Hassani, H. and Silva, E., 2015. A Kolmogorov-Smirnov Based Test for Comparing the Predictive Accuracy of Two Sets of Forecasts. Econometrics, 3 (3), 590 - 609 .
Full text available as:
|
PDF (OPEN ACCESS ARTICLE)
Hassani and Silva (2015).pdf - Published Version Available under License Creative Commons Attribution. 318kB | |
Copyright to original material in this document is with the original owner(s). Access to this content through BURO is granted on condition that you use it only for research, scholarly or other non-commercial purposes. If you wish to use it for any other purposes, you must contact BU via BURO@bournemouth.ac.uk. Any third party copyright material in this document remains the property of its respective owner(s). BU grants no licence for further use of that third party material. |
DOI: 10.3390/econometrics3030590
Abstract
This paper introduces a complement statistical test for distinguishing between the predictive accuracy of two sets of forecasts. We propose a non-parametric test founded upon the principles of the Kolmogorov-Smirnov (KS) test, referred to as the KS Predictive Accuracy (KSPA) test. The KSPA test is able to serve two distinct purposes. Initially, the test seeks to determine whether there exists a statistically significant difference between the distribution of forecast errors, and secondly it exploits the principles of stochastic dominance to determine whether the forecasts with the lower error also reports a stochastically smaller error than forecasts from a competing model, and thereby enables distinguishing between the predictive accuracy of forecasts. We perform a simulation study for the size and power of the proposed test and report the results for different noise distributions, sample sizes and forecasting horizons. The simulation results indicate that the KSPA test is correctly sized, and robust in the face of varying forecasting horizons and sample sizes along with significant accuracy gains reported especially in the case of small sample sizes. Real world applications are also considered to illustrate the applicability of the proposed KSPA test in practice.
Item Type: | Article |
---|---|
ISSN: | 2225-1146 |
Uncontrolled Keywords: | Forecast Accuracy ; Predictive Accuracy ; Kolmogorov-Smirnov ; Stochastic Dominance ; Diebold-Mariano ; Non-parametric |
Group: | Bournemouth University Business School |
ID Code: | 22326 |
Deposited By: | Symplectic RT2 |
Deposited On: | 04 Aug 2015 15:31 |
Last Modified: | 14 Mar 2022 13:52 |
Downloads
Downloads per month over past year
Repository Staff Only - |