We examine the effects of issuing green bond on green premium and green signal transmission by matching green bonds with ordinary bonds. We find that the credit spread of green bonds is significantly lower than that of ordinary bonds, especially for those green bonds with lower information disclosure complexity. Besides, issuing green bonds cannot receive a positive response from the stock market, but can significantly reduce issuer’s loan costs and provide more financial subsidies for high polluting issuers. Furthermore, by obtaining discounted loans and financial subsidies, issuing green bonds can increase issuer’s R&D intensity and reduce their carbon emissions. These findings indicate that issuing green bonds can reduce financing costs and convey green signals to market stakeholders with less investment experience.

The general financial theory predicts a carbon premium, as brown stocks bear greater uncertainty under climate transition. However, a contrary green premium has been identified in China, as evidenced by the return spread between green and brown sectors. The aggregated climate transition sentiment, measured from news data using a large language model, explains 12%-33% of the variability in the anomalous alpha. This factor intensifies after China announced its national commitments. The sentiment-driven green premium is attributed to speculative trading by retail investors targeting green “concept stocks.” Additionally, the discussion highlights the advantages of large language models over lexicon-based sentiment analysis.