Misplaced Pages

2-EPT probability density function

Article snapshot taken from[REDACTED] with creative commons attribution-sharealike license. Give it a read and then ask your questions in the chat. We can research this topic together.
2-EPT Density Function
Parameters

( A N , b N , c N , A P , b P , c P ) {\displaystyle ({\textbf {A}}_{N},{\textbf {b}}_{N},{\textbf {c}}_{N},{\textbf {A}}_{P},{\textbf {b}}_{P},{\textbf {c}}_{P})}

R e ( σ ( A P ) ) < 0 {\displaystyle {\mathfrak {Re}}(\sigma ({\textbf {A}}_{P}))<0}

R e ( σ ( A N ) ) > 0 {\displaystyle {\mathfrak {Re}}(\sigma ({\textbf {A}}_{N}))>0}
Support x ( ; + ) {\displaystyle x\in (-\infty ;+\infty )\!}
PDF f ( x ) = { c N e A N x b N if  x < 0 c P e A P x b P if  x 0 {\displaystyle f(x)=\left\{{\begin{matrix}{\textbf {c}}_{N}e^{{\textbf {A}}_{N}x}{\textbf {b}}_{N}&{\text{if }}x<0\\{\textbf {c}}_{P}e^{{\textbf {A}}_{P}x}{\textbf {b}}_{P}&{\text{if }}x\geq 0\end{matrix}}\right.}
CDF F ( x ) = { c N A N 1 e A N x b N if  x < 0 1 + c P A P 1 e A P x b P if  x 0 {\displaystyle F(x)=\left\{{\begin{matrix}{\textbf {c}}_{N}{\textbf {A}}_{N}^{-1}e^{{\textbf {A}}_{N}x}{\textbf {b}}_{N}&{\text{if }}x<0\\1+{\textbf {c}}_{P}{\textbf {A}}_{P}^{-1}e^{{\textbf {A}}_{P}x}{\textbf {b}}_{P}&{\text{if }}x\geq 0\end{matrix}}\right.}
Mean c N ( A N ) 2 b N + c P ( A P ) 2 b P {\displaystyle -{\textbf {c}}_{N}(-{\textbf {A}}_{N})^{-2}{\textbf {b}}_{N}+{\textbf {c}}_{P}(-{\textbf {A}}_{P})^{-2}{\textbf {b}}_{P}}
CF c N ( I i u A N ) 1 b N + c P ( I i u A P ) 1 b P {\displaystyle -{\textbf {c}}_{N}(Iiu-{\textbf {A}}_{N})^{-1}{\textbf {b}}_{N}+{\textbf {c}}_{P}(Iiu-{\textbf {A}}_{P})^{-1}{\textbf {b}}_{P}}

In probability theory, a 2-EPT probability density function is a class of probability density functions on the real line. The class contains the density functions of all distributions that have characteristic functions that are strictly proper rational functions (i.e., the degree of the numerator is strictly less than the degree of the denominator).

Definition

A 2-EPT probability density function is a probability density function on R {\displaystyle \mathbb {R} } with a strictly proper rational characteristic function. On either [ 0 , + ) {\displaystyle [0,+\infty )} or ( , 0 ) {\displaystyle (-\infty ,0)} these probability density functions are exponential-polynomial-trigonometric (EPT) functions.

Any EPT density function on ( , 0 ) {\displaystyle (-\infty ,0)} can be represented as

f ( x ) = c N e A N x b N , {\displaystyle f(x)={\textbf {c}}_{N}e^{{\textbf {A}}_{N}x}{\textbf {b}}_{N},}

where e represents a matrix exponential, ( A N , A P ) {\displaystyle ({\textbf {A}}_{N},{\textbf {A}}_{P})} are square matrices, ( b N , b P ) {\displaystyle ({\textbf {b}}_{N},{\textbf {b}}_{P})} are column vectors and ( c N , c P ) {\displaystyle ({\textbf {c}}_{N},{\textbf {c}}_{P})} are row vectors. Similarly the EPT density function on [ 0 , ) {\displaystyle [0,-\infty )} is expressed as

f ( x ) = c P e A P x b P . {\displaystyle f(x)={\textbf {c}}_{P}e^{{\textbf {A}}_{P}x}{\textbf {b}}_{P}.}

The parameterization ( A N , b N , c N , A P , b P , c P ) {\displaystyle ({\textbf {A}}_{N},{\textbf {b}}_{N},{\textbf {c}}_{N},{\textbf {A}}_{P},{\textbf {b}}_{P},{\textbf {c}}_{P})} is the minimal realization of the 2-EPT function.

The general class of probability measures on R {\displaystyle \mathbb {R} } with (proper) rational characteristic functions are densities corresponding to mixtures of the pointmass at zero ("delta distribution") and 2-EPT densities. Unlike phase-type and matrix geometric distributions, the 2-EPT probability density functions are defined on the whole real line. It has been shown that the class of 2-EPT densities is closed under many operations and using minimal realizations these calculations have been illustrated for the two-sided framework in Sexton and Hanzon. The most involved operation is the convolution of 2-EPT densities using state space techniques. Much of the work centers on the ability to decompose the rational characteristic function into the sum of two rational functions with poles located in either the open left or open right half plane. The variance-gamma distribution density has been shown to be a 2-EPT density under a parameter restriction.

Notes

  1. Kailath, T. (1980) Linear Systems, Prentice Hall, 1980
  2. Neuts, M. "Probability Distributions of Phase Type", Liber Amicorum Prof. Emeritus H. Florin pages 173-206, Department of Mathematics, University of Louvain, Belgium 1975
  3. Sexton, C. and Hanzon,B.,"State Space Calculations for two-sided EPT Densities with Financial Modelling Applications", www.2-ept.com
  4. Madan, D., Carr, P., Chang, E. (1998) "The Variance Gamma Process and Option Pricing", European Finance Review 2: 79–105

External links

Probability distributions (list)
Discrete
univariate
with finite
support
with infinite
support
Continuous
univariate
supported on a
bounded interval
supported on a
semi-infinite
interval
supported
on the whole
real line
with support
whose type varies
Mixed
univariate
continuous-
discrete
Multivariate
(joint)
Directional
Univariate (circular) directional
Circular uniform
Univariate von Mises
Wrapped normal
Wrapped Cauchy
Wrapped exponential
Wrapped asymmetric Laplace
Wrapped Lévy
Bivariate (spherical)
Kent
Bivariate (toroidal)
Bivariate von Mises
Multivariate
von Mises–Fisher
Bingham
Degenerate
and singular
Degenerate
Dirac delta function
Singular
Cantor
Families
Category:
2-EPT probability density function Add topic