How implied volatilities in energy sector, crude oil and stock market affect the performance of green bond? : Evidence from green bond market
Nguyen, Viet (2020-04-27)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2020042722662
https://urn.fi/URN:NBN:fi-fe2020042722662
Tiivistelmä
This study investigates the connection between the green bond and implied volatility indices from different financial markets such as energy, crude oil and stock market. More specifically, the study examines how these uncertainties from energy market (VXXLE), crude oil (OVX), and stock market (VIX) affect the performance of green bond where the performance is measured as returns. Since most of the green bond indices started to be computed in 2014, the sample period starts from October 2014 to January 2020.
The results of employed OLS regression models confirm the significant impact between green bond returns and VIX in majority of the models. Interestingly, the findings reveal that a negative linkage between OVX and green bond returns exists. However, the negative OVX-green bond relation is insignificant when the regression model is performed separately from other markets while it is barely statistically significant when consider- ing two or more volatility indices simultaneously, with the uncertainty in energy and stock markets. This finding could indicate that the US VIX has a signaling effect and impact on OVX and suggest that the uncertainty could flow from the stock market to the crude oil market volatility. Furthermore, the results show that the VXXLE has only significant effect on green bond returns when considering individually and simultaneously with the OVX. The regression model 7 is also estimated with the GARCH(1,1) specification and show significant results suggesting that the volatility shocks are quite persistent and a large excess return value of not only positive but also negative will lead future forecasts of the volatility to be high for a prolonged period, for example in the periods of high volatility. Overall, the empirical findings show that VIX has the most significant effect on the green bond returns. However, the effect is quite small and considered as weak since the impact on green bond returns ranges between 0.4% and 0.5% when VIX increases by 1 percentage point suggesting that the volatility in fixed-income market might explain stronger effect and impact on the green bond performance and returns.
The results of employed OLS regression models confirm the significant impact between green bond returns and VIX in majority of the models. Interestingly, the findings reveal that a negative linkage between OVX and green bond returns exists. However, the negative OVX-green bond relation is insignificant when the regression model is performed separately from other markets while it is barely statistically significant when consider- ing two or more volatility indices simultaneously, with the uncertainty in energy and stock markets. This finding could indicate that the US VIX has a signaling effect and impact on OVX and suggest that the uncertainty could flow from the stock market to the crude oil market volatility. Furthermore, the results show that the VXXLE has only significant effect on green bond returns when considering individually and simultaneously with the OVX. The regression model 7 is also estimated with the GARCH(1,1) specification and show significant results suggesting that the volatility shocks are quite persistent and a large excess return value of not only positive but also negative will lead future forecasts of the volatility to be high for a prolonged period, for example in the periods of high volatility. Overall, the empirical findings show that VIX has the most significant effect on the green bond returns. However, the effect is quite small and considered as weak since the impact on green bond returns ranges between 0.4% and 0.5% when VIX increases by 1 percentage point suggesting that the volatility in fixed-income market might explain stronger effect and impact on the green bond performance and returns.