Googling Investor’s Sentiment: Powerful Measure in Conventional and Islamic MENA Financial Markets

Trichilli, Yousra; Abdelhédi, Mouna; Abbes, Mouna Boujelbène

doi:10.1080/10168737.2018.1522055

Cited by 18 publications

(15 citation statements)

References 26 publications

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“…In fact, during the Tunisian revolution, the Tunisian investor is increased his connections to Internet to get access to the new information concerning his investment and consequently his searched frequency has increased which lead to an significant high correlation between Tunindex return and investor's sentiment. Furthermore, these empirical findings are consistent with those obtained by Trichilli et al (2018), in which the googling investor's sentiment leads its stock market returns in the almost of MENA financial markets since wavelet coherency analysis indicates that investor's sentiment and returns are strongly correlated.…”

Section: Comovement Betweensupporting

confidence: 88%

“…Along these lines, Cheema and Nartea (2018) have found that investor sentiment indexes of both Baker and Wurgler (2006) and Huang et al (2014) were contrarian predictor of aggregate stock market returns at all horizons but only during high sentiment states. Trichilli et al (2018) have studied the impact of googling investor's sentiment on the monthly Islamic and conventional index returns during the period 2004-2016. They have indicated that investors can use googling investor's sentiment as an indicator to predict returns and volatility of MENA financial markets.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Fifth, we calculate the monthly change in SVI (ΔSVI) for each search term. Then we optimize the extreme observations, eliminate the seasonality and normalize the time series to make them comparable to finally get the change weekly adjusted search volume (ΔASVI) (Trichilli et al, 2018;Trichilli et al, 2019;Trichilli et al, 2020a;Trichilli et al, 2020b).…”

Section: Constructing the Google Search Queries Indexmentioning

confidence: 99%

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The impact of political instability driven by the Tunisian revolution on the relationship between Google search queries index and financial market dynamics

Trichilli

Abbes

Zouari

2020

JCMS

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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.

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Section: Comovement Betweensupporting

confidence: 88%

Section: Literature Reviewmentioning

confidence: 99%

Section: Constructing the Google Search Queries Indexmentioning

confidence: 99%

See 1 more Smart Citation

The impact of political instability driven by the Tunisian revolution on the relationship between Google search queries index and financial market dynamics

Trichilli

Abbes

Zouari

2020

JCMS

Self Cite

View full text Add to dashboard Cite

show abstract

“…Their findings exhibited higher predictability for sentiment-induced keywords in Islamic stocks than non-Islamic stocks. Similarly, Trichilli, Abdelhédi, and Boujelbène (2018) examined FEARS investor sentiment predictability for Islamic stock returns in Middle East and North Africa (MENA) stock markets. They concluded that investor sentiment using search data has higher predictability in Islamic stock markets.…”

Section: Investor Sentiment In the Islamic Stock Marketmentioning

confidence: 99%

A new sentiment index for the Islamic stock market

Khan

Ahmad

Azmi

et al. 2019

Investment Analysts Journal

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This study attempts to examine the predictability of Google search volume (GSV) and to construct an appropriate investor sentiment index for Islamic stock markets for seven United States (US) Islamic stock indices. Using principal component analysis, we construct an appropriate investor sentiment index for Islamic stock markets that depicts more persistent and higher R-squared values for all these seven US Islamic stocks indices compared to the original Financial and Economic Attitudes Revealed by Search (FEARS) sentiment index of Da, Engelberg, and Gao (2015). The observed results can be attributed to the construction of our investor sentiment index as we have included keywords active in the Islamic stock markets. The findings of this study provide strong predictability evidence for our new sentiment index in the Islamic stock markets.

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“…Indeed, the rapid growth of social media content on the internet and the highly growing internet usage over the past few years have led to the exploding interests to measure the investor's sentiment directly via Google Trends, which is a useful tool to reveal information demand. Moreover, many prevalent studies have used the Google search volume as a measure of the investor's sentiment (Aouadi et al, 2013;Da et al, 2011;Vozlyublennaia, 2014;Dimpfl and Jank, 2016;Trichilli et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Predicting the effect of Googling investor sentiment on Islamic stock market returns

Trichilli¹,

Abbes²,

Masmoudi³

2020

IMEFM

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Purpose The purpose of this paper is to evaluate the capability of the hidden Markov model using Googling investors’ sentiments to predict the dynamics of Islamic indexes’ returns in the Middle East and North Africa (MENA) financial markets from 2004 to 2018. Design/methodology/approach The authors propose a hidden Markov model based on the transition matrix to apprehend the relationship between investor’s sentiment and Islamic index returns. The proposed model facilitates capturing the uncertainties in Islamic market indexes and the possible effects of the dynamics of Islamic market on the persistence of these regimes or States. Findings The bearish state is the most persistent sentiment with the longest duration for all the MENA Islamic markets except for Jordan, Morocco and Qatar. In addition, the obtained results indicate that the effect of sentiment on predicting the future Islamic index returns is conditional on the MENA States. Besides, the estimated mean returns for each state indicates that the bullish and calm states are ideal for investing in Islamic indexes of Bahrain, Oman, Morocco, Kuwait, Saudi Arabia and United Arab Emirates. However, only the bullish state is ideal for investing Islamic indexes of Jordan, Egypt and Qatar. Research limitations/implications This paper has used data at a monthly frequency that can explain only short-term dynamics between Googling investor’s sentiment and the MENA Islamic stock market returns. Moreover, this work can be done on the stock markets while taking into account the specificity of each activity sector. Practical implications In fact, the findings of this paper are helpful for academics, analysts and practitioners, and more specifically for the Islamic MENA financial investors. Moreover, this study provides useful insights not only into the duration of the relationship between the indexes’ returns and the investors’ sentiments in the five states but also into the transition probabilities which have implications for how investors could be guided in their choice of future investment in a portfolio with Islamic indexes. Findings of this paper are important and valuable for policy-makers and investors. Thus, predicting the effect of Googling investors’ sentiment on the MENA Islamic stock market dynamics is important for portfolio diversification by domestic and international investors. Moreover, the results of this paper gave new insights into financial analysts about the dynamic relationship between Googling investors’ sentiment and Islamic stock market returns across market regimes. Therefore, the findings of this study might be useful for investors as they help them capture the unobservable dynamics of the changes in the investors’ sentiment regimes in the MENA financial markets to make successful investment decisions. Originality/value To the best of the authors’ knowledge, this paper is the first to use the hidden Markov model to examine changes in the Islamic index return dynamics across five market sentiment states, namely the depressed sentiment (S1), the bullish sentiment (S2), the bearish sentiment (S3), the calm sentiment (S4) and the bubble sentiment (S5).

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Googling Investor’s Sentiment: Powerful Measure in Conventional and Islamic MENA Financial Markets

Cited by 18 publications

References 26 publications

The impact of political instability driven by the Tunisian revolution on the relationship between Google search queries index and financial market dynamics

The impact of political instability driven by the Tunisian revolution on the relationship between Google search queries index and financial market dynamics

A new sentiment index for the Islamic stock market

Predicting the effect of Googling investor sentiment on Islamic stock market returns

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