.
Exercise III: Let L have the Student t distribution with ν degree of freedom. Derive
the
formula
ESα(L) =
(
gν(t
?1
ν (α))
1? α
)(
ν + (t?1ν (α))2
ν ?
1
)
.
You will need to look up the probability density function of the distribution at
hand.
2
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