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The purpose of this paper is to investigate payout smoothing in two emerging markets – China and Taiwan. The authors conduct a comparative study of two emerging market economies that have common cultural and historical characteristics but have experienced different government systems and different approach to the market-based system.

The authors collect firm-level data from Standard and Poor's Compustat Global database, which covers 5,298 public firms in China and Taiwan during the period 1996–2015, and use a variance decomposition methodology to estimate the smoothness of corporate payout in a common empirical framework that includes net income, and debt and investment policies.

Overall, the empirical findings support recently proposed theories of joint determination of corporate payout behavior with debt and investment policies. The authors find that debt and investment policies absorb the majority of shocks to net income, and that debt policy is the main shock absorber. Furthermore, the authors show that firms in China follow a similar strategy with their counterparts in United States and smooth their payout. In contrast to firms in China and US, the payout of the Taiwanese firms is relatively highly sensitive to net income shocks.

To the best of authors’ knowledge, this study is the first to use a joint model to empirically investigate the extent to which debt and investment policies are used to keep corporate payout smooth in emerging markets.

This study examines the extreme quantile connectedness and spillovers between West Texas Intermediate (WTI) crude oil futures and ten Vietnamese stock market sectors. Knowledge of such links is important to both investors and policymakers in understanding the transmission of shocks across markets.

The authors employ the extreme quantile connectedness methodology of Ando et al. (2022).

Initial results show that the size of spillovers is higher during bearish markets than bullish markets and under major financial, political, energy and pandemic events. The oil market is a net receiver of spillovers during downward markets and net contributors during upward markets. The banking sector is a net contributor of spillovers, whereas consumer discretionary and consumer staples are net receivers for different quantiles. The role of the remaining sectors as net receivers/contributors is sensitive to the quantiles. Oil has a large spillover effect on the electricity sector for all quantiles. Comparing all crises, oil offers the best hedging effectiveness to the Vietnamese sector during the coronavirus disease 2019 (COVID-19) crisis. Moreover, oil was a cheap hedge asset during oil crises. Finally, oil provides the highest hedging effectiveness for healthcare during the global financial crisis (GFC) and consumer staples during the European debt crisis (EDC), oil crisis and COVID-19.

Acknowledging the presence of heterogeneity in the relation between oil and economic sectors under different market conditions, this study is the first to examine the extreme quantile connectedness between oil and Vietnamese sectors.

The purpose of this paper is to study the interlinkages between the cryptocurrency and stock market by characterizing their connectedness starting from January 1, 2018 to December 31, 2021.

The author employs a time-varying parameter vector autoregression (TVP-VAR) in combination with an extended joint connectedness approach.

The pandemic shocks appear to have influences on the system-wide dynamic connectedness, which reaches a peak during the COVID-19 pandemic. Net total directional connectedness suggests that each cryptocurrency and stock have a heterogeneous role, conditional on their internal characteristics and external shocks. In particular, Bitcoin and Binance Coin are reported as the net receiver of shocks, while the role of Ethereum shifts from receivers to transmitters. As for the stock market, the US stock market stays persistent as net transmitters of shocks, while the Asian stock market (including Hong Kong and Shanghai) are the two consistent net receivers. During the COVID-19 pandemic shock, pairwise connectedness reveals that cryptocurrencies can explain the volatility of the stock markets with the impact most severe at the beginning of 2020.

Insightful knowledge about key antecedents of contagion among these markets also help policymakers design adequate policies to reduce these markets' vulnerabilities and minimize the spread of risk or uncertainty across these markets.

The author is the first to investigate the interlinkages between the cryptocurrency and the stock market and assess the influences of uncertain events like the COVID-19 health crisis on the dynamic interlinkages among these two markets. The author employs the TVP-VAR combined with an extended joint connectedness approach.

This paper aims to examine the dynamic spillover effects and network connectedness between the oil prices and the Islamic and conventional financial markets in the Gulf Cooperation Council countries. The focus is on network connectedness during the 2008–2009 global financial crisis, the 2014–2016 oil crisis and the COVID-19 pandemic. The authors use daily data covering the period from January 1, 2007 to April 14, 2022.

This study applies a spillover analysis and connectedness network to investigate the risk contagion among the Islamic and conventional stock–bond markets. The authors rely on Diebold and Yilmaz’s (2012, 2014) methodology to construct network-associated measures.

The results suggest that overall connectedness among financial market uncertainties increased during the global financial crisis, the oil price collapse of 2014–2016 and the COVID-19 crisis. In addition, the authors show that the contribution of oil shocks to the financial system is limited, as the oil market was a net receiver during the 2014 oil shock and the COVID-19 crisis. On the other hand, the Islamic and conventional stock markets are extensive sources of network effects on the oil market and Islamic and conventional bond markets. Furthermore, the authors found that the Sukuk market was significantly affected by the COVID-19 pandemic, whereas the conventional and Islamic stock markets were the highest transmitters of shocks during the COVID-19 pandemic outbreak. Moreover, oil revealed a weak connectedness with the Islamic and conventional stock markets during the COVID-19 health crisis, implying that it helps provide diversification benefits for international portfolio investors.

This study contributes to this field by improving the understanding of the effect of fluctuations in oil prices on the dynamics of the volatility connection between oil and Islamic and conventional financial markets during times of stress through a network connectedness framework. The main results of this study highlight the role of oil in portfolio allocation and risk minimization when investing in Islamic and conventional assets.

This study aims to investigate connections between the development of robotic and artificial intelligence (AI) and green crypto investments. The author also explores the influences of global uncertainty shocks like the COVID-19 pandemic and international conflicts on the role of each channel.

In this research, the author uses a cutting-edge model-free connectedness approach to investigate the relationships between the development of Global X Robotics and AI (BOTZ) and the volatility of green crypto investments from November 9, 2017 to March 24, 2023.

In the sample duration, the findings reveal a two-way link between AI and green/nongreen cryptocurrencies. Throughout the examined period, BOTZ has been a net receiver of shocks as determined by the net total connectedness. Among the main spillover shock carriers in the system, green cryptocurrencies are the most significant. The net pairwise directional connectivity reveals that green cryptocurrencies controlled BOTZ throughout the analyzed time, particularly during the COVID-19 era as well as the Ukraine–Russia crisis. According to the findings, the proposed system is vulnerable to a high level of indication influence.

The results have important policy implications for investors and governments, as well as methods from the spillovers across the various indicators and their interconnections. Sharp information on the primary contagions among these indicators aids politicians in designing the most appropriate policies.

To the best of the authors’ knowledge, this paper is the first to look at the link between AI, technological advancement and green cryptocurrency investing. Second, this study developed a methodology for examining instability links between various factors that is more appropriate for investigating these linkages. This study investigates the links between AI, technical advancement and green digital currencies using a cutting-edge model-free connectivity method. This work is also the first to examine the interconnection between volatility derived from AI, technological development and green cryptocurrency investments in light of unknown events, such as the COVID-19 pandemic and the Ukrainian–Russian conflict. Finally, this study includes a daily database from the BOTZ fund, which attempts to invest in firms that stand to gain from rising robotics and AI use. Cardano (ADA), IOTA, NANO (XNO), Stellar Lumens and Tron are examples of green cryptocurrencies, whereas Bitcoin is an example of a nongreen cryptocurrency. These virtual currencies are being used to investigate the relationship between investor mood and green and nongreen digital currencies. The data set spans the period from November 9, 2017 to March 24, 2023.

This study examines the risk spillovers between Indonesian sectorial stocks (Energy, Basic Materials, Industrials, Consumer Cyclicals, Consumer Non-cyclical and Financials), the aggregate index (IDX) and two commodities (gold and West Texas Intermediate Crude Oil [WTI] futures).

The study uses two methodologies: the TVP-VAR model of Antonakakis and Gabauer (2017) and the quantile connectedness approach of Ando et al. (2022). The data cover the period from October 04, 2010, to April 5, 2022.

The results show that the IDX, industrials and materials are net transmitters, while the financials, consumer noncyclical and energy sectors are the dominant shock receivers. Using the quantile connectedness approach, the role of each sector is heterogeneous and asymmetric, and the return spillover is stronger at lower and higher quantiles. Furthermore, the portfolio hedging results show that oil offers more diversification gains than gold, and hedging oil is more effective during the pandemic.

This study provides valuable insights for investors to diversify their portfolios and for policymakers to develop policies, regulations and risk management tools to promote stability in the Indonesian stock market. The results can inform the design of market regulations and the development of risk management tools to ensure the stability and resilience of the market.

This study is the first to examine the spillovers between commodities and Indonesian sectors, recognizing the presence of heterogeneity in the relationship under different market conditions. It provides important portfolio diversification insights for equity investors interested in the Indonesian stock market and policymakers.

This study investigates possible shock transmission and volatility spillover effects among the exchange rate changes and international portfolio flows for United States vis-à-vis two fast-growing emerging country groups: the BRICS (Brazil, Russia, India, China and South Africa) and MINT (Mexico, Indonesia, Nigeria and Turkey).

Applying VAR-BEKK-GARCH model, the evidence indicates that exchange rate fluctuations have a negative impact on net equity flows in Brazil, Russia, India and Turkey; thus, supporting the view that exchange rate uncertainty is an important driver of equity home bias.

As for the comparison of the pre- and post-crisis period, the findings support the evidence that the post-crisis period witnessed a greater number of cases of significant shock and volatility spillovers among exchange rate uncertainty and portfolio flows.

Overall, the empirical results provide fresh insights and policy implications for domestic and international investors through investment activities, and for policymakers through maintaining economic and financial stability.

Internationalization and financial deregulation have caused market participants and policymakers to consider the significance of financial connectedness and the spillover effects of shocks. In this context, this research is a pioneering effort to investigate the direction and magnitude of return volatility spillovers between Pakistan’s financial markets and those of its key trade partners. This paper examines the relationship between return and volatility spillover in the financial markets of Pakistan and its major trading partners.

Ten countries are selected for empirical examination of dynamic connectedness among Pakistan and its major trading partner’s stock markets. This study utilizes a spillover index approach model and considers daily, weekly and monthly datasets spanning 25 years from 1995 to 2019.

The results indicate that stock markets provide efficient channels for return and volatility spillovers. Moreover, it is found that the intensity of spillovers during the financial crisis is more intense as these crises are major determinants of contagion; consequently, investors, speculators and policymakers use these events for their respective purposes.

Researchers, practitioners, policymakers and investors may all benefit from the findings in areas including risk management, portfolio diversification and trading methods.

In this study, we aim to investigate the connectedness spillovers among major cryptocurrency markets. Moreover, we also explore to identify factors driving this connectedness, particularly focusing on the sentimentality of total, short-term, and long-term return connectedness spillovers among cryptocurrencies under Twitter-based economic uncertainties and US economic policy uncertainty. Finally, we investigate the extent to which cryptocurrency markets serve as a safe haven, hedge, and diversifier from news-based uncertainties.

This study employs the connectedness approach following the combination of Ando et al. (2022) QVAR and Baruník and Krehlík's (2018) frequency connectedness methodologies into the framework proposed by Diebold and Yilmaz (2012, 2014). The data covered from November 10, 2017, to April 21, 2023, and the factors driving cryptocurrency connectedness spillovers are identified and examined. The sentimentality of total, short-term, and long-term return connectedness spillovers among cryptocurrencies, concerning Twitter-based economic uncertainties and US economic policy uncertainty, are analyzed. We apply the Wavelet quantile correlation (WQC) method developed by Kumar and Padakandla (2022) to explore the effects of Twitter-based economic uncertainties and US economic policy uncertainty on Cryptocurrency market connectedness risk spillovers. Besides, we check and present the robustness of WQC findings with the multivariate stochastic volatility method.

Our findings indicate that Ethereum and Bitcoin are net shock transmitters at the center of the connectedness return network. Ethereum and Bitcoin hold the highest market capitalization and value in the cryptocurrency market, respectively. This suggests that return shocks originating from these two cryptocurrencies have the most significant impact on other cryptocurrencies. Tether and Monero are the net receivers of return shocks, while Cardano and XRP exhibit weak shock-transmitting characteristics through returns. In terms of return spillovers, Ethereum is the most effective, followed by Bitcoin and Stellar. Further analysis reveals that Twitter economic policy uncertainty and US economic policy uncertainty are effective drivers of short-term and total directional spillovers. These uncertainty indices exhibit positive coefficient signs in short-term and total directional spillovers, which turn predominantly negative in different magnitudes and frequency ranges in the long term. In addition, we also document that as the Total Connectedness Index (TCI) value increases, market risk also rises. Also, our empirical findings provide significant evidence of Twitter-based economic uncertainties and US economic policy uncertainty that affect short-term market risks. Hence, we state that risk-connectedness spillovers in cryptocurrency markets enclose permanent or temporary shock variations. Besides, findings of the low value of long-term spillovers suggest that risk shocks in cryptocurrency markets are not permanent, indicating long-term changes require careful monitoring and control over market dynamics.

In this study, we find evidence that Twitter's news-based uncertainty and US economic policy uncertainty have a significant effect on short-term market risk spillovers. Furthermore, we observe that high cryptocurrency market risk spillovers coincide with periods of events such as the US-China trade tensions in January 2018, the Brexit process in February 2019, and the COVID-19 outbreak in November 2019. Next, we observe a decline in cryptocurrency market risk spillovers after March 2020. The reason for this mitigation of market risk spillover may be that the Fed's quantitative easing signals have initiated a relaxation process in the markets. Because the Fed's signal to fight inflation in March 2022 also coincides with the period when risk spillover increased in crypto markets. Based on this, we present evidence that the FED's communication mechanism with the markets can potentially affect both short- and long-term expectations. In this context, we can say that our hypothesis that uncertainty about the news causes short-term risks to increase has been confirmed. Our findings may have investment policy implications for portfolio managers and investors generally in terms of reducing financial risks.

Our paper contributes to the literature by examining the interconnectedness among major cryptocurrencies and the drivers behind them, particularly focusing on the role of news-based economic uncertainties. More broadly, we calculate the utilization of advanced methodologies and the incorporation of real-time economic uncertainty data to enhance the originality and value of the research, which provides insights into the dynamics of cryptocurrency markets.

The purpose of this paper is to study the short‐term macroeconomic effects of the fiscal policy in Colombia for the 1980‐2007 period using a structural vector autoregression (SVAR) model.

The authors' benchmark is a five‐variable SVAR model which includes government spending, output, tax revenues, inflation and short‐term interest rates. In addition, the authors specified six‐variable VAR models, adding in turn private consumption, private investment, the unemployment rate and the real minimum wage to the last set of variables. Two alternative identification techniques are used in the VARs to check the robustness of the results.

The following effects of a positive government spending shock are found. First, the GDP responds positively and significantly during the first six quarters. The cumulative output multiplier fluctuates between 1.12 and 1.19. Second, both inflation and nominal interest rates respond positively and significantly. Third, the authors find a significant positive response by both private consumption and private investment. Finally, the unemployment rate reacts negatively and significantly.

The most surprising result comes from the response of output to a positive shock in taxes. Nonetheless, the positive respond of the GDP is short lived and has little significance.

The authors' results support the smoothing role of fiscal policy on output fluctuations, which implies its capacity to restore real activity effectively in critical times like the ones currently being forecast.

The negligible results found previously for Colombia could be related to the fiscal data used, which are not keep coherence with national accounting. To solve these obstacles, a quarterly fiscal database is assembled on an approximately accrual basis for the general government.