Proceedings of the 3rd Annual 2017 International Conference on Management Science and Engineering (MSE 2017)

A Nonlinear Dynamic System in Behavioral Finance: Evidence from Chinese Stock Market

Authors
Jun Xie
Corresponding Author
Jun Xie
Available Online October 2017.
DOI
10.2991/mse-17.2017.58How to use a DOI?
Keywords
Investor sentiment; Willingness to investment; Non-linear Granger causality; Behavioral finance
Abstract

This paper uses linear and nonlinear Granger causality tests to examine a dynamic behavioral finance system which composed by the stock index price, investor sentiment and the willingness to investment. We find that the linear dynamic system is simple and unidirectional, but nonlinear dynamic system is complex and bidirectional. And we can predict the index return more accurately by using the nonlinear dynamic system, because the linear dynamic system may lose some variables which have nonlinear effects on the index return.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 3rd Annual 2017 International Conference on Management Science and Engineering (MSE 2017)
Series
Advances in Economics, Business and Management Research
Publication Date
October 2017
ISBN
978-94-6252-394-4
ISSN
2352-5428
DOI
10.2991/mse-17.2017.58How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Jun Xie
PY  - 2017/10
DA  - 2017/10
TI  - A Nonlinear Dynamic System in Behavioral Finance: Evidence from Chinese Stock Market
BT  - Proceedings of the 3rd Annual 2017 International Conference on Management Science and Engineering (MSE 2017)
PB  - Atlantis Press
SP  - 253
EP  - 256
SN  - 2352-5428
UR  - https://doi.org/10.2991/mse-17.2017.58
DO  - 10.2991/mse-17.2017.58
ID  - Xie2017/10
ER  -