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
- 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/).
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 - 10.2991/icmii-15.2015.87 ID - Ying2015/10 ER -