Global warming and climate change have become critical issues for all countries, prompting them to transition from brown (fossil) energy resources to green (clean) energy resources with the aim of achieving a low-carbon economy. However, if financial actors cannot fully anticipate changes in climate policies and regulations, then this situation can trigger climate transition risk. Under certain climate transition scenarios, this new type of financial risk implies a downturn or an upturn in both brown and green stock markets, thereby potentially leading to financial instability in a country.

In this study, we aim to examine whether financial instability is directionally predictable under certain market scenarios related to climate transitions. Financial instability is reflected by a low value of so-called financial stability index (FSI), constructed by integrating financial stability proxies, such as interest rates, exchange rates, yield curves, inflation, and money supply. The FSI construction is carried out using nonlinear principal component analysis (PCA) through some kernel functions. The directional predictability of financial instability is assessed across some quantile levels under climate transition scenarios by proposing some modified versions of the cross-quantilogram. Using data for some selected Asian countries, we reveal significantly positive directional predictability effects, particularly in developed countries.