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Partial Differential Equations : Wiener Process

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Please see the attached file for the fully formatted problems.
1) Suppose: dS = a(S,t)dt + b(S,t)dX,

where dX is a Wiener process. Let f be a function of S and t.
Show that:
(see the attached file for equations)
2) Suppose that S satisfies

(see the attached file for equations)

where u >=0, signa> 0, and dX is a Wiener process. Let

Xi = S/(S + Pm)

where Pm is a positive constant and the range of &#958; is [0,1), if 0 &#8804; S < &#8734;. The stochastic differential equation for &#958; is in the form:

d(Xi)= a(Xi)dt + b(Xi)dX.

Find the concrete expressions for a(Xi) and b(Xi) by Ito's lemma and show:

{a(0) = 0, and {a(1) = 0,
{b(0) = 0, and {b(1) = 0.

Finite Difference Methods in Financial Engineering: A Partial Differential Equation Approach by Duffy. See attached file for full problem description.

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Partial Differential Equations and Wiener Processes are investigated. The solution is detailed and well presented. The response received a rating of "5/5" from the student who originally posted the question.

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Financial Partial Differential Equations : Black-Scholes and Ito's Lemma

Please see the attached file for the fully formatted problems.

If and we let , then , where and . Define . Suppose that the stock pays dividends continuously:

? D(S,t) => dividend
? If dividend is paid continuosly:
* D(S,t)dt = D0Sdt
* D0 is a constant dividend rate

Derive the equation for directly by using Itô's lemma.
(Hint: Take as the portfolio during the derivation)

Notes: Derivation of B-S Equation:

V denotes the value of an option that depends on the value of the underlying asset S and time t, ie, V = V(S,t). In a time step dt, the underlying asset pays out a dividend SD0dt, where D0 is a constant known as the dividend yield. S satisfies According to Itô's lemma, the random walk followed by V is given by:

. *

V has at least one t derivative and two S derivatives. Construct a portfolio consisting of one option and a number -&#916; of the underlying asset. This number is not yet known. The value of this portfolio is:
. **

Because the portfolio contains one option and a number -&#916; of the underlying asset, and the owner of the portfolio receives SD0dt for every asset held, the earnings for the owner of the portfolio during the time step dt is:


Using *, it is apparent that &#928; follows the random walk:

The random component in this random walk can be eliminated by choosing:

. ***

This results in a portfolio whose increment is wholly deterministic:


Because the return for any risk-free portfolio should be r,

. ****

Substituting ** and *** into **** and dividing by dt:


This is the Black-Scholes partial differential equation. The key idea of deriving this equation is to eliminate the uncertainty or the risk. d&#928; is not a differential in the usual sense. It is the earning of the holder of the portfolio during the time step dt. Therefore, appears. In the derivation, in order to eliminate any small risk, &#916; is chosen before an uncertainty appears and does not depend on the coming risk. Therefore, no differential of &#916; is needed.

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