Data-based Automatic Discretization of Nonparametric Distributions
Economics
2020-07-23 v2
Abstract
Although using non-Gaussian distributions in economic models has become increasingly popular, currently there is no systematic way for calibrating a discrete distribution from the data without imposing parametric assumptions. This paper proposes a simple nonparametric calibration method based on the Golub-Welsch algorithm for Gaussian quadrature. Application to an optimal portfolio problem suggests that assuming Gaussian instead of nonparametric shocks leads to up to 17% overweighting in the stock portfolio because the investor underestimates the probability of crashes.
Keywords
Cite
@article{arxiv.1805.00896,
title = {Data-based Automatic Discretization of Nonparametric Distributions},
author = {Alexis Akira Toda},
journal= {arXiv preprint arXiv:1805.00896},
year = {2020}
}