Chapter 7: Problem 9
The function \(c(x, \tau)\) satisfies the following problem in the region
\(0
Short Answer
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Key Concepts
These are the key concepts you need to understand to accurately answer the question.
Chapter 7: Problem 9
The function \(c(x, \tau)\) satisfies the following problem in the region
\(0
These are the key concepts you need to understand to accurately answer the question.
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Get started for freeA space of functions \(\mathcal{K}\) is said to be convex if, whenever \(u \in \mathcal{K}\) and \(v \in \mathcal{K},(1-\lambda) u+\lambda v \in \mathcal{K}\) for all \(0 \leq \lambda \leq 1 .\) Show that the space \(\mathcal{K}\) of all piecewise continuously differentiable functions \(v(x)(-1 \leq x \leq 1)\) satisfying \(v \geq f\) and \(v(\pm 1)=0\) is convex. (These functions are called test functions.) The obstacle problem may also be formulated as: find the function \(u\) that minimises the energy $$E[v]=\int_{-1}^{1} \frac{1}{2}\left(v^{\prime}\right)^{2} d x$$ over all \(v \in \mathcal{K}\). (This is the usual energy minimisation but with the constraint incorporated.) If \(u\) is the minimiser, and \(v\) is any test function, use the fact that \(E[(1-\lambda) u+\lambda v]-E[u] \geq 0\) for all \(\lambda\) to show that $$\int_{-1}^{1} u^{\prime}(v-u)^{\prime} d x \geq 0$$ This is the variational inequality for the obstacle problem.
The function \(u(x, \tau)\) satisfies the following free boundary problem with
free boundary \(x=x_{f}(\tau)\), where \(x_{f}(0)=0\) :
$$\begin{gathered}
\frac{\partial u}{\partial \tau}=\frac{\partial^{2} u}{\partial x^{2}}, \quad
0
Consider American vanilla call and put options, with prices \(C\) and \(P\). Derive the following inequalities (the second part of the last inequality is the version of put-call parity result appropriate for American options): $$\begin{gathered} P \geq \max (E-S, 0), \quad C \geq S-E e^{-r(T-t)} \\ S-E \leq C-P \leq S-E e^{-r(T-t)} \end{gathered}$$ Also show that, without dividends, it is never optimal to exercise an American call option.
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