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a ) . Develop Matlab code for pricing European options under a Black Scholes model d S t S t = r d t +

a). Develop Matlab code for pricing European options under a Black Scholes model
dStSt=rdt+dZt
using a finite difference method as discussed in class. Use forward/backward/central differ-
encing as appropriate to ensure a positive coefficient discretization. The code should be able
to use fully implicit, and Crank-Nicolson method.
You will have to solve a tridiagonal linear system. Use lu Matlab function to solve linear
systems. Avoid unnecessary LU factorization computation.
b). Solve for a European put option, using the data given in the Table 1,(with fully implicit,
and Crank-Nicolson method ) and compare with the exact solution using blsprice in Matlab.
Use constant timestep sizes.
c). Show a convergence table, with a series of grids. Show the option value at t=0,S=100.
Begin with a timestep of =T25, where is the time to maturity, i.e.,=T-t, and
the grid
S=[0:0.1**K:0.4**K,dots
0.45**K:0.05**K:0.8**K,dots
0.82**K:0.02**K:0.9**K,dots
0.91**K:0.01**K:1.1**K,dots
1.12**K:0.02**K:1.2**K,dots
1.25**K:.05**K:1.6**K,dots
1.7**K:0.1**K:2**K,dots
2.2**K,2.4**K,2.8**K,dots
3.6**K,5**K,7.5**K,10**K];
Table 1: Data for Put Example
where K is the strike, and we are interested in the solution near S=K.
Note: to carry out a convergence study, you should solve the pricing problem on a sequence of
grids. Each grid has twice as many intervals as the previous grid (new nodes inserted halfway
between the coarse grid nodes) and the timestep size is halved.
Assume that
Error =O(()2,(S)2);S=maxi(Si+1-Si)
Let
h=C1*S
h=C2*
Suppose we label each computation in the above sequence by a set of h values. Then the
solution on each grid (at a given point) has the form
V(h)=Vexact+A*h2
V(h2)=Vexact+A*(h2)2
V(h4)=Vexact+A*(h4)2
where we have assumed that the mesh size and timestep are small enough that the coefficient
A in equation (2) is approximately constant. Now, equation (2) implies that
V(h)-V(h2)V(h2)-V(h4)4
Check the theory by examining the rate of convergence of your pricer.
Carry out the above tests using fully implicit, and Crank Nicolson method. Show a conver-
gence table for each test.
d). Show plots of the option value for the range S=[50,150], for your solution on the finest
grid for CN method.
Submit your matlab code.
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