Abstract
Based on a sample of 41 Chinese new energy stocks during the period from 2016 to 2022, this paper uses the improved Diebold-Yilmaz method to analyze the volatility connectedness among new energy stocks. We study the essential characteristics of the volatility connectedness network, including major risk transmitters and risk receivers, and find that large company stocks play an important role in volatility spillovers in the new energy stock network. Furthermore, we use the Baidu search volume index of 20 keywords related to the physical climate risk to measure the physical climate risk attention and study the impact of physical climate risk attention on the dynamic volatility connectedness among new energy stocks. We find that the effect of physical climate risk attention on volatility connectedness among new energy stocks is significantly positive. The results remain robust through multiple tests.
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