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Stock Market Autoregressive Dynamics: A Multinational Comparative Study with Quantile Regression
Joint Authors
Li, Lili
Leng, Shan
Yu, Mei
Yang, Jun
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-09-29
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
We study the nonlinear autoregressive dynamics of stock index returns in seven major advanced economies (G7) and China.
The quantile autoregression model (QAR) enables us to investigate the autocorrelation across the whole spectrum of return distribution, which provides more insightful conditional information on multinational stock market dynamics than conventional time series models.
The relation between index return and contemporaneous trading volume is also investigated.
While prior studies have mixed results on stock market autocorrelations, we find that the dynamics is usually state dependent.
The results for G7 stock markets exhibit conspicuous similarities, but they are in manifest contrast to the findings on Chinese stock markets.
American Psychological Association (APA)
Li, Lili& Leng, Shan& Yang, Jun& Yu, Mei. 2016. Stock Market Autoregressive Dynamics: A Multinational Comparative Study with Quantile Regression. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-15.
https://search.emarefa.net/detail/BIM-1111702
Modern Language Association (MLA)
Li, Lili…[et al.]. Stock Market Autoregressive Dynamics: A Multinational Comparative Study with Quantile Regression. Mathematical Problems in Engineering No. 2016 (2016), pp.1-15.
https://search.emarefa.net/detail/BIM-1111702
American Medical Association (AMA)
Li, Lili& Leng, Shan& Yang, Jun& Yu, Mei. Stock Market Autoregressive Dynamics: A Multinational Comparative Study with Quantile Regression. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-15.
https://search.emarefa.net/detail/BIM-1111702
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1111702