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The purpose of this study is to investigate the impact of government policies adopted by the Tunisian government to cope with the COVID-19 sanitary crisis on stock market return.
Abstract
Purpose
The purpose of this study is to investigate the impact of government policies adopted by the Tunisian government to cope with the COVID-19 sanitary crisis on stock market return.
Design/methodology/approach
The author uses daily data from March 2, 2020, to July 23, 2021.
Findings
The author finds that policies interventions have a negative impact on Tunisia's stock market, particularly stock market returns due to stringency, confinement and health measures. Also, Government announcements regarding economic has a negative impact on Tunisia's stock market but this impact is insignificant. By conducting an additional analysis, the author shows that the government interventions policies amplify the negative effect of COVID-19 on stock returns.
Research limitations/implications
These results will be useful for policy authorities seeking to consider the advantages and drawbacks of government measures. Finally, a legislative proposal about the audit of public debt should be included in the Constitution to spur Tunisia's economic and social recovery.
Originality/value
This study contributes to the related literature in two ways: First, it is the first study to examine the impact of government actions on stock market performance. Second, it bridges a gap in the literature by investigating the case of Tunisia, because most studies focus on developed and emerging economies.
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Wassim Ben Ayed, Ibrahim Fatnassi and Abderrazak Ben Maatoug
The purpose of this study is to investigate the performance of Value-at-Risk (VaR) models for nine Middle East and North Africa Islamic indices using RiskMetrics and VaR…
Abstract
Purpose
The purpose of this study is to investigate the performance of Value-at-Risk (VaR) models for nine Middle East and North Africa Islamic indices using RiskMetrics and VaR parametric models.
Design/methodology/approach
The authors test the performance of several VaR models using Kupiec and Engle and Manganelli tests at 95 and 99 per cent levels for long and short trading positions, respectively, for the period from August 10, 2006 to December 14, 2014.
Findings
The authors’ findings show that the VaR under Student and skewed Student distribution are preferred at a 99 per cent level VaR. However, at 95 per cent level, the VaR forecasts obtained under normal distribution are more accurate than those generated using models with fat-tailed distributions. These results suggest that VaR is a good tool for measuring market risk. The authors support the use of RiskMetrics during calm periods and the asymmetric models (Generalized Autoregressive Conditional Heteroskedastic and the Asymmetric Power ARCH model) during stressed periods.
Practical implications
These results will be useful to investors and risk managers operating in Islamic markets, because their success depends on the ability to forecast stock price movements. Therefore, because a few Islamic financial institutions use internal models for their capital calculations, the regulatory committee should enhance market risk disclosure.
Originality/value
This study contributes to the knowledge in this area by improving our understanding of market risk management for Islamic assets during the stress periods. Then, it highlights important implications regarding financial risk management. Finally, this study fills a gap in the literature, as most empirical studies dealing with evaluating VaR prediction models have focused on quantifying the model risk in the conventional market.
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Wassim Ben Ayed and Rim Ben Hassen
This research aims to evaluate the accuracy of several Value-at-Risk (VaR) approaches for determining the Minimum Capital Requirement (MCR) for Islamic stock markets during the…
Abstract
Purpose
This research aims to evaluate the accuracy of several Value-at-Risk (VaR) approaches for determining the Minimum Capital Requirement (MCR) for Islamic stock markets during the pandemic health crisis.
Design/methodology/approach
This research evaluates the performance of numerous VaR models for computing the MCR for market risk in compliance with the Basel II and Basel II.5 guidelines for ten Islamic indices. Five models were applied—namely the RiskMetrics, Generalized Autoregressive Conditional Heteroskedasticity, denoted (GARCH), fractional integrated GARCH, denoted (FIGARCH), and SPLINE-GARCH approaches—under three innovations (normal (N), Student (St) and skewed-Student (Sk-t) and the extreme value theory (EVT).
Findings
The main findings of this empirical study reveal that (1) extreme value theory performs better for most indices during the market crisis and (2) VaR models under a normal distribution provide quite poor performance than models with fat-tailed innovations in terms of risk estimation.
Research limitations/implications
Since the world is now undergoing the third wave of the COVID-19 pandemic, this study will not be able to assess performance of VaR models during the fourth wave of COVID-19.
Practical implications
The results suggest that the Islamic Financial Services Board (IFSB) should enhance market discipline mechanisms, while central banks and national authorities should harmonize their regulatory frameworks in line with Basel/IFSB reform agenda.
Originality/value
Previous studies focused on evaluating market risk models using non-Islamic indexes. However, this research uses the Islamic indexes to analyze the VaR forecasting models. Besides, they tested the accuracy of VaR models based on traditional GARCH models, whereas the authors introduce the Spline GARCH developed by Engle and Rangel (2008). Finally, most studies have focus on the period of 2007–2008 financial crisis, while the authors investigate the issue of market risk quantification for several Islamic market equity during the sanitary crisis of COVID-19.
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Wassim Ben Ayed, Rim Ammar Lamouchi and Suha M. Alawi
The purpose of this study is to investigate factors influencing the net stable funding ratio (NSFR) in the Islamic banking system. More specifically, the authors analyze the…
Abstract
Purpose
The purpose of this study is to investigate factors influencing the net stable funding ratio (NSFR) in the Islamic banking system. More specifically, the authors analyze the impact of the deposit structure on the liquidity ratio using the two-step generalized method of moments approach during the 2000–2014 period.
Design/methodology/approach
Based on IFSB-12 and the GN-6, the authors calculated the NSFR for 35 Islamic banks operating in the Middle East and North Africa (MENA) region.
Findings
The findings of this study show the following: first, ratio of profit-sharing investment accounts have a positive impact on the NSFR, while ratio of non profit-sharing investment accounts increase the maturity transformation risk; second, the results highlight that asset risk, bank capital and the business cycle have a positive impact on the liquidity ratio, while the returns on assets, bank size and market concentration have a negative impact; and third, these results support the IFSB’s efforts in developing guidelines for modifying the NSFR to enhance the liquidity risk management of institutions offering Islamic financial services.
Research limitations/implications
The most prominent limitation of this research is the availability of data.
Practical implications
These results will be useful for authorities and policy makers seeking to clarify the implications of adopting the liquidity requirement for banking behavior.
Originality/value
This study contributes to the knowledge in this area by improving our understanding of liquidity risk management during liquidity stress periods. It analyzes the modified NSFR that was adopted by the IFSB. Besides, this study fills a gap in the literature. Previous studies have used the conventional ratios to determinate the main factors of the maturity transformation risk in a full-fledged Islamic bank based on an early version of NSFR. Finally, most studies focus on the NSFR as proposed by the Basel Committee, whereas the authors investigate the case of the dual-banking system in the emerging economies of seven Arab countries in the MENA region.
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Wassim Albalkhy, Rateb Sweis, Hassan Jaï and Zoubeir Lafhaj
This study explores the role of the Internet of Things (IoT) as an enabler for Lean Construction principles and tools in construction projects.
Abstract
Purpose
This study explores the role of the Internet of Things (IoT) as an enabler for Lean Construction principles and tools in construction projects.
Design/methodology/approach
In response to the scarcity of studies about IoT functionalities in construction, a two-round systematic literature review (SLR) was undertaken. The first round aimed to identify IoT functionalities in construction, encompassing an analysis of 288 studies. The second round aimed to analyze their interaction with Lean Construction principles, drawing insights from 43 studies.
Findings
The outcome is a comprehensive Lean Construction-IoT matrix featuring 54 interactions. The highest levels of interaction were found in the Lean Construction principle “flow” and the functionality of “data transfer and real-time information sharing”.
Research limitations/implications
The study focuses on the role of IoT as an enabler for Lean Construction. Future work can cover the role of Lean as an enabler for advanced technology implementation in construction.
Originality/value
The Lean Construction-IoT matrix serves as a resource for researchers, practitioners, and decision-makers seeking to enhance Lean Construction by leveraging IoT technology. It also provides various examples of how advanced technology can support waste elimination and value generation in construction projects.
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