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This study aims to investigate the interconnectedness across the risk appetite of distinct investor types in Borsa Istanbul. This study also examines the causal impact of global implied volatility indices on the risk appetite of these investor groups.

The authors use a novel time-varying frequency connectedness framework of Chatziantoniou et al. and a new time-varying Granger causality test with a recursive evolving procedure by Shi et al. over June 2008 and July 2022.

The results show a high level of interconnectedness across the risk appetite of different investor types. The sizable spillovers to domestic types of investors either occur from professional or foreign investors, indicating the long-term dominant effect of foreign and more qualified investors on the domestic investors in Borsa Istanbul. The authors provide significant evidence of causality from the global implied volatility to the Borsa Istanbul risk appetite indices, which are getting stronger after the COVID-19 outbreak.

Unlike the previous studies, the authors analyze the risk appetite sub-indices of various types of investors to reveal behavioral distinctions and interconnectedness across them. The authors use a novel econometric framework to assess investors’ risk appetite in different investment horizons in a time-varying system. Together with volatility index (VIX), the authors also use volatilities of oil (OVX), gold (GVZ) and currency (EVZ), considering the information transmission not only from stock markets but also energy, metals and currency markets. The present data set covers significant financial crises, socioeconomic events and the COVID-19 outbreak.

This study aims to examine the uncertainty spillover among eight important asset classes (cryptocurrencies, US stocks, US bonds, US dollar, agriculture, metal, oil and gold) using weekly data from 2014 to 2020. This study also examines the US macro uncertainty and US financial stress spillover on these assets.

The authors use time–frequency connectedness method to study the uncertainty spillover among the asset classes.

This study’s findings revealed that the uncertainty spillover is time-varying and peaked during the 2016 oil supply glut and COVID-19 pandemic. US stocks are the highest transmitter of uncertainty to all other assets, followed by the US dollar and oil. US stocks (US dollar and oil) transmit uncertainty in long (short) term. Furthermore, US macro uncertainty is the net transmitter of uncertainty to the US stocks, industrial metals and oil markets. In contrast, US financial stress is the net transmitter of uncertainty to the US bonds, cryptocurrencies, the US dollar and gold markets. US financial stress (US macro uncertainty) has long (short)-term effects on asset price volatility.

This study complements the studies on volatility spillover among the important asset classes. This study also includes recently financialized asset classes such as cryptocurrencies, agricultural and industrial commodities. This study examines the macro uncertainty and financial stress spillover on these assets.

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 real estate markets may be significantly influenced by the uncertainty in global economic policy. This paper aims to evaluate the time-varying connectedness between global economic policy uncertainty and regional real estate markets to understand how regional real estate markets and uncertainty in global economic policy are related throughout time.

The current study includes the monthly data from April 2007 to August 2022 of major regions (i.e. Asia Pacific, Europe, Africa, North America and Latin America). Moreover, the authors use the time-varying parameter vector auto-regression (TVP-VAR) approach for the analysis.

The finding revealed a significant level of connectedness among global economic policy uncertainty and selected regional real estate markets. The result highlights more than 80% connectivity between the two variables, which makes the current study valuable. Furthermore, results determine Africa and North America are the shock transmitters; thus, they are considered safe-haven for investors to invest in these markets.

The main novelty is that this research highlights the time-varying connectedness between global economic policy uncertainty and five regional real estate markets (Africa, Asian Pacific, Europe, Latin America and North America) using TVP-VAR. Furthermore, the authors used the standard and poor daily real estate investment trust (REIT) indices for the selected REIT markets. Finally, this research suggests practical implications for real estate investors, property developers, stakeholders, policymakers and managers to revise their current policies to maintain the real estate market stability during economic and political uncertainty or in other uncertain situations.

This study aims to investigate the dynamic interconnectedness of economic policy uncertainty (EPU), fiscal policy uncertainty (FPU) and monetary policy uncertainty (MPU) in four nations, the USA, Japan, Greece and South Korea, between 1998 and 2021.

To comprehend the cross-category/cross-country evolution of uncertainty connectedness, the authors use the conditional connectedness approach. By using an inclusive network, this strategy lessens the bias caused by omitted variables. The TVP-VAR method is advantageous as it eliminates outliers that may potentially skew the results and reduces the bias caused by picking arbitrary rolling windows.

Based on the findings, aggregate EPU is a net transmitter of policy uncertainties across all countries when conditional-country connectedness is used. MPU receives significantly more spillovers than FPU does across all countries, even though both are primarily recipients of uncertainties. The USA appears to be a transmitter of categorical spillovers before COVID-19, while Greece appears to be a net receiver of all category spillovers in terms of category-specific connectedness. The existence of extreme global events is also seen to cause an increase in category-specific and country-specific connectedness. Additionally, the authors report that conditional country-specific connectedness is greater than conditional category-specific connectedness.

This study expands existing literature in several ways. Firstly, the authors use a novel conditional connectedness approach, which has not been used to untangle cross-category/cross-country policy uncertainty connectedness. Secondly, they use the TVP-VAR approach which does not depend on rolling windows to understand dynamic connectedness. Thirdly, they use an expanded number of countries in their analysis, a departure from existing studies that have in most cases used two countries to understand categorical EPU connectedness.

This paper aims to examine the dynamic return and volatility connectedness for six major industrial metals (tin, lead, nickel, zinc, copper and aluminium) and the coronavirus media coverage index (MCI).

To that purpose, this study applies the fresh time-varying parameter vector autoregression methodology (TVP–VAR model) during the sample period between 2 January, 2020, and 16 April, 2021, that is, covering the three waves of the COVID-19 pandemic crisis.

This study’s results show interesting findings. First, dynamic total return and volatility connectedness changes over time, highlighting a significant increase during the third wave of the pandemic. Second, the MCI index is a leading net transmitter in terms of return and volatility at the introduction of the SARS-CoV-2 coronavirus crisis. Third, this study clearly distinguishes two profiles among industrial metals: copper and tin/zinc as net transmitters and lead and aluminium as net receivers. Finally, the most relevant differences between them are concentrated not only at the beginning of the COVID-19 pandemic (first wave) but also during the second and third waves of the coronavirus outbreak.

To the best of the authors’ knowledge, this is the first research that explores the dynamic return and volatility connectedness in the industrial metal market, applying the TVP–VAR methodology during the first waves of the COVID-19 pandemic crisis.

This paper examines the time-varying return connectedness between renewable energy, oil, precious metals, the Gulf Council Cooperation region and the United States stock markets during two successive crises: the pandemic Covid-19 and the 2022 Russo-Ukrainian war. The main objective is to investigate the effect of the Covid-19 pandemic and the Russo-Ukrainian war on the connectedness between the considered stock markets.

This paper uses the time-varying parameter vector autoregression approach, which represents an extension of the Spillover approach (Diebold and Yilmaz, 2009, 2012, 2014), to examine the time-varying connectedness among stock markets.

This paper reflects the effect of the two crises on the stock markets in terms of shock transmission degree. We find that the United States and renewable energy stock markets are the main net emitters of shocks during the global period and not just during the two considered crises sub-periods. Oil stock market is both an emitter and a receiver of shocks against Gulf Council Cooperation region and United States markets during the full sample period, which may be due to price fluctuation especially during the two crises sub-periods, which suggests that the future is for renewable energy.

This paper examines the effect of the two recent and successive crises, the Covid-19 pandemic and the 2022 Russo-Ukrainian war, on the connectedness among traditional stock markets (the United States and Gulf Council Cooperation region) and commodities stock markets (renewable energy, oil and precious metals).

This study aims to explore the connectedness of price return index spillovers across eight economic sectors in the Malaysian stock market (Bursa Malaysia).

The analysis uses daily data of sectoral price index from 10 May 2005 to 24 February 2021. The study uses Bayesian time-varying parameter vector autoregressive.

The degree of price return index spillovers varies over time, reaching unprecedented heights during the COVID-19 pandemic in 2020. The industrial economic sector is the main transmitter of price index return shock, whereas the utilities economic sector is the dominant receiver of index return spillovers.

The findings are critical for investors, market participants, businesses and policymakers in developing action plans for the vulnerable sectors. It further enhances investors’ confidence in making investment decisions.

The purpose of this paper is to extend the literature on the spillovers across economic policy uncertainty (EPU) and cryptocurrency uncertainty indices.

This paper uses cross-country economic policy uncertainty indices and the novel data measuring the cryptocurrency price uncertainties over the period 2013–2021 to construct a sample of 946 observations and applies the time-varying parameter vector autoregression (TVP-VAR) model to do an empirical study.

The findings suggest that there are cross-country spillovers of economic policy uncertainty. In addition, the total uncertainty spillover between economic policies and cryptocurrency peaked in 2015 before gradually decreasing in the following periods. Concomitantly, the cryptocurrency uncertainty has acted as the “receiver.” More importantly, the authors found the predictive power of economic policy uncertainty to predict the cryptocurrency uncertainty index. This paper’s results hold robust when using alternative measurement of cryptocurrency policy uncertainty.

This study is the first research that deeply investigates the association between two uncertainty indicators, namely economic policy uncertainty and the cryptocurrency uncertainty index. We provide fresh evidence about the dynamic connectedness between country-level economic policy uncertainty and the cryptocurrency index. Our work contributes a new channel driving the variants of uncertainties in the cryptocurrency market.

The purpose of this paper is to examine the connectedness across a variety of Sukuk and conventional bond indices and the implications for optimal asset allocation for the period January 1, 2010–April 30, 2020.

The data set consists of five major Sukuk (Dow Jones Sukuk, Thompson Reuters BPA Malaysia Sukuk, Indonesia Government Sukuk, S&P MENA Sukuk and Tadawul Sukuk and Bonds Index) and five conventional bond indexes, one for developed (USA) and four for emerging markets (Malaysia, Indonesia, Africa and Qatar). This study investigates the connectedness and volatility spillover effects across the aforementioned indices, by following the Diebold and Yilmaz (2012) approach, based on the time-varying parameter vector autoregressive (TVP-VAR) model. In addition, this paper provides optimal hedge ratios and portfolio weights for investors.

The empirical results show that Sukuk and conventional bond markets are highly integrated and that total connectedness exhibits sensitivity to exogenous shocks. The Dow Jones and the Malaysian Sukuk indices are the primary shock transmitters to other markets. However, the weak volatility spillovers between the Dow Jones and conventional bonds suggest that opportunities for optimal asset allocation may in fact exist. The highest (lowest) hedging effectiveness can be achieved by taking a short position in Malaysian (Qatarian) bonds.

To the best of the knowledge, this is the largest sample taken into account to investigate the connectedness between Sukuk and conventional bonds.