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The purpose of this study was to evaluate the effects of repetitive transcranial magnetic stimulation (rTMS) at different frequencies on working memory (WM) and neuroelectric activity in rats.

Three rTMS protocols involving different frequencies were applied to rats, and 16-channel local field potentials (LFPs) and spikes were recorded from the prefrontal cortex (PFC) of rats in each group during the WM task. First, the behavior of rats during the T-maze task was analyzed, and then, the firing rate of spikes and the energy of the θ-band and γ-band in LFPs when rats performed the WM tasks were calculated. Finally, the spectral coherence between LFPs and spikes was analyzed by wavelet transform.

The results showed that rats in the stimulation groups needed fewer days than those in the control group to reach the task correction standard during the WM experiment (p < 0.05). High-frequency rTMS increases the firing rate of spikes and the degree of synchronization of LFPs-spikes in the θ-band and γ-band in the WM process.

This study showed that high-frequency rTMS can improve the spatial learning ability of rats, which might be due to the increased neuronal excitability of the PFC and the enhancement of co-coding between different modes of neural signals. This study is helpful for understanding the neuroregulatory mechanism of rTMS and will provide a reference for the selection of a suitable frequency for TMS treatment.

The purpose of this paper is to understand the natural wind field characteristics of the tunnel entrance section and analyzing the aerodynamic performance of high-speed railway trains (HSRTs) under natural winds.

Three typical tunnel entrance section sites, namely, tunnel–bridge in a dry canyon (TBDC), tunnel–bridge in a river canyon (TBRC) and tunnel–flat ground (TF), are selected to conduct a continuous wind field measurement. Based on the measured wind characteristics, the natural winds of the TBDC and TF sites are reconstituted and imported into the two corresponding full-scale computational fluid dynamics models. The aerodynamic loads of the HSRT running on TBDC and TF with reconstituted winds are simply analyzed.

The von Kármán spectrum can be used to describe the wind field at the tunnel entrance section. In the reconstituted natural wind condition, a time-varying feature of wind speed distribution and leeward side vortex around the HSRT caused by the wind speed fluctuation is found. The fluctuating amplitude of aerodynamic loads at the TBDC infrastructure is up to 97.9% larger than that at the TF infrastructure.

The natural wind characteristics at tunnel entrance sections on the high-speed railway are first measured and analyzed. A numerical reconstitution scheme considering the temporal and spatial variation of natural wind speed is proposed and verified based on field measurement results. The aerodynamic performance of an HSRT under reconstituted natural winds is first investigated.

This study is designed to examine the dynamic interrelationships between four cryptocurrencies (Bitcoin, Ethereum, Dogecoin and Cardano) and the Indian equity market. Additionally, the study seeks to investigate the potential safe haven, hedge and diversification uses of these digital currencies within the Indian equity market.

This study employs the wavelet approach to examine the time-varying volatility of the studied assets and the lead-lag relationship between stocks and cryptocurrencies. The authors execute the entire analysis using daily data from 1st October 2017 to 30th September 2023.

The result of the study shows that financial distress due to the pandemic and the Russian invasion of Ukraine have a negative effect on the Indian equities and cryptocurrency markets, escalating their price volatility. Also, the connectedness between the returns of stock and digital currency exhibits a strong positive relationship during periods of financial distress. Additionally, cryptocurrencies serve as a tool of diversification or hedging in the Indian equities markets during normal financial circumstances, but they do not serve as a diversifier or safe haven during periods of financial turmoil.

This study contributes to understanding the relationship between the Indian equity market and four cryptocurrencies using wavelet techniques in the time and frequency domains, considering both normal and crisis times. This can offer valuable insights into the potential of cryptocurrencies inside the Indian equities markets, mainly with respect to varying financial conditions and investment horizons.

The purpose of this paper is to investigate the volatility spectral of five major public real estate markets, namely, the USA, the UK, Japan (JP), Hong Kong (HK), and Singapore (SG), during the pre- and post-global financial crisis (GFC) periods.

First, univariate spectral analysis is concerned with discovering price cycles for the respective real estate markets. Second, bivariate cross-spectral analysis seeks to uncover whether any two real estate price series share common cycles with regard to their relative magnitudes and lead-lag patterns of the cyclical variations. Finally, to test the contagion effects, the authors estimate the exact percentage change in co-spectral density (cyclical covariance) due to high frequencies (short run) after the GFC.

The authors find that whilst none of the public real estate markets examined are spared from the crisis, the three Asian markets were less severely affected by the GFC and were accompanied by a reversal in volatility increase three years post-global financial crisis. Additionally, the public real estate markets studied have become more cyclically linked in recent years. This is particularly true at longer frequencies. Finally, these increased cyclical co-movements measure the outcomes of contagion and indicate fairly strong contagious effects between the public real estate markets examined due to the crisis.

The implication of this research is that benefits to investors from international real estate diversification may not be as great during the present time compared to previous periods because national public real estate markets have become more correlated. Nevertheless, the findings do not imply the complete absence of diversification benefits. This is because although cyclical correlations increase in the short run, many of the correlation values are still between low and moderate range, indicating that some diversification benefits may still be realized.

Given the significant market share and the highest levels of securitization in Asia-Pacific markets including JP, HK/China, and SG, this cyclical research including major public real estate markets has practical implications for ongoing international real estate investment strategies, particularly for the USA/UK and Asian portfolio managers.

This paper contributes to the limited research on the cyclical return and co-movement dynamics among major public real estate markets during financial/economic crisis in international finance. Moreover, the frequency-domain analysis conducted in this paper adds to better understanding regarding the impact of GFC on the cyclical return volatility and co-movement dynamics of major developed public real estate markets in international investing.

This study aims to investigate the impact of the COVID-19 pandemic on both of stock prices and investor's sentiment in China during the onset of the COVID-19 crisis.

In this study, the ADCC-GARCH model was used to analyze the asymmetric volatility and the time-varying conditional correlation among the Chinese stock market, the investors' sentiment and its variation. The authors relied on Diebold and Yilmaz (2012, 2014) methodology to construct network-associated measures. Then, the wavelet coherence model was applied to explore the co-movements between these variables. To check the robustness of the study results, the authors referred to the RavenPack COVID sentiments and the Chinese VIX, as other measures of the investor's sentiment using daily data from December 2019 to December 2021.

Using the ADCC-GARCH model, a strong co-movement was found between the investor's sentiment and the Shanghai index returns during the COVID-19 pandemic. The study results provide a significant peak of connectivity between the investor's sentiment and the Chinese stock market return during the 2015–2016 and the end of 2019–2020 turmoil periods. These periods coincide, respectively, with the 2015 Chinese economy recession and the COVID-19 pandemic outbreak. Furthermore, the wavelet coherence analysis confirms the ADCC results, which revealed that the used proxies of the investor's sentiment can detect the Chinese investors' behavior especially during the health crisis.

This study provides two main types of implications: on the one hand, for investors since it helps them to understand the economic outlook and accordingly design their portfolio strategy and allocate decisions to optimize their portfolios. On the other hand, for portfolios managers, who should pay attention to the volatility spillovers between investor sentiment and the Chinese stock market to predict the financial market dynamics during crises periods and hedge their portfolios.

This study attempted to examine the time-varying interactions between the investor's sentiment proxies and the stock market dynamics. Findings showed that the investor's sentiment is considered a prominent channel of shock spillovers during the COVID-19 crisis, which typically confirms the behavioral contagion theory.

This study aims to examine the connectedness among green, Islamic and conventional financial markets from December 2008 to May 2021. Moreover, the impact of global factors on the connectedness of given financial markets is also observed.

This study first employed the time-varying parameter vector autoregressions (TVP-VAR) technique to explore the connectedness of markets. Second, This study utilized the wavelet coherence analysis to test the time-frequency impact of global factors in terms of implied volatilities of stock, oil, gold, currency and bond on the connectedness across financial markets.

This study finds Islamic stocks, sustainability index and S&P500 composite index are the net transmitters, whereas Sukuk, commodity index, bond market, clean energy and green bonds are the net recipient of spillovers. Time-varying features of green, Islamic and conventional financial markets are evident in system-wide connectedness. This study further evidenced that global factors drive the connectedness of financial markets, particularly during stressful times.

The findings of this study furnish significant implications for policymakers, regulatory authorities, investors, financial market participants and portfolio managers in terms of carefully assessing the unique characteristics offered by each financial market in terms of risk mitigation and diversifying the portfolios.

Using a portfolio of green, Islamic and conventional financial markets, the uniqueness of this study lies in the examination of the connectedness of these markets by deploying the TVP-VAR technique. In addition, wavelet analysis offers a significant contribution in terms of global factors driving the connectedness of green, Islamic and conventional markets.

The authors analyse the relationship between the South African real exchange rate and economic fundamentals – demand, supply and nominal shocks. The paper aims to discuss these issues.

The authors use a time-varying parameter VAR to study the coherence, conditional volatility and impulse responses of the exchange rate over specific periods and policy regimes. The model is identified using sign-restrictions that allow for some neutrality of impulse responses over contemporaneous and long horizons.

The results suggest that the importance of fundamental shocks on the exchange rate is time dependent. Hence there is a loss in information when using standard linear models that average out effects over time. The response of the exchange rate to demand and supply shocks have weakened over the 1994-2010 period.

The period following financial crisis has strengthened the relationship between supply and demand shocks to the exchange rate, but has weakened the relationship between interest rate shocks and the exchange rate response.

This paper provides deeper insight as to how the exchange rate responds to fundamental shocks. This should help monetary policy understand the consequences of interest rate decisions on the exchange rate and the indirect effect of inflation on the exchange rate.

This application is new to the South African literature. The authors propose that the use of interest rates is limited in affecting the value of the rand exchange rate over particular periods. Isolating fundamental shocks to exchange rates over time helps policy makers make clearer and more informed decisions.

As the onset of the Russia–Ukraine military conflict on February 24, 2022, individuals from Ukraine have been relocating in search of safety and refuge. This study aims to investigate how the influx of Ukrainian refugees has impacted the stock markets and exchange rates of Ukraine's neighboring states.

The authors focused on the neighboring countries that share a western border with Ukraine and have received the highest number of refugees: Hungary, Poland, Romania and Slovakia. The analysis covered the period from April 24 to December 31, 2022. After this period, the influence of the refugees is small, insignificant. Wavelet coherence, wavelet power spectrum and the time-varying parameter vector autoregressions method were used for data processing.

The key finding are as follows: a link exists between the dynamics of refugees from Ukraine and volatility of the stock indices and exchange rate of the host countries; volatility was significant in the first weeks after the start of the conflict in all the analyzed states; and the highest volatility was recorded in Hungary and Poland; the effect of refugees was stronger on stock indices than that on exchange rates.

To the best of the authors’ knowledge, it is the first research that presents the impact of refugees from Ukraine on stock markets and exchange rates volatility in the countries analyzed.

The authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crises episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak).

The authors use the GARCH and Wavelet approaches to estimate causalities and connectedness.

According to the findings, China and developed equity markets are connected via risk transmission in the long term across various crisis episodes. In contrast, China and emerging equity markets are linked in short and long terms. The authors observe that China leads the stock markets of India, Indonesia and Malaysia at higher frequencies. Even China influences the French, Japanese and American equity markets despite the Chinese crisis. Finally, these causality findings reveal a bi-directional causality among China and its developed trading partners over short- and long-time scales. The connectedness varies across crisis episodes and frequency (short and long run). The study's findings provide helpful information for portfolio hedging, especially during various crises.

The authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crisis episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak). Previously, none of the studies have examined the connectedness between Chinese and its trading partners' equity markets during these all crises.

In this study, the authors analyze the impact of geopolitics risk on Sukuk, Islamic and composite stocks, oil and gold markets and portfolio diversification implications during the COVID-19 pandemic and Russia–Ukraine conflict period.

The study used a mix of wavelet-based approaches, including continuous wavelet transformation and discrete wavelet transformation. The analysis used data from the Geopolitical Risk index (GP{R), Dow Jones Sukuk index (SUKUK), Dow Jones Islamic index (DJII), Dow Jones composite index (DJCI), one of the top crude oil benchmarks which is based on the Europe (BRENT) (oil fields in the North Sea between the Shetland Island and Norway), and Global Gold Price Index (gold) from May 31, 2012, to June 13, 2022.

The results of the study indicate that during the COVID-19 and Russia–Ukraine conflict period geopolitical risk (GPR) was in the leading position, where BRENT confirmed the lagging relationship. On the other hand, during the COVID-19 pandemic period, SUKUK, DJII and DJCI are in the leading position, where GPR confirms the lagging position.

The present study is unique in three respects. First, the authors revisit the influence of GPR on global asset markets such as Islamic stocks, Islamic bonds, conventional stocks, oil and gold. Second, the authors use the wavelet power spectrum and coherence analysis to determine the level of reliance based on time and frequency features. Third, the authors conduct an empirical study that includes recent endogenous shocks generated by health crises such as the COVID-19 epidemic, as well as shocks caused by the geopolitical danger of a war between Russia and Ukraine.

1. We analyze the impact of geopolitics risk on Sukuk, Islamic and composite stocks, oil and gold markets and portfolio diversification implications during the COVID-19 pandemic and Russia–Ukraine conflict period.

2. The results of the wavelet-based approach show that Dow Jones composite and Islamic indexes have observed the highest mean return during the study period.

3. GPR and BRENT are estimated to have the highest amount of risk throughout the observation period.

4. Dow Jones Sukuk, Islamic and composite stock show similar trend of volatility during the COVID-19 pandemic period and comparatively gold observes lower variance during the COVID-19 pandemic and Russia–Ukraine conflict.

We analyze the impact of geopolitics risk on Sukuk, Islamic and composite stocks, oil and gold markets and portfolio diversification implications during the COVID-19 pandemic and Russia–Ukraine conflict period.

The results of the wavelet-based approach show that Dow Jones composite and Islamic indexes have observed the highest mean return during the study period.

GPR and BRENT are estimated to have the highest amount of risk throughout the observation period.

Dow Jones Sukuk, Islamic and composite stock show similar trend of volatility during the COVID-19 pandemic period and comparatively gold observes lower variance during the COVID-19 pandemic and Russia–Ukraine conflict.