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This paper examines the impact of political instability on the investors' behavior, measured by Google search queries, and on the dynamics of stock market returns.

First, 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.

Using 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.

This 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.

The 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.

The purpose of this paper is to study a novel and direct measurement of investor sentiment index in the Tunisian stock market that overcomes the weaknesses of a well-known investor sentiment index by Baker and Wurgler (2006, 2007).

Based on the data of 43 firms of the Tunisian stock market index (Tunindex) over the period 2004–2016, the author constructs a monthly investor sentiment that reflects both the economic fundamentals and the investor sentiment components. Seven indirect indicators collected from investor sentiment literature and Tunisian stock exchange were analyzed. Specifically, after accounting to remove the sentiment component for macroeconomic factors, the author estimates each sentiment proxy with a number of controlling variables. The residual from the estimation is used to define the author’s measure of excessive investor sentiment. To determine the best timing of sentiment indicators, the author employs a factor sentiment series as the first principal component of these total seven sentiment proxies and their lags of a month. Furthermore, by capturing the highest saturations with the first factor analysis, the author regressed each selected indicator’s lead or one-month lag in a second linear principal component analysis to reach the author’s Tunisian market’s total sentiment index.

The results show that all employed indicators may reflect the investor sentiment on the Tunisian stock market. The findings also indicate significant evidence that the author’s sentiment index takes into consideration the political and economic events such as the Jasmine Revolution experienced by Tunisia during the period from January 2, 2004 to December 30, 2016. Moreover, investor sentiment index flow appears to be one leading mechanism for the performance of Tunindex.

Results found have clearly shown that the author’s seven indirect indicators can reflect investor sentiment in the Tunisian context. The various sentiment proxies are bullish indicators of investor sentiment. Brown and Cliff (2004) argue that the higher bull/bear ratio, the more investor sentiment is bullish. An important value of price–earnings ratio implies that the level of investor confidence as for change in market is also important. Liquidity measured by trading volume, market turnover ratio and liquidity ratio reflects individual investor sentiment. Otherwise, it seems that investors only invest when they are optimistic and reduce market liquidity once they became pessimistic. The monthly response rate to initial public offerings (IPOs) represents a bullish sentiment indicator. Indeed, the more optimistic investors are, the higher the response rate to IPOs. Investor satisfaction also reflects investor sentiment. In other words, a high level of satisfaction translates an important level of optimism. In addition, the author also recognizes that the authors’ Tunisian sentiment index follow general trend of stock market prices and appears to be an important determinant of Tunindex returns during the period of study, from January, 2004 to December, 2016. The author suggests investor sentiment can help predict Tunindex returns, distinguishing between turbulent and tranquil periods in the financial market. The graphical illustration of monthly investor sentiment index shows that it captures extreme events such as the Tunisian revolution of January, 2011, also known as the Jasmine revolution which marked the start of the Arab Spring and the consequences of economic and political turmoil in Tunisia that have disrupted economic activity in the next few years. Like all research work, the current research paper has certain limitations. The choice of control variables allowing the author to separate sentiment component of that fundamental might be criticized. Moreover, there is no unanimous number of control variables but they are chosen according to data availability. The author also believes that one of the study’s weaknesses is that the author has not examined the impact of investor sentiment on the Tunisian stock market. For future interesting avenues of research, the author proposes, first, to study the effect of investor sentiment on financial asset returns and check, second, if sentiment factor constitutes an additional source of business risk valued by the marketplace.

Previously elaborated research works, dealing with the political uncertainty effect on stock market, have been primarily concerned with such political events as terrorist attacks, elections, wars, natural catastrophes and financial crashes. Such little research has been concerned with civil uprisings and revolutionary movements, as crucial sources of political uncertainty. The purpose of this paper is to study the impact of political uncertainty (resulting from the Tunisian Revolution) on the volatility of major sectorial stock indices in the Tunisian Stock Exchange (TSE).

The authors apply the fractionally integrated exponential generalized autoregressive conditional heteroscedasticity model (FIEGARCH), which helps maintain a direct shock-persistence as well as a shock asymmetric volatility measurement. This model is applied to the daily returns relevant to nine sectorial stock indices and to the Tunisian benchmark index (TUNINDEX) with respect to three sub-periods (before, during and follows the Tunisian Revolution).

The reached findings suggest that the shock impact throughout the Revolution period on construction, industries, consumer services, financial services, financial companies indices’ sectorial and the TUNINDEX return volatilities have proven to be permanent, while its persistence on the other indices has been discovered to be transitory. In addition, the achieved results appear to reveal a low leverage effect on all indices. This result seems to be very important since the Tunisian Revolution turns out to have a very important effect on the TSE.

The paper’s empirical contribution lies in using the FIEGARCH approach to model the Tunisian sectorial indices’ volatility dynamics, persistence degree and leverage effect. This contribution goes a long way in helping regulators and international investors to further recognize the extent to which political instability does participate in affecting the TSE.

The purpose of this paper is to analyze the impact of public and private information of Tunisian firms on stock liquidity.

The paper uses a sample of 41 Tunisian firms listed in Tunis Stock Exchange for the year 2007. Public information disclosed in annual reports and in web sites is measured by two self‐constructed disclosure indexes. To assess private information the authors use imbalance order flows. The stock liquidity proxy used in the study is Liu's multidimensional measure. Ordinary least squares (OLS) regression is applied to model the relationship between firm's information environment and stock liquidity.

First, the results provide evidence that public and private information are independent. Second, Tunisian investors do not trust the information disclosed in both annual reports and web sites, consequently it has no effect on stock liquidity, in contrast with private information. This result implies that Tunisian investors are overconfident and rely only on their private information.

The paper's findings indicate that Tunisian regulation efforts to enhance corporate transparency are not sufficient. Hence, Tunisian firms need more incentives to disclose more information to investors.

This paper, to the authors’ best knowledge, is the first to investigate the effect of both private and public information on stock liquidity. Moreover, the authors were not limited to annual reports as the only source of public information, as were prior papers, because public information was assessed in both annual reports and corporate web sites.

This chapter examines the existence of dynamic herding behavior by Tunisian investors in the Tunisia stock market during the revolution period of 2011–2013. The sample covers all Tunindex daily returns as a proxy for the Tunisia stock exchange index over the period 2007–2018. The author modifies the cross-sectional absolute deviation model to include all market conditions (bull and bear markets) and the geopolitical crisis effect corresponding to the Tunisian Jasmine revolution during 2011–2013, and show that herding is indeed not present in the Tunisia stock market including during its turmoil periods. These findings imply that the Tunisian emerging financial market became more vulnerable to adverse herding behavior after the revolution. There is also a clear implication for capitalist firms and angel investors in Tunisia that adverse herding behavior tends to exist on days of higher uncertainty and information asymmetry.

The purpose of this study is to investigate the impact of government policies adopted by the Tunisian government to cope with the COVID-19 sanitary crisis on stock market return.

The author uses daily data from March 2, 2020, to July 23, 2021.

The author finds that policies interventions have a negative impact on Tunisia's stock market, particularly stock market returns due to stringency, confinement and health measures. Also, Government announcements regarding economic has a negative impact on Tunisia's stock market but this impact is insignificant. By conducting an additional analysis, the author shows that the government interventions policies amplify the negative effect of COVID-19 on stock returns.

These results will be useful for policy authorities seeking to consider the advantages and drawbacks of government measures. Finally, a legislative proposal about the audit of public debt should be included in the Constitution to spur Tunisia's economic and social recovery.

This study contributes to the related literature in two ways: First, it is the first study to examine the impact of government actions on stock market performance. Second, it bridges a gap in the literature by investigating the case of Tunisia, because most studies focus on developed and emerging economies.

This study aims to explore the failures of Tunisian secondary corporate bond market liquidity to understand the determinants of corporate bond market liquidity at large.

We adopted a qualitative approach to studying the Tunisian Stock Exchange. Dealers’ perceptions were collected through semi-structured face-to-face interviews; the data was recorded, transcribed and thematically analysed.

Secondary corporate bond market failures are due, in part, to microstructural choices – especially the use of an over-the-counter market as a trading venue. The absence of a corporate bond yield curve, a narrow investor base, market participants’ lack of financial education and authorities’ attitudes are equally responsible.

This study is useful to researchers, policymakers and practitioners, as it identifies microstructural and other factors affecting the Tunisian secondary corporate bond market. We interviewed only Tunisian dealers while ignoring other categories of market participants. Furthermore, a focus group discussion could have improved our understanding of the determinants of the Tunisian secondary corporate bond market.

This paper aimed to qualitatively discuss several issues related to the Tunisian secondary corporate bond market. To date, little academic research has addressed this topic in the illiquid and non-transparent corporate bond markets.

The purpose of this paper is to present a new strategy of portfolio selection.

After making a comparative survey of different strategies of portfolio selection adopted by portfolio managers in Tunisia, the paper proposes a new strategy, which it calls weighted overreaction strategy. This strategy consists in over‐weighting the stocks having bad performances in the past.

The new proposed strategy turned out to be more performing than size, PER, and overreaction strategies in the Tunisian stock market via a mean equality test. Those who adopt it should create a loser portfolio and should sell it at a later period (12 months) and generate average annual returns of 241.75 percent.

This result deserves generalization to other stock markets. As the Tunisian stock market is marked by its looseness and low capitalization, applying this strategy over similar or more developed market would open the way for research aiming to define other strategies and to select the best one for each market. Indeed, it should investigate investors' behavior, which is certainly not the same in each stock market and outline the specific strategy for each market.

The weighted overreaction strategy generated a considerable gain compared to other portfolios.

The new proposed strategy turned out to be more performing than the other ones.

The purpose of this paper is to investigate the effect of forecast earnings’ revision on the evolution of securities prices in the Tunisian stock market.

A portfolio study of investor reaction and stock prices following revisions is first conducted to highlight the existence of abnormal return related to analysts’ earnings revisions. Analysis is then supplemented by a second empirical investigation based on the panel data to quantify the effect of revision on the abnormal profitability of securities.

The evidence found in this paper validates the fundamental theoretical hypothesis according to which the psychological bias resulting from the effect of the forecast earnings revision is related to the abnormal profitability of the securities. The authors conclude the importance of the revision impact on investors’ behavior on one hand, and the informational content of the analysts’ forecasts and the biases which they lead on the other hand.

Globally, the empirical illustrations largely validate the findings of behavioral models particularly that of Kormendi and Lippe (1987), Cornell and Letsman (1989), Beaver et al. (2008) which states that investors under psychological bias, react to the effect of forecast earnings revision by an abnormal variation in stock prices.

The purpose of this study is to investigate the impact of terrorist attacks on the volatility and returns of the stock market in Tunisia.

The employed sample comprises 1250 trading day from the Tunisian stock index (Tunindex) and stock closing prices of 64 firms listed on the Tunisian stock market (TSM) from January 2011 to October 2015. The research opts for the general autoregressive conditional heteroscedasticity (GARCH) and exponential generalized conditional heteroscedasticity (EGARCH) models framework in addition to the event study method to further assess the effect of terrorism on the Tunisian equity market.

The baseline results document a substantive impact of terrorism on the returns and volatility of the TSM index. In more details, the findings of the event study method show negative significant effects on mean abnormal returns with different magnitudes over the events dates. The outcomes propose that terrorism profoundly altered the behavior of the stock market and must receive sufficient attention in order to protect the financial market in Tunisia.

Very few evidence is found on the financial effects of terrorism over transition to democracy cases. This paper determines the salient reaction of the stock market to terrorism during democratic transition. The findings of this study shall have relevant implications for stock market participants and policymakers.