Quantifying the effect of investors' attention on stock market

The investors' attention has been extensively used to predict the stock market. Different from existing proxies of the investors' attention, such as the Google trends, Baidu index (BI), we argue the collective attention from the stock trading platforms could reflect the investors' att...

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Bibliographic Details
Published in:PloS one 2017-05, Vol.12 (5), p.e0176836-e0176836
Main Authors: Yang, Zhen-Hua, Liu, Jian-Guo, Yu, Chang-Rui, Han, Jing-Ti
Format: Article
Language:English
Subjects:
Accuracy
Analysis
Asset pricing
Asymmetry
Attention
Autoregressive processes
Biology and life sciences
China
Cognitive ability
Computer and Information Sciences
Currency exchange rate
Data processing
Dictionaries
Econometrics
Economics
Engineering
Finance
Format
Humans
Information dissemination
Information management
Internet
Investment
Investments - trends
Knowledge representation
Lists
Mathematical models
Medicine and health sciences
Models, Economic
Mood
Motivation
Null hypothesis
Online securities trading services
Physics
Platforms
Predictions
Profits
Psychology
Ranking
Regression Analysis
Research and Analysis Methods
Robustness (mathematics)
Securities markets
Security
Services
Social interactions
Social networks
Social organization
Social Sciences
Statistics
Stock exchanges
Stock markets
Stocks
Time series
Topology
Trends
Volatility
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Summary:The investors' attention has been extensively used to predict the stock market. Different from existing proxies of the investors' attention, such as the Google trends, Baidu index (BI), we argue the collective attention from the stock trading platforms could reflect the investors' attention more closely. By calculated the increments of the attention volume for each stock (IAVS) from the stock trading platforms, we investigate the effect of investors' attention measured by the IAVS on the movement of the stock market. The experimental results for Chinese Securities Index 100 (CSI100) show that the BI is significantly correlated with the returns of CSI100 at 1% significance level only in 2014. However, it should be emphasized that the correlation of the new proposed measure, namely IAVS, is significantly at 1% significance level in 2014 and 2015. It shows that the effect of the measure IAVS on the movement of the stock market is more stable and significant than BI. This study yields important invest implications and better understanding of collective investors' attention.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0176836