Asymmetric effects of commodity and stock market on Chinese green market: Evidence from wavelet-based quantile-on-quantile approach

Abstract

This study principally concentrates on evaluating the effects of Chinese commodity and stock market on the green market. The Maximum Overlap Discrete Wavelet Transform (MODWT) technique is utilized for decomposing time series into diverse frequency components. Following this, quantile-on-quantile regression (QQ) is implemented to meticulously demonstrates the dependency structure among the variables under diverse market conditions. Results demonstrate that energy has no short-term impact, while non-ferrous metals, palm oil, sugar, and stock impact the green market at high and low quantiles. Booming gold and declining stock negatively affect the green market. In the medium term, the influence of stocks and most commodities diminishes. Bullish coal and lead prices have a positive impact, while bearish zinc, corn, and palm oil prices have a negative impact. Crude oil does not significantly affect the green market. In the long term, both stock and commodities have a positive impact on the green market, particularly at extreme quantiles. When both markets decline, they negatively affect the green market. Finally, Granger causality test reveals a bi-directional linear and non-linear causality between commodity and stock markets and the green market across all time scales, enabling investors to predict green market returns based on commodity and stock returns.