Finite Difference Schemes

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Finite Difference Schemes Dr. DAI Min

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Finite Difference Schemes. Dr. DAI Min. Type of finite difference scheme. Explicit scheme Advantage There is no need to solve a system of algebraic equations Easy for programming Disadvantage: conditionally convergent Implicit scheme Fully implicit scheme: first order accuracy - PowerPoint PPT Presentation

Transcript of Finite Difference Schemes

Page 1: Finite Difference Schemes

Finite Difference Schemes

Dr. DAI Min

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Type of finite difference scheme

• Explicit scheme– Advantage

• There is no need to solve a system of algebraic equations• Easy for programming

– Disadvantage: conditionally convergent

• Implicit scheme– Fully implicit scheme: first order accuracy– Crank-Nicolson scheme: second order accuracy

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Explicit scheme• European put option:

• Lattice:

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Explicit scheme (continued)

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Explicit scheme (continued)

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Explicit scheme (continued)

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Explicit scheme (continued)

• Monotone scheme

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Explicit scheme for a transformed equation

• Transformed Black-Scholes equation:

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Explicit scheme for a transformed equation

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Explicit scheme for a transformed equation (continued)

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Explicit scheme for a transformed equation (continued)

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Equivalence of explicit scheme and BTM

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Equivalence of explicit scheme and BTM (continued)

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Why use implicit scheme?

• Explicit scheme is conditionally convergent

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Fully implicit scheme

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Fully implicit scheme (continued)

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Matrix form of an explicit scheme

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Monotonicity of the fully implicit scheme

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Second-order scheme: Crank-Nicolson scheme

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Crank-Nicolson scheme in matrix form

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Convergence of Crank-Nicolson scheme

• The C-N scheme is not monotone unless t/h2 is small enough. • Monotonicity is sufficient but not necessary• The unconditional convergence of the C-N scheme (for linear

equation) can be proved using another criterion (see Thomas (1995)).

• Due to lack of monotonicity, the C-N scheme is not as stable/robust as the fully implicit scheme when dealing with tough problems.

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Iterative methods for solving a linear system

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Linearization for nonlinear problems

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Newton iteration

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Handling non-smooth terminal conditions

• C-N scheme has a better accuracy but is unstable when the terminal condition is non-smooth.

• To cure the problem– Rannacher smoothing– Smoothing the terminal value condition

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Upwind (upstream) treatment

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An example for upwind scheme in finance

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Artificial boundary conditions

• Solution domain is often unbounded, but implicit schemes should be restricted to a bounded domain– Truncated domain– Change of variables

• Artificial boundary conditions should be given based on– Properties of solution, and/or– PDE with upwind scheme

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Examples

• European call options

• CIR model for zero coupon bond

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CIR models (continued)

• Method 1: confined to [0,M]

• Method 2: a transformation

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Test of convergence order

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Test of convergence order (alternative method)

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An example: given benchmark values

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An example: no benchmark values