Proceedings of the 3rd International Conference on Mechatronics and Industrial Informatics

Detection of Time Series Change Point of Stock Yield Based on Bayesian Method

Authors
Yi Rong Ying, Feng Jie Ying, Su Zhen Li
Corresponding Author
Yi Rong Ying
Available Online October 2015.
DOI
https://doi.org/10.2991/icmii-15.2015.87How to use a DOI?
Keywords
Bayesian Method; Mean Change Point; Posterior Probability Ratio
Abstract

In this paper we suggest using the method of posterior probability to extend the ICSS algorithm based on the formula of posterior probability ratio. The empirical results of Shanghai Composite Index show that the posterior probability algorithm is convenient and effective.

Copyright
© 2015, 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 International Conference on Mechatronics and Industrial Informatics
Series
Advances in Computer Science Research
Publication Date
October 2015
ISBN
978-94-6252-131-5
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmii-15.2015.87How to use a DOI?
Copyright
© 2015, 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  - Yi Rong Ying
AU  - Feng Jie Ying
AU  - Su Zhen Li
PY  - 2015/10
DA  - 2015/10
TI  - Detection of Time Series Change Point of Stock Yield Based on Bayesian Method
BT  - Proceedings of the 3rd International Conference on Mechatronics and Industrial Informatics
PB  - Atlantis Press
SP  - 509
EP  - 512
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmii-15.2015.87
DO  - https://doi.org/10.2991/icmii-15.2015.87
ID  - Ying2015/10
ER  -