Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/152098
Title: EXAMINING PREDICTABILITY IN THE DISTRIBUTION OF STOCK MARKET RETURNS USING A QUANTILE-BASED APPROACH: A STUDY ON ASEAN STOCK MARKET INTEGRATION
Authors: SYRONE JOHN LAQUINDANUM DAVID
Keywords: ASEAN financial integration
nonparametric Granger causality in quantiles
Predictive quantile regression
Issue Date: 5-Nov-2018
Citation: SYRONE JOHN LAQUINDANUM DAVID (2018-11-05). EXAMINING PREDICTABILITY IN THE DISTRIBUTION OF STOCK MARKET RETURNS USING A QUANTILE-BASED APPROACH: A STUDY ON ASEAN STOCK MARKET INTEGRATION. ScholarBank@NUS Repository.
Abstract: This paper conducts a nonparametric Granger causality test in quantiles to investigate the interdependence of ASEAN stock markets. We find ASEAN stock markets have significant bilateral Granger causality in many of the considered quantiles. We find stronger evidence of Granger causality in the tail quantiles, and this result is more pronounced after adjustment for the common factor. The paper also investigates whether evidence of Granger causality in quantiles imply better forecastability of the features of the stock return distribution, using Thailand daily returns. We find better predictability mainly in the lower quantiles, a result similar to the Granger causality test after accounting for the common factor. However, there are many instances where a significant Granger causality result in the quantile did not translate to better predictive ability. Nonetheless, we find that the point forecasts made from an equal-weighted combination of the different country forecasts performed better than the prevailing median.
URI: http://scholarbank.nus.edu.sg/handle/10635/152098
Appears in Collections:Bachelor's Theses

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
Syrone John Laquindanum David AY1819 Sem 1.pdf1.16 MBAdobe PDF

RESTRICTED

NoneLog In

Page view(s)

20
checked on Apr 20, 2019

Download(s)

9
checked on Apr 20, 2019

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.