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This article accounts for the impact of positive and negative shocks of the news-related Climate Policy Uncertainty (CPU) and the novel Economist Intelligence Unit's report-based global Energy Uncertainty (EU) on the U.S. sectoral stock returns by using the ARDL and NARDL approaches with dynamic multiplier simulations. We also utilize both the DCC-GARCH and ADCC-GARCH approaches to extract the symmetric and asymmetric dynamic conditional correlations between the EU and the U.S. sectoral stock returns and then regress these conditional correlation series on the CPU through series of quantile regressions. Overall, the findings suggest that only the positive CPU shocks negatively impact the U.S. sectoral stock returns of Consumer Services, Financials, Industries, Telecommunication and Utilities in the long-term, whereas the negative CPU shocks insignificantly predict the U.S. sectoral returns. The findings also report that only the negative EU shocks increase the U.S. sectoral stock returns of Consumer Services, Financials, Health Care, Industries, Moreover, the positive (negative) EU shocks cause the U.S. sectoral returns of Materials and Technology to decrease (increase) in the long-term. Portfolio managers may consider diversifying their portfolios to include sectors least susceptible to negative impacts from the CPU and EU shocks such as Health Care and Oil & Gas. Our findings also show that CPU shocks moderate the dynamic conditional correlations between the EU and the U.S. sectoral returns of Consumer Services, Materials, Health Care, Telecommunication, Oil and Gas and Utility. Fund managers should contemplate augmenting the allocations to the Financials, Industrials, and Technology sectors owing to their diminished interconnectivity with the EU during periods of heightened CPU.

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The primary cause of environmental degradation, which poses a danger to the long-term viability of the ecosystem, is the emission of greenhouse gases (GHG). For this reason, the Glasgow Climate Pact (COP26) established a decarbonization goal in response to this ecological concern, for which all economic players have a responsibility. India is among the participants who have a target set for them to decarbonize their economies by the year 2060 via the use of green energy and the advancement of science and innovation. Nevertheless, the asymmetrical effect of green energy, technology, and innovation on India's decarbonization program was not sufficiently explored in the prior study; hence, this research aims to fill this literature vacuum by considering India's GHG emissions from 1990 to 2020 by leveraging the non-linear autoregressive distributed lag (NARDL) model. The findings reveal the asymmetric influences of variables of interest on GHG emissions during the short and long term and under positive and negative shocks. Regarding the positive shock, long-term findings demonstrate that innovation and technical know-how grow GHG emissions and accelerate environmental degradation. However, a negative shock in innovations and technological know-how is opposed to a positive shock and improving environmental conditions. Further, positive shocks in green energy boost environmental effectiveness by reducing GHG secretions in India. In contrast, the negative shock in green energy deteriorates the environment by triggering GHG releases. These factual findings compel the Indian government to prioritize green technologies in addition to green energy generation to decouple economic growth from greenhouse gas emissions and meet rising energy demands.

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We investigate the dynamic volatility connectedness of geopolitical risk, stocks, bonds, bitcoin, gold, and oil from January 2018 to April 2022 in this study. We look at connectivity during the Pre-COVID, COVID, and Russian-Ukraine war subsamples. During the COVID-19 and Russian-Ukraine war periods, we find that conventional, Islamic, and sustainable stock indices are net volatility transmitters, whereas gold, US bonds, GPR, oil, and bitcoin are net volatility receivers. During the Russian-Ukraine war, the commodity index (DJCI) shifted from being a net recipient of volatility to a net transmitter of volatility. Furthermore, we discover that bilateral intercorrelations are strong within stock indices (DJWI, DJIM, and DJSI) but weak across all other financial assets. Our study has important implications for policymakers, regulators, investors, and financial market participants who want to improve their existing strategies for avoiding financial losses.

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In times of crisis, stock markets experience a significant increase in return volatility, which leads to spillovers across equity sectors. The purpose of this study is to investigate the asymmetric spillovers across ten U.S. equity sectors, representing different industries. Daily prices of sector indices were collected from 02 January 2018 to 22 October 2021 for the analysis. In addition, the study applied Diebold and Yilmaz's (2012) dynamic spillover methodology, along with the static and rolling windows phenomena, to examine the daily returns spillovers across sector indices. The results indicate that 82 % of volatility forecast error variance in U.S sector indices is due to the spillover effect. Moreover, both industrials and financials exhibit the highest gross spillovers to other sectors, while they also receive the highest spillovers from other sectors. Furthermore, the oil and gas sector and utilities sector receive the highest net returns spillovers. These empirical findings provide crucial information regarding the interdependence of U.S. sector indices during the COVID-19 pandemic, which is relevant for investors and practitioners.

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The COVID-19 pandemic has resulted in significant financial losses globally, increasing the volatility of financial assets. Thus, this study models the stock market volatility of developed economies during the COVID-19 pandemic. For this purpose, we used the GJR-GARCH (Albulescu, 2020; Albulescu, 2020) [1,1] econometric model on the daily time series returns data ranging from 01st-July-2019 to 18th-November-2020. The entire dataset was equally divided into two subsets; before COVID-19, and after the COVID-19. The empirical results of this study showed the presence of volatility clustering, leverage effect, and excess kurtosis indicating leptokurtic phenomena in all stock indices returns. In addition to this, it can be noted that compared to before COVID-19, the stock markets showed negative returns, and increased volatility during the COVID-19. Hence, based on these findings, this study provides significant insights for global stock market investors and economic policymakers regarding financial portfolio construction particularly during crises times.

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This paper investigates the intricate interplay between carbon emissions and foreign direct investment within the context of Brazil, Russia, India, China, and South Africa (BRICS) for the period spanning 2000 to 2022. In our comprehensive analysis, we incorporate ecological footprint, renewable energy, globalization, and technological innovations as exogenous variables. Employing a system of simultaneous equations across the BRICS panel, we aim to fully elucidate the proposed relationships. Our empirical findings underscore the following key insights: foreign direct investment, technological innovations, and the adoption of renewable energy sources significantly contribute to the mitigation of carbon emissions in these selected nations. However, it is essential to note that ecological footprints exhibit a positive association with carbon emissions, raising concerns on two fronts: escalating environmental degradation and increased land pressure, both of which contribute to rising ecological footprints in BRICS countries. Additionally, our analysis reveals that foreign direct investment is influenced by its capacity to reduce carbon emissions and bolster renewable energy adoption, while globalization amplifies investment trends within the BRICS nations. To address the environmental repercussions of mining activities, it is imperative to implement stringent control and regulation measures, given their potential adverse impacts, including soil pollution, acid mine drainage, erosion, biodiversity loss, excessive water resource consumption, and wastewater disposal challenges. Nevertheless, proactive steps such as recycling mining waste, adopting environmentally friendly mining equipment, combatting illegal mining, and enhancing overall mining sustainability offer promising avenues to mitigate the environmental footprint of mining operations.

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The current study aims to investigate how index returns of conventional and shariah indices of the USA, Europe, and Asia are affected by changes in oil prices, gold prices, VIX, gold-VIX, and oil-VIX. In our investigation, we used the S&P 500, S&P Europe 350, S&P Pan Asia, and their relevant shariah counterparts for the USA, Europe, and Asia. To examine how the explanatory factors affect the overall distribution of the explained variables, we used OLS and quantile regression. For the time frame prior to Covid-19, we discover that all volatility indices-OVX, GVZ, and VIX-influence returns of all indices simultaneously, and that all variables-aside from the spot price of oil-have a greater impact during the bear phase according to QR findings. Further, Volatility indices have a greater impact on volatility of index returns during the Covid-19 period. This is largely because the Covid-19 outbreak had a rapid impact on economies all around the world, and the only thing that affected financial markets consistently was high volatility. This is further supported by the findings of BEKK, which demonstrate that volatility extends across all markets and originates from commodities like gold, oil, gold-VIX, and VIX. Evidence for this can be seen in the fact that during the COVID-19 period, stock prices reacted more favorably to oil price volatility than to oil spot prices, which even went negative on April 20, 2020. Because of this, market stability can be promoted by reducing volatility through the prompt dissemination of crucial information, even while governments have little direct control over the prices of significant commodities like gold and crude oil.

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Maintaining a stable exchange rate is a challenging task for the world, especially for developing economies. This study examines the impact of asymmetric exchange rates on trade flows in selected Asian countries and finds that the effects of increased exchange rate volatility on exports and imports differ among Pakistan, Malaysia, Japan, and Korea. The quarterly data from the period 1980 to 2018 is collected from the International Financial Statistics (IFS) database maintained by the International Monetary Fund (IMF). We employ both linear and non-linear Autoregressive Distributed Lag (ARDL) models for estimation. The non-linear models yielded more significant findings, while the linear models did not indicate any significant effects of exchange rate volatility on trade flows. The results of the study suggest that in the case of Pakistan, both the linear and non-linear models indicate that increased exchange rate volatility adversely affects exports and imports, while decreased volatility enhances both. This implies that stabilizing the exchange rate would be beneficial for Pakistan's trade. In contrast, the linear model applied to Malaysia shows no long-run effects of exchange rate volatility on exports. However, the result suggests that decreased volatility stimulates Malaysia's exports. Therefore, in the case of Malaysia, stabilizing the exchange rate could contribute to boosting exports. We also found that increased exchange rate volatility boosts exports of Japan. On the other hand, decreased volatility hurts exports of Japan. As for the long-run effects of exchange rate volatility on imports, we found that increased volatility boosts imports of Korea. The study provides various policy implications regarding the impact of exchange rate volatility on trade flows in developing economies. The study highlights the importance of country-specific considerations in understanding the impact of exchange rate volatility on trade flows, and has important policy implications for promoting trade and economic growth in these nations. It emphasizes the need to model exchange rate volatility separately for developed and developing countries and to continue research and analysis to identify ways to mitigate its negative effects on the economy.

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Since last decade, firms are facing the challenge of strict compliance in response to the stakeholders' awareness about climate change and environmental degradation. Considering these trends, we examine the effect of environmental innovation such as product innovation and process innovation on firm value and the moderating effect of organizational capital on environmental innovation-firm value nexus. Using the data of U.S. listed firms from 2002 to 2019, we find a significantly positive impact of environmental innovation on firm value. Our findings also reveal that organizational capital strengthens the positive association between environmental innovation and firm value, suggesting that firms with higher organizational capital are more likely to consider the demands of stakeholders to be environment friendly which in turn enhances their market value. These findings are aligned with the resource-based view (RBV) and highlight that organizational capital can play a significant role to increase the firm value through environmental innovation. Our results remain robust to subsample analyses, alternative proxies of main variables and are not subject to potential endogeneity concerns. Our study provides new insights into the environmental innovation-firm value nexus and presents important policy implications.

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The emerging-market banking sector plays a significant role in modern-day banking sector stability. In this study, we have used the dynamic conditional correlation (DCC) version of the Generalised autoregressive conditional heteroscedasticity (GARCH) model to estimate the correlation among Emerging Markets (BANKSEK), Latin America (BANKSLA), Brazil, Russia, India, and China (BRIC) (BANKSBC), Portugal, Ireland, Italy, Greece, and Spain (PIIGS) (BANKSPI) and Far East (BANKSFE). The study covers more than 100, 200 and 300 trading days of the GFC (starting July 8, 2008) and the COVID-19 pandemic (starting January 1, 2020). We have found that generally, in the short-term excluding PIIGS, all banks show similar pairwise correlation, and the pattern holds in the medium and long term. The far east banking sector displays a reduced correlation than their counterparts, even following the same pattern.

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This study reviews the literature related to Islamic microfinance institutions (IMFI) published in reputable international journals. The manuscripts that have been collected consist of 71 papers that are classified into several study topics. The most researched topic is Poverty alleviation with as many as 25 papers (35%). Next are the papers with the topic of Waqf-based microfinance as many as 12 papers (17%). This follows with 11 papers on the topic of Marketing & Fintech (15%), and 10 papers on the topic of Sustainability & Outreach (14%). Meanwhile, the paper with the theme Maqashid Shariah ranks fifth with a total of 7 papers (10%). Finally, there are 6 papers with the theme of Risk management & Governance (8%). At the end of each topic, the essence of research is presented for future research, which will be useful for academics and practitioners.