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• W2897415900 abstract "We study the impact of Twitter sentiment and sentiment divergence on returns, volatility and trading volumes for renewable energy stocks. Based on daily time series for Twitter sentiment and Twitter sentiment divergence, we estimate VAR models and evaluate spillovers between sentiment and renewable energy stock pricing and trading. We find that whereas Twitter sentiment has no sizeable impact on returns, volatility or trading volumes, Twitter sentiment divergence generates feedback effects on volatility and trading volumes. Our evidence would indicate that the wisdom of the Twitter crowd is not substantial in shaping prices and trading for renewable energy companies." @default.
• W2897415900 created "2018-10-26" @default.
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• W2897415900 date "2018-10-01" @default.
• W2897415900 modified "2023-10-18" @default.
• W2897415900 title "The impact of Twitter sentiment on renewable energy stocks" @default.
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• W2897415900 doi "https://doi.org/10.1016/j.eneco.2018.10.014" @default.
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