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Numerical Methods in Computational Finance. Daniel J. Duffy
Читать онлайн.Название Numerical Methods in Computational Finance
Год выпуска 0
isbn 9781119719724
Автор произведения Daniel J. Duffy
Жанр Ценные бумаги, инвестиции
Издательство John Wiley & Sons Limited
2.3.1 Common Schemes
We now introduce a number of important and useful difference schemes that approximate the solution of Equation (2.1). These schemes will pop up all over the place in later chapters. Understanding how the schemes work in a simpler context will help you appreciate them when we tackle partial differential equations based on the Black–Scholes model. They also help in our understanding of notation, jargon, and syntax.
The main schemes are:
Explicit Euler
Implicit Euler
Crank–Nicolson (or Box scheme)
The trapezoidal method.
The explicit Euler method is given by:
whereas the implicit Euler method is given by:
Notice the difference: in Equation (2.10) the solution at level
The next scheme is called the Crank–Nicolson or box scheme, and it can be seen as an average of explicit and implicit Euler schemes. It is given as (see notation in Equation (2.7)):
It is useful to know that the three schemes can be merged into one generic scheme as it were by introducing a parameter
and the special cases are given by:
(2.14)
The solution of Equation (2.13) is given by:
(2.15)
This equation is useful because it can be mapped to C++ code and will be used by other schemes by defining the appropriate value of the parameter
Finally, the trapezoidal method is similar to Crank–Nicolson, but it takes a slightly different averaging mechanism:
(2.16)
2.3.2 Discrete Maximum Principle
Having developed some difference schemes, we would like to have a way of determining if the discrete solution is a good approximation to the exact solution in some sense. Although we do not deal with this issue in great detail, we do look at stability and convergence issues.
Definition 2.1 The one-step difference scheme
(2.17)