In this study, we analyze the quantile dependence for green bond returns and renewable energy stock returns with three major asset classes: corporate bonds, stocks and oil. Furthermore, we control the dependence structure for technology, uncertainties as well as lag structures and time-varying effects. We apply the cross-quantilogram developed by Han et al. (2016) that allows us to study the dependence structures between two time series in arbitrary quantiles. The results led us to three key findings: 1) The returns of thegreen bond market are tail-dependent on the returns of both long and short-term maturities for the corporate bond market but are not dependent on the stock market nor the oil market. The tail-dependence indicates that while investors may hold green bonds due to moral incentives, it is not enough during times of turbulence. Further, the dependence structures are short-lived. 2)The renewable energy market is dependent on oil returns of similar quantiles, suggesting that renewable energy substitutes oil when oil prices increase. However, renewable energy does not influence the oil market, indicating that oil is not a substitutional energy source for renewable energy driven firms. Renewable energy stocks are further highly dependent on the returns of the general stock market but are not influenced by the returns on the corporate bond market. 3) The dependence of both renewable energy and green bonds with the asset markets are time-varying. Our overall results obtained by this paper provides information that could help facilitate new investment allocations towards green investments. Further, the results may have immediate and important implications for investors. For those in the corporate bond market, adding green bonds does not add diversification benefits during turbulence. Similarly, renewable energy stock does not add diversification benefits to investors in the oil or stock market.

Countries participating in a common currency area increase their integration within the area. This paper investigates the impact common currency areas have for economic integration with economies of different characteristic outside the area. Results for a common currency group compares to a sovereign currency group. The common currency group consists of three countries who have adopted the euro, while the sovereign currency group consist of three European countries with sovereign currencies. The level of economic integration is examined towards three different economies; European drivers, global markets and emerging markets. The period ranges from 1993M01 to 2017M09 and includes industrial production indices and stock market indices. Economic integration is studied through a DCC-EGARCH model, on both aggregated and time-dependent level, which yield correlations. In comparison to previous studies, this paper also applies a cross-quantilogram method to examine the impact of different market conditions have on the correlations. Higher correlations for the common currency group than for the sovereign currency group do exist with the European drivers and the global countries. With the emerging markets such pattern is not found, instead low correlations are mainly examined. Besides the correlation with the emerging countries, the results indicate membership in a common currency area, in this case the EMU, to increase the economic integration. Overall, highest levels of correlation are found with the European drivers, followed by the US as a global economy, corresponding with the importance of homogeneity for high economic integration. Due to no conclusive change in correlations during the euro implementation, membership in a common currency area per se does not increase economic integration. However, a common currency area with a strong currency do along with other characteristics influence the economic integration. We find evidence that market regimes have an impact on economic integration. Adverse market conditions overall seem to influence the integration in a higher degree than normal or good conditions. The results indicate that the adverse conditions increase the economic integration, this is in particularly seen for the common currency countries correlation with the European drivers and the US.

This thesis examines the dependence structures between commodity futures and corresponding commodity producer equity indices in bearish, bullish and normal market conditions. We study commodity futures and producer indices in the energy, precious metals, gold and agriculture commodity markets using daily return data that ranges from 16 December 2005 to 28 June 2019. We employ the cross-quantilogram approach developed by Han et al. (2016) to examine dependence structures in the full quantile range, which represents different market states. Furthermore, we control for different lag structures, uncertainties and time-varying dependence structures. From our results we conclude the following: 1) There are time-varying asymmetric and symmetric dependencies in different commodity markets. There is asymmetric dependence between commodity futures and producer indices in the precious metals, gold and agricultural markets. In the oil market, the relationship is symmetrical. No relationship is found in the natural gas market. 2) Heterogenous dependence structures are identified in the gold, precious metals and agricultural commodity markets. The oil market uncovers homogenous dependence structures. 3) The observed spillover in all markets occur in the very short run, at one day, and dissipates after a week and additionally after a month. Our results provide new information regarding commodity diversification attributes which can be useful to investors. Our results also provide important policy implications: Since volatility spillovers between commodity futures and producer indices may deter investors from including commodities in their portfolios, as they might lose their diversifier qualities, it is important to enforce policies that will prevent the spillovers between the assets. Further, regulations of the commodity futures markets could be an alternative to reduce the spillovers.

Climate  change  continues  to  deteriorate  the world around us, causing warmer temperatures, droughts, increased sea-levels, and various other climate fluctuations and shocks all over the world. Through this deterioration, the economic impact of our rapidly declining climate conditions is only becoming more and more prevalent. In this paper, we analyze how the U.S., as a world-leading economy is impacted by climatological conditions in order to answer what effects such conditions have on the economy as a whole. We use municipal bond returns as a benchmark of economic efficiency, due to their interconnectedness with other financial markets. They also represent investors' perceptions of market conditions and credit risk. In order to study how climate fluctuations affect the directionality of the municipal bond market, we employ a Cross-Quantilogram Correlation methodology, which is summarized in heatmap format on a regional level. Furthermore, the Local Projection framework is employed to capture the dynamic responses of the variables. Our findings suggest an overall negative relationship between municipal bond returns and droughts, which varies in strength regionally. Furthermore, sea-level is shown to impact certain regions' municipal bond returns negatively, although this effect is not as prevalent. The Local Projections suggest that there is a benchmark relationship between municipal bond returns and climate shocks of various natures. For the majority of states, our findings suggest an initial, in some cases slightly lagged, decrease in municipal bond returns, followed by a period of recovery, normally around three weeks after the initial shock takes place. There are notable deviations from this relationship, for example, Alabama and Louisiana, which seem to react positively to climate shocks. Furthermore, few states do not necessarily undergo a recovery period during the studied period, suggesting that the negative impact that climate shocks have on the municipal bond market in said states lasts for a minimum of four weeks. However, the Local Projection findings should be taken lightly, due to the absence of statistical significance.