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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... 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.
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... 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.
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... 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.
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... 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.
ABSTRACT
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... 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.
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... 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 ...
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... 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...
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... 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...
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... 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 financial sustainability of microfinance institutions (MFIs). Therefore, each decision making process is of the same importance for these... 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...
This article explores the relation between oil market and the financial stocks market. Particularly, this article examines the impact of oil price shocks on stock markets returns and volatilities for large set of oil importing and... more
This article explores the relation between oil market and the financial stocks market. Particularly, this article examines the impact of oil price shocks on stock markets returns and volatilities for large set of oil importing and exporting countries over 1997:1–2009:08 period. Using VAR approach, we estimate the dynamic relations between oil price shocks, stock markets and other variables, including short-term interest rates, exchange rates, and industrial production. Orthogonalized impulse response function shows that oil exporting countries (Russia, Norway, Canada, Malaysia, Venezuela and Argentina) have a significant positive response of stock market returns to oil price shocks. Although, oil importing countries (UK, France, Italy, Portugal, Sweden, Switzerland and Japan) have a statistically significant negative response of stock returns to an oil price increase. Empirical results from the impact of oil price volatility on stock markets volatilities show that oil price volatili...
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... 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, t...
ABSTRACT
Research Interests:
In this study, we test whether investor learning, herding, and prospect theory explain the variation of beta across different return regimes and return frequencies. Empirically, we use quantile regressions to analyze beta change on the... more
In this study, we test whether investor learning, herding, and prospect theory explain the variation of beta across different return regimes and return frequencies. Empirically, we use quantile regressions to analyze beta change on the French financial market from January 2000 to December 2010. For daily data, we find a larger estimated impact of systematic shocks on extreme quantiles of firm's returns as compared to intermediate quantiles. The beta pattern is probably symmetrically suggesting that whatever the type of shocks have similar effects. This finding can be explained by herding behavior and investor learning. These behaviors lead to beta-increasing in the extreme returns case. For monthly data, beta evolves asymmetrically across return regimes with a greater impact of the market in the lower tail of returns distribution. This finding provides strong evidence in favor of prospect theory explanation. Overall, constant beta estimated by ordinary-least squares overestimate...
Research Interests:
In this study, we test whether the overconfidence bias explains several stylized market anomalous, including a short-term continuation (momentum), a long-term reversal in stock returns, high levels of trading volume and excessive... more
In this study, we test whether the overconfidence bias explains several stylized market anomalous, including a short-term continuation (momentum), a long-term reversal in stock returns, high levels of trading volume and excessive volatility. Using data of French stocks market, we find empirical evidence in support of overconfidence hypothesis. First, based on a restricted VAR framework, we show that overconfident investors overreact to private information and underreact to public information. Second, by performing Granger-causality tests of stock returns and trading volume, we find that overconfident investors trade more aggressively in periods subsequent to market gains. Third, based on a two GARCH specifications, we show that self attribution bias, conditioned by right forecasts, increases investors overconfidence and trading volume. Fourth, the analysis of the relation between return volatility and trading volume shows that the excessive trading of overconfident investors makes a...
In this paper we develop an index of financial stress for the Islamic financial markets (IFMSI) and we compare it to the financial stress index (FSI) that has been developed previously. The methodology uses monthly basis data collected... more
In this paper we develop an index of financial stress for the Islamic financial markets (IFMSI) and we compare it to the financial stress index (FSI) that has been developed previously. The methodology uses monthly basis data collected from financial markets of the Gulf Cooperation Council (GCC) region. The study period is between October 2006 and August 2018, which is regarded as a sensitive period in that region. The paper is structured around the following areas of focus: the measure of the impact of different events and external shocks in financial markets of the GCC countries, the examination of which financial system represented by FSI and IFMSI was less affected by region specific conflicts and exogenous shocks and the dynamic conditional correlation between both indices.
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... 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 an...
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,... more
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...
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... more
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 sta...
Purpose The purpose of this paper is to conduct a behavioral analysis, through overconfidence, in order to understand how this cognitive bias could affect risk taking and inefficiency in Islamic and conventional banks operating in the... more
Purpose The purpose of this paper is to conduct a behavioral analysis, through overconfidence, in order to understand how this cognitive bias could affect risk taking and inefficiency in Islamic and conventional banks operating in the MENA region. Design/methodology/approach To achieve the objective, the authors considered two overconfidence proxies, namely loan growth rate and net interest margin. Using the generalized method of moments method regressions for panel data, the authors found that the two overconfidence proxies have an effect on the risk exposure and consequently on the efficiency level of Islamic and conventional banks. Findings In general, overconfidence bias causes excessive risk taking and the degradation of the cost efficiency level. Moreover, these effects emerge with a delay of three to four years and have implications that are not too different for both types of banks. Originality/value The main motivation underlying this research study is the relatively new fi...
Purpose The purpose of this paper is to empirically investigate the volatility spillover between the Chinese stock market, investor’s sentiment and oil market, specifically during the 2014‒2016 turmoil period. Design/methodology/approach... more
Purpose The purpose of this paper is to empirically investigate the volatility spillover between the Chinese stock market, investor’s sentiment and oil market, specifically during the 2014‒2016 turmoil period. Design/methodology/approach This study used the daily and monthly China market price index, oil-price index and composite index of Chinese investor’s sentiment. The authors first use the DCC GARCH model in order to study the correlation between variables. Second, the authors use a continuous wavelet decomposition technique so as to capture both time- and frequency-varying features of co-movement variables. Finally, the authors examine the spillover effects by estimating the BEKK GARCH model. Findings The wavelet coherency results indicate a substantial co-movement between oil and Chinese stock markets in the periods of high volatility. BEKK GARCH model outcomes confirm this relation and report the noteworthy bidirectional transmission of volatility between oil market shocks an...
The aim of this article is to compare the portfolio optimization generated by the behavioral portfolio theory (BPT) and the mean variance theory (MVT) by investigating the impact of the global financial crisis on the asset allocation. We... more
The aim of this article is to compare the portfolio optimization generated by the behavioral portfolio theory (BPT) and the mean variance theory (MVT) by investigating the impact of the global financial crisis on the asset allocation. We use data from the Canadian Stock Exchange over the 2002–2015 period. By comparing both approaches, we show that for any level of aspiration and admissible failure, the BPT optimal portfolio will always contain a part of the mean–variance frontier. Thus, in the case of higher degree of risk aversion induced by typical BPT investors, the security set is located on the upper right of the Markowitz frontier. However, even if the optimal portfolios of MVT and BPT may coincide, MVT investors associated with an extremely low degree of risk aversion will not systematically choose BPT optimal portfolios. Our results also indicate the period of financial crisis generate huge losses in MVT portfolio values that implies a lower expected return and a higher leve...
... He finds that both return and volatility spillover indices reached their respective peaks during the current ... They show volatility spillovers from USA to all South East Asia. ... Austria, UK, Netherlands, Swiss, Australia, Hong... more
... He finds that both return and volatility spillover indices reached their respective peaks during the current ... They show volatility spillovers from USA to all South East Asia. ... Austria, UK, Netherlands, Swiss, Australia, Hong Kong, Japan, Korea, Malaysia, Singapore, India, Kuwait and ...
ABSTRACT
The present study allows to evaluate the financial performances of a variety of strategies momentum and to explain their excess of return. These strategies are applied for various formation and holding horizons. Various explanatory... more
The present study allows to evaluate the financial performances of a variety of strategies momentum and to explain their excess of return. These strategies are applied for various formation and holding horizons. Various explanatory approaches of the profitability of momentum strategies are considered. The Decomposition of Lo and Mackinlay (1990) emphasized that these profits are due primarily to underreaction of investors to the information. The study of the economic sources shows that these profits can be allotted to delayed overreaction to the factorial component of return and not to a compensation of a high risk.
Research Interests:

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