Incorporating climate considerations into portfolio analysis and systematic investments has drawn numerous attention recently. It is motivated by the pursuit of sustainable investing for a low-carbon transition. In this paper, we propose to integrate both structured and unstructured climate-related data into quantitative investing for stock markets, e.g. carbon emission scores and climate events from news flows. We develop a deep learning framework to consume these data for assessing climate-related opportunities and the risk of stocks in the investing universe. Experimental evaluation on real data demonstrates the low-carbon intensity of the constructed portfolio as well as decent investing return.
