Forecasting Stock Market Volatility via Causal Reasoning-Reference-Cited by-同舟云学术

Forecasting Stock Market Volatility via Causal Reasoning

Published:2023-07-01 Issue:2 Volume:8 Page:3305-3322
ISSN:2444-8656
Container-title:Applied Mathematics and Nonlinear Sciences
language:en
Short-container-title:

Author:

Yang Dan¹,Lu Di²

Affiliation:

1. 1 Shaanxi Business College , Xi’an , China .

2. 2 International Business School , Shaanxi Normal University , Xi’an , China

Abstract

Abstract Studies have shown that Internet financial news has become an important reference for investors in investment behavior. In order to simulate trading experiments that mimic the real stock market, this paper develops a stock volatility prediction model based on causal reasoning. It also gathers and cleans news and stock market data from the Internet, such as opening price, closing price, and change. The findings of the study indicate that the level of stock market volatility can be significantly influenced by online financial news. The proposed model can analyze the effects of news and stock market data in an explainable manner.

Publisher

Walter de Gruyter GmbH

Subject

Applied Mathematics,Engineering (miscellaneous),Modeling and Simulation,General Computer Science

Link

https://www.sciendo.com/pdf/10.2478/amns.2023.2.01131

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