Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/49193
Title: | Dancing with bulls and bears: Nearest-neighbour forecasts for the Nikkei index | Authors: | Fernández-Rodríguez, Fernando Sosvilla-Rivero, Simón Dolores García-Artiles, María |
Keywords: | Efficient Capital-Markets Nonlinear Dynamics Stock Returns Time-Series Regression, et al |
Issue Date: | 1999 | Publisher: | 0922-1425 | Journal: | Japan and the World Economy | Abstract: | In this paper we apply nearest-neighbour local predictors, inspired by the literature on forecasting in nonlinear systems, to the Nikkei 225 Index of the Tokyo Stock Market for the period 1 January 1986-5 June 1997. When forecasting performance is measured by Theil's U statistic, our nearest-neighbour predictors perform worse than a random walk, outperforming the random walk directional forecast. When formally testing for forecast accuracy, the results suggest that predictions from a random walk were statistically significantly better than the nearest-neighbour predictors for the entire forecasting period, as well as for one of the subperiods (a 'bull' market episode). Finally, when assessing the economic value of the nearest-neighbour predictors in absence of trading costs, the results of using them as a filter technique are superior to a buy-and-hold strategy for both the entire forecasting period acid for 'bear' market subperiods, where tests of 'forecast conditional efficiency' (or 'forecast encompassing') detected that the nearest-neighbour predictors contain useful information for forecasting the Nikkei Index that is not contained in the random walk. (C) 1999 Elsevier Science B.V. All rights reserved. JEL classification: C53; G15. | URI: | http://hdl.handle.net/10553/49193 | ISSN: | 0922-1425 | Source: | Japan and the World Economy[ISSN 0922-1425],v. 11, p. 395-413 |
Appears in Collections: | Artículos |
SCOPUSTM
Citations
28
checked on Nov 3, 2024
WEB OF SCIENCETM
Citations
17
checked on Feb 25, 2024
Page view(s)
54
checked on Mar 23, 2024
Google ScholarTM
Check
Share
Export metadata
Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.