This paper examines the dynamic relationship between real oil prices and U.S. monetary policy instruments over more than fifty years. Using symmetric and asymmetric time-varying Granger predictability tests alongside timevarying local projections with stochastic volatility, the study assesses how U.S. monetary aggregates and interest rates predict real oil prices-and how oil prices, in turn, predict monetary variables. The results show that both narrow and broad monetary aggregates, as well as short-and long-term interest rates, Granger predict real oil prices to varying degrees since the 1970s, with notable differences between symmetric and asymmetric specifications. Predictability is bidirectional, yet oil price responses vary substantially over time. Local projections show that interest rates shock real oil prices with high magnitude during early conventional times, especially the 1973 and 1979 oil shocks plus some in the 1980s, but diminish markedly thereafter. In contrast, monetary aggregate shocks dominate in magnitude after 2008, as unconventional monetary policy became manifest. Money supply shocks strongly influence oil prices during the global financial crisis, the 2015-2019 normalization period, the COVID-19 episode, and the 2021-2023 inflation surge. Findings highlight historical time-varying asymmetry in how monetary policy interacts with oil markets, providing implications for policy.

This paper re-examines the relationship between financial development and economic growth in 28 OECD countries over the period 1995–2021 using a comprehensive, multidimensional measure of financial development. Standard fixed-effects panel estimates reveal no statistically significant finance–growth relationship. However, once endogeneity is explicitly addressed through an instrumental-variables framework, financial development is found to exert a positive and statistically significant effect on economic growth. To move beyond average effects and capture distributional heterogeneity, the analysis further employs a fixed-effects panel quantile regression combined with instrumental-variables estimation. The results show that the growth-enhancing impact of financial development is present across the entire growth distribution, but its marginal effect is strongest in low-growth states and declines monotonically as growth increases. At the lowest growth quantiles—corresponding to crisis episodes—the effect becomes statistically insignificant, indicating that periods of severe instability disrupt the transmission mechanisms through which finance supports growth. These findings highlight the importance of proper identification and distribution-sensitive analysis in assessing the finance–growth nexus. From a policy perspective, the results suggest that financial development strategies should be stage-contingent: broadening access and improving efficiency when growth is weak, while prioritizing financial quality, institutional support, and targeted, additionality-tested interventions during high-growth periods.

This paper presents new evidence that US money supply growth and inflation rates Granger predict real oil prices in a two-regime Markov switching vector autoregression (MS-VAR) model. An asset pricing theory motivates the empirical work by showing how jumps in real oil prices approximately follow jumps in the discount factor to keep constant the competitive return to oil capital. Using monthly data from January 1978 to June 2024, we consider alternative data combinations of US money supply growth rates, US inflation rates, and real oil prices to establish volatility regimes through goodness of fit testing. We set baseline model as that model with the highest likelihood in explaining the real oil price, which combines M2, the CPI less energy prices (CPIE), and real oil prices. Robustness considers two M2 variants combined with the CPIE that have the next highest likelihoods, for two alternative models. In the high volatility regime, results show robust Granger predictability of real oil prices by the baseline M2 and the M2 variants. In the low volatility regime for the baseline model, the CPIE inflation rate Granger predicts real oil prices. The paper contributes these new MS-VAR results that combined with the theory provide nuanced non-conventional support that monetary factors contribute to heightened real oil price episodes in volatile times as well as in calmer periods.

This study investigates the impact of financial literacy on financial development across a large set of countries, utilizing data from the Global Financial Inclusion and Consumer Protection (GFICP) surveys conducted in 2017 and 2022. Using baseline OLS regressions, the results reveal that financial literacy significantly enhances financial development, particularly in upper-middle-, lower-middle-, and low-income countries. The study also highlights regional variations, with the East Asia and Pacific region demonstrating the most substantial positive relationship. Additionally, the quantile regression analysis indicates that the effect of financial literacy on financial development is more pronounced in countries with either highly developed or underdeveloped financial systems. These results underscore the importance of designing context-specific financial education policies, particularly in developing economies, where improvements in foundational financial knowledge can play a catalytic role in strengthening financial systems.

Utilizing blockchain technology is transforming traditional business practices into a new paradigm, giving rise to what we refer to as blockchained models. This paper uses wavelet coherence analysis to identify the connectedness of blockchained sectoral indices with Bitcoin and the Fear and Greed Index that represents investor sentiment in the cryptocurrency market. Results show persistent and positive correlations between sector returns and investor sentiment and sectoral return series lead investor sentiment. The relationship between Bitcoin and sectoral indices is consistent for return series and suggests an in-phase (positive) relationship between these variables at all frequencies. We usually have found negative correlations for the co-movements of investor sentiment and sectoral volatility, where investor sentiment leads to sector return volatilities. The application of blockchain technology across various sectors, coupled with the proliferation of altcoins, appears to drive distinct price developments in these cryptocurrency sectors. These developments are predominantly influenced by sentimental factors, often diverging from the trends of Bitcoin.

The transition to a low-carbon economy requires a steady and secure supply of minerals, which are susceptible to international tensions. In particular, the coronavirus pandemic in 2019 and the Russia-Ukraine conflict in 2022 are two novel shocks affecting the clean energy market. Measuring the impact of increasing geopolitical risks due to these shocks on the clean energy sector is critical to the future of sustainable development. In this framework, this study uses wavelet coherence analysis and time-varying parameter VAR methods to examine the impact of geopolitical risks on the prices of aluminum, copper, lead, zinc, cobalt, and nickel from January 1992 to August 2022. The results show that mineral prices decreased during the COVID-19 period and increased after the Russia-Ukraine conflict. The results also indicate that global geopolitical risk has a moderating effect on the prices of copper, aluminum, cobalt, and zinc, while geopolitical risk associated with Russia increases the prices of all minerals except cobalt. These results imply that the problems in Russia destabilize the prices of mineral commodities used in the renewable energy market, while the global geopolitical risks do not pose serious problems. Therefore, the Russian-Ukrainian conflict should be resolved in order to use clean energy minerals more effectively.

This paper investigates the dynamics of the interactions between international stock returns and perceived volatility measured by the VIX index using quantile-on-quantile spillover analysis. Using weekly data from 1995 to 2023 and a comprehensive data set from developed and emerging stock markets, we investigate the relationship between the VIX and stock market returns accounting for time-varying relationships and cross-quantile relationships. Empirical results show that the indirectly related quantile total spillovers between the VIX and equity returns surpasses the directly related quantile total spillovers. High returns occur at low VIX levels and low returns at high VIX levels. The highest total spillovers across all stock markets occur at the highest quantile level for the VIX and the lowest quantile level for stock returns, for both developed and emerging markets. High connectedness between the VIX and stock market returns, particularly at extreme quantiles, suggests that investors should look at other investment vehicles for diversification during uncertain times.

This study examines received and transmitted volatility spillovers of Credit Default Swap (CDS) and Asset-Swap Spread (ASW) for Brazil and Turkey. The empirical analysis is implemented using two country-based (stock markets and exchange rates) and two global (volatility index and global economic activity index) variables to account for the impact of integration into global markets. Empirical results suggest that both countries display distinctive features in their spillover networks. While exchange rates and the stock market figure prominently in Brazil as a source of spillovers, for Turkey, the primary element in spillovers appears to be credit risk indicators. Time-varying analysis results show that the European Debt Crisis of 2010-2011 and the global liquidity crunch of 2018-2019 are two critical periods in volatility spillovers that occurred toward credit risk indicators. Brazil displays more sensitivity to the developments of the pandemic than Turkey, likely due to its dependence on global economic activity and energy prices. Finally, for both countries, the leading variable in spillovers to credit risk indicators during financial turbulence episodes appears to be foreign exchange markets. This result highlights both economies? fragility and vulnerability to foreign exchange market-based shocks. Thus, we suggest effective and solid measures in this regard. Otherwise, those shocks could potentially induce a higher cost of financing in both economies due to the negative impacts on CDS and ASW spreads.

The study aims to examine systemically important stock markets in the global financial system within the scope of portfolio theory. For this purpose, we use daily stock market indices from 46 countries (23 developed and 23 developing stock markets) in North America, Latin America, the Middle East and Africa, Asia, the Pacific, Eastern Europe, and Europe between 1995 and 2021. Based on the Component Expected Shortfall (CES), we identify systemically important stock markets and use the quantile spillover analysis to examine the financial contagion and directional spillovers emanating from downside risks among stock markets. Overall, we observe stock markets of developed countries figured prominently in terms of systemic risk until the Global Financial Crisis (2007-2009; henceforth GFC), while developing country stock markets particularly those of China and India gained traction after the GFC. Moreover, we observe a shift in terms of systemic risk in recent years from the West to the East geographically. To increase global financial market resilience and improve stability, supervision, and macroprudential policies can be formulated to limit risk spillovers in global stock markets. Additionally, it is critical to diversify investments outside equity markets, such as currency, bond, gold, and oil asset classes. When considering overseas portfolio choices for diversity, investors should keep the financial spillover effects in mind.

This research investigates the relationship between clean energy stock and oil market returns utilizing Granger predictability in distribution and quantile impulse response analysis. We find that clean energy stock returns Granger predict oil price returns during “normal times” based on the distribution’s center, but not vice versa. During bullish market episodes, there is bidirectional Granger predictability between the returns of clean energy stocks and oil market returns. Nonetheless, we find that clean energy stock returns Granger predict oil returns in bearish markets without any evidence of the contrary. This indicates that oil returns cannot be used to hedge the downside risk associated with renewable energy company purchases. Quantile impulse responses for the relationship between clean energy stocks and the crude oil market reveal bidirectional and significant responses, where a negative shock during an extremely down market reveals a negative response in the other market and a positive shock during an extremely up market reveals a significant positive response. This shows that neither market can be utilized to offset risks in the other market.

This study examines the impact of two critical events, the introduction of Bitcoin futures and the COVID-19 pandemic, on Bitcoin's returns and volatility. We find that the inception of Bitcoin futures (positively) impacts its returns in the spot market while no significant interaction occurs for volatilities. The pandemic does not seem to influence Bitcoin's returns or volatility, which is consistent with the notion that Bitcoin is insulated from some global economic developments. Our tests also reveal that Bitcoin spot prices dominate its futures. This information might be useful for investors in capturing trend reversals considering the order of information disseminated.

We examine 585 estimates for macroeconomic effects of dollarization reported in 43 studies, codify 39 aspects of study design that may influence the estimates, and use Bayesian model averaging to take into account model uncertainty in meta-analysis. The results indicate that dollarized countries on average display slower and more volatile output growth, and a lower inflation rate than non-dollarized countries, but the estimates vary widely both within and across studies. Fully dollarized countries on average exhibit slower growth than non-dollarized and partially dollarized economies. Dollarization measurement, empirical method selection and authors' affiliation systematically affect reported dollarization effects. The empirical results also suggest that limited control over foreign currency's money supply in dollarized economies reduces the central banks' ability to effectively conduct monetary policy and adjust to macroeconomic shocks.

In this paper, we investigate the relationship between gold, silver, and the US dollar returns and financial stress to shed light on the circumstances where these assets serve as attractive investment vehicles and whether the assets signal financial conditions ahead. Using weekly data from 1994 to 2020 and predictability-in-mean, predictability-in-variance, and predictability-in-distribution, we examine the relationship between returns on gold, silver, and the US dollar and the St Louis Financial Stress Index (STLFSI). While we find no Granger predictability in the mean between gold returns and the aggregate STLFSI, there is some evidence of Granger predictability between silver and US dollar returns and financial stress. However, test results show significant bidirectional Granger predictability in variance between STLFSI and gold, silver, and US dollar returns. Predictability-in-distribution tests generally show significant bidirectional relationships between financial stress and gold, silver, and US dollar returns at the left and right tail of the distribution. We confirm the safe-haven properties of gold, silver, and the US dollar and find novel evidence that very low returns on these assets signal financial calm, and unusually high returns signal high financial stress ahead. In this sense, extreme gold, silver, and US dollar returns are harbingers of calm times or financial distress to come, acting as early financial market news providing risk guideposts for safety.

In this paper, we examine comovements between stock market returns and investments that take into account Environmental, Social, and Governance (ESG) factors by studying the interconnections between the two returns in time and frequency space. We study interdependencies between the conventional stock market and ESG stocks using daily data from 2007 to 2021 for 19 developing and 19 developed countries. Our results show significant comovement patterns between ESG returns and stock returns at various frequencies, time scales, and sample episodes in all countries, particularly during periods of financial turmoil. For the most part, we document positive (in-phase) comovements between the stock returns and ESG returns in developing countries and negative (out-of-phase) comovements in developed countries. This implies limited portfolio gains from adding ESG stocks to portfolio diversification in developing countries but significant gains in developed countries.

We examine the relationship between Islamic and conventional stock market returns to see if Islamic financial markets provide portfolio diversification benefits and safe havens during turbulent times. Using daily data from January 1996 through September 2020 we consider conventional emerging stock market returns and some Islamic stock market returns and examine their interactions using causality-in-variance, dynamic conditional correlations, optimal hedge ratios, and causality-in-risk tests. Causality-in-variance test results show causality between Islamic stock returns and all emerging stock returns which indicates Islamic markets provide limited safe havens. Results from both time-varying conditional correlations and the hedge ratios show that there are positive and significant correlations between emerging stock markets and Dow Jones Islamic Market Index, which implies limited portfolio diversification benefits afforded by Islamic stock markets.

This study examines the relationship between positive and negative investor sentiments and stock market returns and volatility in Group of 20 countries using various methods, including panel regression with fixed effects, panel quantile regressions, a panel vector autoregression (PVAR) model, and country-specific regressions. We proxy for negative and positive investor sentiments using the Google Search Volume Index for terms related to the coronavirus disease (COVID-19) and COVID-19 vaccine, respectively. Using weekly data from March 2020 to May 2021, we document significant relationships between positive and negative investor sentiments and stock market returns and volatility. Specifically, an increase in positive investor sentiment leads to an increase in stock returns while negative investor sentiment decreases stock returns at lower quantiles. The effect of investor sentiment on volatility is consistent across the distribution: negative sentiment increases volatility, whereas positive sentiment reduces volatility. These results are robust as they are corroborated by Granger causality tests and a PVAR model. The findings may have portfolio implications as they indicate that proxies for positive and negative investor sentiments seem to be good predictors of stock returns and volatility during the pandemic.

This paper examines financial stress transmission between the U.S. and the Euro Area. To better understand the linkages between financial stress in the two regions, we construct a financial stress index for the U.S. similar to the Composite Indicators of Systemic Stress (CISS) that has been developed for the Euro Area with a focus on systemic risk. Using weekly data from 2000 to 2021 and Granger predictability in distribution test, we analyze stress transmission in “normal” times as well as under unusually high and low stress episodes. While we document unilateral transmission from the U.S. to the Euro Area under normal conditions based on the center of the distribution, tail dependence tests and impulse response analysis show significant bilateral transmission, particularly in unusually high financial stress episodes. This holds true for aggregate indices as well as the subindicators of financial stress in various financial markets. As such, there must be global efforts to contain financial crises and ensure a strong and resilient financial system.

An important question in banking is whether restrictions placed on Islamic banks make them more resilient to financial market turmoil and less prone to failure than conventional banks. We evaluate this claim by estimating credit default risk measures for a sample of conventional and Islamic banks using a GARCH option pricing model. Using a daily data set that is better suited for the time variation in volatility, we calculate distance to default measures to evaluate credit risk of Conventional Banks (CBs) and Islamic banks (IBs). We find higher default risk measures for IBs than CBs in general except during the Global Financial Crisis. This result holds true after controlling for bank and country specific variables in that IBs seem to have significantly lower default risk during the Global Financial Crisis and higher default risk thereafter. Consequently, while restrictions on risk taking is advantageous in financial turmoil episodes, the same restrictions expose IBs to risks in normal times. Finally, the credit risk of CBs and IBs is negatively affected by the oil crisis in 2014–2015 and the Covid-19 global pandemic. While there is no significant difference between the effects of the oil crisis on IBs versus CBs, the recent Covid-19 pandemic seems to have worsened the credit risk of IBs compared to CBs.

This paper examines the dynamic relation between Bitcoin spot and futures markets during the Covid-19 pandemic. Using hourly data from 2020 combined with quantile impulse response analysis and predictability in the distribution test, we attempt to ascertain whether spot or futures markets lead in the price discovery process under a variety of market conditions. Granger predictability based on the left tail, the right tail, and the center of the distribution show bidirectional predictability between spot and futures markets suggesting significant feedback effects following normal and extreme gains/losses where neither market dominates in price discovery. Using a CAViaR model and the associated impulse response functions with estimates for dynamic tail dependence, we document spillovers between quantiles of spot and futures returns. Estimates of impulse response functions at various risk levels show the futures market has an edge in influencing the spot market and figures more prominently in the price discovery process.

This paper examines the effects of quantitative easing on firm performance using firm-level data in the euro area during the Corporate Sector Purchase Programme. We apply a difference-indifference framework and focus on long-term and short-term book leverage, turnover, and profitability. Despite an increase in leverage, firms in the treatment group did not experience an increase in turnover or profitability as a result of the CSPP. Improved access to credit in the bond market seems to have no statistically discernible effects on the firms' real performance. Our empirical results also show cross country and region heterogeneity in the effects of CSPP. Possible factors driving the results include the limited scope of the CSPP program, financial constraints being less of a concern for firms in the euro area, and that monetary policy is in general less effective in the aftermath of financial crises as the monetary transmission mechanism is partially impaired.