research-article

Price Shock Detection With an Influence-Based Model of Social Attention

Authors:

Hui XiongAuthors Info & Claims

ACM Transactions on Management Information Systems (TMIS), Volume 9, Issue 1

Article No.: 2, Pages 1 - 21

https://doi.org/10.1145/3131781

Published: 29 September 2017 Publication History

Abstract

There has been increasing interest in exploring the impact of human behavior on financial market dynamics. One of the important related questions is whether attention from society can lead to significant stock price movements or even abnormal returns. To answer the question, we develop a new measurement of social attention, named periodic cumulative degree of social attention, by simultaneously considering the individual influence and the information propagation in social networks. Based on the vast social network data, we evaluate the new attention measurement by testing its significance in explaining future abnormal returns. In addition, we test the forecasting ability of social attention for stock price shocks, defined by the cumulative abnormal returns. Our results provide significant evidence to support the intercorrelated relationship between the social attention and future abnormal returns. The outperformance of the new approach in predicting price shocks is also confirmed by comparison with several benchmark methods.

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Cited By

Arrigoni VMasi GMercanti EBartolini NVyetrenko S(2023)Stock Shocks Modelling and Forecasting2023 IEEE 43rd International Conference on Distributed Computing Systems Workshops (ICDCSW)10.1109/ICDCSW60045.2023.00014(67-72)Online publication date: 18-Jul-2023
https://doi.org/10.1109/ICDCSW60045.2023.00014
Madler JHarding SWeibelzahl M(2023)A multi-agent model of urban microgrids: Assessing the effects of energy-market shocks using real-world dataApplied Energy10.1016/j.apenergy.2023.121180343(121180)Online publication date: Aug-2023
https://doi.org/10.1016/j.apenergy.2023.121180
Zhou BChen LZhou FLi SZhao SPan G(2022)Dynamic road crime risk prediction with urban open dataFrontiers of Computer Science: Selected Publications from Chinese Universities10.1007/s11704-021-0136-z16:1Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1007/s11704-021-0136-z
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Index Terms

Price Shock Detection With an Influence-Based Model of Social Attention
1. Applied computing
  1. Law, social and behavioral sciences
2. Information systems
  1. Information systems applications
    1. Data mining
    2. Decision support systems
      1. Data analytics
  2. World Wide Web
    1. Web applications
      1. Social networks

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Published In

cover image ACM Transactions on Management Information Systems

ACM Transactions on Management Information Systems Volume 9, Issue 1

March 2018

89 pages

ISSN:2158-656X

EISSN:2158-6578

DOI:10.1145/3146385

Editor:
Daniel Zeng
University of Arizona, USA

Issue’s Table of Contents

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 September 2017

Accepted: 01 August 2017

Revised: 01 March 2017

Received: 01 June 2016

Published in TMIS Volume 9, Issue 1

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Collaborative Innovation Center for Economics Crime Investigation and Prevention Technology, Jiangxi, China
Youth Innovation Promotion Association of CAS
Jiangxi Social Science Planning Project, China

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Cited By

Arrigoni VMasi GMercanti EBartolini NVyetrenko S(2023)Stock Shocks Modelling and Forecasting2023 IEEE 43rd International Conference on Distributed Computing Systems Workshops (ICDCSW)10.1109/ICDCSW60045.2023.00014(67-72)Online publication date: 18-Jul-2023
https://doi.org/10.1109/ICDCSW60045.2023.00014
Madler JHarding SWeibelzahl M(2023)A multi-agent model of urban microgrids: Assessing the effects of energy-market shocks using real-world dataApplied Energy10.1016/j.apenergy.2023.121180343(121180)Online publication date: Aug-2023
https://doi.org/10.1016/j.apenergy.2023.121180
Zhou BChen LZhou FLi SZhao SPan G(2022)Dynamic road crime risk prediction with urban open dataFrontiers of Computer Science: Selected Publications from Chinese Universities10.1007/s11704-021-0136-z16:1Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1007/s11704-021-0136-z
Liu ZXiao KJin BHuang KHuang DZhang Y(2020)Unified Generative Adversarial Networks for Multiple-Choice Oriented Machine ComprehensionACM Transactions on Intelligent Systems and Technology10.1145/337212011:3(1-20)Online publication date: 3-Apr-2020
https://dl.acm.org/doi/10.1145/3372120
Xiao KYe ZZhang LZhou WGe YDeng Y(2020)Multi-User Mobile Sequential Recommendation for Route OptimizationACM Transactions on Knowledge Discovery from Data10.1145/336004814:5(1-28)Online publication date: 6-Jul-2020
https://dl.acm.org/doi/10.1145/3360048
Chang BChen EZhu FLiu QXu TWang Z(2020) Maximum a Posteriori Estimation for Information Source Detection IEEE Transactions on Systems, Man, and Cybernetics: Systems10.1109/TSMC.2018.281141050:6(2242-2256)Online publication date: Jun-2020
https://doi.org/10.1109/TSMC.2018.2811410
Zhao J(2020)WITHDRAWN: Corporate financial risk prediction based on embedded system and deep learningMicroprocessors and Microsystems10.1016/j.micpro.2020.103405(103405)Online publication date: Nov-2020
https://doi.org/10.1016/j.micpro.2020.103405
Han XYaraghi NGopal R(2019)Catching Them Red-HandedACM Transactions on Management Information Systems10.1145/332552210:2(1-26)Online publication date: 14-Aug-2019
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Lo KChau M(2019)A Penny Is Worth a Thousand? Investigating the Relationship Between Social Media and Penny StocksACM Transactions on Management Information Systems10.1145/33097049:4(1-35)Online publication date: 11-Mar-2019
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Wang HXu TLiu QLian DChen EDu DWu HSu WTeredesai AKumar VLi YRosales RTerzi EKarypis G(2019)MCNEProceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3292500.3330931(1064-1072)Online publication date: 25-Jul-2019
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