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Non-linear long horizon returns predictability: evidence from six south-east Asian markets
Authors:David G. McMillan  Alan E. H. Speight
Affiliation:(1) School of Management, University of St Andrews, The Gateway, North Haugh, St Andrews, KY16 9SS, UK;(2) School of Business & Economics, Swansea University, Swansea, SA2 8PP, UK
Abstract:
Whilst the existence of long-horizon returns predictability has been a recurrent theme in empirical finance research, extant work has focused almost exclusively on the US, and more recent work has cast doubt over the validity of such potential predictability due to non-stationarity and serial correlation in the data. The present paper examines long-horizon returns predictability in six South-East Asian markets in the context of unit root tests conducted under corrections for serial correlation and heteroscedasticity. The analysis conducted also extends the investigation of long-horizon predictability to the non-linear setting, and examines whether any detected non-linear predictability is consistent with behavioural approaches to asset pricing which emphasise the role of noise traders. The results obtained suggest the following conclusions. First, long-horizon predictability is present in each of the six South-East Asian markets considered. Second, whilst forecast power increases with horizon, for the majority of series it is maximised for forecast horizons of between 12 and 48 months. Third, non-linear predictability is reported for all series, suggesting that positive and negative values of the (demeaned) dividend yield impart different levels of predictability for returns at different forecast horizons. However, there is no consistency in the pattern of non-linearity reported, and whilst the observed patterns are consistent with noise traders models for some of the markets considered, this is not true of all the markets considered. Nevertheless, the non-linear dynamics detected are suggestive of potential market inefficiencies in all six cases.
Keywords:Long-horizon predictability  Threshold
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