突尼斯革命导致的政治不稳定对谷歌搜索查询指数和金融市场动态之间关系的影响

Yousra Trichilli, Mouna Boujelbène Abbes, Sabrine Zouari
{"title":"突尼斯革命导致的政治不稳定对谷歌搜索查询指数和金融市场动态之间关系的影响","authors":"Yousra Trichilli, Mouna Boujelbène Abbes, Sabrine Zouari","doi":"10.1108/JCMS-04-2020-0005","DOIUrl":null,"url":null,"abstract":"PurposeThis paper examines the impact of political instability on the investors' behavior, measured by Google search queries, and on the dynamics of stock market returns.Design/methodology/approachFirst, by using the DCC-GARCH model, the authors examine the effect of investor sentiment on the Tunisian stock market return. Second, the authors employ the fully modified dynamic ordinary least square method (FMOL) to estimate the long-term relationship between investor sentiment and Tunisian stock market return. Finally, the authors use the wavelet coherence model to test the co-movement between investor sentiment measured by Google Trends and Tunisian stock market return.FindingsUsing the dynamic conditional correlation (DCC), the authors find that Google search queries index has the ability to reflect political events especially the Tunisian revolution. In addition, empirical results of fully modified ordinary least square (FMOLS) method reveal that Google search queries index has a slightly higher effect on Tunindex return after the Tunisian revolution than before this revolution. Furthermore, by employing wavelet coherence model, the authors find strong comovement between Google search queries index and return index during the period of the Tunisian revolution political instability. Moreover, in the frequency domain, strong coherence can be found in less than four months and in 16–32 months during the Tunisian revolution which show that the Google search queries measure was leading over Tunindex return. In fact, wavelet coherence analysis confirms the result of DCC that Google search queries index has the ability to detect the behavior of Tunisian investors especially during the period of political instability.Research limitations/implicationsThis study provides empirical evidence to portfolio managers that may use Google search queries index as a robust measure of investor's sentiment to select a suitable investment and to make an optimal investments decisions.Originality/valueThe important research question of how political instability affects stock market dynamics has been neglected by scholars. This paper attempts principally to fill this void by investigating the time-varying interactions between market returns, volatility and Google search based index, especially during Tunisian revolution.","PeriodicalId":118429,"journal":{"name":"Journal of Capital Markets Studies","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The impact of political instability driven by the Tunisian revolution on the relationship between Google search queries index and financial market dynamics\",\"authors\":\"Yousra Trichilli, Mouna Boujelbène Abbes, Sabrine Zouari\",\"doi\":\"10.1108/JCMS-04-2020-0005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"PurposeThis paper examines the impact of political instability on the investors' behavior, measured by Google search queries, and on the dynamics of stock market returns.Design/methodology/approachFirst, by using the DCC-GARCH model, the authors examine the effect of investor sentiment on the Tunisian stock market return. Second, the authors employ the fully modified dynamic ordinary least square method (FMOL) to estimate the long-term relationship between investor sentiment and Tunisian stock market return. Finally, the authors use the wavelet coherence model to test the co-movement between investor sentiment measured by Google Trends and Tunisian stock market return.FindingsUsing the dynamic conditional correlation (DCC), the authors find that Google search queries index has the ability to reflect political events especially the Tunisian revolution. In addition, empirical results of fully modified ordinary least square (FMOLS) method reveal that Google search queries index has a slightly higher effect on Tunindex return after the Tunisian revolution than before this revolution. Furthermore, by employing wavelet coherence model, the authors find strong comovement between Google search queries index and return index during the period of the Tunisian revolution political instability. Moreover, in the frequency domain, strong coherence can be found in less than four months and in 16–32 months during the Tunisian revolution which show that the Google search queries measure was leading over Tunindex return. In fact, wavelet coherence analysis confirms the result of DCC that Google search queries index has the ability to detect the behavior of Tunisian investors especially during the period of political instability.Research limitations/implicationsThis study provides empirical evidence to portfolio managers that may use Google search queries index as a robust measure of investor's sentiment to select a suitable investment and to make an optimal investments decisions.Originality/valueThe important research question of how political instability affects stock market dynamics has been neglected by scholars. This paper attempts principally to fill this void by investigating the time-varying interactions between market returns, volatility and Google search based index, especially during Tunisian revolution.\",\"PeriodicalId\":118429,\"journal\":{\"name\":\"Journal of Capital Markets Studies\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Capital Markets Studies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/JCMS-04-2020-0005\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Capital Markets Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/JCMS-04-2020-0005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

本文考察了政治不稳定对投资者行为的影响,通过谷歌搜索查询来衡量,以及对股市回报动态的影响。设计/方法/方法首先,通过使用DCC-GARCH模型,作者检验了投资者情绪对突尼斯股市回报的影响。其次,采用完全修正的动态普通最小二乘法(FMOL)估计投资者情绪与突尼斯股市收益之间的长期关系。最后,作者使用小波相干模型来测试由谷歌趋势测量的投资者情绪与突尼斯股市回报之间的共同运动。使用动态条件关联(DCC),作者发现谷歌搜索查询索引有能力反映政治事件,特别是突尼斯革命。此外,完全修正普通最小二乘(FMOLS)方法的实证结果显示,突尼斯革命后,Google搜索查询索引对Tunindex回报的影响略高于革命前。此外,通过采用小波相干模型,作者发现在突尼斯革命政治不稳定时期,谷歌搜索查询指数和返回指数之间有很强的一致性。此外,在频域中,在不到4个月的时间里,在突尼斯革命期间的16-32个月里,可以发现强相干性,这表明谷歌搜索查询指标领先于Tunindex返回。事实上,小波相干性分析证实了DCC的结果,即谷歌搜索查询指数具有检测突尼斯投资者行为的能力,特别是在政治不稳定时期。本研究为投资组合管理者提供了实证证据,可以将谷歌搜索查询指数作为投资者情绪的有力衡量指标,以选择合适的投资并做出最优的投资决策。政治不稳定如何影响股市动态这一重要的研究问题一直被学者们所忽视。本文主要试图通过调查市场回报、波动性和基于谷歌搜索的指数之间的时变相互作用来填补这一空白,特别是在突尼斯革命期间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
The impact of political instability driven by the Tunisian revolution on the relationship between Google search queries index and financial market dynamics
PurposeThis paper examines the impact of political instability on the investors' behavior, measured by Google search queries, and on the dynamics of stock market returns.Design/methodology/approachFirst, by using the DCC-GARCH model, the authors examine the effect of investor sentiment on the Tunisian stock market return. Second, the authors employ the fully modified dynamic ordinary least square method (FMOL) to estimate the long-term relationship between investor sentiment and Tunisian stock market return. Finally, the authors use the wavelet coherence model to test the co-movement between investor sentiment measured by Google Trends and Tunisian stock market return.FindingsUsing the dynamic conditional correlation (DCC), the authors find that Google search queries index has the ability to reflect political events especially the Tunisian revolution. In addition, empirical results of fully modified ordinary least square (FMOLS) method reveal that Google search queries index has a slightly higher effect on Tunindex return after the Tunisian revolution than before this revolution. Furthermore, by employing wavelet coherence model, the authors find strong comovement between Google search queries index and return index during the period of the Tunisian revolution political instability. Moreover, in the frequency domain, strong coherence can be found in less than four months and in 16–32 months during the Tunisian revolution which show that the Google search queries measure was leading over Tunindex return. In fact, wavelet coherence analysis confirms the result of DCC that Google search queries index has the ability to detect the behavior of Tunisian investors especially during the period of political instability.Research limitations/implicationsThis study provides empirical evidence to portfolio managers that may use Google search queries index as a robust measure of investor's sentiment to select a suitable investment and to make an optimal investments decisions.Originality/valueThe important research question of how political instability affects stock market dynamics has been neglected by scholars. This paper attempts principally to fill this void by investigating the time-varying interactions between market returns, volatility and Google search based index, especially during Tunisian revolution.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Nomination and remuneration committee: a review of literature Short-sale constraints and stock returns: a systematic review Emerging market analysis of passive and active investing under bear and bull market conditions Geopolitical risk, economic policy uncertainty, financial stress and stock returns nexus: evidence from African stock markets Corporate climate change disclosures and capital structure strategies: evidence from Türkiye
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1