Climate risks and predictability of the conditional distributions of rare earth stock returns and volatility

Abstract

Using a nonparametric causality-in-quantiles test, we examine the predictability of rare earth stock returns and volatility based on physical and transition climate risks over the period 2nd January 2008 to 31st January 2025. Our results indicate that, although the linear Granger causality test fails to show any evidence of predictability due to model misspecifications arising from nonlinearity and structural breaks, the nonparametric causality-in-quantiles test shows significant predictability over the entire conditional distribution of rare earth stock returns and volatility. The evidence of predictability is robust to alternative choices of rare earth stock indexes, measures of climate risk, conditional estimates of volatility, and multiple macroeconomic and financial control variables. Further analyses involving the signs of the causal impact and a rolling-window estimation reveal that returns are negatively impacted over the range of lower conditional quantiles till the median, corresponding to weak global conditions; volatility, however, is increased over its entire conditional distribution. The implications of our findings are discussed.