Wavelet Coherence Approach Research Articles

Is the COVID-19 vaccine effective on the US financial market?

ObjectivesCOVID-19 is the most devastating pandemic that affected humanity and the world economy. This paper aimed to study the time-varying connectedness between the COVID-19 vaccination, infection rate (INFR), and the case fatality ratio (CFR) in the United States and the stock market returns. Study designWe used COVID-19 daily confirmed number of infections, deaths, and vaccinations and the daily US stock market index return. MethodsA wavelet coherence approach was used to assess the co-movement of the US stock market with the COVID-19 vaccination, INFR, and the CFR. ResultsThe COVID-19 vaccination, INFR, and CFR have a positive and significant influence on S&P 500 returns at the majority of business cycle frequencies with an in-phase relation. ConclusionsThe wavelet coherence analysis uncovers strong and significant connectedness between COVID-19 vaccination rate and S&P 500 return. From an economic perspective, the US government should continue its intervention with their vaccination strategy, as it is beneficial for fighting the pandemic. This may lead to the recovery of the stock market as well as to the whole economy.

An evaluation of the causal effect between air pollution and renewable electricity production in Sweden: Accounting for the effects ofCOVID‐19

SummaryThe COVID‐19 pandemic has made a significant disruption in the renewable industry, and the effects will last longer. In this context, understanding how and which specific renewable power got affected due to this crisis is of crucial importance. This study examines the nexus between COVID‐19 and Sweden's renewable electricity production from three sources of energy such as nuclear, solar, and wind, where the data ranges from January 1, 2019, to February 17, 2021. Since this study compares the period before and during the pandemic event, the study uses Air Quality Index as a measure of COVID‐19 induced event and thus study the linkage between air quality and electricity production from three types of renewable energy. To analyse the above issue, several advanced techniques such as Wavelet Power Spectrum, Wavelet Coherence, Partial and Multiple Wavelet Coherence have been applied. The findings from the Wavelet Coherence approach demonstrate that COVID‐19 has disrupted the linkage between wind energy generation and air quality, while the disruption in the case of solar and nuclear electricity generation has been minimal. Moreover, solar energy generation and air pollution both negatively affect each other, implying the need to generate solar power as well as reduce the level of air pollution in Sweden. In light of the above findings, the study discusses possible policy actions the country can take to fulfil its renewable development goals.

TREND OF OIL PRICES, GOLD, GCC STOCKS MARKET DURING COVID-19 PANDEMIC: A WAVELET APPROACH

This paper analyzed the co-movement among the stock indices of GCC members like Abudhabi, Bahrain, Oman, Saudi Arabia, Qatar and global oil prices as indicated by Brent, WTI. Gold, S&P 500 index and Dow Jones index has also been taken into account. Daily prices from January 2, 2020 up to September 30, 2020 were used for the analysis. In order to analyze the co-movement among the above mentioned indices in time frequency space wavelet transform approach has been used. The techniques employed in the study include wavelet correlation and wavelet coherence approach. The findings of this empirical study suggests that though there was no much interconnectedness among the above mentioned factors in the short run, the impact of the global pandemic crisis that got added to the oil price shock could be seen in the medium and long run. The study suggests that investors need to be cautious of their investment decisions with respect to the time horizon as these markets show significant co-movement in the long run when hit by global crisis.Keywords: Oil Prices, GCC Stock Indices, Co-movement, Wavelet AnalysisJEL Classifications: G01, G15,C32DOI: https://doi.org/10.32479/ijeep.11365

Bitcoin: Bubble that bursts or Gold that glitters?

This paper aims to shed light on the 2017 Bitcoin bubble. Firstly, by applying the dynamic time warping algorithm, we identify among several financial instruments a subsample of five assets with similar characteristics to the cryptocurrency bubble. Interestingly, among the fluctuations characterizing these assets, the algorithm shows a close affinity between the Bitcoin bubble and the 2000 NASDAQ Dotcom one. Once the subsample is identified, we study the (de)synchronization among these assets via the wavelet coherence approach. Although Bitcoin is poorly correlated with the other indices, given its scarce connection with the real economy, we observe switching phenomena among these instruments. A more careful study on these portfolio reallocations, conducted via an event study analysis, reveals that traders seem to redirect capital from stock markets and gold to Bitcoin in case of positive events of the cryptocurrency.

Real Effective Exchange Rate and Industrial Productivity in Croatia: Wavelet Coherence Analysis

Abstract This paper brings releationship between real effective exchange rate and industry production in Croatia. Research sample consists of monthly data from January 2000 up to June 2019. Following wavelet coherence approach, empirical results reveal the relationship across time and frequency domain. The empirical obtained from wavelet coherence analysis and confirmed with conventional correlation analysis suggested positive relationship between industrial productivity and real effective exchange rate in Croatia, with depreciation as a factor of positive influence on industrial productivity. Research results provided in the paper also contributes to the debate on exchange rate policy in Croatia, extending the discussion on national exchange rate policy implications.

Time-frequency relationship between R&D intensity, globalization, and carbon emissions in G7 countries: evidence from wavelet coherence analysis.

The seven leading industrial countries, called the G7, are becoming a pivotal group to fulfil their emissions-reduction commitments to manage the climate crisis. This paper investigates the relationships between R&D intensity, globalization, and carbon emissions in the context of the G7 countries for the period from 1970 to 2017. Our analysis, which examines these relationships, focuses on the wavelet coherence approach to conduct time-frequency domain analyses. The empirical results show that there is heterogeneity across different time scales and frequencies for R&D intensity, globalization, and carbon emissions within each country. Specifically, R&D intensity and globalization are negatively correlated with carbon emissions for the G7 countries, except Japan, for which they are positive. The long-term correlations between R&D intensity, globalization, and carbon emissions are higher than those in the short- and medium-term periods. In addition, the multiscale connectedness network results reveal that the strongest bidirectional correlations exist between energy consumption, economic growth, and carbon emissions. Our results provide a useful reference for policymakers in the G7 countries to effectively regulate carbon emissions.

A comparative analysis of the monetary policy transmission channels in the U.S: a wavelet-based approach

ABSTRACT This paper evaluates competing approaches to assess the effectiveness of transmission channels for the U.S. monetary policy from 1°Q 1995 to 3°Q 2019. While evaluating the competing approaches, the paper follows wavelet coherence approach providing results in time and frequency domain. The results show how money and credit channels work quite well during low volatile periods generally, whereas they suggest that these channels are less effective during periods of financial turmoil and very low interest rate. However, investment-based channels and the bank-lending channel revisited version show some effects also during periods of instability. In more detail, investment-based channels and the bank-lending channel revisited appear to be the most effective monetary policy transmission mechanisms, while the traditional banking-lending channel seems effective only in low volatile periods. Finally, the results for consumption-based channels and international trade-based channels show the least effectiveness.

A tale of company fundamentals vs sentiment driven pricing: The case of GameStop

By means of the wavelet coherence approach, we study the relationship between the GameStop returns and the sentiment driven pricing, as described by the following indicators: twitter publication count, news publication count excluding twitter, put–call ratio, and short-sale volume. The documented impacts of media-driven sentiment suggest that regulators and policymakers should continuously monitor the investing groups on social media platforms as they can create inefficiency in the market. The put–call ratio strongly and positively affects the GameStop returns prior to the peak of the GameStop saga, being one of the drivers of the January skyrocketing prices. Our results also reveal a positive relationship between the GameStop returns and the short sales volume during the GameStop episode, confirming the short squeeze phenomenon. We highlight the importance for the regulators to consider limiting some predatory short-selling practices, namely “naked” short selling, as excessive short selling may move the market towards inefficiency.

Liquidity Connectedness of Cryptocurrencies and Stock Markets during COVID-19: A Wavelet Coherence Approach

Using wavelet coherence framework on five major cryptocurrencies and three major stock market indices over the COVID-19 period from January 1st, 2020 to February 8th, 2021, our study concludes that SSEC index liquidity co-moves with liquidity of all the cryptocurrencies, while liquidities of Nikkei 225 and NYSE indices very weakly or not at all co-move with the sampled cryptocurrencies over most of our sample period. Our findings show that SSEC index liquidity positively co-moves with liquidities of all sampled crypto currencies over a limited time span and generally at short-term frequency band of 0-8 days; however, Ripple liquidity positively co-moves with liquidity of SSEC index at both shorter-horizon and long-term. Overall, our study provides useful insights that the choice of the crypto currency can play a significant role in portfolio liquidity diversification for investors investing in Nikkei 225 or NYSE index.

Revisiting the nexus between house pricing and money demand: Power spectrum and wavelet coherence based approach

This study examines the impact of house price on money demand in case of China for the period of 1988Q1-2017Q4. The present study used different estimators, which are robust to handling the endogeneity issues in the data, to capture the long-run effect of housing price index on money demand while controlling for interest rate, gross domestic product and consumer price index. The results suggest that house prices along with GDP, inflation and interest rate are important factors in explaining the money demand in China. To capture the vulnerability periods and identify the behaviour of the money demand and house price index variables in China, this study employs wavelet power spectrum. The results further show that there was a significant vulnerability in money demand between 2006 and 2012 in the short and medium terms. Besides, in order to identify the co-movement between house price and money demand in China, the continuous wavelet coherence approach is applied. The outcomes of continuous wavelet coherence approach reveal that there is strong linkage between money demand and house price index between 2002 and 2018 at both short and long terms. The results show that there is a positive and significant correlation between money demand and house price index in China. Thus, house price index can be a predictive factor for future money demand at low, middle and high frequencies.

Economic growth, carbon dioxide emissions and energy consumption in Algeria: a wavelet coherence approach

PurposeThe world is nowadays facing major environmental damage and climate change everywhere. Carbon dioxide emissions are major causes of such change. It is in this respect that the current study provides a fresh insight into the dynamic nexus between energy consumption (EC), economic growth (EG) and CO2 emissions in Algeria, as it is considered as one of the top CO2 emitters in Africa.Design/methodology/approachThe authors use the wavelet approaches and Breitung and Candelon (2006) causality test to gauge the association between EC, EG and CO2 emissions over the period 1971–2018. Specifically, this study implements the wavelet power spectrum (WPS) to identify the power and variability of each variable at different time scales. The wavelet coherence, phase differences and partial wavelet coherence are also used to assess the co-movement and lead lag relationship between economic growth, energy consumption and CO2 emissions over different time scale. Finally, Breitung and Candelon (2006) causality test is used to find the causality among variables.FindingsThe wavelet power spectrum results indicate that economic growth, energy consumption and CO2 emissions share common strong variance in the medium and long run. Furthermore, the wavelet coherence results suggest that there is a significant co-movement between EG and CO2 emissions, and EG is the leading variable for CO2 emissions and EC. The results also unveil that both EG and EC cause CO2 emissions both in short and long run. The results suggest that Algeria should take suitable measures towards the promotion of renewable energy sources.Originality/valueThe present empirical study filled the literature gap of applying the wavelet approach and frequency domain spectral causality test to examine this relevant issue for Algeria.

Co-movement of commodity price indexes and energy price index: a wavelet coherence approach

This research sheds light on the causal link between commodity price indexes, i.e., the Agricultural Raw Materials Price Index, Industry Input Price Index, Metal Price Index, and Energy Price Index, in the global market, using wavelet coherence, Toda–Yamamoto causality, and gradual shift causality tests over the period 1992M1 to 2019M12. Findings from the wavelet power spectrum and partial wavelet coherence reveal that: (1) there was significant volatility in the Agricultural Raw Materials Price Index, Industry Input Price Index, Metal Price Index, and Energy Price Index between 2004 and 2014 at different frequencies; and (2) commodity price indexes significantly caused the energy price index at different time periods and frequencies. It is noteworthy that the outcomes of the Toda–Yamamoto causality and gradual-shift causality tests are in line with the results of wavelet coherence.

Do CO2 emissions, energy consumption and globalization promote economic growth? Empirical evidence from Japan.

In the empirical literature, there is no agreement on the linkage between environmental deterioration and economic growth. Thus, this paper aims to explore the long-run and causal effects of CO2 emissions, globalization energy usage, trade openness and urbanization on economic growth in Japan by employing new econometric techniques. The paper uses a dataset spanning from 1970 to 2015 and employs recent econometric techniques. To the best of the investigator's understanding, no prior studies have examined this linkage utilizing the wavelet coherence technique for Japan. The novelty of the wavelet is that it can capture the causality and long-run linkage between economic variables at different frequencies and periods. Thus, the study's aim is to address the following questions: (i) Is there a long-run and causal linkage between economic growth, energy usage, urbanization, CO2 emissions, trade openness and globalization? (ii) What is the interaction between economic growth and the regressors at various frequencies and periods? The paper utilizes the ARDL, DOLS and FMOLS to catch the long-run effects, whereas the wavelet coherence technique is employed to capture the causal effects among the indicators. The outcomes of the ARDL show that urbanization, CO2 emissions, globalization and energy usage trigger economic growth, while no significant linkage is found between trade openness and economic growth. The wavelet coherence approach reveals (i) positive co-movements between economic growth and the regressors and (ii) a one-way causality from CO2 emissions and energy usage to economic growth.

Investigating the Causal Linkage Among Economic Growth, Energy Consumption and CO2 Emissions in Thailand: An Application of the Wavelet Coherence Approach

The study aims to explore the causal linkage between CO2 emissions, economic growth and energy consumption in Thailand utilizing the wavelet coherence approach, conventional Granger and the Toda-Yamamoto causality techniques. In this study, In this study, time-series data spanning the period between 1971 and 2018 were used. No prior study has used the wavelet coherence approach to collect information on the association and causal interrelationship among these economic variables at different frequencies and timeframes in Thailand. The study objectives are structured to answer the following question: Does economic growth and energy consumption lead to CO2 emissions in Thailand?. The findings revealed that: (a) Changes in economic growth led to changes in CO2 emissions in Thailand at different frequencies (different scales) between 1971 and 2018. (b) A bidirectional causal relationship between CO2 emissions and energy consumption. (c) A positive correlation between CO2 emissions and energy usage in the short and long-run between 1971 and 2018. (d) A positive correlation between GDP growth and CO2 emissions in the short and long-run between 1971 and 2018. The study suggested that Thailand should initiate stronger policies towards enhancing the efficiency of energy and energy-usage programs to minimize unnecessary energy waste.

Who raised from the abyss? A comparison between cryptocurrency and stock market dynamics during the COVID-19 pandemic

This research examines the behaviour of cryptocurrencies and stock markets during the COVID-19 pandemic through the wavelet coherence approach and Markov switching autoregressive model. Our results show a financial contagion in March, since both cryptocurrency and stock prices fell steeply. Despite this turn-down, cryptocurrencies promptly rebounded, while stock markets are trapped in the bear phase. In other words, we observe that the price dynamics during the pandemic depends on the type of the market. These findings are relevant for investors since some hedging properties can be found in the cryptocurrency response to such a drastic event.

Co‐movement of foreign exchange rate returns and stock market returns in an emerging market: Evidence from the wavelet coherence approach

AbstractThis study aims to investigate the causal relationship between the Turkish stock market returns, namely XU100, and foreign exchange rates, namely USD/TRY and EUR/TRY, in Turkey using the wavelet coherence approach. In this study, we focus on the period from April 2000 to March 2019. Our findings reveal the following: (i) While we identify substantial volatility in the exchange rate during the 2000 November (banking crisis), 2001 February (economic crisis), and 2018 July (exchange rate crisis) periods, significant volatility was observed in the Turkish stock market during the 2000 banking crisis, 2001 economic crisis, and 2008 global crisis periods; (ii) There is a negative correlation between the Turkish stock market and foreign exchange rates at different frequencies over the selected sample period; (iii) A unidirectional causality runs from the Turkish stock market to foreign exchange rates between 2000 and 2004 at a scale of 4 months and between 2008 and 2012 at a scale of 32 months; (iv) Although inconsistent results are observed for the models of USD/TRY‐XU100 and EUR/TRY‐XU100, our empirical results show that the correlations between USD/TRY and XU100 are stronger than between EUR/TRY and XU100.

Nexus between non‐performing loans and economic growth in emerging countries: Evidence from Turkey with wavelet coherence approach

AbstractThe study aims to capture the co‐movement between non‐performing loans (NPLs) and economic growth (EG) in Turkey using the quarterly data from 2005/Q1 to 2019/Q4 and applying the wavelet coherence approach, which allows the study to explore both the long‐run and short‐run causal linkages between NPLs and EG in Turkey. The findings reveal that (a) there is a significant vulnerability in NPLs and EG over the selected period at different frequency levels; (b) EG in Turkey has a strong power for explaining NPLs in the long‐run; (c) EG causes NPLs in Turkey in the short‐term between 2007 and 2010, which implies that the credit growth in the period with the increasing NPLs supports EG of Turkey. The outcomes of the tests underline the importance of EG for predicting NPLs in Turkey.

Real effective exchange rate and unemployment across post-transition Europe

Purpose: The aim of this paper is to examine the co-movement between the real effective exchange rate and unemployment across post-transition Europe. Methodology: The research data sample in this paper consists of monthly data from 2000M1 to 2019M6 for ten European post-transition countries. After standard correlation analysis, the research followed a wavelet coherence approach, provided time-series analysis in the time-frequency domain and illustrated evolution of the co-movements in the observed period. Results: Conventional approach research results suggest no significant correlation between variables under consideration in cases of Poland and Lithuania. In cases of Latvia and Slovenia, standard correlation coefficients were positive and not in line with the theory. Correlation coefficients supported the theoretical assumption in six other countries included in the study. Wavelet coherence analysis results provided deeper insights into the relationship over time and the frequency domain. Empirical results gained in this research revealed a decline in the unemployment rate accompanied by depreciation of the real effective exchange rate as a prominent pattern at the beginning of the observation period suggesting pro-cyclical monetary policy. Conclusion: During the crisis of 2008 no link between variables under consideration was confirmed, while after the crisis empirical results were in line with the theoretical assumption, suggesting that depreciation of the real effective exchange rate might be used as an instrument to boost employment.

Effect of Meteorological Parameters on PM10 Concentrations in Ardahan by Wavelet Coherence Analysis

In the city of Ardahan, the PM10 concentrations are high especially in winter and autumn due to heating in buildings. This paper investigates the impact of meteorological parameters (air temperature, air pressure, humidity and wind speed) on the PM10 concentrations in the city of Ardahan by using the Wavelet Coherence analysis. The data have been provided from the records of the Ministry of Environment and Urbanization Continuous Monitoring Center and the Turkish State Meteorological Service in between 2010-2020. The results of the study show that selected meteorological parameters have the different effects on the PM10 concentrations in a period of ten years. Wavelet coherence approach presents clearly the influence of meteorological factors on the PM10 concentrations, and the approach is quite useful in terms of the practical explanation of available data, also.

New insights into an old issue: exploring the nexus between government expenditures and economic growth in the United States

ABSTRACT This study investigates the correlation between government expenditures and economic growth by applying the wavelet coherence approach for the period of 1960Q2 – 2019Q3 in the United States. Two main concepts regarding the correlation between government expenditures and economic growth are the renowned Keynesian approach, which argues that government expenditures lead economic growth, and Wagner’s Law, which advocates the opposite. Our results indicate that economic growth leads government expenditures in the long run, whereas government expenditures only enhance economic growth in the short run and in periods of recession.