gaussHermiteMesh: Generates grid reprensentation of a distribution according to...
In R-Finance/Meucci: Collection of functionality ported from the MATLAB code of Attilio Meucci.
Description
Usage
Arguments
Value
Author(s)
References
Description
Grid representation by this method is an alternative to
representing distribution of the market, such as
importance sampling or stratified sampling.However, these
techniques focus on sub-domains of the distribution, and
thus, in order to apply such methods, we must forego the
full flexibility on the specification of the views. A
different approach, which preserves the generality of the
views specification, consists in selecting the scenarios
x_j deterministically as a grid and then associate with
each of them the suitable probability p_j ( integrated
over I_j ). The the generic interval _j contains the j-th
point of the grid. Once the grid is defined, the entropy
optimization can be applied to replace p_j with the new
posterior probabilities to reflect the views. We generate
the grid here using the Gauss-Hermite quadrature method.
Usage
1
Arguments
J
a numeric containing the number of points on the
grid
Value
x a matrix containing the zeroes of Hermite polynomials
as a function of polynomial degree
Author(s)
Ram Ahluwalia ram@wingedfootcapital.com
References
A. Meucci - "Fully Flexible Extreme Views".
http://ssrn.com/abstract=1542083
R-Finance/Meucci documentation built on May 8, 2019, 3:52 a.m.
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Description Usage Arguments Value Author(s) References
Description
Grid representation by this method is an alternative to representing distribution of the market, such as importance sampling or stratified sampling.However, these techniques focus on sub-domains of the distribution, and thus, in order to apply such methods, we must forego the full flexibility on the specification of the views. A different approach, which preserves the generality of the views specification, consists in selecting the scenarios x_j deterministically as a grid and then associate with each of them the suitable probability p_j ( integrated over I_j ). The the generic interval _j contains the j-th point of the grid. Once the grid is defined, the entropy optimization can be applied to replace p_j with the new posterior probabilities to reflect the views. We generate the grid here using the Gauss-Hermite quadrature method.
Usage
1 |
Arguments
J |
a numeric containing the number of points on the grid |
Value
x a matrix containing the zeroes of Hermite polynomials as a function of polynomial degree
Author(s)
Ram Ahluwalia ram@wingedfootcapital.com
References
A. Meucci - "Fully Flexible Extreme Views". http://ssrn.com/abstract=1542083
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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