Numerical Methods in Computational Finance. Daniel J. Duffy

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Numerical Methods in Computational Finance - Daniel J. Duffy


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      In this chapter we introduce a class of differential equations in which the highest order derivative is one. Furthermore, these equations have a single independent variable (which in nearly all applications plays the role of time). In short, these are termed ordinary differential equations (ODEs) precisely because of the dependence on a single variable.

      ODEs crop up in many application areas, such as mechanics, biology, engineering, dynamical systems, economics and finance, to name just a few. It is for this reason that we devote two dedicated chapters to them.

      The following topics are discussed in this chapter:

       Motivational examples of ODEs

       Qualitative properties of ODEs

       Common finite difference schemes for initial value problems for ODEs

       Some theoretical foundations.

      In Chapter 3 we continue with our discussion of ODEs, including code examples in C++ and Python.

      Consider a bounded interval left-bracket 0 comma upper T right-bracket where upper T greater-than 0. This interval could represent time or distance, for example. In most cases we shall view this interval as representing time values. In the interval we define the initial value problem (IVP) for an ODE:

      where upper L is a first-order linear differential operator involving the derivative with respect to the time variable and a equals a left-parenthesis t right-parenthesis is a strictly positive function in left-bracket 0 comma upper T right-bracket. The term f left-parenthesis t right-parenthesis is called the inhomogeneous forcing term, and it is independent of u. Finally, the solution to the IVP must be specified at t equals 0; this is the so-called initial condition.

      (See Hochstadt (1964), where the so-called integration factor is used to determine a solution.)

      A special case of (2.1) is when the right-hand term f left-parenthesis t right-parenthesis is zero and a left-parenthesis t right-parenthesis is constant; in this case the solution becomes a simple exponential term without any integrals, and this will be used later when we examine difference schemes to determine their feasibility. In particular, a scheme that behaves badly for the above special case will be unsuitable for more general or more complex problems unless some modifications are introduced.

      2.2.1 Qualitative Properties of the Solution and Maximum Principle

      Before we introduce difference schemes for (2.1), we discuss a number of results that allow us to describe how the solution u behaves. First, we wish to conclude that if the initial value upper A and inhomogeneous term f left-parenthesis t right-parenthesis are positive, then the solution u left-parenthesis t right-parenthesis should also be positive for any value t in left-bracket 0 comma upper T right-bracket. This so-called positivity or monotonicity result should be reflected in our difference schemes (not all schemes possess this property). Second, we wish to know how the solution u left-parenthesis t right-parenthesis grows or decreases as a function of time. The following two results deal with these issues.

      Lemma 2.1 (Positivity). Let the operator upper L be defined in Equation (2.1), and let w be a well-behaved function satisfying the inequalities:

StartLayout 1st Row 1st Column Blank 2nd Column upper L w left-parenthesis t right-parenthesis greater-than-or-equal-to 0 for-all t element-of left-bracket 0 comma upper T right-bracket 2nd Row 1st Column Blank 2nd Column w left-parenthesis 0 right-parenthesis greater-than-or-equal-to 0 period EndLayout w left-parenthesis t right-parenthesis greater-than-or-equal-to 0 for-all <hr><noindex><a href=Скачать книгу