Is Separation of Variables the Key to Solving Linear PDEs in Finance?

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Discussion Overview

The discussion centers on the applicability of separation of variables as a method for solving linear partial differential equations (PDEs) in finance, particularly in relation to the Black-Scholes equation. Participants explore the theoretical underpinnings of this method and its implications for various types of linear PDEs, including those encountered in physics.

Discussion Character

  • Exploratory, Technical explanation, Debate/contested

Main Points Raised

  • One participant questions how separation of variables can be reliably applied to linear PDEs, noting that it seems to identify a specific form of the solution and referencing the wave equation as an example.
  • Another participant suggests a connection to a previous discussion, introducing a mathematical relationship involving integrals and functions, although the relevance to the original question about PDEs is unclear.
  • A third participant clarifies that the focus is on partial differential equations, specifically mentioning Laplace's equation as an example of a linear equation.
  • A later reply emphasizes that while PDEs have families of solutions, it is the boundary and initial conditions that determine the specific solution, rather than the coordinate system used.

Areas of Agreement / Disagreement

Participants express differing views on the role of boundary conditions in determining solutions to PDEs, indicating that there is no consensus on the effectiveness of separation of variables in the context of finance-related PDEs.

Contextual Notes

The discussion highlights the dependence on boundary and initial conditions for determining specific solutions to PDEs, as well as the potential ambiguity in applying separation of variables across different contexts.

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this may seem like a simple question but how does one know that separation of variables for solving linear PDE's will work. What i mean is that it seems to pick out a form of the solution to a given problem (I have heard that linear PDE's have an infinite number of functions of a particular form, e.g. for the wave equation the solution is of the form f(x-vt) + g(x+vt)). I can understand that for problems in e&m the separation of variables technique picks out a particular form (like for a cartesian coordinates for laplace's equation for a box, the solutions come out to be sines and cosines), but what about linear PDE's in finance (like the Black scholes equation). Thanks in advance to anyone who can clarify this.
 
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Didn't we just have this? Or was that on another forum?

Do you agree that if F(x)= G(x), then \int F(x)dx= \int G(x)dx?
(If not I have no idea what to say!)

If dy/dx= f(x)g(y) then (1/g(y))dy/dx= f(x). Since y is itself a function of x, this is the "F(x)= G(x)" above.

Then \int [(1/g(y)) dy/dx]dx= \int f(x)dx. And, of course, (dy/dx)dx= dy so this is \int (1/g(y))dy= \int f(x)dx.
 
I was actually talking about partial differential equations like Laplace's equation or other such linear equations
 
Yes PDE's have families of solutions, it's the boundary and initial conditions that let you pin down the actual solution. It doesn't have anything to do with the coordinate system. You get sines and cosines in your example because of nice boundary conditions.
 

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