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This study explores the interdependence of exchange rates between the West African Monetary Zone and the West African Economic and Monetary Union countries using monthly data from 2000 to 2021. Employing wavelet multiple correlation and wavelet multiple cross-correlation by Fernando-Macho, we generally uncovered low degrees of integration between the two blocs at higher frequencies, but the level of integration gradually becomes stronger as it navigates from higher a frequency (lower scale) to a lower frequency (higher scale). This implies that ex-ante convergence of exchange rates is difficult; however, in the long time horizon, exchange rate convergence is possible. Evidence from cross-correlation analysis shows that lead (lag) effects is time-varying and heterogeneous, showing no particular country’s exchange rates as leaders or followers. Different currencies have the potential to lead or lag on varying scales. These results suggest that member states establish a regional surveillance mechanism that can monitor macroeconomic indicators in the region. The effective implementation of this mechanism can aid in identifying macroeconomic imbalances and potential risks to macroeconomic stability and convergence.Exchange rate comovement is important for guaranteeing the introduction of a single currency. This is not different from the Economic Community of West African States (ECOWAS). The region seeks to accomplish this by developing robust and sound policies that ensure the synchronization of exchange rates. This study examines the comovements of exchange rates between WAMZ and the WAEMU countries. The results show that the ex-ante convergence of exchange rates is difficult for the region; however, in the long time horizon, exchange rate convergence is possible. Evidence from cross-correlation analysis shows that lead (lag) effects is time-varying and heterogeneous, showing no particular country’s exchange rate as leader or follower. The study recommends that the heads of states of ECOWAS consider the introduction of the ‘eco’ ex-post because exchange rates can converge in the long run.

The recent 2020 Atlantic Hurricane Season was the most active, with 31 storms. September was the most active month of the season, with a simultaneous occurrence of five storms. This study probed into the meteorological and oceanographic conditions prevailing in the Atlantic Main Development Region (MDR) during the high activity months of August, September, and October of 2020. The mean sea surface temperature (SST) for the month of September 2020 was around 0.2 °C higher than the 30 years climatological average. Vertical wind shear (WSH) was well below the threshold for cyclogenesis, with a mean of ~ 5 m/s. Such conditions favoured the consecutive storm formations in the basin. Statistical sensitivity analysis was extended for the above three months of 1991–2020, using SST, WSH, and low-level relative vorticity (VOR) as predictors. The analysis showed mean difference between MDR and tropical region SST (SSTDIFF) to be a better influencer of hurricane count (HC) variability, with r2 values of 0.43 and 0.35 for the months of August and October of 1991–2020 period, respectively. VOR was found to be the dominant influencer of hurricane activity in the month of September, with r2 value of 0.47. Wavelet local multiple correlation technique showed correlation values to be higher (~ 0.75) for a SSTDIFF–HC pair for the months of August and October. However, VOR–HC pair had the highest correlation (~ 0.8) for the month of September. The WSH condition of the region, although favourable, was not found to be influencing hurricane activity significantly for this period.

In this study, we investigate the connectedness between sharia stock index and three Islamic bond yields within a global perspective of the Gulf Cooperation Council Islamic financial markets. The main novelty of the present study is that we extend previous studies by performing three wavelet variants in bivariate and multivariate frameworks, namely the wavelet multiple correlation, the wavelet multiple cross correlation and wavelet cohesion. The findings point out a significant changing pattern in the dynamic linkage between sharia stocks and Islamic bond yields in the time-frequency domain. A strong positive association is evidenced in the short horizons and a negative linkage is branded for longer time-scales. Some resemblances are found for the wavelet cohesion corroborating the existence of potential portfolios’ diversification opportunities at lower frequencies. The multivariate wavelet cross correlation unveils that the intensity of the co-movement reaches its zenith at high frequencies. These results are not similar to the bivariate wavelet coherence but are coincident with the wavelet cohesion approach, which may be due to the difference in dimensionality of the wavelet approaches. The implications of this study will be useful for Islamic portfolio managers, international investors and market regulators in better encircling the best ways to adopt a proactive knowledge of Islamic financial markets behavior.

We examine the time-frequency lead-lag relationships and the degree of integration between the US financial stress index and global commodity prices (i.e., oil, gold, silver, and cocoa) with data covering over 47 decades (January 1975 to December 2021). For this purpose, we resort to the bi- and multiple wavelet econometric approaches. Findings from the bivariate wavelet analysis evidence the significant influence of the US financial stress in driving the price-generating process in commodities markets. Our findings support the hedging abilities of commodities across the time-frequency space. Findings from the multiple correlations explicate that the interrelation between the commodities and financial stress is attributable to their interdependence in the long term during financial market meltdowns. The dynamic and nonhomogeneous lead/lag relations underscored by our findings highlight the importance of cross-commodity investments. As such, by acknowledging the response of different commodities to financial stress, asset allocation should factor in commodities that offer opposing responses to a financial stress to hedge downside risks associated with portfolios. Our findings are of interest to regulators, risk managers, investors, and commodities producers.

Purpose This study aims to investigate the dynamic co-movement and interconnection among 69 security investment indices in China using the multi-time scale framework. Design/methodology/approach The authors first use the multiple coherence analysis method to exhibit the degree of relationships among the variables under study. In addition, the wavelet multiple correlation and wavelet multiple cross-correlation analyses are used to examine the time-frequency synchronization interdependence structure among the variables. Findings From the empirical findings, one may infer less opportunity for portfolio diversification at higher time scales. Obviously, at these scales, the authors find that the 69 Chinese investment indices generate a simple security investment class, as indicated by higher interconnection between the indices. Research limitations/implications Further research can increase the sample size to re-investigate the empirical relationship for security investment indices. Practical implications In the nutshell, the results demonstrate the potential for Chinese investors to invest in security investment indices to earn from portfolio diversification at lower time frequencies. The Chinese investment market indices under study yield further opportunities of portfolio diversification toward the short-term investors than the long-term investors. Originality/value To the best of the authors’ knowledge, this is the first paper to examine the dynamic co-movement and interconnection for security investment indices in China.

The novelty of this study is the use of wavelets, which make it possible to assess simultaneously how the Greater China (GC) and international securitized real estate markets comove at various frequencies. From the wavelet analysis, investors can extract the time scale that most interests them. We apply both continuous wavelet coherency modeling and discrete decompositions to unveil the multi-horizon nature of the comovement relationship. We find that the examined real estate market comovement is a “multi-scale” phenomenon. The strength of the return linkage increases with scales. The comovement within and across the three GC markets is unstable and the pattern of the relationship is non-uniform across various time scales. The strongest degree of cross-market connection occurs during the global financial crisis period and at the longest investment horizon of 256–512 days. Moreover, the real estate-stock returns of the three GC economies are less correlated in the long run, implying potential opportunities for both time and scale in GC real estate-stock portfolio diversification activities.

This paper examines the combined and separate effects of geopolitical risk, economic policy uncertainty, and oil prices on the stock market within a multivariate time-frequency framework, focusing on Saudi Arabia as an oil-rich country. We implement the wavelet local multiple correlation approach using monthly data from January 2000 to December 2024. Our results reveal that oil prices, geopolitical risk, and economic uncertainty are key drivers of Saudi market behavior. The joint and individual effects vary significantly across time scales and frequencies. Increasing uncertainty surrounding economic policies and rising geopolitical tensions in the region have intensified the impact of oil price movements on the Saudi market. These findings have several implications for portfolio managers, foreign investors, and policymakers. When analyzing and forecasting stock returns, portfolio managers should consider oil prices, geopolitical risk, and changes in economic policy uncertainty.

This study examines the integration of nine Asian stock markets using the new methodology of wavelet multiple correlation and multiple cross-correlation proposed by Fernandez (2012). This novel approach eliminates several limitations which are encountered when conventional pairwise wavelet correlation and cross-correlation are used to assess the comovement of a set of stock indices. Our results show that Asian stock markets are highly integrated at lower frequencies and comparatively less integrated at higher frequencies. From the perspective of international investors, the Asian stock markets therefore offer little potential gains from international portfolio diversification especially for monthly, quarterly, and bi-annual time horizon investors, whereas, higher potential gains are expected at intraweek, weekly, and fortnightly time horizons.

Enhancing future economic growth through higher economic complexity is vital for sustainable growth strategies. Even though most studies are concerned with the key factors governing the economic complexity process, there needs to be more studies about the impact of risk factors on economic sophistication evolvement, particularly for oil-rentier economies. The present paper intends to delve into the dynamic connectedness between some risk factors, such as economic, political, and geopolitical risks and oil price volatility and the progress of economic complexity. We utilized quarterly data (1995Q1-2021Q4) for Saudi Arabia as a heavy oil-rich economy. As the first study to delve into the short-long term connections at various time scales and frequencies within a multivariable setting, we contribute to the literature by offering a spotless picture of economic complexity risk factors. In doing so, we resort to a novel wavelet local multiple correlation method, which can explore the varying patterns of time periods in the interconnections between the variables. Our findings disclose that oil volatility, geopolitical risk, and global uncertainties are positively connected to economic complexity over the long run. In contrast, their short-term effect is weak and mostly insignificant. These results indicate the resiliency of the Saudi economy to external to oil volatility shocks and intensification of global and local uncertainties. These outcomes offer policymakers new insights and prominent policy recommendations when designing economic strategies to achieve higher economic sophistication and sustainable growth.

This is a study on the integration between the six largest African stock markets at different timescales. The study determines whether the various measures and reforms undertaken to integrate the African stock markets have been effective. Wavelet methods and the Diebold and Yilmaz (2012) spillovers index were used. This approach allows an analysis in both time and frequency. The study results reveal that the integration of African stock exchanges is low at smaller time scales but tends to grow at larger timescales. Despite all the reforms, the transmission of financial information from one market to other remains slow. However, large-scale integration appears to decline in recent years. More effective policies are therefore needed for faster transmission and more efficient integration of African financial markets as well as for promoting exchanges between African stock markets.