E3S Web Conf.
Volume 214, 20202020 International Conference on Energy Big Data and Low-carbon Development Management (EBLDM 2020)
|Number of page(s)||7|
|Section||Machine Learning and Energy Industry Structure Forecast Analysis|
|Published online||07 December 2020|
Prediction and Empirical Study of Stock Yield Volatility Based on Event Study
Statistics institute, Chengdu University of Information Technology Chengdu, Sichuan, China
Stock market event is an important source of information for investment decision, and it is of practical significance to quantify the event and predict the fluctuation range of future return under such event. Most researchers study stock market events horizontally, that is, to study the impact of a current event on the stock price of a certain sector or industry, while the paper attempts to study vertically the impact of a certain event of a single listed company on the return. Based on the internal relations between public announcement and stock yield of listed companies, the paper deduced the daily yield prediction model of event window by VAR(p) to exclude subjective “estimation” in the past and verifies the feasibility of the model.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.