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We analyze return and volatility connectedness of the rising green asset and the well-established US industry stock and commodity markets from September 2010 to July 2021. We find that the time-varying return and volatility connectedness have exhibited serious crisis jumps. Some individual assets of both the green and commodity markets are in connection to the US sectoral stock market returns, and the volatility connections are even more common than the return connections. Furthermore, some financial and economic uncertainty indicators manifest positive impacts from the volatility of some `big pond markets for e.g. commodities, whereas some others affect the connectedness negatively. Additional analysis of financial and economic uncertainty indicators manifests positive impacts from the volatility of some `big pond markets, e.g., commodities, while others negatively affect the connectedness., Funding Agencies|University of Jyvaskyla School of Business and Economics under the JYU Visiting Fellow Programme [444/13.00.05.00/2021]

The high volatility of the blockchain markets has driven the attention of investors and market participants to concentrate on the diversification avenues of NFTs, DeFi Tokens, and Cryptocurrencies. We examined the extreme risk transmission of blockchain markets using the quantile connectedness technique at the median, extreme low, and extreme high volatility conditions. We find significant risk spillovers among blockchain markets with strong disconnection of NFTs. Meanwhile, time-varying features characterized various uneven economic circumstances. Overall, NFTs offer greater diversification avenues with substantial risk-bearing potential among other blockchain markets to shelter the investments and minimize extreme risks.

The high volatility of the blockchain markets has driven the attention of investors and market participants to concentrate on the diversification avenues of NFTs, DeFi Tokens, and Cryptocurrencies. We examined the extreme risk transmission of blockchain markets using the quantile connectedness technique at the median, extreme low, and extreme high volatility conditions. We find significant risk spillovers among blockchain markets with strong disconnection of NFTs. Meanwhile, time-varying features characterized various uneven economic circumstances. Overall, NFTs offer greater diversification avenues with substantial risk-bearing potential among other blockchain markets to shelter the investments and minimize extreme risks.

We analyze return and volatility connectedness of the rising green asset and the well-established US industry stock and commodity markets from September 2010 to July 2021. We find that the time-varying return and volatility connectedness have exhibited serious crisis jumps. Some individual assets of both the green and commodity markets are in connection to the US sectoral stock market returns, and the volatility connections are even more common than the return connections. Furthermore, some financial and economic uncertainty indicators manifest positive impacts from the volatility of some `big pond markets for e.g. commodities, whereas some others affect the connectedness negatively. Additional analysis of financial and economic uncertainty indicators manifests positive impacts from the volatility of some `big pond markets, e.g., commodities, while others negatively affect the connectedness., Funding Agencies|University of Jyvaskyla School of Business and Economics under the JYU Visiting Fellow Programme [444/13.00.05.00/2021]

Governments around the world have responded to the COVID-19 outbreak with a mix of policies. The strictest responses of the New Zealand government are notable, given their abilities to contain and limit the spread of the virus. However, their impacts on stock returns remain unclear. This paper investigates the impact of three policies, namely lockdown, the stimulus package, and the travel ban, on the returns of 14 New Zealand industry stock indices. Using daily data from 1 January 2019 to 25 August 2020, evidence points to a heightened level of integration among the various industry stock indices during the early stages of the pandemic. Only lockdown has had a positive impact on aggregate stock returns, suggesting its ability to raise investors’ confidence in the overall stock market. At the industry level, the impact of the three response policies is generally positive but heterogeneous across industry stock indices. Notably, none of the three adopted policies significantly impact technology, healthcare, and real estate returns.

This study draws a comparison between the Global Financial Crisis (GFC) and the COVID-19 pandemic crisis to assess the safehaven potential of Islamic stocks for G7 stock markets. We employ the cross-quantilogram framework of Han et al., which considers the non-linearity in the relationship, and thus captures the correlation between the Islamic and G7 stock markets across various quantiles reflecting different market conditions. The analysis also includes the time-varying cross-quantile correlation to observe the evolution of Islamic stocks’ safe-haven potential. Our full sample analysis shows that Islamic stocks do not exhibit safe-haven properties for G7 stock markets. During the GFC period, Islamic stocks show some diversification benefits for the G7 stock markets. Notably, Islamic stocks emerged as a robust safe-haven asset for the G7 stock markets during the pandemic crisis. The study carries essential insights for equity investors and regulators of G7 and other countries to implement diversification/hedging strategies that would involve Islamic stocks to protect equity investments and the overall financial system amid the financial downturns.

We analyze return and volatility connectedness of the rising green asset and the well-established US industry stock and commodity markets from September 2010 to July 2021. We find that the time-varying return and volatility connectedness have exhibited serious crisis jumps. Some individual assets of both the green and commodity markets are in connection to the US sectoral stock market returns, and the volatility connections are even more common than the return connections. Furthermore, some financial and economic uncertainty indicators manifest positive impacts from the volatility of some `big pond markets for e.g. commodities, whereas some others affect the connectedness negatively. Additional analysis of financial and economic uncertainty indicators manifests positive impacts from the volatility of some `big pond markets, e.g., commodities, while others negatively affect the connectedness., Funding Agencies|University of Jyvaskyla School of Business and Economics under the JYU Visiting Fellow Programme [444/13.00.05.00/2021]

The high volatility of the blockchain markets has driven the attention of investors and market participants to concentrate on the diversification avenues of NFTs, DeFi Tokens, and Cryptocurrencies. We examined the extreme risk transmission of blockchain markets using the quantile connectedness technique at the median, extreme low, and extreme high volatility conditions. We find significant risk spillovers among blockchain markets with strong disconnection of NFTs. Meanwhile, time-varying features characterized various uneven economic circumstances. Overall, NFTs offer greater diversification avenues with substantial risk-bearing potential among other blockchain markets to shelter the investments and minimize extreme risks.

Australian National Electricity Market (NEM) provides efficient and smooth electricity transmission via a unique integration mechanism of different Australian regional electricity markets. We, therefore, examined the asymmetric time-frequency connectedness across five physically interconnected Australian regional electricity markets in the NEM using daily wholesale price data from 17 May 2005 to 31 December 2020. Due to direct physical interconnections and close geographical vicinities, Australian regional electricity markets have more connectedness within the region than across regions. The results of deseasonalized data revealed high spillovers among electricity markets during a crisis event, periods of abnormal weather, and regulatory sanctions implied on the NEM, which the findings from previous studies have not fully captured. Meanwhile, seasonality-adjusted results using X 13-ARIMA method highlighted dominance of negative spillovers both in the short- and long-run. Moreover, reforms in electricity policies by the Australian government played a significant role in shaping the total spillover index. Our study offers fresh insights on the NEM and stipulates significant policy implications for NEM, which the Australian state and federal government, policymakers, investors, retailers, and power suppliers must consider., Funding: ERIA

The unprecedented challenges caused by the COVID-19 pandemic have led to a need to re-examine sustainable corporate governance practices. Within this context, the current study investigates the moderated effect of gender-diverse corporate boards on sustainable corporate governance practices in Malaysian financial and non-financial firms during the period 2011–2020, employing the dynamic estimator (S-GMM). During the COVID-19 pandemic, a negative relationship between ownership constructs and Global Reporting Initiative (GRI) indicators is observed in non-financial firms, whereas the opposite is reported for financial firms. Moreover, the moderated effect of gender-diverse boards is only substantiated in financial firms. The findings reveal that sustainable corporate governance is practised in financial firms but not in non-financial firms. Particularly, we draw significant implications for policymakers and regulatory bodies of Malaysia to carefully monitor the implementation of sustainable corporate governance given uncertain circumstances of COVID-19 pandemic. Further, our study is beneficial for academics, practitioners, and research scholars for their future research endeavours.

This study draws a comparison between the Global Financial Crisis (GFC) and the COVID-19 pandemic crisis to assess the safehaven potential of Islamic stocks for G7 stock markets. We employ the cross-quantilogram framework of Han et al., which considers the non-linearity in the relationship, and thus captures the correlation between the Islamic and G7 stock markets across various quantiles reflecting different market conditions. The analysis also includes the time-varying cross-quantile correlation to observe the evolution of Islamic stocks’ safe-haven potential. Our full sample analysis shows that Islamic stocks do not exhibit safe-haven properties for G7 stock markets. During the GFC period, Islamic stocks show some diversification benefits for the G7 stock markets. Notably, Islamic stocks emerged as a robust safe-haven asset for the G7 stock markets during the pandemic crisis. The study carries essential insights for equity investors and regulators of G7 and other countries to implement diversification/hedging strategies that would involve Islamic stocks to protect equity investments and the overall financial system amid the financial downturns.

Governments around the world have responded to the COVID-19 outbreak with a mix of policies. The strictest responses of the New Zealand government are notable, given their abilities to contain and limit the spread of the virus. However, their impacts on stock returns remain unclear. This paper investigates the impact of three policies, namely lockdown, the stimulus package, and the travel ban, on the returns of 14 New Zealand industry stock indices. Using daily data from 1 January 2019 to 25 August 2020, evidence points to a heightened level of integration among the various industry stock indices during the early stages of the pandemic. Only lockdown has had a positive impact on aggregate stock returns, suggesting its ability to raise investors’ confidence in the overall stock market. At the industry level, the impact of the three response policies is generally positive but heterogeneous across industry stock indices. Notably, none of the three adopted policies significantly impact technology, healthcare, and real estate returns.

We analyze return and volatility connectedness of the rising green asset and the well-established US industry stock and commodity markets from September 2010 to July 2021. We find that the time-varying return and volatility connectedness have exhibited serious crisis jumps. Some individual assets of both the green and commodity markets are in connection to the US sectoral stock market returns, and the volatility connections are even more common than the return connections. Furthermore, some financial and economic uncertainty indicators manifest positive impacts from the volatility of some `big pond markets for e.g. commodities, whereas some others affect the connectedness negatively. Additional analysis of financial and economic uncertainty indicators manifests positive impacts from the volatility of some `big pond markets, e.g., commodities, while others negatively affect the connectedness., Funding Agencies|University of Jyvaskyla School of Business and Economics under the JYU Visiting Fellow Programme [444/13.00.05.00/2021]

We analyze return and volatility connectedness of the rising green asset and the well-established US industry stock and commodity markets from September 2010 to July 2021. We find that the time-varying return and volatility connectedness have exhibited serious crisis jumps. Some individual assets of both the green and commodity markets are in connection to the US sectoral stock market returns, and the volatility connections are even more common than the return connections. Furthermore, some financial and economic uncertainty indicators manifest positive impacts from the volatility of some `big pond markets for e.g. commodities, whereas some others affect the connectedness negatively. Additional analysis of financial and economic uncertainty indicators manifests positive impacts from the volatility of some `big pond markets, e.g., commodities, while others negatively affect the connectedness., Funding Agencies|University of Jyvaskyla School of Business and Economics under the JYU Visiting Fellow Programme [444/13.00.05.00/2021]

The high volatility of the blockchain markets has driven the attention of investors and market participants to concentrate on the diversification avenues of NFTs, DeFi Tokens, and Cryptocurrencies. We examined the extreme risk transmission of blockchain markets using the quantile connectedness technique at the median, extreme low, and extreme high volatility conditions. We find significant risk spillovers among blockchain markets with strong disconnection of NFTs. Meanwhile, time-varying features characterized various uneven economic circumstances. Overall, NFTs offer greater diversification avenues with substantial risk-bearing potential among other blockchain markets to shelter the investments and minimize extreme risks.

The high volatility of the blockchain markets has driven the attention of investors and market participants to concentrate on the diversification avenues of NFTs, DeFi Tokens, and Cryptocurrencies. We examined the extreme risk transmission of blockchain markets using the quantile connectedness technique at the median, extreme low, and extreme high volatility conditions. We find significant risk spillovers among blockchain markets with strong disconnection of NFTs. Meanwhile, time-varying features characterized various uneven economic circumstances. Overall, NFTs offer greater diversification avenues with substantial risk-bearing potential among other blockchain markets to shelter the investments and minimize extreme risks.

With many studies highlighting the heterogeneous impact of the COVID-19 pandemic on different commodity markets, this study provides evidence of quantile connectedness between energy, metals, and agriculture commodity markets before and during the COVID-19 outbreak. Since mean-based measures of connectedness are not necessarily suitable to measure connectedness in the crisis period, especially in the tails of the return distribution, thus in this study, we use the newly developed approach of quantile-based connectedness. The full-sample analysis results show that return shocks only propagate within the energy commodity group. The findings manifest that transmission of return spillovers is stronger in the left and right tails of the conditional return distribution. In addition, the results unveil that degree of tail-dependence between energy, metals, and agriculture commodities are time-varying. Meanwhile, our sub-sample analysis clearly shows that the commodity market return connectedness demonstrates a significant shift over time due to COVID-19 shocks. There is evidence of strong transmission of return shocks between energy, metals, and agriculture commodities during the COVID-19 fiasco. Finally, the results also illustrate that softs and livestock commodities hold significant diversification benefits for energy market investors.

The volatility spillover is defined as the transmission of instability from market to market. It occurs when the volatility price change in one market causes a lagged impact on volatility price in another market above the local effects of market. In this study the garchmodels are used to examine the possibility of volatility transmission between the KSE100 index (Pakistan) and S&P500 index (usa); in other words, to examine how the volatility in one market mayinfluence the other and vice versa. The egarchmodel is also applied and it was observed thatour attempt to analyze symmetry and persistence in the KSE100 index and the S&P500 index volatility proved that there is clear evidence that shocks to the volatitlity of the KSE100 and S&P500 indexes have asymmetric and persistent effects. It is observed from the study that the shocks to the stock returns in one market do not transmit to the other; in other words, it appears that there is no spillover effect between the two stock markets., O derramamento volátil é definido como a instabilidade entre mercados. Acontece quando o preço da volatilidade muda em um mercado causando um impacto atrasado no preço da volatilidade em outro mercado que se encontra por cima dos efeitos locais do mercado. Neste estudo os modelos GARCH são utilizados paraexaminar a possibilidade de transmissão de volatilida de entre o índice KSE100 (Paquistão) e o índice S&P500 (Estados Unidos). Em outras palavras, para examinar a influência da volatilidade em outro e vice-versa. O modelo EGCARCH também foi aplicado e se observa nossa tentativa por analisar a simetria e a persistência da volatilidade no KSE100 e o S&P500, se evidencia com claridade que choques na volatilidade de ambos os dois tem um efeito assimétrico e persistente. A partir do estudo se observou que os choques ao rendimento das ações em um mercado não se transmitem ao outro, em outras palavras, não há presença de efeito de derramamento entre as duas bolsas de Valores., El derrame volátil es definido como la inestabilidad entre mercados. Sucede cuando el precio de la volatilidad cambia en un mercado causando un impacto rezagado en el precio de la volatilidad en otro mercado que se encuentra por encima los efectos locales del mercado. En este estudio los modelos GARCH son utilizados para examinar la posiblidad de transmición de volatilidad entre el índice KSE100( Pakistan) y el índice S&P500 (Estados Unidos). En otras palabras, para examinar la influencia de la volatilidad en otro y vice versa. El modelo EGCARCH también fue aplicado y se observa nuestro intento por analizar la simetría y la persistencia de lavolatilidad en el KSE100 y el S&P500, se evidencia con claridad que choques en la volatilidad de ambos tiene un efecto asimetrico y persistente. A partir del estudio se observó que los choques al rendimiento de las acciones en un mercado no se transmiten al otro, en otras palabras, no hay presencia de efecto de derrame entre las dos bolsas de Valores.

The volatility spillover is defined as the transmission of instability from market to market. It occurs when the volatility price change in one market causes a lagged impact on volatility price in another market above the local effects of market. In this study the garchmodels are used to examine the possibility of volatility transmission between the KSE100 index (Pakistan) and S&P500 index (usa); in other words, to examine how the volatility in one market mayinfluence the other and vice versa. The egarchmodel is also applied and it was observed thatour attempt to analyze symmetry and persistence in the KSE100 index and the S&P500 index volatility proved that there is clear evidence that shocks to the volatitlity of the KSE100 and S&P500 indexes have asymmetric and persistent effects. It is observed from the study that the shocks to the stock returns in one market do not transmit to the other; in other words, it appears that there is no spillover effect between the two stock markets., O derramamento volátil é definido como a instabilidade entre mercados. Acontece quando o preço da volatilidade muda em um mercado causando um impacto atrasado no preço da volatilidade em outro mercado que se encontra por cima dos efeitos locais do mercado. Neste estudo os modelos GARCH são utilizados paraexaminar a possibilidade de transmissão de volatilida de entre o índice KSE100 (Paquistão) e o índice S&P500 (Estados Unidos). Em outras palavras, para examinar a influência da volatilidade em outro e vice-versa. O modelo EGCARCH também foi aplicado e se observa nossa tentativa por analisar a simetria e a persistência da volatilidade no KSE100 e o S&P500, se evidencia com claridade que choques na volatilidade de ambos os dois tem um efeito assimétrico e persistente. A partir do estudo se observou que os choques ao rendimento das ações em um mercado não se transmitem ao outro, em outras palavras, não há presença de efeito de derramamento entre as duas bolsas de Valores., El derrame volátil es definido como la inestabilidad entre mercados. Sucede cuando el precio de la volatilidad cambia en un mercado causando un impacto rezagado en el precio de la volatilidad en otro mercado que se encuentra por encima los efectos locales del mercado. En este estudio los modelos GARCH son utilizados para examinar la posiblidad de transmición de volatilidad entre el índice KSE100( Pakistan) y el índice S&P500 (Estados Unidos). En otras palabras, para examinar la influencia de la volatilidad en otro y vice versa. El modelo EGCARCH también fue aplicado y se observa nuestro intento por analizar la simetría y la persistencia de lavolatilidad en el KSE100 y el S&P500, se evidencia con claridad que choques en la volatilidad de ambos tiene un efecto asimetrico y persistente. A partir del estudio se observó que los choques al rendimiento de las acciones en un mercado no se transmiten al otro, en otras palabras, no hay presencia de efecto de derrame entre las dos bolsas de Valores.

This dissertation presents three essays on commodity market uncertainties. Fundamentally, uncertainty relates to a decrease in investment and reduction in the production of goods and services that causes a momentary decline in aggregate output as well as employment. Hence, the increase in uncertainty has a pervasive impact on the aggregate income received by all the factors of production in an economy. In the first study, we measure the daily price uncertainty of 22 commodities and analyze the time and frequency connectedness among them. Applying spillover analysis and network graphs, we find that overall connectedness among commodity uncertainties increase during the global financial crisis (GFC) and the oil price collapse of 2014-16. Network analysis shows more spillover within a specific commodity class, and that precious metals due to less spillover with other commodities may serve as safe-haven during the crisis. The decomposition of the spillover index reveals that commodity markets are more connected in the long-run. The second study builds on the energy – stock nexus by investigating the impact of energy commodity uncertainties on the systematic risk of twelve industries in the US. The dynamic betas indicate that real estate, financials, and basic materials are the high-risk industries. Notably, the systematic risk of the oil and gas sector was significantly affected during the Global Financial Crisis (GFC) and the Shale Oil Revolution (SOR) sub-periods. Our results provide convincing evidence of the positive impact of energy uncertainties on basic material, basic resources, financials, oil and gas, and real estate. On the other hand, we identify the negative impact on consumer goods, consumer services, health care, industrials, and technology industries. Finally, our third study investigates the causal impact of global factors as drivers of transmission between oil and other commodity markets using the commodity uncertainty indexes. We estimate strong bi-di