The dynamic volatility nexus of geo-political risks, stocks, bond, bitcoin, gold and oil during COVID-19 and Russian-Ukraine war.

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.

Riding the waves: A study of retrun spillovers and inter-sector linkages in US equity markets during the COVID-19 pandemic.

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.

Unleashing the pandemic volatility: A glimpse into the stock market performance of developed economies during COVID-19.

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.

Emerging trends of carbon emissions and foreign direct investment: accounting for ecological footprints, renewable energy, globalization, and technological innovations in BRICS.

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.

Do implied volatilities of stock and commodity markets affect conventional & shariah indices differently? An evidence by OVX, GVZ and VIX.

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.

Unpacking the asymmetric impact of exchange rate volatility on trade flows: A study of selected developed and developing Asian economies.

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.

The probabilities of type I and II error of null of cointegration tests: A Monte Carlo comparison.

This paper evaluates the performance of eight tests with null hypothesis of cointegration on basis of probabilities of type I and II errors using Monte Carlo simulations. This study uses a variety of 132 different data generations covering three cases of deterministic part and four sample sizes. The three cases of deterministic part considered are: absence of both intercept and linear time trend, presence of only the intercept and presence of both the intercept and linear time trend. It is found that all of tests have either larger or smaller probabilities of type I error and concluded that tests face either problems of over rejection or under rejection, when asymptotic critical values are used. It is also concluded that use of simulated critical values leads to controlled probability of type I error. So, the use of asymptotic critical values may be avoided, and the use of simulated critical values is highly recommended. It is found and concluded that the simple LM test based on KPSS statistic performs better than rest for all specifications of deterministic part and sample sizes.