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Article
Publication date: 30 August 2022

Ines Abdelkafi, Youssra Ben Romdhane, Sahar Loukil and Fatma Zaarour

The purpose of this paper is to investigate the dynamic relationship between 19 pandemic and government actions, such as governmental response index and economic support packages.

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Abstract

Purpose

The purpose of this paper is to investigate the dynamic relationship between 19 pandemic and government actions, such as governmental response index and economic support packages.

Design/methodology/approach

The authors use a panel dataset of 10 American and Latin countries for the period spanning from January 2020 to April 2021 to analyze the effect of government actions on stock market returns. The authors provide robust test results that improve the understanding of the impact of the pandemic on stock market indices through the break-up structure method and the new measure of Covid-19 extracted from Narayan et al. (2021) study.

Findings

Empirical results show the harmful effect of the corona virus on stock prices, hence the risk adverse behavior of investors. On the other hand, the quantitative approach reveals that the positive impact of government actions is degraded during Covid-19.

Originality/value

This article highlight that government actions may be effective in reducing new infections but could generate perverse economic impact through increasing uncertainty. The authors conclude that the adjustment of macroeconomic factors and the integration of financial news improve the forecasting performance of the model based on health news.

Details

Managerial Finance, vol. 49 no. 1
Type: Research Article
ISSN: 0307-4358

Keywords

Available. Open Access. Open Access
Article
Publication date: 28 March 2023

Youssra Ben Romdhane, Souhaila Kammoun and Sahar Loukil

This study attempts to explain the impact of Fintech on the Asian economies through two main indicators, inflation and unemployment over the period 2011-2014-2017.

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Abstract

Purpose

This study attempts to explain the impact of Fintech on the Asian economies through two main indicators, inflation and unemployment over the period 2011-2014-2017.

Design/methodology/approach

This study uses panel data regression models to explain the relationship between Fintech, inflation as an indicator of currency circulation and unemployment since Fintech has disrupted the labor market.

Findings

Empirical results show a consistently strong and positive relationship between the development of financial technologies and the reduction of inflation and unemployment unless these technologies are actively used. Digital finance has become a new driver of economic development. Therefore, governors should not only improve their economies but also expand their information and communication technologies to develop their digital infrastructure, especially for businesses.

Originality/value

The present study contributes to the existing literature on the impact of disruptive digital innovation on the socioeconomic development of emerging countries. The empirical evidence highlights the importance of distinguishing between active and passive uses of Fintech in order to anticipate its economic impact.

Details

Arab Gulf Journal of Scientific Research, vol. 42 no. 1
Type: Research Article
ISSN: 1985-9899

Keywords

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Article
Publication date: 10 October 2024

Hind Alnafisah, Sahar Loukil, Azza Bejaoui and Ahmed Jeribi

This paper aims to analyze the connectedness between the natural gas, wheat, gold, Bitcoin and Gulf Cooperation Council (GCC) stock indices with the advent of exogenous and…

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Abstract

Purpose

This paper aims to analyze the connectedness between the natural gas, wheat, gold, Bitcoin and Gulf Cooperation Council (GCC) stock indices with the advent of exogenous and unexpected shocks related to the health and political crises.

Design/methodology/approach

For this end, a quantile-based connectedness method is applied on returns of different assets during the period 01/01/2016–05/01/2024.

Findings

The empirical findings display that the existence of time-varying connectedness between markets is well-documented and seems to be stronger during the COVID-19 pandemic and the Russia–Ukraine war. The connectedness is fostered with extreme events, showing that shocks propagate increasingly during turbulent periods compared with calm ones. The connectedness is event-dependent.

Practical implications

The empirical results offer insightful information for policymakers and investors about the contagion effect and volatility spillover among GCC stock markets and other asset classes during different crises.

Originality/value

This study examines different asset classes’ dynamism connection with sock prices in the GCC countries to better apprehend the (dis)similarities between different asset classes in terms of information transmission. It also investigates the connectedness structure among different asset classes under extreme market conditions and how spillover effects across GCC markets and other ones can be time- and event-dependent.

Details

International Journal of Islamic and Middle Eastern Finance and Management, vol. 17 no. 6
Type: Research Article
ISSN: 1753-8394

Keywords

Available. Open Access. Open Access
Article
Publication date: 20 June 2022

Achraf Ghorbel, Sahar Loukil and Walid Bahloul

This paper analyzes the connectedness with network among the major cryptocurrencies, the G7 stock indexes and the gold price over the coronavirus disease 2019 (COVID-19) pandemic…

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Abstract

Purpose

This paper analyzes the connectedness with network among the major cryptocurrencies, the G7 stock indexes and the gold price over the coronavirus disease 2019 (COVID-19) pandemic period, in 2020.

Design/methodology/approach

This study used a multivariate approach proposed by Diebold and Yilmaz (2009, 2012 and 2014).

Findings

For a stock index portfolio, the results of static connectedness showed a higher independence between the stock markets during the COVID-19 crisis. It is worth noting that in general, cryptocurrencies are diversifiers for a stock index portfolio, which enable to reduce volatility especially in the crisis period. Dynamic connectedness results do not significantly differ from those of the static connectedness, the authors just mention that the Bitcoin Gold becomes a net receiver. The scope of connectedness was maintained after the shock for most of the cryptocurrencies, except for the Dash and the Bitcoin Gold, which joined a previous level. In fact, the Bitcoin has always been the biggest net transmitter of volatility connectedness or spillovers during the crisis period. Maker is the biggest net-receiver of volatility from the global system. As for gold, the authors notice that it has remained a net receiver with a significant increase in the network reception during the crisis period, which confirms its safe haven.

Originality/value

Overall, the authors conclude that connectedness is shown to be conditional on the extent of economic and financial uncertainties marked by the propagation of the coronavirus while the Bitcoin Gold and Litecoin are the least receivers, leading to the conclusion that they can be diversifiers.

研究目的

本文分析於2020年2019冠狀病毒病肆虐期間、主要的加密貨幣、七國集團 (G7) 股價指數與黃金價格三者之間在網絡上的連通性。

研究設計/方法/理念

分析使用迪博爾德和耶爾馬茲 (Diebold and Yilmaz (2009, 2012, 2014)) 提出的多變量分析法。

研究結果

就一個股票指數投資組合而言,靜態連結的結果顯示、在2019冠狀病毒病肆虐期間,股票市場之間有更高的獨立性。值得我們注意的是:一般來說,加密貨幣在股票指數投資組合起著多元化投資作用,這可減低不穩定性,尤其是在危機時期。動態連結的結果與靜態連結的結果沒有顯著的分別。我們剛提到、比特幣黃金已成為純接收者。除了處於先前水平的達世幣和比特幣黃金外,就大部分的加密貨幣而言,連通的範圍在衝擊後都得以維持。事實上,在這危機時期,比特幣一直是波動性連結或溢出的最大淨傳播者。掛單者 (Maker) 是從全球系統中出現的最大波動淨接收者。至於黃金,我們注意到在危機時期、它仍然是在網絡接收方面擁有顯著增長的淨接收者,這確認其為安全的避難所。

研究的原創性/價值

總的來說,我們的結論是:連通性被確認為取決於標誌著受廣泛傳播的冠狀病毒影響下的經濟和金融欠缺穩定的程度,而比特幣黃金和萊特幣則是最小的接收者,這帶出一個結論、就是:比特幣黃金和萊特幣、可以成為多元化投資項目。

Details

European Journal of Management and Business Economics, vol. 33 no. 4
Type: Research Article
ISSN: 2444-8451

Keywords

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Article
Publication date: 16 December 2024

Ram Singh, Aina Rafat and Smriti Srivastava

This study aims to determine the factors that influence payment Fintech application adoption intention among low-income groups in India.

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Abstract

Purpose

This study aims to determine the factors that influence payment Fintech application adoption intention among low-income groups in India.

Design/methodology/approach

This study used an expanded technology acceptance model (TAM; covering perceived usefulness, perceived ease of use, social influence, perceived risk and financial literacy), which was tested using 310 low-income respondents in Northern India. The PLS-SEM approach was used to analyse the data.

Findings

The results indicate that perceived usefulness, perceived ease of use, social influence and financial literacy all has a direct positive relationship with the intention to use Fintech. Furthermore, financial literacy was found to be the moderator in moderating the relationship between social influence and intention to use the Fintech app.

Research limitations/implications

This study ameliorates existing research and deepens the authors’ understanding of users’ intentions to use Fintech among low-income groups. The findings of the study help both policymakers and academicians in designing effective strategies for promoting Fintech usage.

Originality/value

This study examines the factors that determine Fintech application adoption, particularly among low-income individuals. The TAM framework was expanded to include perceived risk and financial literacy as two of the factors influencing Fintech adoption. Furthermore, the moderating role of financial literacy on intention to use Fintech app was considered in this study in the context of a developing country such as India.

Details

Journal of Science and Technology Policy Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2053-4620

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Article
Publication date: 23 August 2019

Sahar Tadayonirad, Hany Seidgar, Hamed Fazlollahtabar and Rasoul Shafaei

In real manufacturing systems, schedules are often disrupted with uncertainty factors such as random machine breakdown, random process time, random job arrivals or job…

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Abstract

Purpose

In real manufacturing systems, schedules are often disrupted with uncertainty factors such as random machine breakdown, random process time, random job arrivals or job cancellations. This paper aims to investigate robust scheduling for a two-stage assembly flow shop scheduling with random machine breakdowns and considers two objectives makespan and robustness simultaneously.

Design/methodology/approach

Owing to its structural and algorithmic complexity, the authors proposed imperialist competitive algorithm (ICA), genetic algorithm (GA) and hybridized with simulation techniques for handling these complexities. For better efficiency of the proposed algorithms, the authors used artificial neural network (ANN) to predict the parameters of the proposed algorithms in uncertain condition. Also Taguchi method is applied for analyzing the effect of the parameters of the problem on each other and quality of solutions.

Findings

Finally, experimental study and analysis of variance (ANOVA) is done to investigate the effect of different proposed measures on the performance of the obtained results. ANOVA's results indicate the job and weight of makespan factors have a significant impact on the robustness of the proposed meta-heuristics algorithms. Also, it is obvious that the most effective parameter on the robustness for GA and ICA is job.

Originality/value

Robustness is calculated by the expected value of the relative difference between the deterministic and actual makespan.

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