PurposeThis article unveils first the lead–lag structure between the confirmed cases of COVID-19 ... more PurposeThis article unveils first the lead–lag structure between the confirmed cases of COVID-19 and financial markets, including the stock (DJI), cryptocurrency (Bitcoin) and commodities (crude oil, gold, copper and brent oil) compared to the financial stress index. Second, this paper assesses the role of Bitcoin as a hedge or diversifier by determining the efficient frontier with and without including Bitcoin before and during the COVID-19 pandemic.Design/methodology/approachThe authors examine the lead–lag relationship between COVID-19 and financial market returns compared to the financial stress index and between all markets returns using the thermal optimal path model. Moreover, the authors estimate the efficient frontier of the portfolio with and without Bitcoin using the Bayesian approach.FindingsEmploying thermal optimal path model, the authors find that COVID-19 confirmed cases are leading returns prices of DJI, Bitcoin and crude oil, gold, copper and brent oil. Moreover, the authors find a strong lead–lag relationship between all financial market returns. By relying on the Bayesian approach, findings show when Bitcoin was included in the portfolio optimization before or during COVID-19 period; the Bayesian efficient frontier shifts to the left giving the investor a better risk return trade-off. Consequently, Bitcoin serves as a safe haven asset for the two sub-periods: pre-COVID-19 period and COVID-19 period.Practical implicationsBased on the above research conclusions, investors can use the number of COVID-19 confirmed cases to predict financial market dynamics. Similarly, the work is helpful for decision-makers who search for portfolio diversification opportunities, especially during health crisis. In addition, the results support the fact that Bitcoin is a safe haven asset that should be combined with commodities and stocks for better performance in portfolio optimization and hedging before and during COVID-19 periods.Originality/valueThis research thus adds value to the existing literature along four directions. First, the novelty of this study lies in the analysis of several financial markets (stock, cryptocurrencies and commodities)’ response to different pandemics and epidemics events, financial crises and natural disasters (Correia et al., 2020; Ma et al., 2020). Second, to the best of the authors' knowledge, this is the first study that examine the lead–lag relationship between COVID-19 and financial markets compared to financial stress index by employing the Thermal Optimal Path method. Third, it is a first endeavor to analyze the lead–lag interplay between the financial markets within a thermal optimal path method that can provide useful insights for the spillover effect studies in all countries and regions around the world. To check the robustness of our findings, the authors have employed financial stress index compared to COVID-19 confirmed cases. Fourth, this study tests whether Bitcoin is a hedge or diversifier given this current pandemic situation using the Bayesian approach.
The aim of this paper is to investigate whether the dynamic integration across a large set of dev... more The aim of this paper is to investigate whether the dynamic integration across a large set of developed and emerging Islamic stock markets allows potential diversification benefits in tranquil and turmoil periods. Using the multivariate cointegration test, we find the presence of long-run equilibrium relationship among Islamic stock markets of similar economic grouping. While, Islamic stock markets from different economic grouping are partially segmented. Empirical results of estimated Vector Error Correction Model provide a lowest level of short run integration among the economic grouping of European-Asian emerging markets, MENA-Latin American and European-Latin American Islamic stock markets. In addition, the level of integration and causality relations among Islamic stock markets tends to change over time, mainly during periods characterized by financial crises. Overall, our results suggest that Shariah compliant stocks could offer potential diversification benefits by considering different economic grouping such as that in developed and emerging countries.
Purpose-This paper examines the impact of political instability on the investors' behavior, measu... more Purpose-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. Design/methodology/approach-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. Findings-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. Research limitations/implications-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. Originality/value-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.
Asia-pacific Journal of Business Administration, Jul 19, 2021
PurposeThe aim of this study was to investigate the dynamic network connectedness between stock m... more PurposeThe aim of this study was to investigate the dynamic network connectedness between stock markets and commodity futures and its implications on hedging strategies. Specifically, the authors studied the impact of the 2014 oil price drop and coronavirus disease 2019 (COVID-19) pandemic on risk spillovers and portfolio allocation among stock markets (United States (SP500), China (SSEC), Japan (Nikkei 225), France (CAC40) and Germany (DAX)) and commodities (oil and gold).Design/methodology/approachIn this study, the authors used the Baba, Engle, Kraft and Kroner–generalized autoregressive conditional heteroskedasticity (BEKK–GARCH) model to estimate shock transmission among the five financial markets and the two commodities. The authors rely on Diebold and Yılmaz (2014, 2015) methodology to construct network-associated measures.FindingsRelying on the BEKK–GARCH, the authors found that the recent health crisis of COVID-19 intensified the volatility spillovers among stock markets and commodities. Using the dynamic network connectedness, the authors showed that at the 2014 oil price drop and the COVID-19 pandemic shock, the Nikkei225 moderated the transmission of volatility to the majority of markets. During the COVID-19 pandemic, the commodity markets are a net receiver of volatility shocks from stock markets. In addition, the SP500 stock market dominates the network connectedness dynamic during the COVID-19 pandemic, while DAX index is the weakest risk transmitter. Regarding the portfolio allocation and hedging strategies, the study showed that the oil market is the most vulnerable and risky as it was heavily affected by the two crises. The results show that gold is a hedging tool during turmoil periods.Originality/valueThis study contributes to knowledge in this area by improving our understanding of the influence of fluctuations in oil prices on the dynamics of the volatility connection between stock markets and commodities during the COVID-19 pandemic shock. The study’s findings provide more implications regarding portfolio management and hedging strategies that could help investors optimize their portfolios.
Asian Academy of Management Journal of Accounting and Finance, 2015
In this paper, we test the role of the American investor sentiment in the amplification of the su... more In this paper, we test the role of the American investor sentiment in the amplification of the subprime financial crisis by examining the volatility spillover between the Standard & Poor's 500 Index (S&P 500) returns and investor sentiment measures. We show a significant effect of investor sentiment variation on return and volatilities, and we reveal the contribution of returns shocks to the variability of investor sentiment variation during the subprime crisis. Moreover, we notice the determinant role of investor sentiment in the amplification of the subprime financial crisis by the intense spillover of volatility from investor sentiment to returns. Our finding indicates that investors can use investor sentiment as an indicator to predict returns-volatility.
International Journal of Managerial and Financial Accounting, 2013
This study offers a new perspective on crisis transmission through an examination of herding cont... more This study offers a new perspective on crisis transmission through an examination of herding contagion during 2008-global financial crisis across Asian and European financial markets. Using a bivariate GARCH-BEKK model, results show that the volatility of US stock market during the subprime crisis is significantly transmitted to Asian and European financial markets. Moreover, UK and Swiss financial markets present an important role in emitting volatility to Asian markets. In addition, Singapore constitutes the Asian channel through which crisis is transmitted across global equity markets. Using Kalman filter, residuals of index returns are estimated after controlling for macroeconomic-fundamentals and global shocks. All residuals showed enhanced volatility during the financial crisis period of mid 2007-2008. Moreover, the crosscountry residual correlation between US markets and European and Asian markets increases in the turmoil period as compared to tranquil period. This finding is evidence of the presence of herding contagion in Asian and European markets during US crisis, and that can partly explains the severity of the crisis.
PurposeIn this paper, the authors investigate the impact of the confirmation bias on returns, exp... more PurposeIn this paper, the authors investigate the impact of the confirmation bias on returns, expectations and hedging of optimistic and pessimistic traders in the cryptocurrencies, commodities and stock markets before and during COVID-19 periods.Design/methodology/approachThe authors investigate the impact of the confirmation bias on the estimated returns and the expectations of optimistic and pessimistic traders by employing the financial stochastic model with confirmation bias. Indeed, the authors compute the optimal portfolio weights, the optimal hedge ratios and the hedging effectiveness.FindingsThe authors find that without confirmation bias, during the two sub periods, the expectations of optimistic and pessimistic trader’s seem to convergence toward zero. However, when confirmation bias is particularly strong, the average distance between these two expectations are farer. The authors further show that, with and without confirmation bias, the optimal weights (the optimal hedge ratios) are found to be lower (higher) for all pairs of financial market during the COVID-19 period as compared to the pre-COVID-19 period. The authors also document that the stronger the confirmation bias is, the lower the optimal weight and the higher the optimal hedge ratio. Moreover, results reveal that the values of the optimal hedge ratio for optimistic and pessimistic traders affected or not by the confirmation bias are higher during the COVID-19 period compared to the estimates for the pre-COVID period and inversely for the optimal hedge ratios and the hedging effectiveness index. Indeed, either for optimists or pessimists, the presence of confirmation bias leads to higher optimal hedge ratio, higher optimal weights and higher hedging effectiveness index.Practical implicationsThe findings of the study provided additional evidence for investors, portfolio managers and financial analysts to exploit confirmation bias to make an optimal portfolio allocation especially during COVID-19 and non-COVID-19 periods. Moreover, the findings of this study might be useful for investors as they help them to make successful investment decision in potential hedging strategies.Originality/valueFirst, this is the first scientific work that conducts a stochastic analysis about the impact of emotional biases on the estimated returns and the expectations of optimists and pessimists in cryptocurrency and commodity markets. Second, the originality of this study stems from the fact that the authors make a comparative analysis of hedging behavior across different markets and different periods with and without the impact of confirmation bias. Third, this paper pays attention to the impact of confirmation bias on the expectations and hedging behavior in cryptocurrencies and commodities markets in extremely stressful periods such as the recent COVID-19 pandemic.
International Journal of Islamic and Middle Eastern Finance and Management, Mar 2, 2023
Purpose This paper aims to examine the dynamic spillover effects and network connectedness betwee... more Purpose This paper aims to examine the dynamic spillover effects and network connectedness between the oil prices and the Islamic and conventional financial markets in the Gulf Cooperation Council countries. The focus is on network connectedness during the 2008–2009 global financial crisis, the 2014–2016 oil crisis and the COVID-19 pandemic. The authors use daily data covering the period from January 1, 2007 to April 14, 2022. Design/methodology/approach This study applies a spillover analysis and connectedness network to investigate the risk contagion among the Islamic and conventional stock–bond markets. The authors rely on Diebold and Yilmaz’s (2012, 2014) methodology to construct network-associated measures. Findings The results suggest that overall connectedness among financial market uncertainties increased during the global financial crisis, the oil price collapse of 2014–2016 and the COVID-19 crisis. In addition, the authors show that the contribution of oil shocks to the financial system is limited, as the oil market was a net receiver during the 2014 oil shock and the COVID-19 crisis. On the other hand, the Islamic and conventional stock markets are extensive sources of network effects on the oil market and Islamic and conventional bond markets. Furthermore, the authors found that the Sukuk market was significantly affected by the COVID-19 pandemic, whereas the conventional and Islamic stock markets were the highest transmitters of shocks during the COVID-19 pandemic outbreak. Moreover, oil revealed a weak connectedness with the Islamic and conventional stock markets during the COVID-19 health crisis, implying that it helps provide diversification benefits for international portfolio investors. Originality/value This study contributes to this field by improving the understanding of the effect of fluctuations in oil prices on the dynamics of the volatility connection between oil and Islamic and conventional financial markets during times of stress through a network connectedness framework. The main results of this study highlight the role of oil in portfolio allocation and risk minimization when investing in Islamic and conventional assets.
Cours financement et budgétisation Les concepts de base des projets d'investissement 2 Mouna Bouj... more Cours financement et budgétisation Les concepts de base des projets d'investissement 2 Mouna Boujelbène Abbes Université Virtuelle de Tunis Chapitre 1 : Les concepts de base des projets d'investissement Objectifs du chapitre Ce chapitre a pour objectifs de : Distinguer entre les différents types d'investissement. Reconnaître les différents paramètres de l'investissement. Evaluer les cash flows nets des investissements. Cours financement et budgétisation Les concepts de base des projets d'investissement 3 Mouna Boujelbène Abbes Université Virtuelle de Tunis 3. Classification des investissements 3.1. Classification des investissements selon leur nature a. La distinction investissement matériel/investissement immatériel Cette distinction est l'une des plus anciennes dans la mesure où jusque les années soixante, dans un environnement essentiellement industriel, on associait à la notion d'investissement, les seuls investissements matériels qui, à travers l'acquisition de machines ou la construction et l'aménagement d'immeubles destinées à la production, constituaient l'essentiel des dépenses en capital des sociétés. Contrairement à l'investissement matériel, l'OCDE définit l'investissement immatériel, comme "toutes les dépenses de long terme, autres que l'achat d'actifs fixes, que les entreprises consentent dans le but d'améliorer leurs résultats. En plus des investissements de technologie (R&D ou acquisition de ses résultats), est investissement immatériel tout investissement dans la formation, dans les relations de travail, dans les structures de gestion, dans l'organisation de la production, l'élaboration des relations commerciales et technologiques, l'investigation des marchés, l'acquisition et l'exploitation de logiciels". b. La distinction Investissement de remplacement/de modernisation/ou de capacité Cours financement et budgétisation Les concepts de base des projets d'investissement 4 Mouna Boujelbène Abbes Université Virtuelle de Tunis de réussite, ces investissements fourniront une chance de développement importante à l'entreprise qui les a initiés, mais qui en cas d'échec, ils risqueraient d'obérer ses chances de survie. 3.2. Classification des investissements selon la nature de leurs relations réciproques au sein d'un programme d'investissement Cette classification est fondée sur le degré de dépendance entre les projets d'un programme d'investissement. On peut distinguer les projets dépendants, les projets indépendants, les projets mutuellement exclusifs. ales projets dépendants sont des projets complémentaires dont la réalisation de l'un exige au préalable la réalisation des autres. b-les projets indépendants où la décision concernant l'un n'affecte en rien la décision concernant l'autre : l'acceptation ou le rejet de l'un n'a aucun effet sur l'acceptation ou le rejet de l'autre. c-les projets mutuellement exclusifs sont des projets dont la réalisation de l'un d'entre eux rend impensable la réalisation des autres : l'adoption de l'un entraîne automatiquement le rejet de l'autre. 4. Les paramètres d'un projet d'investissement L'évaluation de la rentabilité financière d'un projet repose sur le calcul de certains paramètres : Cours financement et budgétisation Chapitre 2 : Choix des investissements en avenir certain 11 Mouna Boujelbène Abbes Université Virtuelle de Tunis Objectifs du chapitre L'apprenant sera capable : D'estimer les différents critères d'évaluation des projets en avenir certain. De choisir un projet d'investissement en avenir certain. Chapitre 3 : Choix des investissements en avenir incertain 26 Mouna Boujelbène Abbes Université Virtuelle de Tunis Objectifs du chapitre Ce chapitre a pour objectifs d' : Analyser et interpréter les méthodes empiriques de prise en considération du risque. Evaluer un projet d'investissement dans un contexte de risque et dans un contexte de portefeuille. 12 12 Cours financement et budgétisation Chapitre 5 : Structure optimale du capital 44 Mouna Boujelbène Abbes Université Virtuelle de Tunis Objectifs du chapitre Ce chapitre a pour objectifs de : Distinguer entre les différentes théories de structure du capital Identifier l'impact de la décision de financement sur la décision d'investissement. Cours financement et budgétisation Chapitre 6 : La budgétisation des projets 54 Mouna Boujelbène Abbes Université Virtuelle de Tunis Objectifs du chapitre Ce chapitre a pour objectifs de : Préparer le budget prévisionnel d'un projet. Préparer le plan de financement prévisionnel d'un projet.
The paper aims to explain the risk taking in Islamic and conventional banks from a behavioral pro... more The paper aims to explain the risk taking in Islamic and conventional banks from a behavioral prospect as proposed by Kahneman and Tversky (1979) and Tversky and Kahneman (1992). We used the thermal optimal path (TOP) method to test the prospect theory predictions on a sample of 128 Islamic and conventional banks operating in 13 Middle Eastern and North African (MENA) countries. We found significant correlation coefficients for each measure of the returns, except with the IINTL measure for conventional banks, which is situated below the target and the ROE measure for Islamic banks, which is situated below the target and conventional banks, which is located above the target. Indeed, in the areas of a loss below the target level, the correlation coefficient results are positive for the ROE, ROA and IINTL measures for both Islamic and conventional banks, suggesting an excessive risk-taking behavior. Furthermore, empirical results revealed that unlike the return measures, all the other measures, except the EQTA measure for conventional banks situated above the target, are significant. The results also indicated that for the areas below the benchmark, positive correlation coefficients are obtained for all the risk measures for conventional and Islamic banks except for the LLPTL measure. In fact, these results have several implications for policymakers and banks’ regulators who better supervise the banking system. Moreover, these results show how bank managers behave facing the risk.
This paper sheds lights on the predictive power of googling investor sentiment on MENA market ind... more This paper sheds lights on the predictive power of googling investor sentiment on MENA market indexes returns from 2004 to 2018 by using a novel approach based on the thermal optimal path model, Diebold-Yilmaz Spillover Indexes and the wavelet coherence model. Thermal optimal path reveals that googling investor sentiment exhibits a lead effect for Islamic and conventional indexes returns which is influenced by political, social and economic conditions. Using Diebold-Yilmaz Spillover Indexes, we find that googling investor's sentiment is the main net transmitter of shocks to Saudi Arabia, Egypt, Qatar, Bahrain, Oman and Jordan Islamic market indexes and the majority of conventional indexes. Further, the wavelet coherence model confirms the thermal optimal path results of the leading effect of googling investor sentiment, especially during crises periods. These results depict the robust and significant predictive power of googling investor's sentiment to detect the behavior of investor, especially during instability periods and to predict market returns in MENA financial markets. Consequently, investor can exploit googling investor sentiment measure in portfolio investments and trading strategy in MENA financial markets.
PurposeThis study aims to investigate the impact of the COVID-19 pandemic on both of stock prices... more PurposeThis study aims to investigate the impact of the COVID-19 pandemic on both of stock prices and investor's sentiment in China during the onset of the COVID-19 crisis.Design/methodology/approachIn this study, the ADCC-GARCH model was used to analyze the asymmetric volatility and the time-varying conditional correlation among the Chinese stock market, the investors' sentiment and its variation. The authors relied on Diebold and Yilmaz (2012, 2014) methodology to construct network-associated measures. Then, the wavelet coherence model was applied to explore the co-movements between these variables. To check the robustness of the study results, the authors referred to the RavenPack COVID sentiments and the Chinese VIX, as other measures of the investor's sentiment using daily data from December 2019 to December 2021.FindingsUsing the ADCC-GARCH model, a strong co-movement was found between the investor's sentiment and the Shanghai index returns during the COVID-19 ...
Zenodo (CERN European Organization for Nuclear Research), Jun 30, 2022
Impact of the COVID-19 pandemic on the relationship between uncertainty factors, investor behavio... more Impact of the COVID-19 pandemic on the relationship between uncertainty factors, investor behavioral biases and the stock market reaction 101
Object: This article investigate the impact of the COVID 19 on the relationship between uncertain... more Object: This article investigate the impact of the COVID 19 on the relationship between uncertainty factors (Economic Policy Uncertainty, Equity Market Volatility–Infectious Diseases, Financial Stress) and investors’ behavioral biases (overconfidence, herding, mental accounting and loss aversion) with the US Fintech stock market abnormal returns. Methodology: we analyze this relationship by using Johensen’s cointegration test, Granger causality test and Ordinary least square method (OLS), for the period from July 20, 2016 to December 31, 2021. Results: The Empirical results indicated the presence of a long-run equilibrium relationship between all the studied variables, before and during the COVID-19 pandemic period. In fact, the obtained results indicated that the COVID-19 pandemic is a crucial source for resulting abnormal returns in the US Fintech market. Especially, during the COVID-19 pandemic, the Fintech market under-reacted to the common signal of fina...
European Journal of Management and Business Economics
PurposeThis paper aims to analyze the connectedness between Gulf Cooperation Council (GCC) stock ... more PurposeThis paper aims to analyze the connectedness between Gulf Cooperation Council (GCC) stock market index and cryptocurrencies. It investigates the relevant impact of RavenPack COVID sentiment on the dynamic of stock market indices and conventional cryptocurrencies as well as their Islamic counterparts during the onset of the COVID-19 crisis.Design/methodology/approachThe authors rely on the methodology of Diebold and Yilmaz (2012, 2014) to construct network-associated measures. Then, the wavelet coherence model was applied to explore co-movements between GCC stock markets, cryptocurrencies and RavenPack COVID sentiment. As a robustness check, the authors used the time-frequency connectedness developed by Barunik and Krehlik (2018) to verify the direction and scale connectedness among these markets.FindingsThe results illustrate the effect of COVID-19 on all cryptocurrency markets. The time variations of stock returns display stylized fact tails and volatility clustering for all...
This study aims to predict GCC financial stress on oil market, and GCC Stock and bond markets whi... more This study aims to predict GCC financial stress on oil market, and GCC Stock and bond markets while considering the effect of the 2008 financial crisis, 2014 oil drop price and the 2019 novel COVID-19 outbreak. For this purpose, we use a new approach for predicting the financial stress, based on the One-Dimensional Convolutional Neural Network (1D-CNN). This article introduces a parameters optimization method, which provides the best parameters for 1D-CNN to improve the prediction performance of the financial stress indices. The results suggest that indexes of financial stress help to improve forecasting performance. It implies that the 1D-CNN model shows a better predictive performance in the out-of-sample findings.Regarding the influence of financial stress on hedging between Brent, and financial markets, the outcomes emphasize the role of oil in hedging stock market risks in positive market stress case. Another interesting result is that the out-of-sample estimates for stock-bond markets, hedging with oil have higher variability for negative (positive) financial stress. The findings highlight the predictive information captured by financial stress in accurately forecasting oil market volatility and financial markets, offering a valuable opening for investors to monitor oil market volatility using information on traded assets.
This study investigates the predictive power of the financial stress on the dynamic of the Middle... more This study investigates the predictive power of the financial stress on the dynamic of the Middle East and North Africa (MENA) financial market returns from 2007 to 2021. Based on a Quantile Regression, we show that financial stress has highest predictive abilities at the lower quantiles when the market is bearish. Then, we propose a Hidden Markov Model (HMM) based on the transition matrix to understand the relationship between financial stress index and the MENA stock market dynamics. We find that the effect of financial stress on stock market return reveals the persistence of regimes: Bullish state exists and persists, and has the longest conditional expected duration for the majority of MENA markets, except Bahrain, Qatar and Jordan. However, the transition probability from the bullish to the calm regime is too low for the financial market of Bahrain, United Arab Emirates and Egypt. Besides, the estimated mean returns for each regime divulge that the bearish and calm states are more attractive destination for both portfolio managers and investors.
PurposeIn this paper, the authors investigate the impact of the confirmation bias on returns, exp... more PurposeIn this paper, the authors investigate the impact of the confirmation bias on returns, expectations and hedging of optimistic and pessimistic traders in the cryptocurrencies, commodities and stock markets before and during COVID-19 periods.Design/methodology/approachThe authors investigate the impact of the confirmation bias on the estimated returns and the expectations of optimistic and pessimistic traders by employing the financial stochastic model with confirmation bias. Indeed, the authors compute the optimal portfolio weights, the optimal hedge ratios and the hedging effectiveness.FindingsThe authors find that without confirmation bias, during the two sub periods, the expectations of optimistic and pessimistic trader’s seem to convergence toward zero. However, when confirmation bias is particularly strong, the average distance between these two expectations are farer. The authors further show that, with and without confirmation bias, the optimal weights (the optimal hedg...
Capital and Financing structure are considered of a crucial importance for the operational and fi... more Capital and Financing structure are considered of a crucial importance for the operational and financial sustainability of microfinance institutions (MFIs). Therefore, each decision making process is of the same importance for these institutions. The purpose of this study is to draw attentions toward the microfinance sector and to take into consideration the human factor and the role that managers play in funding and financing modalities and decision making process in microfinance institutions. In this context, this paper explores the differences between conventional and Islamic MFIs’ capital structure choices on one hand. And, reviews the insights provided by the literature examining capital structure decisions and managerial behavioral biases on the other hand. The theoretical and comparative analysis revealed the substantial differences between capital structure of both Conventional and Islamic MFIs. Furthermore, the empirical literature points that managers’ behavioral biases pl...
PurposeThis article unveils first the lead–lag structure between the confirmed cases of COVID-19 ... more PurposeThis article unveils first the lead–lag structure between the confirmed cases of COVID-19 and financial markets, including the stock (DJI), cryptocurrency (Bitcoin) and commodities (crude oil, gold, copper and brent oil) compared to the financial stress index. Second, this paper assesses the role of Bitcoin as a hedge or diversifier by determining the efficient frontier with and without including Bitcoin before and during the COVID-19 pandemic.Design/methodology/approachThe authors examine the lead–lag relationship between COVID-19 and financial market returns compared to the financial stress index and between all markets returns using the thermal optimal path model. Moreover, the authors estimate the efficient frontier of the portfolio with and without Bitcoin using the Bayesian approach.FindingsEmploying thermal optimal path model, the authors find that COVID-19 confirmed cases are leading returns prices of DJI, Bitcoin and crude oil, gold, copper and brent oil. Moreover, the authors find a strong lead–lag relationship between all financial market returns. By relying on the Bayesian approach, findings show when Bitcoin was included in the portfolio optimization before or during COVID-19 period; the Bayesian efficient frontier shifts to the left giving the investor a better risk return trade-off. Consequently, Bitcoin serves as a safe haven asset for the two sub-periods: pre-COVID-19 period and COVID-19 period.Practical implicationsBased on the above research conclusions, investors can use the number of COVID-19 confirmed cases to predict financial market dynamics. Similarly, the work is helpful for decision-makers who search for portfolio diversification opportunities, especially during health crisis. In addition, the results support the fact that Bitcoin is a safe haven asset that should be combined with commodities and stocks for better performance in portfolio optimization and hedging before and during COVID-19 periods.Originality/valueThis research thus adds value to the existing literature along four directions. First, the novelty of this study lies in the analysis of several financial markets (stock, cryptocurrencies and commodities)’ response to different pandemics and epidemics events, financial crises and natural disasters (Correia et al., 2020; Ma et al., 2020). Second, to the best of the authors' knowledge, this is the first study that examine the lead–lag relationship between COVID-19 and financial markets compared to financial stress index by employing the Thermal Optimal Path method. Third, it is a first endeavor to analyze the lead–lag interplay between the financial markets within a thermal optimal path method that can provide useful insights for the spillover effect studies in all countries and regions around the world. To check the robustness of our findings, the authors have employed financial stress index compared to COVID-19 confirmed cases. Fourth, this study tests whether Bitcoin is a hedge or diversifier given this current pandemic situation using the Bayesian approach.
The aim of this paper is to investigate whether the dynamic integration across a large set of dev... more The aim of this paper is to investigate whether the dynamic integration across a large set of developed and emerging Islamic stock markets allows potential diversification benefits in tranquil and turmoil periods. Using the multivariate cointegration test, we find the presence of long-run equilibrium relationship among Islamic stock markets of similar economic grouping. While, Islamic stock markets from different economic grouping are partially segmented. Empirical results of estimated Vector Error Correction Model provide a lowest level of short run integration among the economic grouping of European-Asian emerging markets, MENA-Latin American and European-Latin American Islamic stock markets. In addition, the level of integration and causality relations among Islamic stock markets tends to change over time, mainly during periods characterized by financial crises. Overall, our results suggest that Shariah compliant stocks could offer potential diversification benefits by considering different economic grouping such as that in developed and emerging countries.
Purpose-This paper examines the impact of political instability on the investors' behavior, measu... more Purpose-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. Design/methodology/approach-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. Findings-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. Research limitations/implications-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. Originality/value-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.
Asia-pacific Journal of Business Administration, Jul 19, 2021
PurposeThe aim of this study was to investigate the dynamic network connectedness between stock m... more PurposeThe aim of this study was to investigate the dynamic network connectedness between stock markets and commodity futures and its implications on hedging strategies. Specifically, the authors studied the impact of the 2014 oil price drop and coronavirus disease 2019 (COVID-19) pandemic on risk spillovers and portfolio allocation among stock markets (United States (SP500), China (SSEC), Japan (Nikkei 225), France (CAC40) and Germany (DAX)) and commodities (oil and gold).Design/methodology/approachIn this study, the authors used the Baba, Engle, Kraft and Kroner–generalized autoregressive conditional heteroskedasticity (BEKK–GARCH) model to estimate shock transmission among the five financial markets and the two commodities. The authors rely on Diebold and Yılmaz (2014, 2015) methodology to construct network-associated measures.FindingsRelying on the BEKK–GARCH, the authors found that the recent health crisis of COVID-19 intensified the volatility spillovers among stock markets and commodities. Using the dynamic network connectedness, the authors showed that at the 2014 oil price drop and the COVID-19 pandemic shock, the Nikkei225 moderated the transmission of volatility to the majority of markets. During the COVID-19 pandemic, the commodity markets are a net receiver of volatility shocks from stock markets. In addition, the SP500 stock market dominates the network connectedness dynamic during the COVID-19 pandemic, while DAX index is the weakest risk transmitter. Regarding the portfolio allocation and hedging strategies, the study showed that the oil market is the most vulnerable and risky as it was heavily affected by the two crises. The results show that gold is a hedging tool during turmoil periods.Originality/valueThis study contributes to knowledge in this area by improving our understanding of the influence of fluctuations in oil prices on the dynamics of the volatility connection between stock markets and commodities during the COVID-19 pandemic shock. The study’s findings provide more implications regarding portfolio management and hedging strategies that could help investors optimize their portfolios.
Asian Academy of Management Journal of Accounting and Finance, 2015
In this paper, we test the role of the American investor sentiment in the amplification of the su... more In this paper, we test the role of the American investor sentiment in the amplification of the subprime financial crisis by examining the volatility spillover between the Standard & Poor's 500 Index (S&P 500) returns and investor sentiment measures. We show a significant effect of investor sentiment variation on return and volatilities, and we reveal the contribution of returns shocks to the variability of investor sentiment variation during the subprime crisis. Moreover, we notice the determinant role of investor sentiment in the amplification of the subprime financial crisis by the intense spillover of volatility from investor sentiment to returns. Our finding indicates that investors can use investor sentiment as an indicator to predict returns-volatility.
International Journal of Managerial and Financial Accounting, 2013
This study offers a new perspective on crisis transmission through an examination of herding cont... more This study offers a new perspective on crisis transmission through an examination of herding contagion during 2008-global financial crisis across Asian and European financial markets. Using a bivariate GARCH-BEKK model, results show that the volatility of US stock market during the subprime crisis is significantly transmitted to Asian and European financial markets. Moreover, UK and Swiss financial markets present an important role in emitting volatility to Asian markets. In addition, Singapore constitutes the Asian channel through which crisis is transmitted across global equity markets. Using Kalman filter, residuals of index returns are estimated after controlling for macroeconomic-fundamentals and global shocks. All residuals showed enhanced volatility during the financial crisis period of mid 2007-2008. Moreover, the crosscountry residual correlation between US markets and European and Asian markets increases in the turmoil period as compared to tranquil period. This finding is evidence of the presence of herding contagion in Asian and European markets during US crisis, and that can partly explains the severity of the crisis.
PurposeIn this paper, the authors investigate the impact of the confirmation bias on returns, exp... more PurposeIn this paper, the authors investigate the impact of the confirmation bias on returns, expectations and hedging of optimistic and pessimistic traders in the cryptocurrencies, commodities and stock markets before and during COVID-19 periods.Design/methodology/approachThe authors investigate the impact of the confirmation bias on the estimated returns and the expectations of optimistic and pessimistic traders by employing the financial stochastic model with confirmation bias. Indeed, the authors compute the optimal portfolio weights, the optimal hedge ratios and the hedging effectiveness.FindingsThe authors find that without confirmation bias, during the two sub periods, the expectations of optimistic and pessimistic trader’s seem to convergence toward zero. However, when confirmation bias is particularly strong, the average distance between these two expectations are farer. The authors further show that, with and without confirmation bias, the optimal weights (the optimal hedge ratios) are found to be lower (higher) for all pairs of financial market during the COVID-19 period as compared to the pre-COVID-19 period. The authors also document that the stronger the confirmation bias is, the lower the optimal weight and the higher the optimal hedge ratio. Moreover, results reveal that the values of the optimal hedge ratio for optimistic and pessimistic traders affected or not by the confirmation bias are higher during the COVID-19 period compared to the estimates for the pre-COVID period and inversely for the optimal hedge ratios and the hedging effectiveness index. Indeed, either for optimists or pessimists, the presence of confirmation bias leads to higher optimal hedge ratio, higher optimal weights and higher hedging effectiveness index.Practical implicationsThe findings of the study provided additional evidence for investors, portfolio managers and financial analysts to exploit confirmation bias to make an optimal portfolio allocation especially during COVID-19 and non-COVID-19 periods. Moreover, the findings of this study might be useful for investors as they help them to make successful investment decision in potential hedging strategies.Originality/valueFirst, this is the first scientific work that conducts a stochastic analysis about the impact of emotional biases on the estimated returns and the expectations of optimists and pessimists in cryptocurrency and commodity markets. Second, the originality of this study stems from the fact that the authors make a comparative analysis of hedging behavior across different markets and different periods with and without the impact of confirmation bias. Third, this paper pays attention to the impact of confirmation bias on the expectations and hedging behavior in cryptocurrencies and commodities markets in extremely stressful periods such as the recent COVID-19 pandemic.
International Journal of Islamic and Middle Eastern Finance and Management, Mar 2, 2023
Purpose This paper aims to examine the dynamic spillover effects and network connectedness betwee... more Purpose This paper aims to examine the dynamic spillover effects and network connectedness between the oil prices and the Islamic and conventional financial markets in the Gulf Cooperation Council countries. The focus is on network connectedness during the 2008–2009 global financial crisis, the 2014–2016 oil crisis and the COVID-19 pandemic. The authors use daily data covering the period from January 1, 2007 to April 14, 2022. Design/methodology/approach This study applies a spillover analysis and connectedness network to investigate the risk contagion among the Islamic and conventional stock–bond markets. The authors rely on Diebold and Yilmaz’s (2012, 2014) methodology to construct network-associated measures. Findings The results suggest that overall connectedness among financial market uncertainties increased during the global financial crisis, the oil price collapse of 2014–2016 and the COVID-19 crisis. In addition, the authors show that the contribution of oil shocks to the financial system is limited, as the oil market was a net receiver during the 2014 oil shock and the COVID-19 crisis. On the other hand, the Islamic and conventional stock markets are extensive sources of network effects on the oil market and Islamic and conventional bond markets. Furthermore, the authors found that the Sukuk market was significantly affected by the COVID-19 pandemic, whereas the conventional and Islamic stock markets were the highest transmitters of shocks during the COVID-19 pandemic outbreak. Moreover, oil revealed a weak connectedness with the Islamic and conventional stock markets during the COVID-19 health crisis, implying that it helps provide diversification benefits for international portfolio investors. Originality/value This study contributes to this field by improving the understanding of the effect of fluctuations in oil prices on the dynamics of the volatility connection between oil and Islamic and conventional financial markets during times of stress through a network connectedness framework. The main results of this study highlight the role of oil in portfolio allocation and risk minimization when investing in Islamic and conventional assets.
Cours financement et budgétisation Les concepts de base des projets d'investissement 2 Mouna Bouj... more Cours financement et budgétisation Les concepts de base des projets d'investissement 2 Mouna Boujelbène Abbes Université Virtuelle de Tunis Chapitre 1 : Les concepts de base des projets d'investissement Objectifs du chapitre Ce chapitre a pour objectifs de : Distinguer entre les différents types d'investissement. Reconnaître les différents paramètres de l'investissement. Evaluer les cash flows nets des investissements. Cours financement et budgétisation Les concepts de base des projets d'investissement 3 Mouna Boujelbène Abbes Université Virtuelle de Tunis 3. Classification des investissements 3.1. Classification des investissements selon leur nature a. La distinction investissement matériel/investissement immatériel Cette distinction est l'une des plus anciennes dans la mesure où jusque les années soixante, dans un environnement essentiellement industriel, on associait à la notion d'investissement, les seuls investissements matériels qui, à travers l'acquisition de machines ou la construction et l'aménagement d'immeubles destinées à la production, constituaient l'essentiel des dépenses en capital des sociétés. Contrairement à l'investissement matériel, l'OCDE définit l'investissement immatériel, comme "toutes les dépenses de long terme, autres que l'achat d'actifs fixes, que les entreprises consentent dans le but d'améliorer leurs résultats. En plus des investissements de technologie (R&D ou acquisition de ses résultats), est investissement immatériel tout investissement dans la formation, dans les relations de travail, dans les structures de gestion, dans l'organisation de la production, l'élaboration des relations commerciales et technologiques, l'investigation des marchés, l'acquisition et l'exploitation de logiciels". b. La distinction Investissement de remplacement/de modernisation/ou de capacité Cours financement et budgétisation Les concepts de base des projets d'investissement 4 Mouna Boujelbène Abbes Université Virtuelle de Tunis de réussite, ces investissements fourniront une chance de développement importante à l'entreprise qui les a initiés, mais qui en cas d'échec, ils risqueraient d'obérer ses chances de survie. 3.2. Classification des investissements selon la nature de leurs relations réciproques au sein d'un programme d'investissement Cette classification est fondée sur le degré de dépendance entre les projets d'un programme d'investissement. On peut distinguer les projets dépendants, les projets indépendants, les projets mutuellement exclusifs. ales projets dépendants sont des projets complémentaires dont la réalisation de l'un exige au préalable la réalisation des autres. b-les projets indépendants où la décision concernant l'un n'affecte en rien la décision concernant l'autre : l'acceptation ou le rejet de l'un n'a aucun effet sur l'acceptation ou le rejet de l'autre. c-les projets mutuellement exclusifs sont des projets dont la réalisation de l'un d'entre eux rend impensable la réalisation des autres : l'adoption de l'un entraîne automatiquement le rejet de l'autre. 4. Les paramètres d'un projet d'investissement L'évaluation de la rentabilité financière d'un projet repose sur le calcul de certains paramètres : Cours financement et budgétisation Chapitre 2 : Choix des investissements en avenir certain 11 Mouna Boujelbène Abbes Université Virtuelle de Tunis Objectifs du chapitre L'apprenant sera capable : D'estimer les différents critères d'évaluation des projets en avenir certain. De choisir un projet d'investissement en avenir certain. Chapitre 3 : Choix des investissements en avenir incertain 26 Mouna Boujelbène Abbes Université Virtuelle de Tunis Objectifs du chapitre Ce chapitre a pour objectifs d' : Analyser et interpréter les méthodes empiriques de prise en considération du risque. Evaluer un projet d'investissement dans un contexte de risque et dans un contexte de portefeuille. 12 12 Cours financement et budgétisation Chapitre 5 : Structure optimale du capital 44 Mouna Boujelbène Abbes Université Virtuelle de Tunis Objectifs du chapitre Ce chapitre a pour objectifs de : Distinguer entre les différentes théories de structure du capital Identifier l'impact de la décision de financement sur la décision d'investissement. Cours financement et budgétisation Chapitre 6 : La budgétisation des projets 54 Mouna Boujelbène Abbes Université Virtuelle de Tunis Objectifs du chapitre Ce chapitre a pour objectifs de : Préparer le budget prévisionnel d'un projet. Préparer le plan de financement prévisionnel d'un projet.
The paper aims to explain the risk taking in Islamic and conventional banks from a behavioral pro... more The paper aims to explain the risk taking in Islamic and conventional banks from a behavioral prospect as proposed by Kahneman and Tversky (1979) and Tversky and Kahneman (1992). We used the thermal optimal path (TOP) method to test the prospect theory predictions on a sample of 128 Islamic and conventional banks operating in 13 Middle Eastern and North African (MENA) countries. We found significant correlation coefficients for each measure of the returns, except with the IINTL measure for conventional banks, which is situated below the target and the ROE measure for Islamic banks, which is situated below the target and conventional banks, which is located above the target. Indeed, in the areas of a loss below the target level, the correlation coefficient results are positive for the ROE, ROA and IINTL measures for both Islamic and conventional banks, suggesting an excessive risk-taking behavior. Furthermore, empirical results revealed that unlike the return measures, all the other measures, except the EQTA measure for conventional banks situated above the target, are significant. The results also indicated that for the areas below the benchmark, positive correlation coefficients are obtained for all the risk measures for conventional and Islamic banks except for the LLPTL measure. In fact, these results have several implications for policymakers and banks’ regulators who better supervise the banking system. Moreover, these results show how bank managers behave facing the risk.
This paper sheds lights on the predictive power of googling investor sentiment on MENA market ind... more This paper sheds lights on the predictive power of googling investor sentiment on MENA market indexes returns from 2004 to 2018 by using a novel approach based on the thermal optimal path model, Diebold-Yilmaz Spillover Indexes and the wavelet coherence model. Thermal optimal path reveals that googling investor sentiment exhibits a lead effect for Islamic and conventional indexes returns which is influenced by political, social and economic conditions. Using Diebold-Yilmaz Spillover Indexes, we find that googling investor's sentiment is the main net transmitter of shocks to Saudi Arabia, Egypt, Qatar, Bahrain, Oman and Jordan Islamic market indexes and the majority of conventional indexes. Further, the wavelet coherence model confirms the thermal optimal path results of the leading effect of googling investor sentiment, especially during crises periods. These results depict the robust and significant predictive power of googling investor's sentiment to detect the behavior of investor, especially during instability periods and to predict market returns in MENA financial markets. Consequently, investor can exploit googling investor sentiment measure in portfolio investments and trading strategy in MENA financial markets.
PurposeThis study aims to investigate the impact of the COVID-19 pandemic on both of stock prices... more PurposeThis study aims to investigate the impact of the COVID-19 pandemic on both of stock prices and investor's sentiment in China during the onset of the COVID-19 crisis.Design/methodology/approachIn this study, the ADCC-GARCH model was used to analyze the asymmetric volatility and the time-varying conditional correlation among the Chinese stock market, the investors' sentiment and its variation. The authors relied on Diebold and Yilmaz (2012, 2014) methodology to construct network-associated measures. Then, the wavelet coherence model was applied to explore the co-movements between these variables. To check the robustness of the study results, the authors referred to the RavenPack COVID sentiments and the Chinese VIX, as other measures of the investor's sentiment using daily data from December 2019 to December 2021.FindingsUsing the ADCC-GARCH model, a strong co-movement was found between the investor's sentiment and the Shanghai index returns during the COVID-19 ...
Zenodo (CERN European Organization for Nuclear Research), Jun 30, 2022
Impact of the COVID-19 pandemic on the relationship between uncertainty factors, investor behavio... more Impact of the COVID-19 pandemic on the relationship between uncertainty factors, investor behavioral biases and the stock market reaction 101
Object: This article investigate the impact of the COVID 19 on the relationship between uncertain... more Object: This article investigate the impact of the COVID 19 on the relationship between uncertainty factors (Economic Policy Uncertainty, Equity Market Volatility–Infectious Diseases, Financial Stress) and investors’ behavioral biases (overconfidence, herding, mental accounting and loss aversion) with the US Fintech stock market abnormal returns. Methodology: we analyze this relationship by using Johensen’s cointegration test, Granger causality test and Ordinary least square method (OLS), for the period from July 20, 2016 to December 31, 2021. Results: The Empirical results indicated the presence of a long-run equilibrium relationship between all the studied variables, before and during the COVID-19 pandemic period. In fact, the obtained results indicated that the COVID-19 pandemic is a crucial source for resulting abnormal returns in the US Fintech market. Especially, during the COVID-19 pandemic, the Fintech market under-reacted to the common signal of fina...
European Journal of Management and Business Economics
PurposeThis paper aims to analyze the connectedness between Gulf Cooperation Council (GCC) stock ... more PurposeThis paper aims to analyze the connectedness between Gulf Cooperation Council (GCC) stock market index and cryptocurrencies. It investigates the relevant impact of RavenPack COVID sentiment on the dynamic of stock market indices and conventional cryptocurrencies as well as their Islamic counterparts during the onset of the COVID-19 crisis.Design/methodology/approachThe authors rely on the methodology of Diebold and Yilmaz (2012, 2014) to construct network-associated measures. Then, the wavelet coherence model was applied to explore co-movements between GCC stock markets, cryptocurrencies and RavenPack COVID sentiment. As a robustness check, the authors used the time-frequency connectedness developed by Barunik and Krehlik (2018) to verify the direction and scale connectedness among these markets.FindingsThe results illustrate the effect of COVID-19 on all cryptocurrency markets. The time variations of stock returns display stylized fact tails and volatility clustering for all...
This study aims to predict GCC financial stress on oil market, and GCC Stock and bond markets whi... more This study aims to predict GCC financial stress on oil market, and GCC Stock and bond markets while considering the effect of the 2008 financial crisis, 2014 oil drop price and the 2019 novel COVID-19 outbreak. For this purpose, we use a new approach for predicting the financial stress, based on the One-Dimensional Convolutional Neural Network (1D-CNN). This article introduces a parameters optimization method, which provides the best parameters for 1D-CNN to improve the prediction performance of the financial stress indices. The results suggest that indexes of financial stress help to improve forecasting performance. It implies that the 1D-CNN model shows a better predictive performance in the out-of-sample findings.Regarding the influence of financial stress on hedging between Brent, and financial markets, the outcomes emphasize the role of oil in hedging stock market risks in positive market stress case. Another interesting result is that the out-of-sample estimates for stock-bond markets, hedging with oil have higher variability for negative (positive) financial stress. The findings highlight the predictive information captured by financial stress in accurately forecasting oil market volatility and financial markets, offering a valuable opening for investors to monitor oil market volatility using information on traded assets.
This study investigates the predictive power of the financial stress on the dynamic of the Middle... more This study investigates the predictive power of the financial stress on the dynamic of the Middle East and North Africa (MENA) financial market returns from 2007 to 2021. Based on a Quantile Regression, we show that financial stress has highest predictive abilities at the lower quantiles when the market is bearish. Then, we propose a Hidden Markov Model (HMM) based on the transition matrix to understand the relationship between financial stress index and the MENA stock market dynamics. We find that the effect of financial stress on stock market return reveals the persistence of regimes: Bullish state exists and persists, and has the longest conditional expected duration for the majority of MENA markets, except Bahrain, Qatar and Jordan. However, the transition probability from the bullish to the calm regime is too low for the financial market of Bahrain, United Arab Emirates and Egypt. Besides, the estimated mean returns for each regime divulge that the bearish and calm states are more attractive destination for both portfolio managers and investors.
PurposeIn this paper, the authors investigate the impact of the confirmation bias on returns, exp... more PurposeIn this paper, the authors investigate the impact of the confirmation bias on returns, expectations and hedging of optimistic and pessimistic traders in the cryptocurrencies, commodities and stock markets before and during COVID-19 periods.Design/methodology/approachThe authors investigate the impact of the confirmation bias on the estimated returns and the expectations of optimistic and pessimistic traders by employing the financial stochastic model with confirmation bias. Indeed, the authors compute the optimal portfolio weights, the optimal hedge ratios and the hedging effectiveness.FindingsThe authors find that without confirmation bias, during the two sub periods, the expectations of optimistic and pessimistic trader’s seem to convergence toward zero. However, when confirmation bias is particularly strong, the average distance between these two expectations are farer. The authors further show that, with and without confirmation bias, the optimal weights (the optimal hedg...
Capital and Financing structure are considered of a crucial importance for the operational and fi... more Capital and Financing structure are considered of a crucial importance for the operational and financial sustainability of microfinance institutions (MFIs). Therefore, each decision making process is of the same importance for these institutions. The purpose of this study is to draw attentions toward the microfinance sector and to take into consideration the human factor and the role that managers play in funding and financing modalities and decision making process in microfinance institutions. In this context, this paper explores the differences between conventional and Islamic MFIs’ capital structure choices on one hand. And, reviews the insights provided by the literature examining capital structure decisions and managerial behavioral biases on the other hand. The theoretical and comparative analysis revealed the substantial differences between capital structure of both Conventional and Islamic MFIs. Furthermore, the empirical literature points that managers’ behavioral biases pl...
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