Proceedings of the 5th International Conference on Social Sciences and Economic Development (ICSSED 2020)

The Conception of Stock Price Volatility Analysis System Based on News Events

Authors
Liu Xin, Sheng Mingcai, Huang Xi, Su Ganya
Corresponding Author
Su Ganya
Available Online 2 April 2020.
DOI
10.2991/assehr.k.200331.002How to use a DOI?
Keywords
news events, stock price volatility, factor of corpus, text segmentation
Abstract

News events are one of the factors influencing stock price fluctuations. The analysis system proposed in this paper quantifies the influence of historical news events into “limitation period” and “stock price fluctuation range”, predicts the possible impact of real-time news events on stock price, and gives the limitation period and stock price fluctuation range. Keyword factors are used to link historical news events with real-time news events.

Copyright
© 2020, 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/).

Download article (PDF)

Volume Title
Proceedings of the 5th International Conference on Social Sciences and Economic Development (ICSSED 2020)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
2 April 2020
ISBN
978-94-6252-946-5
ISSN
2352-5398
DOI
10.2991/assehr.k.200331.002How to use a DOI?
Copyright
© 2020, 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  - Liu Xin
AU  - Sheng Mingcai
AU  - Huang Xi
AU  - Su Ganya
PY  - 2020
DA  - 2020/04/02
TI  - The Conception of Stock Price Volatility Analysis System Based on News Events
BT  - Proceedings of the 5th International Conference on Social Sciences and Economic Development (ICSSED 2020)
PB  - Atlantis Press
SP  - 7
EP  - 10
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.200331.002
DO  - 10.2991/assehr.k.200331.002
ID  - Xin2020
ER  -