How Australia's economy gained momentum because of Covid-19

The objective of the paper is to assess the resilience of the economy of Australia following the Covid-19 pandemic that hit the global economy in Q4 2019, in years 2020, 2021 and 2022. Quarterly growth rates (annualised) of the Real GDP of Australia and Canada are forecasted between Q2 2022 and Q4 2050. Two sets of forecasts are generated: forecasts using historical data including the pandemic (from Q1 1961 to Q1 2022) and excluding the pandemic (from Q1 1961 to Q3 2019). The computation of the difference of their averages is an indicator of the resilience of the economies during the pandemic, the greater the difference the greater the resilience. Used as a benchmark, Canada's economy shows a slightly lower resilience to the Covid-19 pandemic (+0.37%) than Australia's economy (+0.39%) based on Q2 2022-2050 forecasts. However, driven by stronger growth than Canada, the average estimate of the Q2 2022-Q4 2050 quarterly (annualised) growth rate forecasts of Australia is expected to be +2.09% with the Q1 1961-Q1 2022 historical data while it should be +1.61% for Canada. Supported by higher growth, Australia's Real GDP is expected to overtake Canada's in Q1 2040.

An investigation of financial contagion between cryptocurrency and equity markets: Evidence from developed and emerging markets

The present study conducts a dynamic conditional cross-correlation and time–frequency correlation analyses between cryptocurrency and equity markets in both advanced and emerging economies. The purpose of the study is twofold. First, the study investigates the presence of the pure (narrow) form of financial contagion between cryptocurrency and stock markets in both advanced and emerging economies, during the black swan event of the COVID-19 crisis. Second, the study examines the hedging and safe-haven properties of cryptocurrencies against equity markets, before and during periods of financial upheaval triggered by the COVID-19 pandemic. Two econometric models are used: (1) the dynamic conditional correlation (DCC) GARCH and (2) the wavelet analysis models. Using the DCC GARCH model, the study found the evidence of high conditional correlations between cryptocurrency and equity markets. The high conditional correlation was mostly detected in periods of financial turmoil corresponding to the first quarter and the second quarter of 2020. The increase in conditional correlation during periods of financial upheaval (compared to a tranquil period) indicates the presence of the pure form of financial contagion. The wavelet cross-correlation analysis showed the evidence of positive cross-correlation between the Bitcoin and the equity markets during period of financial turmoil. The cross-correlation was identified in both short and long (coarse) scales. In short scales, the equity markets lead the cryptocurrency market, while the cryptocurrency market leads equity markets in coarse scales. The findings of the present study revealed that the degree of interdependence between cryptocurrency and equity markets has substantially increased during the COVID-19 period, and this has negated the safe-haven and hedging benefits of cryptocurrencies over equity markets. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Resilient Control for Macroeconomic Models.

This paper derives a macroeconomic resilient control framework that provides the optimal feedback fiscal and monetary policy responses in response to a potentially large negative external incident. We simulate the model for the U.S. under the conditions that prevailed throughout the 2020 economic crisis that occurred due to the government lockdown that was caused by the coronavirus pandemic. We develop a discrete-time soft-constrained linear-quadratic dynamic game under a worst-case design with multiple disturbances. Within this context, we introduce a resilience feedback response and compare the case where the policymakers counter in response the external incident with the case when they do not counter. This framework is especially applicable to large-scale macroeconomic tracking control models and wavelet-based control models when formulating the magnitudes of the policy changes necessary for the unemployment rate and national output variables to maintain acceptable tracking errors in the periods following a major disruption. Our policy recommendations include the maintenance of "rainy day" funds at appropriate levels of government to mitigate the effects of large adverse events.

Impact of the COVID-19 lockdown on typical ambient air pollutants: Cyclical response to anthropogenic emission reduction.

Preliminary studies have confirmed that ambient air pollutant concentrations are significantly influenced by the COVID-19 lockdown measures, but little attention focus on the long term impacts of human countermeasures in cities all over the world during the period. Still, fewer have addressed their other essential properties, especially the cyclical response to concentration reduction. This paper aims to fill the gaps with combined methods of abrupt change test and wavelet analysis, research areas were made of five cities, Wuhan, Changchun, Shanghai, Shenzhen and Chengdu, in China. Abrupt changes in contaminant concentrations commonly occurred in the year prior to the outbreak. The lockdown has almost no effect on the short cycle below 30 d (days) for both pollutants, and a negligible impact on the cycle above 30 d. PM2.5 (fine particulate matter) has a stable short-cycle nature, which is greatly influenced by anthropogenic emissions. The analysis revealed that the sensitivity of PM2.5 to climate is increased along with the concentrations of PM2.5 were decreasing by the times when above the threshold (30-50 µg m-3), and which could lead to PM2.5 advancement relative to the ozone phase over a period of 60 d after the epidemic. These results suggest that the epidemic may have had an impact earlier than when it was known. And significant reductions in anthropogenic emissions have little impact on the cyclic nature of pollutants, but may alter the inter-pollutant phase differences during the study period.

A Wavelet Analysis of the Dynamic Connectedness among Oil Prices, Green Bonds, and CO2 Emissions

Wavelet power spectrum (WPS) and wavelet coherence analyses (WCA) are used to examine the co-movements among oil prices, green bonds, and CO2 emissions on daily data from January 2014 to October 2022. The WPS results show that oil returns exhibit significant volatility at low and medium frequencies, particularly in 2014, 2019-2020, and 2022. Also, the Green Bond Index presents significant volatility at the end of 2019-2020 and the beginning of 2022 at low, medium, and high frequencies. Additionally, CO2 futures' returns present high volatility at low and medium frequencies, expressly in 2015-2016, 2018, the end of 2019-2020, and 2022. WCA's empirical findings reveal (i) that oil returns have a negative impact on the Green Bond Index in the medium term. (ii) There is a strong interdependence between oil prices and CO2 futures' returns, in short, medium, and long terms, as inferred from the time-frequency analysis. (iii) There also is evidence of strong short, medium, and long terms co-movements between the Green Bond Index and CO2 futures' returns, with the Green Bond Index leading.

Growth evaluation of fintech connectedness with innovative thematic indices – An evidence through wavelet analysis

Purpose This study evaluated the growth of Fintech to measure the contribution towards the sustainable development goal of the United Nation in terms of financial inclusion through exploring the connectedness of fintech with several thematic indices. The study navigates the co-movements in short and long window-time frames. Design/methodology/approach This study used wavelet coherence method to analyze linkages between two-time series by considering the stock market co-movements. Wavelet coherence is applied on the pairwise Fintech-Index with the MSCI benchmarks for investment portfolio purposes. Findings The global correlation among indices signifying that the benchmark of MSCI USA has a greater level of interactions with the nascent industries but is not highly correlated with other benchmark equity indices. The Global FinTech Index indicates the highest values among the thematic indices. The Artificial Intelligence & Big Data Index has revealed a lower level of association with the MSCI Latin American Index among the overall correlations. Practical implications First, borrowing and lending and mitigating the risk needs to be addressed. Second, financial regulations would deal with market failures and vulnerabilities. Third, people would be expected to access innovative financial services and would be treated fairly with adequate access to payments, credit, insurance, and savings products. Originality The study covers Artificial Intelligence & Big Data Index (IAIQ), Blockchain Index (ILEGR), Disruptive Technology Index (IDTEC), Global Fintech Index (IFINIX). A key contribution of this research is to analyze the growth of Fintech in terms of size, participants, user market growth, and the role of stakeholders and policymakers.

COVID-induced sentiment and the intraday volatility spillovers between energy and other ETFs.

Did Covid19 induce market turmoil impact the intraday volatility spillovers between energy and other ETFs?. To examine this, we first estimate the realized volatility of ETFs using the 5-min high-frequency data. Next, we employ time-varying parameter vector autoregressions (TVP-VAR). Finally, we utilize the wavelet coherence measure to test the time-frequency impact of COVID-induced sentiment on the spillovers by employing investors' psychological and behavioural factors. We find that oil and stock markets are net transmitters while currency, bonds, and silver markets are net receivers. The wavelet analysis embarked significant impact of media coverage and fake news index towards shaping investors' pessimism for their investments. We proposed useful implications for policymakers, governments, investors, and portfolio managers.

Sukuk and bond dynamics in relation to exchange rate

PurposeThis study aims to contribute by expanding the existing literature on Sukuk return and volatility and exploring the implications of the Sukuk-exchange rate interactions.Design/methodology/approachThis study examines the dynamic interactions of Sukuk with exchange rate in 15 countries, employing the Wavelet approach that considers both time and investment horizons.FindingsThe results reveal significant evolving coherence of Sukuk return and volatility with the underlying exchange rate. The relationship is more potent than what this study witnesses in their counterpart bond market. For Sukuk returns, the coherence is negative, whereas it is positive for volatility. Notably, the coherence is strong in the medium to long term and intensifies during extreme economic episodes, especially during the COVID-19 pandemic. These findings are further validated by comparing firm-level matched data for Sukuk and conventional bond.Originality/valueTo the best of the authors' knowledge, this is the first study that reports the dynamic relationship of Sukuk return and volatility with the underlying exchange rate in 15 countries. Collectively, this study unites valuable insights for faith-based active Islamic investors and cross-border portfolio managers.

Connectedness between emerging stock markets, gold, cryptocurrencies, DeFi and NFT: Some new evidence from wavelet analysis

This paper examines the dynamic connectedness between Gulf countries and BRICS stocks markets with a sample of cryptocurrencies, as well as two newly developed digital assets, namely NFT and DeFi, and Gold. The period under examination spans from January 2019 until September 2022. Our analysis is based on wavelet coherence, which is a suitable methodology considering the nonlinear dynamics present in data. Our empirical results clearly identify nontrivial time-varying connectedness between different assets and the stock markets. Asymmetric patterns in the interconnections of newly developed digital assets, cryptocurrencies, Gold and emerging market indices are well-documented, especially during the advent of the health and political events. Our empirical findings have relevant implications for portfolio managers, investors and researchers about portfolio allocation, investment strategies and potential diversification benefits of NFT and DeFi digital assets. © 2023 The Author(s)

Hedging effectiveness of bitcoin and gold: Evidence from G7 stock markets

Geopolitical uncertainty creates huge pressure on financial markets, forcing decision-makers and investors to analyze risks and manage their investment portfolios. Against this background, this study investigates the risk-hedging effects of Bitcoin and Gold in the stock markets of the G7 countries. The research focuses on the period from January 5, 2017 to June 30, 2022, covering a significant portion of the COVID-19 pandemic and the Russo-Ukrainian War. The study utilizes wavelet analysis to analyze the hedging effects in the time–frequency domain, allowing for a more in-depth analysis. The findings show that bitcoin provides stronger short-term risk hedging in the G7 stock markets compared to gold during the COVID-19 and Russo-Ukrainian War periods, making a valuable contribution to the limited existing literature on the topic. © 2023 Elsevier B.V.

Wavelet analysis of S&P 500, oil prices, and economic policy uncertainty

We collect a total of 1830 data from January 2020 to June 2022 and use R for data processing and wavelet analysis. Moreover, we analyze the interactions between the COVID-19 pandemic, the Russian-Ukrainian war, crude oil price, the S&P 500 and economic policy uncertainty within a time-frequency frame work. As a result that the COVID-19 pandemic and the Russian-Ukrainian war has the extraordinary effects on the three indexes and the effect of the Russian- Ukrainian war on the crude oil price and US stock price higher than on the US economic uncertainty. © COPYRIGHT SPIE.

SEASONALITY OF METEOROLOGICAL FACTORS INFLUENCING THE COVID-19 ERA IN COASTAL AND INLAND REGIONS OF BANGLADESH

We aim to explore the seasonal influences of meteorological factors on COVID-19 era over two distinct locations in Bangladesh using a generalized linear model (GLM) and wavelet analysis. GLM model findings show that summer humidity drives COVID-19 transmission to coastal and inland locations. During the summer in the coastal area, a 1 °C earth's skin temperature increase causes a 41.9% increase in COVID (95% CL 86.32%-2.54%) transmission compared to inland. Relative humidity was recorded as the highest at 73.97% (95% CL, 99.3%, and 48.63%) for the coastal region, while wind speed and precipitation reduced confirmed cases by -38.62% and -22.15%, respectively. Wavelet analysis showed that coastal meteorological parameters were more coherent with COVID-19 than inland ones. The outcomes of this study are consistent with subtropical climate regions. Seasonality and climatic similarity should address to estimate COVID-19 trends. High societal concern and strong public health measures may decrease meteorological effect on COVID-19. [ FROM AUTHOR] Copyright of Geocarto International is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Novel COVID-19 Outbreak and Global Uncertainty in the Top-10 Affected Countries: Evidence from Wavelet Coherence Approach

This study explores the association of novel COVID-19 with the dominant financial assets, global uncertainty, commodity prices, and stock markets of the top ten corona-affected countries. We employ a wavelet coherence technique to unearth this linkage using daily data of COVID-19 deaths and reported cases from 1 January 2020 until 26 February 2021. The study finds a weak coherence between COVID-19 and global uncertainty variables in the short and medium term, while a strong positive correlation has been witnessed in the long run. The COVID-19 cases impact the stock markets in the short and medium term, while no significant impact is reported in the long run. On the other hand, a substantial impact of the COVID-19 outbreak has also been found on the exchange rate. In addition, the real asset market, such as gold, remains more stable during the COVID-19 outbreak. Thus, the study recommends that investors and portfolio managers should add such assets to their investment options to safeguard the excessive risk and downside momentum of the equity market. The study also has implications for regulators who are concerned with the neutrality of the COVID-19 effect and market stability. © 2023 by the authors.

Analysis of the relationship between bitcoin, oil prices, and the Dow Jones Industrial Average using a wavelet-based approach

This paper analyzes the correlation between bitcoin, oil price fluctuations and the DOW Jones Industrial Index in the time-frequency framework. Coherent wavelet method applied to recent daily data in the United States (1863 in total). Our research has several implications and supports for policy makers and asset managers. We find that oil prices lead the U.S. market at both low and high frequencies throughout the observation period. This result suggests that sanctions against Russia by a number of countries, including the U.S., are influencing oil prices, while oil remains a major source of systemic risk to the U.S. economy and economic uncertainty between the international level is exacerbated by tensions between Russia and Ukraine. © COPYRIGHT SPIE.

Le vaccin contre la Covid-19 a-t-il un impact sur le marché financier marocain ?

L'objectif de cet article est d'examiner le co-mouvement et la corrélation dynamique entre l'évolution du taux de vaccination contre la Covid-19 au Maroc et la performance de la bourse de Casablanca, sur la base des données quotidiennes couvrant la période du 1 Mars 2020 au 6 août 2021. Pour ce faire, l'approche de Cohérence en Ondelettes (CEO) a été adopté. Nos résultats empiriques montrent la vulnérabilité de ce marché financier à performer en période de crise sanitaire. De plus, CEO révèle une cohérence forte et significative entre la performance boursière et le taux de vaccination contre la Covid-19, avec une dominance positive de la vaccination sur les rendements.Alternate abstract: The aim of this article is to examine the co-movement and dynamic correlation between the evolution of the COVID-19 vaccination rate in Morocco and the performance of the Casablanca Stock Exchange, based on daily data forecast for the period from March 1, 2020 to March 6, 2020. August 2021. We used the wavelet coherence technique (WCT) for this purpose. Our empirical results reveal the vulnerability of this financial market to perform in times of financial turmoil. In addition, CWT reveals a strong and significant coherence between stock market performance and the COVID-19 vaccination rate, with a positive dominance of vaccination over returns.

VIX and major agricultural future markets: dynamic linkage and time-frequency relations around the COVID-19 outbreak

PurposeThe purpose of this paper is to examine the volatility spillover and lead-lag relationship between the Chicago Board Options Exchange volatility index (VIX) and the major agricultural future markets before and during the Coronavirus disease 2019 (COVID-19) outbreak.Design/methodology/approachThe methods used were the vector autoregression-Baba, Engle, Kraft and Kroner-generalized autoregressive conditional heteroskedasticity method, the Wald test and wavelet transform method.FindingsThe findings indicate that prior to the COVID-19 outbreak, there was a two-way volatility spillover impact between the majority of the sample markets. In comparison, volatility transmission between the VIX index and the agricultural future market was significantly lower following the COVID-19 outbreak, the authors observed greater coherence at higher frequencies than at lower frequencies, implying that the interdependence between the two VIX indices and the agricultural future market was stronger over a longer time-frequency domain and the VIX's signalling effect on various agricultural future prices after the COVID-19 outbreak was significantly lower.Originality/valueThe authors conducted the first comprehensive investigation of the VIX's correlation with major agricultural futures, especially during COVID-19. The findings contribute to a better understanding of the risk transmission mechanism between the VIX and major agricultural commodities futures contracts. And our findings have significant implications for investors and portfolio managers, as well as for policymakers who are concerned about the price of agricultural futures.

An Wavelet analysis of connectedness between volatility of the energy and other markets during the COVID-19 crisis

By applying novel partial wavelet coherency, this paper investigates the transmission mechanism of the volatility from the oil, gold, and silver sector to the energy sector in the time and frequency dimensions as well as the influence of the COVID-19 health crisis on this linkage. The multiple coherencies suggest at least five multiple cycles, which are located at high frequencies (the 52 – 132-day frequency band). Among these cycles, the largest one occurs at the low frequency (the 120 – 132-day frequency band), and this cycle is persistently prolonged. Notably, the four sectors' remarkable interlinkages of the volatility are presented more clearly since the COVID-19 pandemic first appeared and hit the globe (from the end of 2019 to the middle of 2020). The partial coherency between the volatility of the energy sector and the volatility of the oil sector reveals that the relations between two sectors are relatively persistent, which changes in the energy sector's volatility cause the oil sector to become more volatile. The partial coherency between the volatility of the energy sector and the volatility of the gold and silver sector suggests their interlinkages are time-varying and can be divided into four phases. The relationships are either positive or negative, and the energy sector or the silver or gold sector could be an attendant of other market's rising volatility. During the time of the COVID-19 pandemic, the energy sector's volatility is in-phase with the oil and silver sector's volatility leading, whilst the gold sector's volatility leads to the energy sector's volatility, and the relation is negative. © 2023

COVID-19, Russia-Ukraine war and interconnectedness between stock and crypto markets: a wavelet-based analysis

This paper aims to investigate the impacts of the COVID-19 pandemic and Russia-Ukraine war on the interconnectedness between the US and China stock markets, major cryptocurrency and commodity markets using the wavelet coherence approach over the period from January 1 2016 to April 18 2022. The aim is to understand how the COVID-19 pandemic and the Russia-Ukraine war have affected the hedging efficiency of volatile crypto-currencies and gold. Wavelet coherency analysis unveils perceptual differences between the short-term and longer-term market reactions. In the short-run, we find strong co-movements during the first and second waves of the pandemic. During the first wave, longer-term investors were driven by the belief of future pandemic demise. They make use of time diversification that results in positive returns. During the Russia-Ukraine war, S&P 500 leads Bitcoin, BNB, and Ripple whereas Ethereum leads S&P 500 and SSE. © 2023 The Operational Research Society.

ASSESSING THE RESILIENCE OF UK'S ECONOMY AFTER THE COVID-19 PANDEMIC AND BREXIT

The objective of the paper is to assess the resilience of UK's economy towards two economic shocks: the Covid-19 pandemic that hit the global economy in Q4 2019, in years 2020, 2021 and 2022 and the Brexit following the withdrawal of UK from the European Union on 31 January 2020. To assess the resilience of UK's economy, two sets of forecasts are generated: forecasts using historical data including the pandemic and the Brexit (from Q1 1998 to Q4 2021) and not including the pandemic and the Brexit (from Q1 1998 to Q3 2019). The computation of the difference of their averages is an indicator of the resilience of the economy during the pandemic, the greater the difference the greater the resilience. Eurozone is used as benchmark. By subtracting the average forecasted 2022-2050 Eurozone quarterly GDP growth rate (annualized) obtained with the Q1 1998-Q4 2021 data, +2.93%, by the one obtained with the Q1 1998-Q3 2019 data, +1.59%, the difference is +1.33%, whereas with UK the difference is -2.33% [-0.24% - (-2.09%)]. Thus, Eurozone shows a greater resilience (+1.33%) than the UK (-2.33%) based on 2022-2050 forecasts. In addition, the authors pointed out that the average of the 2022-2050 quarterly (annualized) growth rate forecasts of the Eurozone is expected to be +2.93% with the 1998-2021 data whereas it is expected to be only -2.09% forUK The Eurozone economy shows better prospects than the UK economy © 2022, Online Journal Modelling the New Europe.All Rights Reserved.

Assessment of Blood Microcirculation Changes after COVID-19 Using Wearable Laser Doppler Flowmetry.

The present work is focused on the study of changes in microcirculation parameters in patients who have undergone COVID-19 by means of wearable laser Doppler flowmetry (LDF) devices. The microcirculatory system is known to play a key role in the pathogenesis of COVID-19, and its disorders manifest themselves long after the patient has recovered. In the present work, microcirculatory changes were studied in dynamics on one patient for 10 days before his disease and 26 days after his recovery, and data from the group of patients undergoing rehabilitation after COVID-19 were compared with the data from a control group. A system consisting of several wearable laser Doppler flowmetry analysers was used for the studies. The patients were found to have reduced cutaneous perfusion and changes in the amplitude-frequency pattern of the LDF signal. The obtained data confirm that microcirculatory bed dysfunction is present in patients for a long period after the recovery from COVID-19.