Hedging gas in a multi-frequency semiparametric CVaR portfolio

The price of natural gas has experienced a huge increase in recent years due to the pandemic and the war in Ukraine, which has created a high risk for agents working with gas. This paper tries to reduce extreme risk of gas in multi-scale six-asset portfolios, combining gas with developed and BRICS stock indices. Wavelet transformed time-series are used to create the portfolios in the midterm and long-term horizons. Extreme downside risk of portfolios is measured by parametric CVaR and more complex semi-parametric CVaR. The results indicate that semiparametric CVaR is capable of recognizing leptokurtic and platykurtic features in multiscale distributions, making it superior to parametric CVaR. Both groups of indices significantly reduce extreme risk of gas, but the portfolios with BRICS indices have slight upper hand, probably due to lower integration of BRICS markets. To make the analysis more detailed, several other concepts are also examined in the paper.

Automated summary

This paper examines the extreme risk of natural gas in multi-scale six-asset portfolios and constructs portfolios of different horizons using wavelet transformed time-series. The results indicate that the semi-parametric CVaR is better at identifying different distribution features and the portfolios with BRICS indices have a slight advantage in reducing the risk of natural gas.