Middle Quantiles Research Articles

Asymmetric dependency among US national financial conditions and clean energy markets

This paper examines the relationship between the US National Financial Conditions Index (NFCI) and the clean energy industry using quantile and frequency connectedness, cross-quantile, and wavelet quantile correlation (WQC) techniques. Results reveal (a) a stronger dependence between the NFCI and clean energy under bullish market states. Moreover, the total connectedness between the NFCI and clean energy mostly exhibits time-varying characteristics. In particular, clean energy has a greater spillover effect than the NFCI. (b) Dynamic frequency total connectedness at extreme quantiles provided a more comprehensive view of structural shocks in financial markets, and major crises, such as COVID-19, significantly amplified this connectedness. Overall, the WilderHill Clean Energy Index and the NASDAQ OMX Renewable Energy Index demonstrate substantial potential for hedging financial conditions. (c) The cross-quantile correlation results revealed an asymmetric dependency, demonstrating a sustained significant positive relationship between the NFCI and clean energy index (CEI) across the relative higher quantiles and middle quantiles. The WQC showed that the NFCI and specific CEIs tended to exhibit the strongest positive correlations in nonextreme quantiles and lower frequencies. These results can be of considerable interest to various financial market participants.

How does energy resource diversification affect economic development? Evidence from BRICS economies

This study explores the impact of energy diversification on economic growth in the BRICS (i.e. Brazil, Russia, India, China and South Africa) from 1995 to 2018. The study has used a newly constructed energy diversification index. The results based on the Quantile-on-Quantile (QQR) methodology demonstrate that the impact of energy diversification on the growth of the economy is heterogeneous among nations. It appears that lower and middle quantiles of the energy diversification reduce economic growth, while higher quantile of the energy diversification increases it. It is advised that the BRICS countries should develop crucial steps while transitioning from fossil fuels to renewable energy without hampering economic growth. It is further suggested that the BRICS countries need to ensure energy sustainability through effective energy diversification. Such steps will enhance economic prosperity for BRICS countries in the long run.

Receiver or transmitter? Unlocking the role of green technology innovation in sustainable development, energy, and carbon markets

In the context of sustainable development, the energy crisis and the volatile carbon trading markets have made the integration of green technology increasingly essential. This study explores the spillover effects between green technology innovation (GTI), oil price, clean energy (CE), carbon emissions trading prices (CETP), and sustainable development (SD) using quantile connectedness. The static analysis reveals that the connectedness relationship in extreme quantiles is remarkably more related than the middle quantile. The dynamic results indicate that major events significantly strengthen the overall risk correlation, but spillover effects are asymmetric under different quantiles. Further analysis under extreme market conditions demonstrates that SD and CE have produced a continuous and steady risk spillover to GTI, while CETP increased the risk transmission to GTI following the COVID-19 pandemic. This research underscores the significance of coordinating the development of GTI, energy, carbon markets, and SD by investigating risk contagion mechanisms in various market scenarios. In terms of policy implications, the findings indicate that stable energy system and reasonable carbon prices can stimulate the advancement of GTI.

Hedge and safe haven functions of gold and Bitcoin around COVID-19: evidence from U.S. financial assets

ABSTRACT The COVID-19 outbreak triggered an unparalleled health crisis and financial shock. We re-examine whether gold and Bitcoin can function as hedges and safe havens for U.S. financial assets before and after the COVID-19 outbreak. This study employs the quantile-on-quantile and causality-in-quantiles methods to detect the nonlinear and asymmetric relationship of gold and Bitcoin with U.S. financial assets. The results reveal negative dependence of the U.S. dollar, real estate, crude oil, and natural gas on gold and Bitcoin in some quantiles during both periods, indicating that gold and Bitcoin are hedges for these four assets. Following the COVID-19 outbreak, the negative correlations that exist for stock and clean energy with Bitcoin almost all turn positive, gold and Bitcoin lose their ability to hedge stocks and clean energy. Bitcoin can still hedge bonds in middle and high quantiles, whereas gold does not possess this capability against the bond. Additionally, there is an asymmetric causality in the mean and variance from U.S. financial assets to gold and Bitcoin, which generally exists in the middle quantiles but not in the extreme (high and low) quantiles. Our findings provide clear guidelines to market participants on risk management and policy decisions according to market conditions.

Does an environmental stringent policy really matter to achieve environmental sustainability in BRICS-T region? Evidence from novel method of moments quantile regression approach

Amidst pressing global environmental challenges, exacerbated by climate change and the imminent threat of global warming, there is a critical need to assess the efficacy of environmental policies. This study centers its attention on the pivotal role of these policies in addressing environmental concerns. Specifically, our research aims to scrutinize the impact of stringent environmental policies on environmental quality under the theoretical underpinnings of environmental Kuznets curve. To achieve this objective, the study collected data from BRICS-T economies over the period of 1990–2020. This study employed the method of moments quantile regression technique for empirical analysis. Our study validates the presence of the Environmental Kuznets curve (EKC hypothesis). Empirical findings reveal the sustained significance of environmental stringency across all quantiles, demonstrating a positive correlation in lower quantiles and a negative correlation in higher quantiles. At lower quantiles, the impact is insignificant initially, but pronounced due to efficiency improvements induced by stringent policies. The effects became negative at middle quantiles, indicating stringent policies might encounter diminishing returns where policy measures start stabilizing ecological impacts. At higher quantiles, the influence of ESI remains significant, reflecting ongoing adaptations in larger economies with higher ecological footprints. This suggests the potential effectiveness of stringent regulatory measures in mitigating environmental impacts and reducing ecological footprints. The identified inverted U-shaped curve signifies that while stringent policies may not inherently enhance environmental health, beyond a certain threshold, they can indeed contribute to its improvement. Our policy recommendation advocates for the widespread adoption and promotion of such stringent measures to safeguard environmental health.

The Impact of Financial Stress and Uncertainty on Green and Conventional Bonds and Stocks: A Nonlinear and Nonparametric Quantile Analysis

This study aims to investigate the impact of financial stress and uncertainty on the returns of green and conventional bonds and stocks in the United States from 2010 to 2022. The research utilizes nonlinear and nonparametric analysis, which includes the quantile-on-quantile and nonparametric causality-in-quantiles approaches to examine the relationship between variables. The data analyzed using R programming language show that financial stress positively impacts the middle quantiles of both conventional and green equity, while financial uncertainty negatively impacts upper quantiles. The study also finds that financial stress has a more significant impact on all types of bonds compared to financial uncertainty, with conventional bonds being more affected. This study proposes a pyramid that classifies financial assets based on their susceptibility to financial stress, which could help investors evaluate risk levels and make better investment decisions. The study recommends that policymakers should encourage green investments by offering incentives, such as tax credits. They should also focus on enhancing the efficiency of volatile assets by implementing new investment rules and regulations.

Towards sustainable initiatives: Evidence from green finance mitigating ecological footprint in East Asia and Pacific nations

Green finance serves as a bridge between development and ecological sustainability. It provides a roadmap for countries to accomplish sustainable development goals by simultaneously curbing their ecological footprint. Green financing prioritizes eco-friendly technologies, sustainable behaviors, renewable energy, and green infrastructure, promoting positive changes. This study examines the role of green finance on the ecological footprint of 11 East Asian and Pacific countries from 2000 to 2023. This study uses different diagnostic tests to prove the existence of cross-sectional dependency, non-normality, and slope heterogeneity. The coefficients are estimated using the fully modified ordinary least squares (FMOLS) approach and panel quantile regression at different quantiles. The results show the validity of an inverted U-shaped relationship between green finance and the ecological footprint. Further analysis explores that at the middle quantile, all selected countries except Mongolia and the Philippines, while the FMOLS approach shows that all countries’ green finance reduces their ecological footprint. Additionally, globalization reduces the ecological footprint, while economic growth, industrialization, and urbanization increase the ecological footprint. This study recommends that to fight against climate change, the selected countries should focus more on green finance. Financial institutions should provide funds only for environment-friendly technologies.

Suboptimal micronutrient intake among children aged 6 to 23 months in Ethiopia: Further analysis of the demographic and health survey.

The recommended essential micronutrient such as food rich in vitamin-A or iron, multiple micronutrient powder or iron supplement, routine daily consumption of iodine, and vitamin-A supplement are deficient among children in Ethiopia. This has been a significant public health problem despite the government efforts. Although few studies have examined the micronutrient intake among children, they are limited in scope and methodological measurements. Analyzing the micronutrient intake among children across all regions and leveraging all essential micronutrient elements are crucial for generating improved evidence to better inform policy. Thus, we examined the micronutrient intake among children aged 6 to 23 months in Ethiopia. We used data from the Ethiopian Demographic and Health Survey. A two-stage stratified sampling technique was employed, and 1392 children aged 6 to 23 months were included in our analysis. We conducted a multilevel mixed-effect binary logistic regression analysis to identify determinants of micronutrient intake. In the final model, we used a p-value of less than 0.05 and Adjusted Odds Ratio (AOR) with their 95% confidence interval (CI). We found that only 27.6% (95% CI: 26.8-31.6) of children aged 6 to 23 months were received the recommended micronutrients in Ethiopia. We identified that maternal educational status (Educated mothers (AOR = 2.09, 95%CI:1.23-3.58)), health facility delivery (AOR = 2.14, 95%CI:1.42-2.98), household wealth status (middle quantile (AOR = 1.80, 95%CI:1.01-3.21)), children's age (12 to 23 months age (AOR = 2.36, 95% CI: 1.33-4.21)), and mother's exposure to media (AOR = 1.70, 95%CI: 1.42-2.04) were increased micronutrient intake, whereas residing in the rural communities (AOR = 0.27, 95%CI: 0.21-0.34) decreased micronutrient intake. Nearly three-fourths of children aged 6 to 23 months did not receive the recommended essential micronutrients in Ethiopia. Therefore, there is a need to broaden strategies aimed at enhancing the intake by improving information and knowledge dissemination among mothers during facility visits and through media channels.

Asymmetric interactions among cutting-edge technologies and pioneering conventional and Islamic cryptocurrencies: fresh evidence from intra-day-based good and bad volatilities

This study examines the nexus between the good and bad volatilities of three technological revolutions—financial technology (FinTech), the Internet of Things, and artificial intelligence and technology—as well as the two main conventional and Islamic cryptocurrency platforms, Bitcoin and Stellar, via three approaches: quantile cross-spectral coherence, quantile-VAR connectedness, and quantile-based non-linear causality-in-mean and variance analysis. The results are as follows: (1) under normal market conditions, in long-run horizons there is a significant positive cross-spectral relationship between FinTech's positive volatilities and Stellar’s negative volatilities; (2) Stellar’s negative and positive volatilities exhibit the highest net spillovers at the lower and upper tails, respectively; and (3) the quantile-based causality results indicate that Bitcoin’s good (bad) volatilities can lead to bad (good) volatilities in all three smart technologies operating between normal and bull market conditions. Moreover, the Bitcoin industry’s negative volatilities have a bilateral cause-and-effect relationship with FinTech’s positive volatilities. By analyzing the second moment, we found that Bitcoin's negative volatilities are the only cause variable that generates FinTech's good volatility in a unidirectional manner. As for Stellar, only bad volatilities have the potential to signal good volatilities for cutting-edge technologies in some middle quantiles, whereas good volatilities have no significant effect. Hence, the trade-off between Bitcoin and cutting-edge technologies, especially FinTech-related advancements, appear more broadly and randomly compared with the Stellar-innovative technologies nexus. The findings provide valuable insights for FinTech companies, blockchain developers, crypto-asset regulators, portfolio managers, and high-tech investors.

From black to green: Quantifying the impact of economic growth, resource management, and green technologies on CO2 emissions

In an exploration of environmental concerns, this groundbreaking research delves into the relationship between GDP per capita, coal rents, forest rents, mineral rents, oil rents, natural gas rents, fossil fuels, renewables, environmental tax and environment-related technologies on CO2 emissions in 30 highly emitting countries from 1995 to 2021 using instrumental-variables regression Two-Stage least squares (IV-2SLS) regression and two-step system generalized method of moments (GMM) estimates. Our results indicate a significant positive relationship between economic growth and CO2 emissions across all quantiles, showcasing an EKC with diminishing marginal effects. Coal rents exhibit a statistically significant negative relationship with emissions, particularly in higher quantiles, and mineral rents show a negative association with CO2 emissions in lower and middle quantiles, reinforcing the idea of resource management in emissions reduction. Fossil fuels exert a considerable adverse impact on emissions, with a rising effect in progressive quantiles. Conversely, renewable energy significantly curtails CO2 emissions, with higher impacts in lower quantiles. Environmental tax also mitigates CO2 emissions. Environment-related technologies play a pivotal role in emission reduction, particularly in lower and middle quantiles, emphasizing the need for innovative solutions. These findings provide valuable insights for policymakers, highlighting the importance of tailoring interventions to different emission levels and leveraging diverse strategies for sustainable development.

Quantifying Environmental Degradation through Renewable Energy, Financial Development and Economic Sustainability: Insights from Panel Quantile Regression Analysis

The degradation of the environment is a global concern that needs serious attention, including the environmental Kuznets curve (EKC) hypothesis. This article examines the effects of renewable energy, financial development and economic sustainability on the environmental quality of newly industrialized countries (NICs) from 1998 to 2021 in light of the increasing severity of environmental problems associated with industrialization. This study utilized different panel cointegration estimation techniques and panel quantile regression (PQR) estimates to obtain robust findings by examining the variance of each quantile. The results of the cointegration tests confirm the long-run relationship among the variables. Nevertheless, the outcomes from the PQR unveiled that renewable energy negatively and significantly influences CO2 emissions in NICs, namely in the lower and middle quantiles (20th–50th). Financial development showed heterogeneity in the results of all the quantiles. It results in an increase in CO2 emissions from the 70th to 90th quantiles in NICs. The EKC hypothesis is relevant to these findings as this study presents the economic sustainability index, which postulates that when NICs achieve sustainability, they give greater importance to environmental preservation and sustainability. This shift is characterized by reduced emissions throughout all quantiles, ranging from the 10th to the 90th. Economic sustainability corresponds to the falling part of the U-shaped curve of the EKC, wherein sustainability gets priority, resulting in reduced CO2 emissions. Analogous results have been confirmed by comparing heterogeneous panel estimators; nonetheless, there was a significant variation in the intensity of their parameters. Moreover, the robustness analysis through quantile slope equality and symmetric quantiles tests proved legitimate results. The study’s findings offer policymakers with valuable policy recommendations. JEL Codes: C1, F36, F43, O44, Q56

Trade policy and environmental sustainability in Africa: An empirical analysis

AbstractThis study investigates whether trade policy instruments—tariffs—strengthen or worsen African environmental sustainability. To drive out the objectives of the study, fully modified ordinary least square (FMOLS), dynamic OLS (DOLS), augmented mean group (AMG), method of moment quantile regression (MMQR) and Dumitrescu–Hurlin panel causality approaches are used to analyse the effect of tariff in addition to other control variables on carbon and ecological footprints as measured of environmental sustainability from 2001 to 2020. The results from the MMQR reveal that tariffs have a significant positive effect on carbon footprints in the 0.15 quantile, while the effect becomes insignificant between 0.25 and 0.5 quantiles. However, at the upper quantiles level (0.75–0.95), the impact of the tariff on carbon footprint is negative and significant, with increasing coefficients. Furthermore, tariffs significantly positively affect lower and middle quantiles' ecological footprints (0.15–0.5). However, the effect turns negative at the upper quantiles (0.9 and 0.95), suggesting that tariff reduces ecological footprint at these levels. In addition, the long‐run estimates (FMOLS, DOLS and AMG) also support the upper quantile estimates of MMQR. A one‐way causality between tariffs, carbon and ecological footprint was found. These findings reveal that tariffs do not create market inefficiency in Africa. This study recommends that tariffs as a trade policy instrument could be used to strengthen Africa's environmental quality. The government can use the tariff revenue to subsidize cleaner production and consumption and move the economy from a traditional energy source to renewable energy.

Role of energy transition in easing energy security risk and decreasing CO2 emissions: Disaggregated level evidence from the USA by quantile-based models

Consistent with the increasing environmental interest, the clean energy transition is highly critical to achieving decarbonization targets. Also, energy security has become an important topic under the shadow of the energy crisis,. Accordingly, countries have been trying to stimulate clean energy use to preserve the environment and ensure energy security. So, considering the leading role of economic size and volume of energy use, the study examines the USA to define whether energy transition helps decrease energy security risk (ESR) and curb CO2 emissions. So, the study applies a disaggregated level analysis by performing quantile-based models for the period from 2001/Q1 through 2022/Q4. The results demonstrate that (i) the energy transition index decreases environmental ESR at higher quantiles and reliability ESR at lower and middle quantiles, whereas it is not beneficial in declining economic and geopolitical ESR; (ii) energy transition curbs CO2 emissions in building and transport sectors at lower quantiles, whereas it does not help decrease CO2 emissions in industrial and power sectors; (iii) energy transition is mostly ineffective on ESR, whereas it is highly effective in curbing CO2 emissions in all sectors except for transport across various quantiles as time passes; (iv) the results differ according to the aggregated and disaggregated levels; (v) the results are consistent across main and alternative models. Hence, the study highlights the dominant effect of energy transition in curbing sectoral CO2 emissions rather than easing ESR. Accordingly, the study discusses various policy implications for the USA.

Impact of environmental policy stringency on sectoral GHG emissions: evidence from Finland and Sweden by nonlinear quantile-based methods

ABSTRACT The growing societal concern regarding environmental matters has led to the implementation of many environmental measures intended to protect the environment and address global warming by lessening emissions and mitigating climate change. In line with this movement, this study scrutinizes the impact of these environmental measures on greenhouse gas (GHG) emissions to analyze the cases of Finland and Sweden. More specifically, the study employs the Environmental Policy Stringency (EPS) index as a proxy for environmental measures, explores sector-specific GHG emissions by employing nonlinear quantile-based methodologies (including quantile-on-quantile regression and Granger causality-in-quantiles methods as the primary model and quantile regression for robustness checking) spanning the period from 1991/Q1 to 2020/Q4. The findings show that: (i) EPS lessens GHG emissions from fuel exploitation, industrial combustion, and the power industry sector at lower and middle quantiles in Finland and Sweden; (ii) EPS decreases GHG emissions from processes, transportation, and waste sectors in Finland but increases them in Sweden at higher quantiles; (iii) EPS leads to an increase in GHG emissions from the agriculture and construction sectors at higher quantiles; (iv) EPS has a causal effect on sector-specific GHG emissions across different quantiles; (v) the robustness of the findings is largely confirmed. Hence, the study underscores the varying impacts of EPS on sectoral GHG emissions based on quantiles, sectors, and countries, emphasizing the need for policymakers to adopt environmental policies to comprise these differences and adjust the policy framework accordingly.

Dynamic effect of disaggregated level electricity generation on residential carbon emissions: Daily inference from the largest EU economies

This study examines the dynamic effects of electricity generation (EG) on CO2 emissions from the residential sector. The study focuses on the EU-4 countries (Germany, Spain, France, and Italy), considers residential CO2 emissions as the dependent variable, and includes disaggregated level fossil and renewable EG as explanatory variables. In this context, the study runs nonlinear quantile-on-quantile (QQ) regression and Granger causality in quantiles (GQ) as the main models with daily data from January 2, 2019, to March 10, 2023, while quantile regression (QR) is used for robustness check. The findings present that in terms of CO2 emissions: (i) EG from coal, natural gas, and oil has a stimulating effect at higher quantiles in all countries; (ii) EG from hydro has an increasing effect at higher quantiles, while it has a decreasing effect at lower and middle quantiles in all countries except France; (iii) EG from solar has a dampening effect at higher quantiles in all countries except France; (iv) EG from wind has a declining effect at higher quantiles in both Spain and France; (v) both fossil and renewable energy EG have a causal effect on residential sector CO2 emissions at the disaggregated level except at some quantiles. Overall, the effect size and the causal effect of EG on CO2 emissions change for quantiles, countries, and EG sources. Therefore, the study proposes to rely on the specific EG sources for Germany and Italy (solar energy), Spain, and France (wind energy) to mitigate climate change by reducing residential CO2 emissions.

Assessing the impact of resource efficiency, renewable energy R&D spending, and green technologies on environmental sustainability in Germany: Evidence from a Wavelet Quantile-on-Quantile Regression

One important challenge in the world today is how to reverse the growth of carbon dioxide emissions to save the planet from environmental degradation without putting economic growth at risk. Several measures and initiatives such as resource efficiency, green energy transition, energy technologies, emission control, etc. Have been adopted by several countries worldwide in order to mitigate CO2 emissions. This study investigates the impact of resource efficiency, renewable energy Research and Development (R&D) expenditures, and green technologies towards fostering environmental sustainability in Germany. Using quarterly data spanning from 1974 to 2019, the study applies the Wavelet Quantile-on-Quantile Regression (WQQR) approach. This method embeds a wavelet kernel into quantile-on-quantile regression to capture the time-varying coefficients. The empirical findings reveal a negative impact of resource efficiency, renewable energy R&D expenditures, and green technologies on energy-based carbon intensity. The results further reveal that, with the exception of green technologies, the negative effects of resource efficiency and renewable energy R&D expenditures are stronger in the middle quantiles. The study demonstrates the robustness of these results through the wavelet quantile regression analysis. Finally, the study offers valuable policy implications that align with the United Nations’ Sustainable Development Goals (SDGs) 7 and 13, aiming to achieve a sustainable environment.

A quantile regression approach to assess the impact of water-related environmental innovations on water stress

This paper examines the further question of whether water-related environmental innovations affect water stress in three main sectors such as agriculture, industry and services. The sample consists of 30 OECD countries for the period 2000–2019. This paper employs the method of moments quantile regression (MMQR) with fixed effects to analyze the effects of water-related innovative activities across different quantiles of water stress for all three sectors separately. The empirical results indicate that water-related innovations positively affect water stress in the agricultural sector in the lower and middle quantiles, while it has a negative effect in the middle and higher quantiles for the services sector and the higher quantiles for the industrial sector. These findings reveal nuanced effects of water-related innovations on water stress across sectors. Furthermore, the study suggests that while innovations in the industrial and services sectors can mitigate water stress beyond a certain threshold level, the agricultural sector appears to benefit comparatively less from such innovations. These findings underscore the importance of complementing water-related innovations with appropriate regulatory measures, to address informal practices such as losses and leakages in agricultural irrigation. Ultimately, this study provides valuable insights for policy makers to formulate targeted environmental policies and strategies, especially in the context of climate change adaptation, thereby enabling a more effective allocation of resources to mitigate water stress within each sector.

Evaluating the nexus between energy transition and load capacity factor in Germany: evidence from novel quantile-based approaches

ABSTRACT This study attempts to investigate how Germany’s energy transition has affected environmental quality by considering natural resources, economic growth, financial development, and financial globalization for the period from 1980 to 2021. It is also aimed to discover that the interactions alter with different levels of load capacity factor and explanatory variables using novel quantile-based approaches. Thanks to the unique approaches utilized, the environmental efficacy of the energy transition process can be determined for different quantiles and time periods. The results reveal that although financial globalization and financial development enhance environmental quality, economic growth and increasing natural resource rents harms environment. In addition, the increase in energy transition in all quantiles also has a positive effect on the load capacity. This impact is weak in quantiles with high and low environmental quality, but it becomes more pronounced in middle quantiles of load capacity. Our study offers various policy recommendations to increase the short- and long-term low-level environmental effectiveness of the energy transition process in Germany.

Investigating extreme linkage topology in the aerospace and defence industry

This paper analyses return and volatility spillovers among 21 global aerospace and defence (A&D) companies from six countries and three continents using quantile-based models and daily data from August 23, 2010, to July 1, 2022. The results show that both return and volatility spillovers vary over time, and those estimated at normal market conditions, intensify during COVID-19 and Russia–Ukraine war periods. Spillovers of returns estimated at lower and upper quantiles exceed those estimated at the middle quantile. Volatility spillover is extremely high at the upper quantile and exhibits low variability. Chinese defence stocks are segmented from the rest under normal return conditions and a moderate volatility state. In contrast, they are somewhat integrated under extreme return conditions and volatility states. Hence, Chinese defence stocks entail more diversification benefits under normal conditions than in bear or bull markets. Further analysis shows that geopolitical risk consistently plays a significant role in driving both returns and volatility spillovers, especially during the pandemic and war periods, without ignoring the role of macroeconomic and financial variables. These results have implications for investors concerned with stock portfolio management under various return and volatility conditions and for policymakers preoccupied with policy design under unstable periods

Relationship between monetary policy and financial asset returns in Türkiye: Time, frequency, and quantile-based effects

This study analyzes the effect of monetary policy, which are proxied by weighted average cost of funding (WACF) and Borsa Istanbul repurchase interest rate (REPO), on the returns of the main financial assets of monetary policy in Türkiye. Using daily data between January 4, 2011 and August 31, 2023, the study applies novel nonlinear time-series methods, such as wavelet coherence (WC) and quantile-on-quantile regression (QQ) as baseline methods and quantile regression (QR) for robustness. The findings demonstrate that (i) monetary policy has a stronger effect on financial asset returns at middle and higher frequencies across different periods; (ii) monetary policy has mainly declines (increases) effect on financial asset returns at lower and middle (higher) quantiles; (iii) the robustness of the outcomes is confirmed. Thus, the outcomes show that monetary policy has a significant effect on financial asset returns, and the effects vary across times, across frequencies, quantiles, and financial assets.