舆情传播、风险感知与投资者行为——基于系统模糊控制的视角

田婧倩, 刘晓星

系统工程理论与实践 ›› 2021, Vol. 41 ›› Issue (12) : 3147-3162.

PDF(1630 KB)
中国科学院数学与系统科学研究院期刊网
PDF(1630 KB)
系统工程理论与实践 ›› 2021, Vol. 41 ›› Issue (12) : 3147-3162. DOI: 10.12011/SETP2020-2822
论文

舆情传播、风险感知与投资者行为——基于系统模糊控制的视角

    田婧倩, 刘晓星
作者信息 +

Public opinion dissemination, risk perception and investor behavior: Based on system fuzzy control

    TIAN Jingqian, LIU Xiaoxing
Author information +
文章历史 +

摘要

大数据时代下，互联网和新媒体的迅速发展在加速网络舆情流动性的同时，通过增加投资者的模糊风险感知程度加剧了金融市场波动，给舆情传播的系统性监管带来难度.本文首次将物理学倒立摆模型跨学科应用到微观投资者行为系统的构建，并基于模糊理论对比不同策略下的系统稳定性控制效果，验证该模型在金融领域的可行性与可控性.选取2020年1月至6月的微博文本为实证分析数据，测度投资者行为的变化效率，检验了我国舆情传播通过投资者模糊风险感知对金融市场稳定性的控制效果.研究结果表明：1）理论上存在能够动态控制投资者行为系统稳定的舆情传播有效程度；2）舆情信息会跨市场影响不同金融市场上的投资者决策；3）我国政府主导下的舆情环境在面对重大突发事件时具有良好的稳定市场能力.

Abstract

The rapid development of the internet and new media in the era of big data accelerates the liquidity of public opinion on the internet and increases the vague perception of risk by investors, which intensifies financial market volatility. These have brought difficulties to the systematic supervision of public opinion dissemination. This paper applies the physics inverted pendulum model to the construction of micro investor behavior systems for the first time, and compares the system stability control effects under different strategies based on fuzzy theory, which verifies the feasibility and controllability of the model in the financial field. Weibo texts from January to June 2020 are selected as empirical analysis data to measure the efficiency of investor behavior changes and then the control effect of public opinion communication on financial market stability through investors' fuzzy perception of risk in China is tested. The research results show that:1) In theory, there is an effective degree of public opinion dissemination, which can control the behavior of investors and the stability of the system dynamically; 2) Public opinion information can influence investors' decision-making in different financial markets; 3) In the face of major emergencies, the public opinion environment led by the Chinese government has the ability to stabilize the market.

关键词

风险感知 / 倒立摆系统 / 模糊逻辑控制 / 社交舆情传播有效性指数 / DEA模型

Key words

risk perception / inverted pendulum system / fuzzy logic control / social public opinion communication effectiveness index / DEA model

引用本文

EndNote

Ris (Procite)

Bibtex

导出引用
田婧倩 , 刘晓星. 舆情传播、风险感知与投资者行为——基于系统模糊控制的视角. 系统工程理论与实践, 2021, 41(12): 3147-3162 https://doi.org/10.12011/SETP2020-2822
TIAN Jingqian , LIU Xiaoxing. Public opinion dissemination, risk perception and investor behavior: Based on system fuzzy control. Systems Engineering - Theory & Practice, 2021, 41(12): 3147-3162 https://doi.org/10.12011/SETP2020-2822
中图分类号： F830   

参考文献

[1] Bollen J, Mao H, Zeng X. Twitter mood predicts the stock market[J]. Journal of Computational Science, 2011(2):1-8.
[2] Kim S H, Kim D. Investor sentiment from internet message postings and the predictability of stock returns[J]. Journal of Economic Behavior & Organization, 2014, 107:708-729.
[3] 部慧,解峥,李佳鸿,等.基于股评的投资者情绪对股票市场的影响[J].管理科学学报, 2018, 21(4):86-101.Bu H, Xie Z, Li J H, et al. Investor sentiment extracted from internet stock message boards and its effect on Chinese stock market[J]. Journal of Management Sciences in China, 2018, 21(4):86-101.
[4] Aman H. Firm-specific volatility of stock returns, the credibility of management forecasts, and media coverage:Evidence from Japanese firms[J]. Japan & the World Economy, 2011, 23(1):28-39.
[5] 王晓丹,尚维,汪寿阳.互联网新闻媒体报道对我国股市的影响分析[J].系统工程理论与实践, 2019, 39(12):3038-3047.Wang X D, Shang W, Wang S Y. The effects of online news on the Chinese stock market[J]. Systems Engineering-Theory & Practice, 2019, 39(12):3038-3047.
[6] 徐戈,李宜威.空气质量对公众感知风险与应对意愿的影响研究[J].系统工程理论与实践, 2020, 40(1):93-102.Xu G, Li Y W. Impact of air quality on public perception of risk and coping intension[J]. Systems Engineering-Theory & Practice, 2020, 40(1):93-102.
[7] 李鑫,张军.基于系统动力学的SIRS信息传播模型研究[J].情报科学, 2017, 35(11):17-22.Li X, Zhang J. Research on SIRS information diffusion model based on system dynamics[J]. Information Science, 2017, 35(11):17-22.
[8] 尹楠.有限群体内舆情危机扩散SIR模型及仿真模拟实现[J].统计与决策, 2018, 34(18):62-66.Yin N. SIR model of public opinion crisis diffusion in a limited group and its simulation realization[J]. Statistics & Decision, 2018, 34(18):62-66.
[9] 王筱莉,赵来军,谢婉林.无标度网络中遗忘率变化的谣言传播模型研究[J].系统工程理论与实践, 2015, 35(2):458-465.Wang X L, Zhao L J, Xie W L. Rumor spreading model with variable forgetting rate in scale-free network[J]. Systems Engineering-Theory & Practice, 2015, 35(2):458-465.
[10] Nekovee M, Moreno Y, Bianconi G, et al. Theory of rumour spreading in complex social networks[J]. Physica A:Statistical Mechanics and its Applications, 2007, 374(1):457-470.
[11] 王家坤,于灏,王新华,等.基于用户相对权重的在线社交网络舆情传播控制模型[J].系统工程理论与实践, 2019, 39(6):1565-1579.Wang J K, Yu H, Wang X H, et al. Dissemination and control model of public opinion in online social networks based on users' relative weight[J]. Systems Engineering-Theory & Practice, 2019, 39(6):1565-1579.
[12] 张玉亮,张昊苏.突发事件网络舆情主体静态博弈分析及相关政策建议[J].情报杂志, 2014, 33(8):150-154+167.Zhang Y L, Zhang H S. The static game analysis of network public opinion on emergencies and the policy suggestions[J]. Journal of Intelligence, 2014, 33(8):150-154+167.
[13] Liu Y, Han S C, Zhang Y C, et al. Dynamic game theory with incomplete information in opinion dynamic[J]. Journal of Convergence Information Technology, 2012, 7(1):297-306.
[14] 李燕凌,丁莹.网络舆情公共危机治理中社会信任修复研究——基于动物疫情危机演化博弈的实证分析[J].公共管理学报, 2017, 14(4):91-101+157.Li Y L, Ding Y. Research on social trust repair of public crisis governance under network public opinion[J]. Journal of Public Management, 2017, 14(4):91-101+157.
[15] 林燕霞,谢湘生,张德鹏.复杂交互行为影响下的网络舆情演化分析[J].中国管理科学, 2020, 28(1):212-221.Lin Y X, Xie X S, Zhang D P. Analysis of online public opinion evolution under the influence of complex interaction behaviors[J]. Chinese Journal of Management Science, 2020, 28(1):212-221.
[16] 王会东,李兆东,姚金丽,等.基于对称三角模糊集的股票投资者情绪传播模型[J].自动化学报, 2020, 46(5):1031-1043.Wang H D, Li Z D, Yao J L, et al. Sentimental propagation model of stock investors based on symmetric triangular fuzzy set[J]. Acta Automatica Sinica, 2020, 46(5):1031-1043.
[17] 郭耿,陈福集,陈蕾雯.基于观点模糊相似度的微博舆情演化研究[J].情报科学, 2020, 38(1):82-86.Guo G, Chen F J, Chen L W. Research on Weibo public opinion evolution based on similarity measure of fuzzy perspective[J]. Information Science, 2020, 38(1):82-86.
[18] 刘久兵,周献中,李华雄,等.基于直觉模糊相似度的直觉模糊三支决策方法[J].系统工程理论与实践, 2019, 39(6):1550-1564. Liu J B, Zhou X Z, Li H X, et al. An intuitionistic fuzzy three-way decision method based on intuitionistic fuzzy similarity degrees[J]. Systems Engineering-Theory & Practice, 2019, 39(6):1550-1564.
[19] 杨申燕,明雷,唐慧,等.不确定性、投资者犹豫程度与永久美式期权定价[J].系统工程理论与实践, 2020, 40(11):2839-2847.Yang S Y, Ming L, Tang H, et al. Uncertainty, hesitancy degree of investors and pricing perpetual American options[J]. Systems Engineering-Theory & Practice, 2020, 40(11):2839-2847.
[20] 党小超,张春娇,郝占军.基于模糊元胞自动机的网络舆情传播模型研究[J].计算机工程, 2014, 40(4):209-213.Dang X C, Zhang C J, Hao Z J. Study on propagation model of network public opinion based on fuzzy cellular automata[J]. Computer Engineering, 2014, 40(4):209-213.
[21] 刘健,孙小明.新浪微博信息传播效果评价及实证研究——基于DEA方法的分析[J].现代情报, 2016, 36(9):88-94.Liu J, Sun X M. Evaluation and empirical study on the effect of sina micro Blog information dissemination[J] Journal of Modern Information, 2016, 36(9):88-94.
[22] Zedeh L A. Fuzzy sets[J]. Information and Control, 1965, 8(3):338-353.
[23] 丁学君,李临霄.反沉默螺旋效应下社交媒体谣言传播动力学研究[J].系统工程理论与实践, 2020, 40(12):3149-3163.Ding X J, Li L X. The spreading dynamics of rumors in social media under the anti-silence spiral effect[J]. Systems Engineering-Theory & Practice, 2020, 40(12):3149-3163.
[24] 顾秋阳,琚春华,鲍福光.融入用户群体行为的移动社交网络舆情传播动态演化模型研究[J].系统科学与数学, 2020, 40(12):2278-2296.Gu Q Y, Ju C H, Bao F G. Study on dynamic evolution model of the spread of public opinion in mobile social network incorporated with the behavior of user group[J]. Journal of Systems Science and Mathematical Sciences, 2020, 40(12):2278-2296.
[25] 陈庭强,马百超,李心丹.投资者情绪、偿债能力与CDS交易对手流动性风险传染[J].系统工程理论与实践, 2020, 40(3):559-578.Chen T Q, Ma B C, Li X D. Investor sentiment, debt solvency and the contagion of CDS counterparty liquidity crisis[J]. Systems Engineering-Theory & Practice, 2020, 40(3):559-578.
[26] 齐丽云,李晓鸿,曹硕.企业社会责任负面事件网络舆情演化与政企合作研究[J].系统工程理论与实践, 2020, 40(7):1792-1805.Qi L Y, Li X H, Cao S. A research on the evolution of net-mediated public sentiment in corporate social responsibility negative events and government-enterprise cooperation[J]. Systems Engineering-Theory & Practice, 2020, 40(7):1792-1805.
[27] Minsky H P. The financial instability hypothesis:A restatement[J]. Social Science Electronic Publishing, 1978.
[28] Liu B, Liu Y K. Expected value of fuzzy variable and fuzzy expected value models[J]. IEEE Transactions on Fuzzy Systems, 2002, 10(4):445-450.
[29] 白志慧,周志光,杨瑞飞,等.非对称高斯函数的时变体数据特征跟踪及可视化[J].中国图象图形学报, 2015, 20(4):576-584.Bai Z H, Zhou Z G, Yang R F, et al. Time-varying volume visualization and feature tracking based on asymmetric Gaussian function[J]. Journal of Image and Graphics, 2015, 20(4):576-584.
[30] 陈富国. 基于模糊逻辑的多级倒立摆控制系统研究[D]. 大连:大连理工大学, 2009.Chen F G. Research on control system for multistage inverted pendulum based on fuzzy logic[D]. Dalian:Dalian University of Technology, 2009.
[31] 虞晓雯,雷明,王其文,等.中国商业银行效率的实证分析(2005-2011)——基于时间序列回归和随机DEA的机会约束模型[J].中国管理科学, 2012, 20(S1):356-362.Yu X W, Lei M, Wang Q W, et al. Chinese commercial bank's efficiency (2005-2011):Based on time-series regression and chance-constrained DEA model[J]. Chinese Journal of Management Science, 2012, 20(S1):356-362.
[32] 刘虹,孟凡赛,孙建军.基于DEA方法的政务微博信息交流效率研究[J].情报科学, 2017, 35(6):9-13.Liu H, Meng F S, Sun J J. Research on information exchange efficiency of government microblogs based on data envelopment analysis method[J]. Information Science, 2017, 35(6):9-13.
[33] 王旭,蓝以信,王应明.考虑规模与时滞双重效应的中国商业银行运营效率分析[J/OL].中国管理科学, 1-13[2020-09-08]. https://doi.org/10.16381/j.cnki.issn1003-207x.2018.0465.Wang X, Lan Y X, Wang Y M. The operational efficiency of Chinese commercial banks in consideration of Scale effect and time-lag effect[J/OL]. Chinese Journal of Management Science, 1-13[2020-09-08].https://doi.org/10.16381/j.cnki.issn1003-207x.2018.0465.
[34] Lynde C, Richmond J. Productivity and efficiency in the UK:A time series application of DEA[J]. Economic Modelling, 1999, 16(1):105-122.
[35] 颜鹏飞,王兵.技术效率、技术进步与生产率增长:基于DEA的实证分析[J].经济研究, 2004(12):55-65.Yan P F, Wang B. Technical efficiency, technical progress & productivity growth:An empirical analysis based on DEA[J]. Economic Research Journal, 2004(12):55-65.
[36] 赵当如,陈为.基于时间序列的DEA地方财政科技投入效率测算:1997-2014——以湖北省为例[J].科技与创新, 2017(21):29-31.Zhao D R, Chen W. Estimation of the efficiency of DEA's local financial investment in science and technology based on time series:1997-2014[J]. Science and Technology & Innovation, 2017(21):29-31.
[37] 杜栋, 庞庆华, 吴炎. 现代综合评价方法与案例精选[M]. 北京:清华大学出版社, 2008.Du D, Pang Q H, Wu Y. Modern comprehensive evaluation methods and selected cases[M]. Beijing:Tsinghua University Press, 2008.
[38] 郑君君,程翼,马刚,等.基于数据爬虫与动态社会网络的公众环保行为演化研究[J].系统工程理论与实践, 2020, 40(1):219-229.Zheng J J, Cheng Y, Ma G, et al. Research on evolution of public environmental protection behavior based on data crawler and dynamic social network[J]. Systems Engineering-Theory & Practice, 2020, 40(1):219-229.
[39] 熊熊,许克维,沈德华.投资者情绪与期货市场功能——基于沪深300股指期货的研究[J].系统工程理论与实践, 2020, 40(9):2252-2268.Xiong X, Xu K W, Shen D H. Investor sentiment and futures market functions:Evidence from CSI 300 index futures market[J]. Systems Engineering-Theory & Practice, 2020, 40(9):2252-2268.

基金

国家自然科学基金（71673043）；国家社科基金重大专项课题（18VSJ035）
PDF(1630 KB)

1006

Accesses

0

Citation

Detail
段落导航
相关文章

/

〈 〉