A Highly Efficient Regression Estimator for Skewed and/or Heavy-tailed Distributed Errors

Download PDF: Working Paper 19

This paper introduces a regression model for extreme events that can be useful for financial market analysis and prediction 

Authors: Lorenzo Ricci, Vincenzo Verardi and Catherine Vermandele

Abstract:

This paper proposes a simple maximum likelihood regression estimator that outperforms Least Squares in terms of efficiency and mean square error for a large number of skewed and/or heavy tailed error distributions.

Disclaimer: This Working Paper should not be reported as representing the views of the ESM. The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the ESM or ESM policy. No responsibility or liability is accepted by the ESM in relation to the accuracy or completeness of the information, including any data sets, presented in this Working Paper.

JEL codes: C13, C16, G17

Source: European Stability Mechanism | Working Paper Series | Volume 2016 | No 19 | November 2016 | 8 Pages
 

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